ESCUELA TÉCNICA SUPERIOR DE INGENIERÍA Y SISTEMAS...
Transcript of ESCUELA TÉCNICA SUPERIOR DE INGENIERÍA Y SISTEMAS...
UNIVERSIDAD POLITÉCNICA DE MADRID
ESCUELA TÉCNICA SUPERIOR DE INGENIERÍA Y
SISTEMAS DE TELECOMUNICACIÓN
CHARACTERISATION OF THE OPERATION &
MAINTENANCE PHASE IN PV RURAL
ELECTRIFICATION PROGRAMMES
THESIS
AUTHOR: LUIS MIGUEL CARRASCO MORENO
DIRECTOR: LUIS NARVARTE FERNÁNDEZ MADRID, MAY 2015
Dedicado a mis padres,
mi hermana,
mi abuela,
a toda mi familia,
mis amigos
y cómo no, a Adelita.
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ACKNOWLEDGEMENTS
"[...] el olmo ya seco de la ermita debe su único verdor a la hiedra que le abraza, pero ella a su vez sólo gracias al viejo tronco
logra crecer hacia el sol."
José Luis Sampedro (La Sonrisa Etrusca)
Escribió Galdós que la experiencia es una llama que no alumbra sino quemando. Creo que en
mi vida me he chamuscado bastante, pero no lo he hecho solo y por eso tengo que agradecer a
muchas personas todo lo que de ellas he aprendido trabajando codo con codo hasta llegar aquí,
empezando por Luis Narvarte, mi tutor y director de tesis, alma mater de este trabajo, excelente
persona y amigo, quien me animó a emprenderme en esto de investigar y quien siempre ha estado
disponible para escuchar, pensar y resolver. A Eduardo Lorenzo, por su experta mirada desde lo alto
que tanto ha servido para enderezar mis torcidos renglones. A todos mis compañer@s del grupo de
sistemas fotovoltaicos del IES, que forman entre tod@s el más cordial ambiente de camaradería de
trabajo que he conocido. A tod@s mis compañer@s de la extinta Isofoton en España y Marruecos
con los que trabajé y aprendí muchas más cosas además de fotovoltaica. Y a much@s más, que
aunque no mencionados, fueron fuente de iluminación.
Agradezco a Isofoton Maroc s.a.r.l. por su colaboración al poner los enormes cimientos en los
que se ha basado el trabajo experimental de esta tesis.
Un último reconocimiento a la Universidad Politécnica de Madrid por su ayuda al financiar
parte de los estudios llevados a cabo en esta tesis con el proyecto 35_FOTOVOLT perteneciente a la
XI Convocatoria de Acciones de Cooperación Universitaria para el Desarrollo.
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ABSTRACT
With 1,300 million people worldwide deprived of access to electricity (mostly in rural environments),
photovoltaic solar energy has proven to be a cost‐effective solution and the only hope for electrifying
the most remote inhabitants of the planet, where conventional electric grids do not reach because
they are unaffordable. Almost all countries in the world have had some kind of rural photovoltaic
electrification programme during the past 40 years, mainly the poorer countries, where through
different organizational models, millions of solar home systems (small photovoltaic systems for
domestic use) have been installed. During this long period, many barriers have been overcome, such
as quality enhancement, cost reduction, the optimization of designing and sizing, financial
availability, etc. Thanks to this, decentralized rural electrification has recently experienced a change
of scale characterized by new programmes with thousands of solar home systems and long
maintenance periods. Many of these large programmes are being developed with limited success, as
they have generally been based on assumptions that do not correspond to reality, compromising the
economic return that allows long term activity. In this scenario a new challenge emerges, which
approaches the sustainability of large programmes. It is argued that the main cause of unprofitability
is the unexpected high cost of the operation and maintenance of the solar systems. In fact, the lack
of a paradigm in decentralized rural services has led to many private companies to carry out
decentralized electrification programmes blindly. Issues such as the operation and maintenance cost
structure or the reliability of the solar home system components have still not been characterized.
This situation does not allow optimized maintenance structure to be designed to assure the
sustainability and profitability of the operation and maintenance service.
This PhD thesis aims to respond to these needs. Several studies have been carried out based on a real
and large photovoltaic rural electrification programme carried out in Morocco with more than 13,000
solar home systems. An in‐depth reliability assessment has been made from a 5‐year maintenance
database with more than 80,000 maintenance inputs. The results have allowed us to establish the
real reliability functions, the failure rate and the main time to failure of the main components of the
system, reporting these findings for the first time in the field of rural electrification.
Both in‐field experiments on the capacity degradation of batteries and power degradation of
photovoltaic modules have been carried out. During the experiments both samples of batteries and
modules were operating under real conditions integrated into the solar home systems of the
Moroccan programme. In the case of the batteries, the results have enabled us to obtain a proposal
of definition of death of batteries in rural electrification.
A cost assessment of the Moroccan experience based on a 5‐year accounting database has been
carried out to characterize the cost structure of the programme. The results have allowed the major
costs of the photovoltaic electrification to be defined. The overall cost ratio per installed system has
been calculated together with the necessary fees that users would have to pay to make the
operation and maintenance affordable.
Finally, a mathematical optimization model has been proposed to design maintenance structures
based on the previous study results. The tool has been applied to the Moroccan programme with the
aim of validating the model.
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ACRONYMS
AECID: Agencia Españolda de Cooperación para el Desarrollo
AEG: Allgemeine Elektrizitäts Gesellschaft
CC: Charge Controller
CFL: Compact Fluorescent Lamp
CM: Corrective Maintenance
DOD: Depth Of Discharge
EC: European Communities
ECU: European Currency Unit
EDP: Energy Demonstration Programme
ESCO: Energy Service Company
EVA: Ethylene‐Vinyl‐Acetate
GEF: Global Environmental Facility
HW: Hardware
IEA: International Energy Agency
IEC: International Electrotechnical Commission
IES‐UPM: Instituto de Energía Solar ‐ Universidad Politécnica de Madrid
LC: Low power Consumption light lamps
LED: Light‐Emitting Diode
LEDC: Less Economically Developed Countries
MAD: ISO code for the Moroccan currency (dirham)
MDG: Millennium Development Goals
MNRE: Ministry of New and Renewable Energy of India
MPPT: Maximum Power Point Tracker
MTTF: Mean Time To Failure
NGO: Non‐Governmental‐Organizations
O&M: Operation and Maintenance
OEI: Organización de Estados Iberoamericanos
ONEE: Office National de l'Electricité et l'Eau (Morocco)
OW: Orgware
pdf: probability density distribution
PERG: Programme d'Electrification Rurale Globale (Morocco)
PLANER: Plan Nacional de Electrificación Rural (Spain)
PM: Preventive Maintenance
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PPER: Programme Pilote d'Electrification Rurale (Morocco)
ppp: public‐private‐partnership
PV: Photovoltaic
PVPS‐IEA: Photovoltaic Power Systems Programme ‐ IEA
PVRE: Photovoltaic Rural Electrification
PWM: Pulse‐Width Modulation (charge controller)
REA: Rural Electrification Administration
REDP: Renewable Energy Development Project
SE4ALL: Sustainable Energy for All
SGA: Société Générale Agricole
SHS: Solar Home Systems
SLI: Start‐Lighting‐Ignition (Battery)
SOC: State Of Charge
Solar‐PERG: Photovoltaic PERG programme
Solar‐PERGISO: Solar‐PERG carried out by the private company ISOFOTON
SW: Software
UN: United Nations
UNDP: United Nations Development Programme
USAID: United States Agency for International Development
UTSfSHS: Universal Technical Standard for Solar Home Systems
VAT: Value Added Tax
VRLA: Valve‐Regulated Lead‐Acid (Battery)
WB: World Bank
Wp: Watt peak
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SUMMARY
1 INTRODUCTION ......................................................................................................... 2
1.1 THE GLOBAL ACCESS TO ELECTRICITY ................................................................................... 3
1.2 THE ORIGINS OF RURAL ELECTRIFICATION .......................................................................... 10
1.3 REVIEW OF THE DEVELOPMENT OF THE PHOTOVOLTAIC RURAL ELECTRIFICATION .......... 17
1.4 OBJECTIVES OF THE THESIS ................................................................................................. 35
1.5 METHODOLOGY OF THE WORK ........................................................................................... 35
1.6 THESIS STRUCTURE ............................................................................................................. 35
2 THE MOROCCAN PV RURAL ELECTRIFICATION PROGRAMME .................................. 38
2.1 INTRODUCTION ................................................................................................................... 38
2.2 THE PERG PROGRAMME ..................................................................................................... 38
2.3 THE SOLAR‐PERG ORIGIN, DEVELOPMENT AND FEATURES ................................................ 40
2.4 THE ISOFOTON‐PERG PROGRAMME ................................................................................... 43
2.5 SOME COMMENTS ABOUT THE SOLAR PERG DEVELOPMENT ............................................ 50
2.6 THE ISOFOTON‐PERG DATABASE ........................................................................................ 50
3 RELIABILITY ASSESSMENT OF SHS COMPONENTS .................................................... 54
3.1 INTRODUCTION ................................................................................................................... 54
3.2 RELIABILITY ANALYSIS ......................................................................................................... 54
3.3 ANALYSIS OF THE RESULTS .................................................................................................. 60
3.4 APPLICATION EXAMPLE ...................................................................................................... 65
3.5 CONCLUSIONS ..................................................................................................................... 66
4 IN‐THE‐FIELD ASSESSMENT OF BATTERIES AND PV MODULE RELIABILITY IN THE PERG
PROGRAMME ................................................................................................................. 70
4.1 INTRODUCTION ................................................................................................................... 70
4.2 IN‐FIELD BATTERY TESTING ................................................................................................. 71
4.3 IN‐THE‐FIELD PV‐MODULE TESTING .................................................................................... 81
4.4 CONCLUSIONS ..................................................................................................................... 84
5 CHARACTERIZATION OF THE OPERATIONAL & MAINTENANCE COSTS ...................... 88
5.1 INTRODUCTION ................................................................................................................... 88
5.2 COST ANALYSIS .................................................................................................................... 88
5.3 SENSITIVITY ANALYSIS ......................................................................................................... 94
5.4 INFLUENCE OF THE SHS SPATIAL DENSITY ........................................................................... 96
5.5 APPLICATION EXAMPLE ...................................................................................................... 97
5.6 CONCLUSIONS ..................................................................................................................... 99
6 DESIGN OF DECENTRALIZED MAINTENANCE STRUCTURES IN PHOTOVOLTAIC RURAL
ELECTRIFICATION ...........................................................................................................102
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6.1 INTRODUCTION ................................................................................................................. 102
6.2 BASELINE DATA ................................................................................................................. 103
6.3 METHODOLOGY ................................................................................................................ 103
6.4 MODEL APPLICATION ........................................................................................................ 111
6.5 CONCLUSIONS ................................................................................................................... 115
7 CONCLUSIONS AND FUTURE RESEARCH ..................................................................118
7.1 CONCLUSIONS ................................................................................................................... 118
7.2 FUTURE LINES OF RESEARCH ............................................................................................. 121
PUBLICATIONS GENERATED DURING THIS PHD ..............................................................124
BIBLIOGRAPHY ..............................................................................................................128
CHAPTER 1
INTRODUCTION
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1 INTRODUCTION
Beyond the reasons that justify the right of every human to have access to modern sources of
energy, the importance of electricity as energy vector, from the first application of the late
nineteenth century to today, lies in the fact that it is easy to transport and simple to operate.
Nowadays there are still 1,300 million people deprived of electricity, 85% of them in remote rural
areas where electrification encounters problems such as high economic investments, low
profitability or difficulty of operation, among others. In these cases, decentralised electrification by
means of solar home systems (SHS) has aimed to be a technical and cost‐effective solution for over
40 years in many countries of the world. Currently, large‐scale electrification programmes with
thousand of SHSs are established in remote and impoverished regions, whose results, in terms of
sustainability, are in doubt. These attempts at electrification are frequently based on assumptions,
such as electricity consumption, device reliability, operating costs, rural spending habits, etc, which
bear little resemblance to reality. The consequences are the long term economic instability of the
programmes, the failure of private operators and the abandonment of SHSs, which has happened in
many initiatives developed in recent decades.
This work presents a study based on a real and large photovoltaic rural electrification (PVRE)
programme, taking advantage of the excellent opportunity that the author took advantage of
whilst, for five years, being part of the management team of the company that operated that
programme, having full access to the detailed maintenance data, failure of the SHS components,
unit costs, management structure, activity organization, etc, during that period. The study provides
the chance, for the first time, to contrast the real data of decentralised electrification with the
classic assumptions, by means of the SHS's reliability statistic research, the characterization of the
actual costs in the operation and maintenance (O&M) phase and the study of the application of the
results in the formulation of PVRE programmes.
This chapter introduces the detailed historical evolution of rural electrification, in general and the
photovoltaic rural technology, in particular, which nowadays has culminated in the implementation
of large PVRE programmes. First, it focuses on the problem of access to electricity and discusses the
difficulties that it faces. Then, a review of the rural electrification origins throughout the 20th
century is presented to show that barriers and solutions at the beginning of rural electrification are
similar to the current challenges. Finally, an historical review of photovoltaic rural technology
evolution shows that the three dimensions that integrate it (hardware, software and orgware) have
unequally evolved to the present day, which gives rise to a still non‐mature technology.
The chapter concludes with the main objectives of the thesis, a brief explanation of the
methodology of the work and the description of the document structure.
Chapter 1: Introduction
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1.1 THEGLOBALACCESSTOELECTRICITY
1.1.1 Currentstatus:1,300millionpeoplewithoutelectricity
Nowadays, the lack of access to electricity affects to 1,300 million people worldwide, 20% of the
world’s population. This figure, published by the International Energy Agency (IEA) in 2012 ‐ World
Energy Outlook Report, [1] ‐ gives us an overall idea of a problem to be solved globally, similar to
other issues such as hunger, access to clean water, sanitation, etc. According to the IEA, this figure
has decreased since 1990, from 2,000 million people, to 1,300 million in 2010. Not only that, in just
in 8 years (2002 ‐ 2010), it has been reduced from 1,623 million to 1,267, a gap of new 356 million
people with access to electricity (more than the population of the United States of America).
However, these figures are just estimations (as recognized by the IEA), since the lack of access to
electricity is something specific to the marginal and rural areas of the less economically developed
countries (LEDC), where the inaccuracy of the population census, also affected by the double and
opposing effect of population growth and migration to urban areas, precludes any accurate
estimations [2].
1.1.2 TheIEAexpectsthatuniversalaccesstoelectricitywillbeachievedinpartwithSolarHomeSystems
From the perspective of reducing the world population without access to electricity, in 2010 the
United Nations (UN) launched the Sustainable Energy for All (SE4ALL) initiative to "achieve universal
energy access, improve energy efficiency, and increase the use of renewable energy" [3] (It must be
remembered that the UN for many years did not include action on energy poverty in the
Millennium Development Goals).
The 2011 World Energy Outlook report [4] published by the IEA estimated the necessary
investment for electricity universal access, between 2010 and 2030, at US$ 640 billion (this
requirement is small when compared to overall energy‐related infrastructure investment,
equivalent to around 3% of the total). The report suggests that 70% of the required infrastructure
would consist of off‐grid systems: mini‐grids (65% of this share) and stand‐alone off‐grid solutions
(the remaining 35%), that is, solar home systems (SHS), small hydro systems, and others (wind and
biogas). We estimate that nowadays, the SHSs represent 95% of the stand alone system installed
worldwide. So, the IEA foresees an investment of around US$ 150 billion for SHSs to reach universal
access to electricity before 2030. If photovoltaic (PV) systems were sized to meet housing
consumption between 250 and 500 kWh/year [5], the required SHS power would be 180 ‐ 365
watts peak (Wp). Taking into account a unit cost for the installed SHSs of between US$ 6 ‐ 8 /Wp1, it
would correspond to installing more than 50 million SHSs, giving access to electricity to 250 million
people.
1.1.3 Whythelackofelectricityisaproblem
Access to electricity is not considered a universal fundamental right of people [6]. However, there is
a unanimous opinion that electrical supply is a priority factor which is urgent to resolve. Therefore,
in the last decade there have been numerous initiatives to address the problem, such us the Global
1 It includes equipment, transportation, installation of the SHSs and 10% of overhead expenses.
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Environmental Facility ‐ GEF [7], the Millennium Development Goals [8] and the Sustainable Energy
for ALL (SE4ALL) from the UN [3], "Luz para Todos" in Brazil [9], Power for all in India [10] or "Luces
para aprender" from the Organization of Ibero‐American States (OEI) [11], among others.
Apart from the extended consideration in Western culture that human enrichment as a society, in
economic, social, political and cultural aspects, is necessarily linked to infrastructure development
[12, 13], perhaps, the best arguments that justify the need for access to electricity are included in
the Millennium Development Goals (MDG). In this resolution, adopted by the UN in 2000, although
there are no specific MDGs relating to energy, it has been recognized that MDGs cannot be met
without affordable, accessible and reliable energy services (Table 1):
Table 1: Importance of electrical access for achieving the MDGs
Goal 1:
Eradicate extreme poverty
Access to modern electricity increases household incomes through economic development and reduces the burden of time‐consuming domestic labour. Electricity supply enables poor households to engage in activities that generate income by providing lighting that extends the working day and by powering machines that increase output.
Goals 2 and 3:
Achieve universal primary education and promote gender equality and empowerment of women
For poor people everywhere, access to electricity frees time for education; time that would otherwise be spent collecting traditional fuels, fetching water, processing food or in other physical work. Access to electricity contributes to the empowerment of women. Increasing access to energy brings major benefits for women and girls; in health, education, and productive activities.
Goals 4, 5 and 6:
Reduce child and maternal mortality and reduce diseases
Electricity helps improve health by powering equipment for pumping and treating water; it enable health clinics to refrigerate vaccines, operate and sterilize medical equipment, and provide lighting. It allows the use of modern tools of mass communication needed to fight the spread of HIV/AIDS and other preventable diseases. Access to electricity helps attract and retain health and social workers in rural areas by improving living conditions.
Goal 7:
Ensure environmental sustainability
Energy use and production affect in local, regional and global environments. The environmental damage and its harmful effects can be reduced by increasing energy efficiency, introducing modern technologies for energy production and using renewable energy.
Goal 8:
Develop a global partnership for development
The World Summit for Sustainable Development called for partnerships between public entities, development agencies, civil society and the private sector to support sustainable development, including the delivery of affordable, reliable and environmentally sustainable energy services.
However, these arguments, usually very common in the literature, should be treated with caution,
since, very often, the availability of electricity does not directly involve any development [14, 15].
Chapter 1: Introduction
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An example that refutes this attribution is the Moroccan Global Rural Electrification Programme
(PERG in French acronym), which will be widely discussed in this work. This electrification
programme focused on providing electricity mainly to housing and not to farmlands, which are the
places where electrification could have some impact on the development of the local economy. The
case of Tizi n'Ait Amer, a small village of just 700 inhabitants in the south of Morocco, is illustrative.
It got access to electricity 10 years ago and every dwelling is connected to the grid. However, no
new economical activities have been developed since the electrification of the village. The only
hope of carrying out new activities has been the extension of agricultural lands, which has recently
become possible thanks to the installation of a photovoltaic water pumping system to irrigate the
new crops, as the wells are 400 meters from the village and the grid does not reach it2. This
example shows that giving access to dwellings is not enough for economical development. Rural
electrification must be more ambitious if new economical activities are to be implemented.
From a different point of view, most modern societies are economically based on the so‐called
"consumer economy", thus it is not surprising that private corporations, financial institutions and
public administrations are interested in the extension of the economy to the rural population,
focusing in the fact that access to electricity contributes to the acceleration of that process
(consider, however, the existing criticisms of the dominant current model of economic growth, but
this subject is far from the arguments addressed in this thesis).
Beyond corporate or market interests, the extension of the access to electricity is currently in the
hands of the people themselves, that even knowing about the electricity, they still live without it
and therefore they demand it. To a greater or lesser extent, modern standards of living have spread
to the most remote areas of the planet, and so electric lighting, television and mobile phones are
currently perceived as basic needs in the rural areas of impoverished countries. The introduction of
these everyday uses requires the availability of electricity. It can be said that after more than a
century of electrification, the current demand for electricity is global.
1.1.4 Blockingfactors
Despite the efforts made to enhance the conditions for people in rural environments, the fact is
that the access to electricity rates are still very low in some regions of the planet (Sub‐Saharan
Africa and South Asia constitutes 95% of the world population without access to electricity).
The evolution of the rate of access to electricity is affected by several factors:
a) Positive factors that increase the electrification rate:
‐ Migration from rural to urban areas
‐ Rural electrification
‐ Maturity, quality and cost reduction of new technologies
b) Negative factors that reduce the electrification rate:
‐ The high birth rates in rural areas of impoverished countries
2 Own sources. The PV pump installed in Tizi n'Ait Amer belongs to a project financed by the Spanish International Cooperation (AECID) and the Universidad Politécnica de Madrid (UPM)
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‐ The increased costs of conventional technologies
These factors, which could be quantified, depend on other more unpredictable and difficult
weighting factors, such as political will, armed conflict, famine, natural disasters, etc.
Considering the last 3 decades (1980 ‐ 2010), an analysis of the factors involved in global access to
electricity could be carried out just by assigning an indicator to each factor (Table 2).
Table 2: Factors that quantitatively affect the evolution of global access to electricity
Factor Indicator 1980 2010
Migration from rural to urban areas
Rural population (nº of people living in rural environment)
2,675,822,000 (61% of the population)
3,320,679,000 (48% of the population)
Birth World population (nº of people)
4,413,536,000 6,861,918,000 (increased by
55%) Rural electrification programmes
People without access to electricity
2,000,000,000 (45%)
1,300,000,000 (20%)
Maturity and reduced costs of new technologies
Photovoltaic systems costs ($/Wp of the photovoltaic module)
$12 $0.8 (93% reduction)
Increased costs of conventional technologies
Crude oil prices (US$/ barrel) [16]
Jan. 1970 (Before 1970s oil crisis)
US$ 21.00
July 2010 US$ 82.25
1.1.4.1 Theincreaseintheruralpopulation
On the one hand, in spite of the strong migration impact towards the cities (in 2007 there was the
historical phenomenon that, for the first time, the world population changed from mainly rural to
urban), the high global birth rate has meant that in 3 decades the world’s rural population has
increased by 25% (more than 600 million people).
On the other hand, although the rural electrification programmes have contributed to increasing
the rate of access to electricity, it is not known precisely what was this rate in the 1980s, but it can
be estimated that the overall number of people without access to electricity remained constant
during that decade at 2,000 million, which means 45% of the population [17]. If the figure was
reduced to 1,300 million in 2010, it means that the rate of access to electricity is still higher than
the growth rate of the rural population, which is a very encouraging fact (see Figure 1) on the
evolution of the global access to electricity, especially in Asia, where the ratio of people without
power is declining rapidly (China gave access to electricity to more than 700 million people
between 1980 and 2000 [18], and the country's electrification rate currently exceeds 99% [5]). Sub‐
Saharan Africa, however, remains as the only region of the world where the number of people
without access to electricity is increasing.
Chapter 1: Introduction
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Figure 1: Global evolution of population, rural population and lack of access to electricity until 2013. World Bank [19]
1.1.4.2 Conventionalelectrificationisbecomingmoreexpensive
The current high costs of conventional rural electrification systems are affected, among other
factors, by the increased prices of fossil fuels. For example, in US, the cost of electricity for
residential use has doubled in three decades. In Europe, between 2002 and 2013, the cost of
electricity for households has gone up by 61%.3
Among the less electrified regions of the world, Sub‐Saharan Africa has the most expensive
electricity tariff in the world, on average between US$ 0.13 ‐ $0.14/kWh (in comparison, electricity
tariffs in Latin America, Eastern Europe and East Asia are around US$ 0.08/kWh.) [5], which lie well
below the true cost of production, which on average is US$ 0.18/kWh, preventing any return in
capital, thus threatening the long‐term sustainability of the utilities in the region [20].
If, in addition, we consider the investment needed to provide access to electricity to rural
communities, it should be noted that the infrastructure costs for conventional electrification
(extensions of electricity grids mainly through the medium and low voltage lines) has increased
considerably. These lines use raw materials such as iron and copper, whose market prices have
increased 2 and 5 fold respectively from 1980 to now [21]. The average cost of a medium voltage
line is around €6,000/km (case of 11 kV; cost of medium voltage transformers or operation and
maintenance not included [22, 23, 24, 25]) and its impact on the energy costs can be estimated at
€2.5c/kWh/km [26].
At the same time, during the last 40 years, the silicon flat‐plate photovoltaic industry (that
represents more than 90% of the global photovoltaic market) has reduced its costs by 93%, so in
the sunniest countries, such as the Mediterranean area, or most of the African continent, it is now
3 Note, however, that the integration of renewable energy sources into the European energy mix has also affected the increase in tariffs.
‐
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1950 1960 1970 1980 1990 2000 2010 2020
Million of peo
ple World
Rural WorldWithout electricity access
7,125
3,336
1,285
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feasible to produce solar electricity at a cost around4 €8c/kWh , which could lead to the possibility
of a medium term change of paradigm.
On other matters, from 1980 to 2010, electrical power consumption in the world has increased by
more than 150%, at a rate nearly 5% per year (Figure 2). However, the human population has
grown at a rate of 1.8% per year, which indicates that electricity consumption per capita has
increased almost 3 fold in 30 years. Although the development of the industry carries a lot of
weight in these results, it is also obvious that home electricity consumption is growing. This fact
suggests that providing access to electricity leads not only to an increase in the power required to
meet the new connections, but also that this power needs to be gradually increased according to
trends in household consumption.
Figure 2: Evolution of the World’s electricity capacity, generation, consumption and losses [27]
Within the great figures of the world electricity generation, it is worth mentioning the importance
of the distribution energy losses (see Figure 2), which represent 8 ‐ 9% of the electricity generated
every year worldwide. This means annual losses of 1,800∙106 MWh, enough to supply electricity to
a country of more than 300 million inhabitants with the European standard consumption of
electricity (5.4 MWh/person/year [28]). Not only that. Taking into account the minimum electrical
consumption to guarantee basic life conditions (1 MWh/person/year [29]), the figure would
become 1,800 million people; and considering the average consumption per capita in Africa (0.5
MWh/person/year), this figure would rise to 3,600 million people, almost 3 times the world’s
population without access to electricity.
4 It concerns large photovoltaic (PV) power plants. Taking into account a power degradation rate of 1%/year for PV modules and a lifetime of 25 years, 1 kWp PV power could produce around 44,500 kWh for 25 years (solar radiation = 5.5 kWh/m2/day). At current PV power plant investment prices (€1.5 /Wp), a performance ratio PR = 0.75 and O&M costs corresponding to 3% yearly of the investment cost, the produced solar energy
cost would be €7.8c/kWh.
0
1,000
2,000
3,000
4,000
5,000
6,000
0
5,000
10,000
15,000
20,000
25,000
1975 1980 1985 1990 1995 2000 2005 2010 2015
Total Electricity Net Consumption (Billion Kilowatthours)
Electricity Distribution Losses (Billion Kilowatthours)
Total Electricity Installed Capacity (Million Kilowatts)
109 kWh 106 kW
Chapter 1: Introduction
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1.1.4.3 Politicalandsocialfactors
In the current global energy scenario, with a declining growth rate of the world’s rural population
and viable alternatives to conventional electrification, we can estimate that technical and
economical aspects are not the only cause impeding access to electricity. The development of rural
electrification also depends on other factors such as political will, social acceptance, subsidies and
agricultural development policies, among others.
It is socially accepted that renewable energies, especially photovoltaic technology, are "expensive"
and have low reliability compared to conventional technologies, so they would require a great deal
of investment for implementation and the power supply could not be guaranteed. But, in 2013
subsidies to conventional energies, such as petroleum, reached US$550 billion all around the world,
4 times higher than the amount dedicated to renewable energies [30]; or, in the same context, as
regards rural electrification, the World Bank (WB) argues that subsidies for grid electrification are
significantly greater than those for off‐grid electrification [31].
As regards rural development in impoverished countries, the lack of structure in the agricultural
sector also contributes to impeding access to electricity, since the agricultural policies require
investments in infrastructures to be made in the agricultural economy and dignify the peasant's
lives. Thus, it is very unlikely that a country without agricultural policies will be able to allow the
rural population to get access to electricity. As will be set out below, rural electrification in almost
all Western countries in the mid‐20st century was developed in parallel with agriculture with the
aim of modernizing the countryside and increasing agricultural production ratios.
Finally, it must be taken into account that rural electrification especially addresses a particular part
of society, the peasants. They have been historically constituted as an independent economy
characterized by the fact that the peasantry has always supported itself. The peasant community is
the most aware class with regard to its economy, which determines the decisions that they take
daily. The difference between a peasant and other society member is that the former knows
perfectly what he obtains from his work: he produces what he needs to live and the rest of the
production can be a surplus value when sold on. On the other hand, a worker from the "standard"
society never knows the real value of the product of his work. Thus, is important to realize that
giving access to electricity to rural people means an incursion from the macro‐economy into the
peasant economy, with all the difficulties involved (resistance to change). For example, rural
inhabitants from countries like Morocco are not familiarized with public services such as electricity,
and it is difficult to admit concepts like the payment of monthly fees or the long term contracts, or
contractual rights and obligations.
To better understand the phenomenon of contrast in the development of rural electrification,
which prevails both in the effort to electrify and the problem of electrification, there is nothing
better than referring back at the origins of rural electrification in the Western countries carried out
during the twentieth century.
10
1.2 THEORIGINSOFRURALELECTRIFICATION
1.2.1 Theappealofelectricity
1.2.1.1 Startofthemarketingofelectricity.The1881ParisExposition
Electricity and its applications have fascinated humans since the beginning of the industry over 130
years ago. When today a peasant family without access to electricity in an impoverished country
finally gets access to it, the ability to marvel at the optimum quality of electric lighting in addition to
the possibility of using appliances like TV or mobile phone must be very similar to that experienced
by our ancestors in the late nineteenth century.
It may be argued that the commercial inception of the electrical industry began with the
International Exhibition in Paris in 1881, exclusively dedicated to electricity, that brought together
many of the inventors and industrialists from the emerging sector at the time to exhibit their
creations and show them to the world (Figure 3). It was the closest thing to what we now
understand as an industrial exhibition. It was attended by over 600,000 visitors and had over a
thousand exhibitors (including Thomas A. Edison, Joseph W. Swan, Zénobe T. Gramme, A. Graham
Bell, William Thomson, etc), 19 of whom came from Spain [32].
Figure 3: Overview of the International Exhibition of Electricity, Paris 1881 (appeared in Nature, 1881 second quarter)
Inside the Palais de l'Industrie, which then occupied the place where now stands the Grand Palais
des Champs Elisées, the latter built to host 1900 Universal Exhibition, all kinds of inventions for
electric power generation, transmission and application were exhibited, from a lighthouse, boats
and even an airship driven by electric motors, submarine cables, telegraphy apparatuses,
electrochemical batteries, electric stoves, large magneto‐electric machines, microphones, trams,
etc.
Chapter 1: Introduction
11
But surely, there were two applications which caused more excitement: the phone and lighting. On
the latter, the Spanish magazine "La Ilustración Española y Americana" published in reference to
the Paris Exhibition the following [32]:
"On the bottom left, there are all the known generators: steam, gas, or by means of batteries. Further, a series of powerful gas engines or steam, which set in motion the dynamo‐magneto‐electric machines of Gramme, Lontin, Siemens and Meritens, which send torrents of electricity to the lamps of various systems, which shine splendidly inside the Palace with the most brilliant clarity that human industry has ever produced and with the astonished gaze of man has ever seen."
Thus, electric lighting was the first application of electricity that amazed humanity and became the
engine of development and expansion, thus making other means of artificial lighting practically
inconceivable.
1.2.1.2 Firstpublicsupplyofelectricityinaruralsetting:Godalming1881
Coinciding with the 1881 Exhibition in Paris, and one year before that the famous electric power
plant of Pearl Street in New York (September, 1882) was inaugurated, it took place in September,
1881 in Godalming (England) the first experience in the rural supply of electricity on record, built to
provide street lighting for the town, and replacing the existing gas‐lighting system. In the last
quarter of the nineteenth century, electricity was perceived by society within the realm of the
"scientific". The fact that it was applied in a small town of only 2,000 inhabitants caused a huge
interest around the country. The power generation genius system and the welcome given by not
only the local and surrounding population, but also by the press, because of the good quality of
lighting [33], started the paradigm of what electricity would mean for humanity throughout the
coming century. However, the enormous expectation of the pioneering system and its initial
success had to deal with its technical immaturity and despite the enthusiasm of its promoters, the
private company of electricians Calder & Barnet, eventually abandoned its contract with the Town
of Godalming, which in turn was taken over by Siemens and after numerous problems, causing
continuous and repeated outages, Godalming went back to gas lighting only 2 and a half years after
the start of the new experience. Electricity would come back to Godalming in 1904 and this time
would be forever.
1.2.1.3 Theurbandevelopmentoftheelectrification
Electrification applied to lighting was really confined to the big cities, whose beginnings were
marked by the fierce competition against gas‐lighting, but the rapid popularity of electricity and its
great reception brought about its rapid expansion.
The first urban experiences of using electricity did not go beyond being mere exhibitions. For
example the lighting of Puerta del Sol in Madrid in 1875, or in 1878, to mark the engagement
between King Alfonso XII and his cousin Maria de las Mercedes (who was only 17 years old. She
would die of typhus just five months later, giving rise to the famous legend of the love between
them and the traditional songs that have survived in popular heritage), or other more extravagant
events, like the first night bullfight with not very good results in 1879, which "La Ilustración
Española y Americana" would outline [32]:
"If the shadows of our grandparents hold bullfight functions in the Otherworld, they should be
very similar, because what we saw was a show of silhouettes."
12
In the late nineteenth century, European cities were equipped with a gas lighting service operated
by private companies. The pioneers of electrification were also private companies, and after
electricity superseded gas lighting, many gas companies turned to electricity. Thus emerged a
network of companies that obtained concessions (from municipalities) to illuminate streets or even
whole neighbourhoods. The companies employed steam engines and alternators installed
wherever they could (rented basements, cellars, etc) to power the street lights. Very soon,
theatres, cafes, public buildings, and later dwellings, would also be electrified which led to complex
commercial competition between the numerous electric companies (Figure 4), generating a price
war in order to win customers. Electrical distribution was born, therefore, as a totally private and
decentralized system.
Figure 4: Electricity sales advertisement appeared in an early 20th century newspaper from Barcelona
1.2.1.4 Theworld'slargestindustryemerges:theelectricalindustry
The development of the electricity supply industry was possible thanks to private equity, closely
linked to the European industry. In the case of Spain, the first electric company, also founded in
1881, was the "Sociedad Española de Electricidad", with a company's share capital of 20 million
pesetas, and created by D. Tomás Dalmau, who owned an "optics and physics" shop in Barcelona,
and who had previously introduced the Gramme machine in Spain in 1873, which subsequently
obtained a license for manufacturing.
The "Sociedad Española de Electricidad" installed a multitude of electrical supply equipment for
public and interior lighting in many cities in Spain, especially Barcelona and its surroundings, even
overseas (Cuba and the Philippines) and navy warships. The representative of the company in
Madrid, who was also a partner, the engineer and inventor Artilleryman Colonel Isodoro Cabanyes,
had already equipped his atelier with electricity in 1881 for lighting and motive power. He was
responsible for many of the first electrical project demonstration in Spain. It is worth mentioning
that Cabanyes would work some years later on the use of solar energy for decentralized rural
applications in the field of agricultural irrigation, firstly through a "solar reflector system" (Figure 5)
and afterward with the "solar air engine" [34].
The company was taken over in 1894 by the German company Allgemeine Elektrizitäts Gesellschaft
(AEG) who founded the "Compañía Barcelonesa de Electricidad" in the same year [35, 36, 37, 38,
39].
Chapter 1: Introduction
13
Figure 5: Cabanyes's solar reflector. It appeared in 1890 in the magazine La Gaceta Industrial [34]
Electricity generation, initially produced by means of the steam engine, made the leap to
hydroelectricity, which meant a reduction in the costs of production and consequently electricity
tariffs, initiating the development of large electrical distribution networks.
This new situation led to the need to make major investments in the construction of dams and
reservoirs, artificial waterfalls, high voltage distribution lines, etc. However, the enormous
investments necessary could not be covered by the limited national electric companies, nor even
the public administration, so since the very early days, the electricity industry in Spain, which in the
1930s was the most important in terms of investment, exceeding that of the rail and mining
industries, needed the intervention of international investment holdings to meet the costs of the
rapid development of the electricity sector. In the early 1930s all European utilities were already in
the hands of roughly 20 companies, thus shaping what would later become the paradigm of
centralized electrification [36].
1.2.2 Thebeginningsofruralelectrificationanditsproblemofprofitability
After the introduction of use of electricity in the cities, the Spanish countryside showed little
interest in the new technology. However, the public administration considered electricity as the
panacea for the 3 major rural problems of the Spanish post‐civil war years [40]: unemployment,
poverty and the consequent rural exodus. However, access to electricity in the countryside had to
face two major obstacles: "the enormous cost of setting up the transmission and distribution of
electricity" and the lack of interest of the rural population towards technological innovation. The
first problem was solved through subsidies and as regards the latter, Luis González Abela in his
book "La Electrificación Rural, Problema Nacional " published in 1942 described the problem in thus
[40]:
"... there is only one way to overcome it, which is a very active advertising through pamphlets, daily and technical press, radio, cinema and whatever means possible, which will highlight the transcendental benefits that would result giving access to electricity to our honoured peasants, because there is no reason for them to be second‐class citizens and because they did not commit any offense in having born in the countryside ... "
14
An example of these transcendental benefits was cited in the Congress of Rural Electrification in
1948, held at the School of Industrial Engineers of Madrid [41], in which the importance of using
radio receivers for the Spanish peasant was mentioned:
"... [the peasant] isolation is broken in this way. He belongs to the great human family. He can cultivate his Spirit, increase his knowledge, participate in the national life and enjoy the artistic beauties of music whenever he wants. Not enough can ever be said about the benefits of radio in the life of an isolated peasant. "
Much less documented than urban electrification, rural electrification was carried out in parallel
with the urban, but with a different approach and significant limitations. On the one hand, the
existence of small waterfalls that were used in the flour mills, saw mills, foundries, etc, were
exploited by means of small generators (dynamos) to provide electricity to small towns. Again, the
origin of the electrification system, like the urban one, was absolutely decentralized. From that
mentioned at the 1948 Congress of Rural Electrification, the following is extracted [41]:
"The typical electric mill that is used in many towns and all of its electrical industry is known; it is a completely logical solution, which adequately meets the needs of these people. It is enough to have a small water flow, provided by any ravine that goes to a canal that carries the water to a small pond. At the foot of it, a turbine with a dynamo and engine is installed, achieving a power of 5 to 20 CV; the latter serves to supply electricity to several towns. During the daytime it works as mill, and at night, the dynamo supplies lighting to the town. This is the reality for a large area of the country, and as long as the Spanish countryside does not change its habits, what nowadays seems to be difficult, the National power distribution networks and the rural electrification will be superfluous."
They were small companies including municipalities and agricultural cooperatives which were
commissioned in the early decades to deal with these matters. The technical and productive
limitations of the electrical rural generators, the distribution losses (voltage drops) and the gradual
increase in loads (users added more lighting points, or appliances every year), caused the electric
service to be of very poor quality, with frequent power outages and failures of the generator or
even in the distribution network. From the aforementioned 1948 publication, the following was
cited [41]:
"... the technical solution for creating small local power plants or, at most, at a regional level, installed in waterfalls that are built ad hoc or even using already existing mill and sawmill facilities, is usually not effective, unless, even within modesty of the installations, their energy power far exceeds that required for the loads."
At the time, the notion of critical mass of users that would allow to a company to manage an
electrical network with an economic return was already mentioned [41]:
"... the towns where electrical lighting has not yet arrived, not only will not give profits but losses, even if the facilities were freely outsourced to the nearest distributor, as the expected revenue would be 75‐100 pesetas per month on average at current tariffs, because towns have between 15 and 40 neighbours, most of them with poor access, and therefore the operation of electrical services is very expensive."
"The solution must be sought permitting the rural distributors to apply an adapted tariff throughout its region. In this way, while tariffs remain moderate for the entire electricity rates, the distributors can increase it to get the real rural electrification in the area that they
Chapter 1: Introduction
15
manage. So these new rates shall be applied to the rural market in which villages with up to 2,000 subscribers must be included. "
Another singularity of the rural electrification, which directly affects the problem of the
profitability should also be noted: the collection of the user fees. Given that the peasant and his
family spend most of the daylight hours in agricultural activities, it is most likely that collectors,
when they visit their customers will not find anyone at home, so the already high cost of moving
around remote regions is increased as they have to return repeatedly. In this regard, another
extract from the 1948 Congress is shown [41]:
"Collection of receipts.‐ currently, they are charged at home, which is very expensive because the collector does not always find all the neighbours at home, so he is bound to make several trips, and very likely he may not be able to complete the collection."
As a result of this historical evidence, it can be argued that some of the problems that rural
electrification had to face in the first half of the twentieth century were based on the lack of
profitability for the utilities, due to the high costs of infrastructure (network extensions), no return
on investment (very low consumption of electricity) and insurmountable operation and
maintenance tasks (remote and dispersed customers and difficulty in managing users' fee
collection). As will be seen below, these problems have remained to date.
1.2.3 Ruralelectrificationtomodernizeagriculture
In 1932, during the Second Spanish Republic, the Instituto de Ingenieros Civiles (now known as the
Instituto de la Ingeniería de España [42]), organized a series of conferences on rural electrification
dedicated to electrical energy applied to agriculture, where in a somewhat visionary way it
addressed the tilling of the land by means of electric machines, in addition to the "electroculture of
crops" (direct application of electricity to the crops to influence their development). The focus of
the conferences was the French experience, which had already almost 40,000 electrified towns and
used the "electric‐tiller" (Figure 6) for agricultural work in France, its Protectorates and Colonies
[43]:
"... the Gas Lebón Company, in Algeria [...] had decided to give a subsidy of 300,000 Francs to private farmers and agricultural cooperatives that purchased electric‐tillers of more than 100 H.P."
Figure 6: Electric‐tiller with cable winch, owned by the Société Générale Agricole (SGA). Photo from [43]
16
It is known that later, during the second half of the twentieth century, the engine of development
of rural electrification were policies focused on agricultural modernization, carried out in the
European post‐war as a means of activating the European economy.
"... to turn electrification into a profitable activity, it must cover electric‐tilling, harvesting, threshing and other available operations using electric motors ..." [41]
Thus, the idea was to extend the grids, at the time fed by large hydraulic and thermal power plants,
toward farms with the aim of increasing crop yields through the use of new electrical equipment.
However, the private companies, which had flourished within urban electrification, did not perceive
the same business opportunity in rural electrification that had it had seen in the cities, for the
aforementioned reasons.
1.2.4 Publicsubsidiesforruralelectrification
Then government intervention was required through incentives for both the utilities and the rural
users in order to make the rural electrification attractive to them. In most Western countries rural
electrification was achieved through grants and loans provided to the electricity companies to
ensure a return on the investment, and carrying out awareness campaigns addressed to the rural
population to ensure a minimal electric power consumption.
For example, the US created a rural electrification agency (the Rural Electrification Administration ‐
REA) with the aim of funding the utilities that were electrifying the rural areas [44, 45]. In the
1930s, the US administration launched a promotional campaign aimed at encouraging the peasants
to use electricity (at the time they were reluctant to pay for an electric service that never had
needed before) for different domestic appliances and machinery for agriculture and livestock farm
work (Figure 7).
Figure 7: Two of the advertisements that the REA agency used for electrification promotion in the 1930s to increase awareness among the rural population on the benefits of electricity.
Chapter 1: Introduction
17
Thanks to this campaign, an electrification rate close to 100% in US was attempted in few decades,
which contributed to popularizing the use of domestic appliances, such as television, oven, iron,
bread machine, vacuum cleaner, etc, which would later be exported all over the world. It had the
same impact on agriculture, and the consequent employment of sophisticated electrical power
tools.
1.2.4.1 Publicsubsidies:TheSpanishPLANER
In 1974, in Spain, more than 900,000 rural people still lacked access to the public service electricity
lines (over 6% of rural population). Giving access to electricity to that remote population meant a
huge investment and negative profitability because of the wide dispersion and low purchasing
power of the population. The 1973 National Electrical census indicated that while the density of
subscribers in urban areas was 116.68 per km2, in rural areas it was 11.42 per km2. Moreover, while
the mean urban consumption was 6,244 kWh/year (per dwelling), the rural rate was 885 kWh/year,
i.e. the rural household consumption was 7 times lower than the urban one and the dispersion of
the dwellings was 10 times higher, what meant that the rural electrification costs were 70 times
higher than the urban costs [46].
Although most of the electricity companies in Spain were private, the Spanish government
launched the rural electrification plan, PLANER in Spanish acronym, [47] with the aim of providing
access to the non‐electrified rural population, upgrading rural power grids and contributing to the
increase in agricultural and rural electricity consumption. The programme was carried out between
1976 and 1989. Just from 1982 to 1989 [48], the amount of these subsidies reached 32 billion
pesetas (more than €700 million at current rates [49]).
In parallel to the modernization and extension of the conventional power grids,the first experiences
in decentralized electrification was carried out in the 1980s by means of renewable energies,
promoted by the National Institute for Reform and Development (IRYDA in Spanish acronym) within
the PLANER programme. Around 3 million ECU (European Currency Unit) were dedicated between
1982 and 1985 (€4.6 million at current rates, applying inflation rate) to install more than 2,200
photovoltaic systems [50] in dwellings from decentralized areas.
1.3 REVIEW OF THE DEVELOPMENT OF THE PHOTOVOLTAIC RURALELECTRIFICATION
1.3.1 Introduction
During the second half of the nineteenth century, the rising cost of coal led to the exploration of
other alternatives to replace the coal in industrial applications where thermal processes intervene.
That was how the French professor M. Augustin Mouchot developed his solar thermal system, later
perfected by the engineer Frank Shuman in US in the early twentieth century [51] (see Figure 8).
After the First World War, oil prices dropped dramatically, putting an end to the new global energy
paradigm based on this fossil fuel while technological initiatives based on solar energy were
abandoned.
18
Figure 8: Left: 1878 Universal exhibition in Paris. First parabolic trough solar collector developed by Mouchot in 1866; right: First solar‐generating plant set up in 1913 in Egypt at Maadi by Frank Shuman
The use of solar energy was absolutely forgotten for 6 decades until the 1970s, when the oil crises
of 1973 and 1979 shook the entire energy sector. Then the emerging photovoltaic technology, at
the time restricted to aerospace since in the 50s, Bell laboratories in US developed the first
photovoltaic cells, making the jump to terrestrial applications. This coincided with the first steps in
the manufacture of silicon cells at a much lower cost than existed to date (in 1971, the price of
silicon photovoltaic cells for the aerospace industry was $100/Wp [51]).
Since then, the use of photovoltaics was conceived as a possible solution to electrification in
remote areas. On the one hand, the solar resource is available, to a greater or lesser extent,
everywhere in the World and on the other hand, the photovoltaic module is an element of high
reliability and long life, which makes it ideal for use in isolated areas.
Despite these two great qualities, there have been other factors that have played against the
supposed "idealism" of the photovoltaic technology, such as high costs or low reliability of the
other system components. These negative factors have been evolving during the 40 years of PV
history thanks to the efforts of industry, researchers, installers and especially the users, who
throughout the world have been the great laboratory of the decentralized PV electrification.
1.3.2 TheSolarHomeSysteminPhotovoltaicRuralElectrification
Although the global PV market is currently shared by around 99% dedicated to the grid‐connection
and only 1% (see Figure 9) to off‐grid applications, the use of PV technology in stand‐alone systems
was, until 2000, the most extended application, mainly to provide electricity (lighting and small
appliances) to rural homes through the so‐called solar home systems (SHS). The PV rural
electrification is currently growing annually at a rate greater than 20% [52]. For example, the off‐
grid PV systems power installed in 2013 may have been more5 than 600 MW (with 500 MW
installed in China alone) [53].
5 The author have not found any source reporting reliable data about global off‐grid PV markets
Chapter 1: Introduction
19
Figure 9: Evolution of the off‐grid and grid‐connected global market. The worldwide cumulated PV installed power at the end of 2014 was 177 GWp
The solar home system has been the most used concept for mass electrification of houses in
remote areas, versus the centralized PV systems (pure or hybrid power‐plants) or commonly so‐
called mini‐grids (Figure 10).
Figure 10: Left: Village electrified by SHSs; Right: PV off‐grid power plant (both in Morocco)
The idea in favour of SHS argues that PV users invariably consume more electricity when they are
not personally responsible for the system. This concern is linked to the capacity and size of the
systems, to which the operation and maintenance factor could be added. The management of
collective structures (need of local organizations, agreements, etc) seems to be more difficult than
individual systems. However, SHS has also been imposed versus the mini‐grids for the following
reasons:
0
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% Grid‐Connected % Off‐Grid Cumuled GWp GWp
20
Standardization. The same design can be used in different homes or applications of similar ranks, which makes it easier for engineers, developers and installers;
Geographical spread. SHS can be applied in both dense and sparse populations. Mini‐grids are justified only in geographically dense villages;
Local availability of spare parts. SHS components are more standardized than those of mini‐grid power plants, so it is easier to find spare parts locally in countries where PVRE is developed, such as electrochemical batteries, regulators or light bulbs adapted to the SHSs.
An SHS is typically made up of (Figure 11) a small PV generator (35 – 100 Wp), a charge controller,
an electrochemical lead‐acid battery, several lamps and DC plugs to connect low loads, such as TVs,
radios or mobile phone chargers. These systems are usually set up to a 12 Vdc output [54].
Figure 11: Left: Solar Home System electric scheme, right: PV module of the SHS on the dwelling roof
Even though photovoltaic technology applied to rural electrification has reached a solid maturity
after 40 years of development, it still faces several problems, some of which are dealt with in this
thesis. These problems involve not only the body of the technology itself, the SHS (what we are
going to call hardware), but they mainly affect the management of decentralized services in rural
electrification (known as orgware).
To understand this issue we consider the two approaches presented below:
1.3.3 SHS:electrificationsystemordomesticappliance
Taking into account the millions of SHSs that are installed in the world, it can be said that they
consist of a standardized assembly of basic components (generator, charge controller, battery and
loads). The user, in accordance with his economic resources, can purchase an SHS, and even install
it himself in exchange for an equipment warranty. This is something very similar to buying a
domestic appliance.
To refer to an SHS as an electrification facility, similar to the conventional power grid, it must satisfy
certain requirements, which make it equivalent to the electric power grid.
The electrical service from the conventional power grids is managed by large companies that
ensure the supply through a strong system of generation, transmission, distribution and O&M. The
resources of these companies range from sophisticated media and control management to
departments with specialized technical staff, mobility and transport capabilities, intervention
Chapter 1: Introduction
21
protocols, etc. A similar deployment of resources is used for commercial issues, for example to
ensure the collection of fees to end users by means of precise energy meters, switches to which
only the companies can access, direct debit payments, billing departments, etc.
In PVRE, it is difficult to obtain these sophisticated, large and effective management tools, perhaps
due to the limited size of most of the PVRE programs, when compared with the grid, which does
not apparently justify the necessary investment. While, in general, some PVRE programs
demonstrate meticulous care in terms of the quality of the devices, they pay little attention to the
management mechanisms that must ensure the operation and maintenance of the SHSs. So it can
guarantee the quality of the PV system but not its sustainability.
As a response to this problem, many electrification experiences have considered PVRE as
something further from a service notion and closer to a domestic appliance. Thus, the figure of the
service manager is replaced by the figure of the sales and guarantee manager. This model is a copy
of the common domestic appliance market, which has the peculiarity that it has been
institutionalized within the rural electrification field.
As an example for purposes of illustration, PVRE can be compared to bicycle hire services that exist
in many European cities. The purpose of this service is to provide mobility to citizens by means of
bicycles. The bikes are apparently similar to those that we have at home, but they have certain
special features, such as the automatic identification codes for tracking, parking anchorage devices,
etc, which make them different and adapted to a management system. The user rides the bike just
like a normal one, but in parallel to a registration system, subscriptions, card payments, etc. Behind
it there is a complex (and usually expensive) management system that allows the concessionaire to
carry out the O&M of bicycles and renting facilities, and to collect the leasing charges with
guarantees (obviously the correct use of bicycles and the collection of fees is not left to the good
faith of users).
To date it has been usual in PVRE for, even in programmes configured as electric service, the SHS to
be set up in a similar way to the bicycle that we have at home, in accordance with the
aforementioned example. Thus, the O&M managers of these systems do not have any tool to
manage the service offered to their customers and there is no choice but to trust in the honesty of
thousands of SHS's users.
The result of this fact is the well‐known dilemma about whether an SHS is a domestic appliance or,
on the other hand, an electrification system comparable to the conventional one [55]. If the
tendency is to achieve the universality of the access to electricity rights, the SHS cannot be a simple
appliance purchased by the user from any dealer. If the SHS is a real electric supply system, its set
up cannot be simplified to the minimum required components, and in the same way as the public
service of bicycle renting, it will need hardware (the SHS) adapted to the management system
(orgware) to provide the necessary tools to administrate the O&M and allow the user to benefit
from a service with the same guarantees given by conventional electrification.
1.3.4 PVREastechnologicalsystem
As regards the photovoltaic rural technology, understood as a system [56], from a holistic point of
view it consists of three dimensions (Figure 12):
22
The hardware (HW), that refers to the system material body: the SHS, its components, quality,
lifetime, reliability, cost, etc.
The software (SW) is about the use of the system by the user: the consumption, the time of use of
each appliance, the signals of the charge controller and reaction of the user, etc.
The orgware (OW) is the organization model of the rural electrification programme, which provides
the electricity service to the dwellings. In this regard it is taken into account on the one hand,
whether the programme is developed through subsidies, credits, cash sales or a fee for service,
among others. On the other hand, the orgware dimension deals with programme management,
from marketing and installation of the SHSs, to the "after sales" service and the operation and
maintenance.
Figure 12: Hardware, software and orgware interactions in the photovoltaic rural technology system
This scheme, proposed and analyzed for technological systems by the Ukrainian Gennady M.
Dobrov [57] in the late 1970s, has certain peculiarities concerning the 3‐dimension interaction. One
of them is that, traditionally in technical innovation, more attention has been paid (and more
resources dedicated) to the HW and SW than the OW. This negatively affects the technological
system’s sustainability. The orgware, defined by Dobrov as "a set of organizational arrangements
specially designed and integrated using human, institutional and technical factors to support the
appropriate interaction of the technology and the external systems", plays a key role in photovoltaic
rural technology, which has been underestimated throughout PVRE history and currently still
suffers significant deficiencies.
The element that perhaps has evolved most in the PV rural system has been the hardware, both in
the quality of the SHS devices, and adaptation of international standards, and recently, in the
dramatic reduction in market cost.
•SHS components•Quality•Prices•Reliability•Installation
•User SHS know‐how•Consumption
•SHS interface•User manual
•Financementmodel (subsidies, credits, cash sales, fee for service, etc)
•Normes, tenders, engineering•ESCO: marketing, installation, O&M, fee collection•Internal skills and training•Management structure
•O&M management and costs
•Datalogger•Monitoring•Prepayment system•Technical standard•Spare parts
•Enquiries•User skills•Fee payment•O&M fees•Maintenance service
HARDWARE
ORGWARE
SOFTWARE
Chapter 1: Introduction
23
Second, the development of the software dates back to the beginnings of PVRE, when the task of
accommodating the needs and abilities of users to the management and operation of the PV
systems was the first requirement for the successful implementation of this technology. This has
remained until today, constantly adapting to new hardware advancements.
As regards the orgware, despite its developmental delay in PVRE, some of the factors that integrate
it have reached a high degree of maturity. Several management and organizational models have
been well described in the literature and applied in the field, especially since the 1990s, and they
have been studied in depth by recognized international organizations such as the World Bank [17,
58, 59, 60, 61, 62, 63, 64] or the International Energy Agency [65, 66, 67]. However, the orgware
has had several weak points during the development of PVRE, as will be discussed below.
1.3.5 EvolutionoftheHW,SWandOWinPVRE
1.3.5.1 The1960sand1970s. Hardwaredevelopment:reliabilityandcost‐effectivenessindecentralizedruralelectrification
The first terrestrial experiences of PV technology date back to the 1960s when Japan began to use
it in maritime applications (light beacons, communications, etc) [68]. Paradoxically, oil companies
such as Exxon, Texaco and Shell, among others, pioneered the use of photovoltaic solar energy.
These companies had equipped their platforms in the Gulf of Mexico with lighted beacons, which
were fed from non‐rechargeable batteries which were frequently replaced, at an operating cost of
about US$2,100 per replaced battery. In the 1970s, these companies decided to change these
accumulators for rechargeable batteries with a photovoltaic generator, thus reducing the operating
costs by 95%.
It was in 1968, in Niger, when PVRE started formally, through the installation of a system to feed a
television in the Gondel school, close to Niamey [69]. The experience was expanded to other
schools until 1977, after installing 123 PV systems. They were made up of a 282 watt peak (Wp)
photovoltaic power generator, a 40 ampere‐hour (Ah) and 32 nominal volt (V) battery, and a charge
controller to feed a television receiver of 32 W. The cost of these systems was US$3,100 per school
in 1975, with an estimating price of US$0.12/hour of television, which meant US$3.75/kWh.
Despite this enormous cost and considering that the lifetime of the PV system was 10 years (PV
manufacturers at the time gave 5‐year warranties), the solution was 4 times cheaper than the
option of using high‐capacity alkaline cells, for which the TV receivers were originally designed.
In the 1970s, Father Verspieren in Mali [70], and his organization Mali Aqua Viva [71], instigated
the first photovoltaic pumping systems programme for extracting water from wells, in order to try
to solve the disastrous situation of thousands of people affected by the severe drought that
suffered the Sahel region in those years. The use of PV pumps by Verspieren was the result of years
of bad experiences with hand pumps and diesel generators because of their low reliability and high
O&M costs. Mali Aqua Viva carried out the installation of 16 PV pumping systems (reaching a total
power of 21.8 kW) between 1975 and 1980, which was one of the first milestones of PVRE to
consolidate this technology as a cost effective and reliable alternative to diesel generators and
hand pumps.
24
1.3.5.2 FirstpromotionandR&DprogramstoreducethecostsofPV
The oil crisis was the trigger for the first political incentives for industry and research into
photovoltaic technology and its application in rural electrification. As PV was still a technology with
high manufacturing costs, a first researching phase focused on the cost reduction was necessary.
Some of these initiatives were as follows:
In 1975 the Commission of the European Communities financed the first R&D program in the field of non‐nuclear and non‐fossil fuel energies. It devoted US$6.4 million to photovoltaic conversion [72], with the aim of studying and enhancing the photovoltaic cells, to later evaluate them in several 5 kWp prototype systems [73].
In 1976, the Department of Science and Technology of the Government of India launched their Solar Cell Programme Plan with the aim of researching and developing different projects in areas such as the "development of conventional type single crystal silicon solar cells" to get 7‐9% PV conversion efficiencies. The programme was motivated by the low rate of access to electricity in India (less than 10% of the rural inhabitants). They took PV energy into account as a technological and cost‐effective solution, as alternative to the electric grid extensions. At the time a cost of US$60 billion was estimated to mass electrify 100% of the population at 1 kWp per dwelling [74].
In the mid 1970s Mexico had a rural electrification rate of 35% (10.7 million people without access to electricity). The Centro de Investigación y de Estudios Avanzados of the Instituto Politécnico Nacional carried out some projects for PV terrestrial applications against the background of the rural electrification problem. In 1976 two pilot projects were established: "the demonstration project in educational TV" and "PV for two rural telephone stations", both in the East of the Mexican Rocky Mountains, using PV modules of 7 Wp and 12‐15 V with 10% efficiency [75].
In Japan, also in the 1970s, the "Sunshine Project" had the final goal of reducing the cost of PV by a factor of 100 through 5 fields of research: silicon ribbon crystals, silicon thin film, new types of solar cells, II‐IV compound semiconductors and fundamental research [76].
In the same vein, the UK Department of Industry (DIn), the Science Research Council and the European Economic Community (EEC), started research work in the field of the PV cells in the 1970s a with the aim of reducing the manufacturing costs by half (less than £8/Wp) by means of the development of new manufacturing processes of photovoltaic cells [77].
By the mid‐1970s the first pilot projects began, which aimed to direct PV technology applications
towards decentralized electrification, integrating the software dimension while its purpose was to
electrify remote rural populations:
In 1976 in the USA, the "PV Stand‐Alone Application Project", led by the NASA Lewis Research Centre and the United States Agency for International Development (USAID), developed "universal" stand alone PV systems in order to open up a new market for rural electrification in developing countries for domestic lighting applications, water pumping, grain mills, etc. [78, 79, 80, 81].
In 1978 The United Nations Development Programme (UNDP) and the World Bank (WB) launched the UNDP funded GLO/78/004 project to develop small‐scale pumping systems for water supply and irrigation applications in developing countries [82], including field trials of systems in Mali, the Philippines and Sudan.
Chapter 1: Introduction
25
In some forums, such as the "Solar Energy for Development" conference in 1979, Varese (Italy) [83] the need for subsidies began to be discussed, with emphasis to the fact that giving PV systems to the users as a "gift" was something quite inappropriate.
In 1979, during the "Interregional Symposium on Solar Energy for Development" in Japan, the first NASA pilot experiences in the USA and Africa were set out [68]. The key factors related to the reduction in manufacturing costs were shown (between 1975 and 1978 the market price of the PV module had been reduced from US$35/Wp to US$13/Wp and it was expected that it would reach US$0,61/Wp by 1986), together with the high reliability of the PV systems, which would turn this technology into a competitive alternative versus power grids in developing countries in the short‐term.
1.3.5.3 The1980s.EvolutionaryconsolidationofHWandSW
After the first initiatives emerged in the 1970s and glimpsed the enormous potential of PV and the
brilliant expectations of cost reduction in the short and medium term, the 1980s saw the boom in
PV applications in rural electrification. The 1980s was the decade of the demonstration projects and
the beginning of the development and evolution of the 3 dimensions of the PV rural electrification
system together. Some of these projects are listed below:
Energy Demonstration Programme (EDP). The Commission of the European Communities (EC‐Commission DGXII), in addition to carrying out the first EC projects in the field of energy co‐operation overseas (Cameroon, Comoros, Syria, Jordan, Mali, Senegal, etc) [84], it launched the Energy Demonstration Programme (EDP) (15.3 million ECU [85]) in the 1980s and the THERMIE programme in the 1990s [86], from which 145 pilot projects were successfully established in European countries, installing a power capacity of up to 5.7 MW. 61 of these projects were devoted to rural electrification. The purpose of the initiatives was to encourage the photovoltaic market, reducing costs and building up a know‐how on key issues such as the quality and performance of the systems (hardware), the assessment of usage patterns and interaction with the user (software) and the funding models in rural electrification (orgware). As regards the latter, the successful experience of the French Pyrenees electrification, in which the users created local associations for financing, operating and maintaining their PV systems proved interesting [87]. Another significant demonstration project was the PV rural electrification of dwellings in Sierra de Segura (Spain), a remote location in the South of the country [88]. It involved different entities such as the regional utility, two research institutes and a PV module provider. Some of the lessons learned were that PV technology was perceived by the inhabitants as a limited electric source and they feared that getting SHS would be an obstacle to reaching the grid in the future. In addition, they were aware of the need for maintenance and were willing to pay a periodic fee to assure the energy supply [89].
4‐year Energy R&D Programme. Belonging to the EDP programme, 15 pilot projects were carried out with power of between 30 and 300 kWp, reaching almost 1 MWp. It was carried out in decentralized locations within the European Community, most of them on isolated islands such as French Guyana, Crete, Terschelling Island in Holland, Corsica, Giglio in Italy, Pellworm in Germany (with a PV power plant of 300 kWp), or Kythnos in Greece (with a 100 kWp hybrid PV‐diesel power plant) [90]. The evaluation of these projects gave rise to the publication of the first IEC (International Electrotechnical Commission) quality standards dedicated to terrestrial PV technology through the TC‐82 Committee [91].
The Navajo Engineering and Construction Authority ‐ Indian Health Service Home Photovoltaic Power Systems Project provided solar home systems to 191 dwellings on the Navajo Reserve, in the Southwest of the USA. ARCO Solar, the supplier and installer, guaranteed the SHSs to the users for a period of 3 years [92].
26
An agreement between Spanish Cooperation and Senegal in 1985 was responsible for the electrification of the Village of Noto (Senegal), which had 400 inhabitants, by means of SHSs and an 8 kW PV power plant [93].
USAID developed a cooperation solar project in Egypt to check the performance of PV
technology applied to different usages, such as water pumping, an ice‐machine, water
desalination, village stand‐alone systems and grid‐connection. The aim was to demonstrate
the economic viability and open the Egyptian market to this technology [94].
Colombia was highlighted through a boom in PV technology applied in rural electrification, with more than 6,000 SHS installed in the mid‐80s of the decade and over 10,000 telecommunications systems [95].
France began on its own PV programme in the 1980s for industrial development in order to manufacture PV modules locally reducing costs and creating a national PV market [96]. Several PVRE projects were carried out in some of its islands, for example Polinesia [97], New Caledonia, Guadeloupe and the Marie‐Galante Islands [98], even in regions from the South of France [87] by means of the EC‐Commission DGXVII programme (the Solar Energy Demonstration Projects), which also financed the provision of PV systems to electrify mountain refuges in the Alps and Pyrenees mountains [99].
Some demonstration projects were also carried out in Spain, for example the 100 kW power plant in San Agustín de Guadalix (close to Madrid) [100], 10 kW in Caravaca (Murcia), in addition to other CEC DG‐XVII projects. However, the development of a spontaneous and non‐demonstration PV market was quite remarkable. It was the largest in the world during that decade, after the United States, with more than 8,000 SHSs installed between 1980 and 1986, which represented 35% of the more than 1.6 MW installed in total in the country [50, 101, 102]. The other PV facilities were professional applications such as telecommunications (20%) or holiday homes located in the countryside (40%). The Spanish experience was studied in depth by the Insitituto de Energía Solar from the Universidad Politécnica de Madrid (IES‐UPM). For the first time the consumption profiles and usage habits of the SHSs were characterized, which contributed to the software evolution providing a valuable feedback [103, 104]. One of the most revealing conclusions was that, in general, electricity consumption in PVRE was low, which has been a common trend in many other experiences analyzed later in other countries.
The software approach was also studied in depth by researches in Chile [105], in rural communities in the North of the country (the Camarones commune), where several aspects of the software were characterized such as the different consumption habits, the available information of the users with respect the use of the system, its maintenance and procurement of spare parts, the degree of satisfaction in using SHSs, the adaptability to the electrical applications, etc. These studies conclude that social aspects must be considered before formulating and sizing the SHSs to adapt them to real needs and get wide acceptance by the users.
The importance that the software dimension gained within the technological system was
mentioned in different studies, which took into account the sociological factor [106]. Some of the
failures in the first pilot projects were justified by technical problems, for example the low quality
of SHS components, limited size of the PV system or high prices. Instead, it was common that the
real problems came from the ignorance of certain sociological factors:
even if the technology impact assessments were frequently carried out after the installation, the cases in which the studies were done before the implementation of the projects were few;
Chapter 1: Introduction
27
without the previous sociological study, it was difficult to size the system adapted to the real needs of the future users correctly;
these deficiencies in the implementation of PV rural projects caused conflicts regarding the existing social structure, so many of these projects were doomed to failure.
Some referent literature at the time approached the need to consider the maintenance and
reliability of the systems as the most important criteria when formulating PVRE projects in
developing countries [107, 108, 109]. The efficiency and reliability enhancement of SHSs, as well as
the need for technically qualified staff to carry out the maintenance services were some of the
most important issues to ensure the success of the projects. However, this key factor (the orgware)
was not paid enough attention during the coming decades.
1.3.5.4 The1990sand2000.Theorgwareevolution
During the 1990s the photovoltaic rural technology reached some maturity that crystallized in new
programs and projects, mainly in impoverished countries. Many of these electrification experiences
have been the subject of studies that have highlighted the different financing models applied in
each case. The studies published by the World Bank were outstanding, such as the "Best practices
for photovoltaic household electrification programs" [17], which, based on several real experiences
in Indonesia, Sri Lanka, the Philippines and the Dominican Republic, released the first
recommendations about the implementation of financing and management models in PVRE
programs (OW), which in theory would ensure their success.
The outstanding attention given during the 1990s and 2000s to the management models and the
orgware in general has been reflected in some studies such as the Photovoltaic Power Systems
Programme (PVPS‐IEA) [53], on the nature of the institutional and financial framework, the
implementation and financing mechanisms used and the level of capacity building and quality
assurance that affect the success of PV deployment in 16 different programs carried out in 16
countries from Asia, Africa, the Pacific, South America, Middle East [66].
The results of many of these studies agreed on the generalized lack of available information on the
performance of SHSs and projects. Some experts had realized at the time that "independent
evaluations of PV projects are scarce (and also difficult to perform), so, despite some interesting
exceptions [...], data related to technical problems on realities in the field have rarely reached the
available literature" [110].
As regards this concern, the Netherlands Energy Research Foundation was very conclusive and it
made a large assessment based on experiences from 32 countries in Africa, the Pacific, South
America and Asia. The study was articulated on the basis of the HW, SW and OW [111]. The main
conclusion of the study was the marked lack of feedback of the programs carried out and its
disastrous impact on the learning curve of the technological system.
As regards the SHS, in parallel to the proliferation of rural electrification programs, tens of technical
standards emerged, most of them for local specific projects. They served to define the technical
requirements of these programs. In order to standardize the technical criteria in one standard rule
that might serve in any PVRE programme, the Thermie B: SUP‐995‐96 initiative, carried out by the
IES‐UPM and based on already existing standards made ad hoc for real experiences in countries
28
such as Bolivia, India, Brazil, Kenya, Indonesia, etc, [112] resulted in an international quality
standard for SHSs, which is still used in PVRE programs worldwide [113].
Due to this concern about the quality of SHSs, an ambitious in‐field study of batteries working in a
large PVRE programme was carried out for the first time, with 40,000 SHSs in Mexico, with the aim
of assessing the performance of previously installed photovoltaic (PV) rural electrification systems
[114]. 555 batteries were analyzed within their first 18 months of operation. Despite the
maintenance of the systems being devolved to the users, the study demonstrated that the state of
the batteries was satisfactory (only 4% of the batteries showed malfunctioning or high
degradation).
The beginning of the century led to the assessment of many PVRE experiences carried out at the
time. The most significant programs were reviewed, from which significant conclusions were
extracted on the financing and management models that were implemented (OW). More
international technical standards for SHSs were published (HW), and the user perception (SW) was
analyzed in depth [115]. It was thus preparing for the jump to large PVRE programs.
The historical overview of the PVRE evolution shows that the orgware development during the
1990s and the beginning of 21th century was mainly devoted to the role of the financing models.
The change in scale of PVRE meant the need to mobilize large sums of money to finance the
decentralized electrification. When mobilizing funds, large financial institutions needed a good
definition and structuring of business models, which had just been defined and studied thoroughly,
with support, for example, from the WB.
In this way , the development of large PVRE programs was possible in the first decade of the 21st
century, for example in Senegal (10,000 SHS [116], where there is currently an additional
concessions programme which aims to electrify the rural regions of the country by means of 18,000
SHSs [117, 118] ), Ghana (10,000 SHSs [119]), South Africa (30,000 SHSs [120]) the PERG in
Morocco (51,000 SHSs [121]), Sri Lanka (20,000 SHSs [122, 123]), Nepal (110,000 SHSs [122]), India
(the Remote Village Electrification Programme has equipped more than 10,000 villages by means of
SHS and PV power plants as of 2013 [124]. Kenya and Tanzania (more than 320,000 SHSs have been
installed in Kenya and more than 40,000 in Tanzania as of 2013 [125, 126]), China (from 2002 to
2007, more than 400,000 solar home systems were sold in north‐western China under the US$316
million World Bank/Global Environment Facility‐supported Renewable Energy Development Project
(REDP) [127]). Also in Latin America some large programs have seen the light [119], such as in
Bolivia (60,000 SHSs), Honduras (5,000 SHSs), Peru (10,000 SHSs), Dominica Republic (3,000 SHSs)
or Argentina (30,000 SHSs).
But among all these experiences, it highlights the case of Bangladesh [128, 129, 130, 131]. From
mid‐2000 to May 2013 over 2,000,000 SHSs were installed [132], in a power range of between 30
Wp and 75 Wp per SHS. In 2013 the installation rate was 1,000 SHSs/day, therefore at the end of
2014 the operational SHSs could have got around 3,000,000 SHSs [133]. This programme is
currently the most important in the world in terms of volume. It has been developed under a credit
sales model. The keys to its success are found in the correct balance of the HW, SW and OW
dimensions, highlighting an economically affordable HW for users which is also sized to meet their
needs; an efficient microcredit funding system which is well supported by solid institutions; and an
O&M structure based on the creation of local employment through the training of technicians.
Chapter 1: Introduction
29
Therefore it is evident that the "financial model" factor has been developed in depth leading to a
worldwide phenomenon of investments, loans, financial products, etc. that has allowed the leap in
scale of PVRE programs in terms of size, which is manifested by the millions of SHSs installed in less
than 15 years worldwide (some studies estimate more than 5 million [134]).
1.3.6 StateoftheartoftheHW,SWandOWinPVRE
Throughout the history of PVRE, rural photovoltaic technology has evolved in the three dimensions
(HW, SW and OW) as summarized below:
1. The SHS (Hardware)
‐ PV modules. The most used PV technology at the beginning of PVRE was amorphous silicon (a‐Si), which was rapidly replaced by crystalline silicon (c‐Si), up to now. Other technologies such as thin‐film, CdTe, etc [135] have not still found an application niche in PVRE. The c‐Si PV module has reduced its cost by 95% in four decades, has increased its power efficiency by 2.5 (in 2014 an efficiency of 25% had been reached [136]), and the quality of the assembly components have been optimized (front glass, EVA‐tedlar encapsulate 6 , electrical connections, module insulation, etc) to obtain a long lifetime product (more than 25 years) and low degradation rates (PV manufacturers guarantee currently 80% of the PV module nominal power up to 20 years). The cost of the PV cells has been reduced from US$100/Wp in the early 1970s to less than US$0.36 today (Figure 13). The photovoltaic industry has also contributed to this reduction by lowering the production process costs, from metallurgical silicon to the assembly and lamination of the PV modules, in addition to the enhancement of its efficiency.
Figure 13: The price evolution of Silicon PV cell (in US$ per watt). Source Bloomberg, New Energy Finance & pv.energytrend.com
6 The Ethylene‐vinyl acetate (EVA) and the Polyvinyl fluoride (PVF, known by the trade mark Tedlar®) are two polymers used for PV module encapsulation
30
‐ SHS components (Balance Of System):
i. The solar battery. The technology of electrochemical lead‐acid batteries has not significantly changed in 4 decades. The deep‐cycle lead‐acid battery, used in stationary applications such as telecommunications since the 1970s, has been the most adapted battery for PV systems. However, the usual budget constraints linked to the local unavailability of deep‐cycle batteries in many developing countries has extended the use of start‐lighting‐ignition (SLI) batteries in PVRE programs due to its low cost.
In the field of PVRE the most significant progress in storage technology has been the use of VRLA (valve‐regulated lead‐acid) batteries, known as "free maintenance", which have a gel‐electrolyte, thus they do not require the periodic filling of water to keep the electrolyte. This aspect makes the VRLA very attractive in decentralized electrification as it represents a significant lowering of the maintenance costs.
The lead‐acid battery, with over 100 years of existence, has very little chance nowadays to reduce its cost. Rather, the lead, as major component of the battery, is a metal which is becoming more expensive every year. The hope of reducing the cost of the SHS batteries is the development of new technologies, such as lithium‐ion, but this solution seems to be still far from becoming an economically viable alternative.
ii. Charge controllers. The evolution of this device has basically been an improvement in the control algorithms and adaptation to the SHS‐user system. On the one hand, the electronic progress has led to PWM control (Pulse‐Width Modulation), the voltage thresholds in charging and discharging considering the temperature and the setup of algorithms presumably adapted to the charge and discharge curves of the batteries. In recent years the maximum power point tracker (MPPT) technology [137] has been imposed, especially in medium‐sized controllers. On the other hand the user interface is becoming more "friendly" through the implementation of LEDs and acoustic signals or digital displays from which information about the battery status, circuit faults, etc. can easily be obtained.
iii. Lamps. Lighting is the main load in SHSs. Even if lamps are not a part of the energy generator, they become part of the system. The importance of lamps is that the performance of the SHS depends on the quality of its loads. Typically SHSs run at 12 VDC, so the lamps must be adapted to that voltage, and their consumption very low, according to the size of the SHS [138]. The lamps have evolved from early fluorescent tubes to the later compact fluorescent lamps (CFL) and the current LED lamps. This development has led to more reliable lamps, larger lifetime, cost reduction and better quality of lighting [139].
‐ Quality: PVGAP (Global Approval Program for Photovoltaics), IEC (International Electrotechnical Commission) or Thermie‐B are some of the initiatives carried out throughout the three decades, which have generated a wide set of technical norms and quality standards as regards PVRE [134, 140, 141]. The IEC has published since the founding of the TC‐82 technical committee for solar photovoltaic energy systems in 1981, the largest collection of technical standards relating to both the photovoltaic technology and PV systems and components. Specifically, the IEC TS 62257 series [142] is devoted to PVRE and aims to provide different players (such as project implementers, contractors, supervisors, installers, etc.) the foundations for the setting up of renewable energy and hybrid systems with AC voltage below 500 V, DC voltage below 50 V and power below 50 kVA.
The role that these standards have played in PVRE has been called into question by different authors [110] due to their effectiveness which could often not be demonstrated, among other things because the decentralized nature of PVRE has not allowed the required feedback from these in‐field experiences to be obtained, which would be necessary in a
Chapter 1: Introduction
31
correct process of developing standards. Furthermore, the behaviour of rural users is difficult to standardize, and difficult to simulate in the laboratories.
By the mid‐90s, under the Thermie‐B program, The Universal Technical Standard for Solar Home Systems (UTSfSHS) was released as the result of an ambitious survey of experiences in the field, resulting in a set of standards and recommendations that are still applied today in PVRE programs (Peru, Bolivia, Morocco, Tunisia, among others)7. The UTSfSHS guarantees the quality and proper operation of the SHS components as well as proposing easy and cheap quality control procedures to check the SHS performance "in situ", with no need for prestigious laboratories far from the locations where PVRE programs are developed.
‐ Installation: as with the SHS components, their installations and connections have to fulfil several quality criteria to ensure an optimal performance of the system. These criteria are compiled in international standards such as the aforementioned UTSfSHS. This issue was one of the first concerns that were addressed in terms of quality at the beginning of the development of SHSs and has been the object of several publications [143].
‐ Reliability: it has been indicated that the PV module is a very reliable device, its failure rate is very low and its lifetime very long. However, the other components of the system have not enjoyed the same features. For example, it is said that a battery has a lifetime of 3 to 10 years, according to some factors such as its quality, kind of technology or even its cost. The same applies to the charge controller or lamps. But, in rural electrification there is another factor that affects the reliability of SHS: the user. In a PVRE programme with thousands of SHSs, the users' behaviour as regards SHS will largely determine the possibility of having more or less failures depending on the good or bad use of the system.
To date, there are no studies reporting the reliability of SHSs working under real conditions and considering the intervention of the user, so this component of the hardware is one of the outstanding pending issues in photovoltaic rural technology.
2. Use of the SHS (software).
The trend over the 40 years life of PVRE as regards software has been:
The user should be familiar with both the operation and the limitations of the SHS
The SHS interface should be as clear as possible so that the user is able to diagnose the state of operation of the system
The user must know the procedure to follow in case of failure (warning the ESCO)
The few reported experiences show that consumption is in general lower than expected but they gradually grow as users become more familiar with the system and get new appliances
The size of the SHSs is a controversial matter since the needs perceived by the users rarely match those considered by engineers and promoters. For example, lighting is often considered a priority for rural inhabitants, while they may prefer to have access to TV.
3. The management of the rural electrification programs (Orgware)
The good use of SHS by the users and their correct operation and maintenance are aspects linked to how the PVRE programs are designed and configured (orgware). Some of the first experiences devolved the maintenance responsibility to the user, giving very poor results. Other
7 Own sources.
32
programs have persisted in this practice by supplementing with a period of warranty service that could be of 2 years or more.
In the so‐called fee for service model, in which specialized technicians are responsible for the maintenance in exchange for a fee charged to the user, she/he only receives training on the proper use of the system. The warranty and maintenance falls to the concessionaire energy service company (ESCO).
The wide range of organizational models [144] that have been used to develop hundreds of PVRE programs worldwide in the last 4 decades is due to the presumed well‐intentioned will of their promoters in order to adapt the programs to the social and economic realities of the rural communities. The first experiences were pilot projects, as has been mentioned above, many of which remained at that stage and few gave rise to large‐scale projects. Non‐governmental‐organizations (NGOs) implemented programs in which the SHS was given to the user as a gift, after a technical training addressed to the user in order to be responsible for the maintenance. The experience led to some authors to advise against this practice due to the maintenance not being carried out properly and the SHS not being appreciated enough (simply for being free) by the user and then the SHS had the risk of being abandoned.
The cash sales model was implemented in the 1990s in Kenya, Tanzania and Uganda [145, 126, 146, 147, 148] with great success in terms of the number of SHSs sold. The model has been replicated in other countries with varying degrees of success. This model treats the SHS as a domestic appliance. To run the model it is necessary for people to have a high purchasing power, which is not common in most rural regions without access to electricity in the world. So, this model is geographically limited. As mentioned above, with the goal of increasing rural electrification ratios by means of access to lower‐income households, a new innovation has been introduced: the pico‐system. These systems are currently being commercialized in countries where the cash sales model has been successful [149], reaching a target of customers with lower resources.
Based on the low income of rural inhabitants, this concern has been addressed by micro‐credit schemes. Micro‐credits are usually used for small business activities, but they are granted for SHSs in countries where favourable social and cultural conditions ensure the repayment of loans even if using an SHS is not a profitable activity. This model is running with enormous success in India and Bangladesh, 2 countries with the largest PVRE programs in the World. The success when extending this scheme to other countries has not been demonstrated yet.
Finally, the fee for service model is generally based on subsidizing much of the cost of the SHS and then the user pays the rest. A specialized energy service company (ESCO) who installs the SHSs will be responsible for their maintenance for 10 years or more, and receives a fee from the user (usually monthly). This model would be the one closest to the notion of a public utility service.
In addition to these factors relating to financial issues of the orgware, there are other questions linked to the operation of the photovoltaic rural technological system. The sustainability of the programs requires a number of factors which are still in an underdeveloped state, and which have been the cause of failure of most them:
Monitoring: A 10‐year O&M activity needs a constant feedback in all aspects: technical, economical, etc.
Maintenance structure: to date the cost and the necessary size of the operation and maintenance structure for providing electricity in decentralized rural environments is still not known. This can be considered one of most significant technical challenges in PVRE which has been responsible for the lack of economic sustainability in most PVRE programs
Chapter 1: Introduction
33
Spare parts: the reliability of the SHS components are not known when they operate in real conditions. Thus the forecasting of spare parts through the programme lifetime is not available. This concern affects the design of the maintenance structure and the profitability of the programme
Fee collection: as most of the programs carried out to date have not considered a hardware adapted to the management of non‐payment cases, the ESCO has to devote many resources and time to collecting the fees, with long, frequent and recurrent displacements, even to the dwellings, where it is often not easy to meet the customers or gain to access to the houses. In response to this problem some experiences have integrated a control system of payments into the hardware, such as prepayment cards [126, 150, 151], or the "pay as you go" strategy [152, 153], among others. These innovations have had limited impact and effectiveness to date. In addition PVRE tends to minimize the investment costs, however these innovations tend to increase the capital costs.
1.3.7 ThechallengeofPVRE
After this assessment and a review of 40 years of PV rural technology development the following
conclusions can be extracted:
‐ Progress in the technology has been affected by the gap in the development of the three dimensions. Both the HW and the SW have co‐evolved since the early 1970s and it was not until the 1990s that the OW started to play an important role in PVRE. Some authors argue that when introducing new technologies into human communities, the OW and SW should go ahead of the HW in order to "prepare" the receiver for the new technology and ensure that he will adopt it successfully [154]. In PVRE the opposite has happened.
‐ Despite the integration of the OW into the technological system, the implementation of this dimension has been arduous. A widespread case in PVRE has been the lack of promotion and awareness addressed to the future users, which is generally a source of problems related to the bad use of the SHS and consequently the cause of failures and non‐payments of the fees to the ESCOs.
‐ The poor integration of the rural PV system elements between the 3 dimensions is the cause of the lack of sustainability of PVRE programs. Another illustrative example is the economic imbalances of the ESCOs in many PVRE programs, due to the low fees paid by the users. The "fee", which can be collected monthly, is intended to cover the maintenance costs. It is an orgware element, since it determines the economic viability of the operation and maintenance service. If the quota is set incorrectly, the system will have a financial imbalance that would wreck the programme.
‐ Finally, the lack of feedback or monitoring leads to ignorance of the effectiveness of the
measures taken for the programme development. If there is no feedback during the O&M
phase, the replacement rates of the SHS components are unknown, as well as the lifetime of
the systems, the degree of satisfaction of the users, the economic viability of the O&M, etc.
As the funding mechanisms for PVRE are well defined and have a good monitoring, the same
care during the operation phase would be desirable. But this element has implementation
problems in remote areas with difficult access and poor communications. Only a very well
organized structure with sufficient and adequate resources to develop the activity over a
long period of time can ensure the necessary feedback for the system.
34
Thus it could be argued that photovoltaic rural technology has reached a remarkable maturity in
the HW and SW dimensions, except HW adaptation to the notion of a public utility service and the
lack of understanding of the real reliability of the SHS components. The OW, however, has
progressed well in some of its factors, such as the financing models, but it has still serious
limitations in matters relating to the sustainability of PVRE programs, firstly due to the lack of
feedback, and secondly, because there is still no paradigm concerning the design of specific
maintenance structures for decentralized environments. The lack of both the reliability of the SHS
working under real conditions and the O&M costs left without tools for those responsible for the
programme when designing the maintenance structures.
So far, both the public body responsible for the formulation of electrification programs and private
companies charged with implementing them, have designed the maintenance structures based on
theoretical estimates, such as those assuming that the annual maintenance cost corresponds to 1%
‐ 3% of the capital cost (investment) [155, 156, 157], or fitting the maintenance costs to the
remuneration obtained from the user fees, which were previously established according to the
economic possibilities of the users or calculated from what was previously spent using conventional
lighting systems, such as candles, kerosene or others.
This situation reflects the lack of a paradigm on the O&M in PVRE programs. Many of the programs
carried out so far imposed, apparently, low fees, such as South Africa [120] (monthly fee: 6
US$/SHS∙month), Zambia [158] (12 US$/SHS∙month), Peru [159] (5 – 8 US$/SHS∙month), Tunisia
[115] (5.2 US$/SHS∙month) or the Pacific Islands [17] (5 US$/SHS∙month). Note that the dispersion
of the fee's can also be intended as an indicator on the immaturity of the paradigm. The experience
has proved that many programs have experienced economic imbalances in the operation phase as
the user fees did not cover the real costs of the O&M, after which the ESCO abandoned the
programme, leaving thousands of SHSs without a maintenance service [17, 120, 158, 160, 161].
Therefore, the O&M is, in general, a more expensive activity than expected; moreover, the fees
paid by the users for the maintenance service are generally lower than necessary. These two facts
lead to an unsustainable financial situation of the PVRE programs.
Thus, the current challenge is to ensure the sustainability in PVRE programs, introducing the notion
of public service in the decentralized rural environment in order to achieve the paradigm in which
the conditions that make the global access to electricity affordable will be defined.
This PhD thesis will address some of the identified problems for PVRE sustainability, as shown in
Table 3:
Table 3: PV rural system factors discussed in this work
HARDWARE Reliability of the SHSs working in real conditions.
SOFTWARE O&M tariff sizing adapted to the real maintenance costs.
ORGWARE Design of maintenance structures for decentralised environments. Characterization of the O&M cost structure.
Chapter 1: Introduction
35
1.4 OBJECTIVESOFTHETHESIS
The general objective of this thesis is to contribute to the technical and economic characterization
of large PVRE programs, including the O&M phase to ensure their sustainability.
This objective is broken down into the following specific objectives:
‐ Determining the real reliability parameters of the SHS components working under real conditions in which the "user" is involved
‐ Characterizing the actual operation and maintenance cost of a real PVRE programme
‐ Studying the battery and PV module degradation when working under real conditions within a PVRE programme
‐ Establishing the design criteria to optimize the maintenance structures in PVRE programs.
1.5 METHODOLOGYOFTHEWORK
To achieve the proposed objectives a wide experimental work based on the data collected during
the 5 years of development of a real PVRE programme carried out in Morocco with more than
13,000 SHSs installed and managed by an ESCO in a vast region of more than 200,000 km2 has been
carried out. A great effort has been dedicated to the assessment of a database with more than
80,000 inputs related to the technical data of the maintenance phase, in order to carry out a
comprehensive reliability study of the SHSs.
Furthermore, both in‐the‐field experiments have been conducted in several SHSs belonging to the
Moroccan PVRE programme in order to study the power degradation of a PV modules sample after
6 years of operation and the capacity degradation of a sample of batteries which have been tracked
for 18 months. Both have been working in real SHSs of the programme. In the case of the battery
assessment, several electrical operation parameters have been collected weekly and the battery
capacities have been measured every 6 months.
The second line of work has addressed the characterization of the management and O&M cost
during the same 5‐year period, based on the accounting records from the same ESCO.
Finally, a mathematical model has been developed based on a mixed integer linear optimization
with the aims of designing maintenance structures adapted to the special criteria concerning the
PVRE activity, illustrating its functionality through several examples from the Moroccan
programme.
1.6 THESISSTRUCTURE
The thesis is structured as follows:
Chapter 2: A brief description to the Moroccan electrification programme, known as PERG, because
all the experimental work of this thesis has been articulated around this programme.
Chapter 3: The description of the procedure carried out for the reliability study of the SHS
components, from the debugging of the maintenance database to the study results and application
examples.
36
Chapter 4: The results of the in‐the‐field experiments related to the degradation of PV modules and
batteries working under real conditions.
Chapter 5: The characterization of the real costs corresponding to the first 5 years of development
of the PERG programme and to the forecast for 10 years of O&M.
Chapter 6: The modelling process of the decentralised maintenance structures, based on a mixed
integer linear optimization, as well as its application to several regions of the Moroccan
programme.
Chapter 7: Summary of the most significant contributions of this thesis in terms of publications and
some possible future directions of research.
Bibliography: references and bibliography referred in this work.
CHAPTER 2
THE MOROCCAN PV RURAL
ELECTRIFICATION PROGRAMME
38
2 THEMOROCCANPVRURALELECTRIFICATIONPROGRAMME
2.1 INTRODUCTION
The research work of this PhD is based on a real PVRE experience. The PVRE programme chosen has
been one of the concessions of the Moroccan Rural Electrification Global Programme (PERG in the
French acronym) which installed more than 13,000 SHSs in 3 years, disseminated in around 200,000
km2 in the South of the country. This programme belongs to a global initiative managed by the
Moroccan national utility to provide access to electricity by means of grid extensions and stand
alone systems to almost 100% of the rural inhabitants.
The PERG programme is paradigmatic because, despite being formulated in a careful manner in
terms of financing and organizational schemes, supported by previous studies in social,
demographic, technical and economical issues, the Solar‐PERG concessionaries (ESCOs)
experienced serious financial problems when carrying out their work during the maintenance
phase. These problems have led to most of the ESCOs leaving their concessions because of financial
imbalances.
This chapter describes the Solar‐PERG concession assigned to the private ESCO ISOFOTON (it will be
referred to as Solar‐PERGISO). Being a public‐private‐partnership (ppp) between the ESCO and the
national utility, the development rules of the programme are set out, as are the objectives of the
concession and the real achievements and main barriers encountered during the implementation
and operation.
In the operative frame, ISOFOTON was responsible for selling the SHSs directly to the final users
through a fee for service mechanism, as well as its supply and installation within the 3 first years of
the programme (from 2006 to 2008). The installed SHSs were subject to a 10‐year maintenance
period. The ESCO must guarantee the systems during this period and must repair or replace
damaged components. The ESCO was also responsible for collecting the monthly fees that the users
must pay for the maintenance service.
The maintenance and cost databases in which almost all the experimental work of this thesis has
been based are described and explained at the end of the chapter.
2.2 THEPERGPROGRAMME
In 1995, more than 82% of the Moroccan rural population lived still without access to electricity,
that is, around 10 million people. The Government of Morocco declared universal rural access to
electricity as a political priority and in 1996 began supporting the implementation of the Rural
Electrification Global Programme. After this great effort, the electrification rate in Morocco is
currently 98.5%.
Chapter 2: The Moroccan PV Rural Electrification Programme
39
During this period (1996 ‐ 2013), the PERG programme gave access to electricity to 2,027,120 rural
households in 37,099 towns by means of electric grid extensions and 51,559 more by means of
solar home systems in 3,663 towns (the Solar‐PERG) [162]. These achievements have been made
through the construction of 42,900 km of Medium Voltage lines, 111,700 km of Low Voltage lines
and 21,650 MV/LV transformers (a power of more than 1,500 MVA). Moreover, for the off‐grid
electrification, 51,559 solar home systems have been installed with a mean peak power of 60
Wp/SHS (more than 3 MWp installed).
The PERG was promoted by the ONEE (Water and Electricity National Office), the National Utility,
who needed the financing of more than €2.27 billion to complete the programme, from which,
around €1 billion came from international institutions. However, it is worth mentioning that local
authorities have greatly contributed to financing the programme, although these figures rarely
appear in the published summaries.
The ONEE established the financial terms that would apply in the PERG development. In the case of
the grid electrification, the financing model determined that the users paid 2,500 dirhams (MAD)
for the subscription (grid connection)8, the local municipality contributed 2,085 MAD/connection
and the remaining cost would be covered by the utility (the ONEE) until a fixed maximum threshold
per household, set out in Table 4, that varied during the four consecutive phases of the
programme.
Table 4: Maximum threshold cost for household grid connection
Period PERG phase Maximum threshold cost per
household (MAD)
1996 ‐ 2002 1 & 2 10,000
2002 ‐ 2004 3 14,000
2004 ‐ 2006 4 ‐ 1st phase 20,000
2006 ‐ 2016 4 ‐ 2nd phase 27,000
The PERG rules dictate that when the grid connection cost to electrify a rural household exceeded
the mentioned maximum thresholds, the house would be electrified by solar energy, unless the
local authority covered the additional costs.
At the beginning it was estimated that 150,000 households would be equipped with SHSs [163]. At
the end of the programme, just 51,559 homes had been electrified by means of PV systems, and
not only that, most of these solar households are currently being connected to the grid. It can be
deduced that more than 100,000 households have been connected to the electrical grid exceeding
the threshold cost, reaching amounts that sometimes exceed 90,000 MAD/connection. Overall, the
global cost of the PERG may have been close to €3.5 billion (taking into account the local
authorities financing), in addition to €0.86 billion corresponding to the user subscriptions and the
municipality contributions, what means an average PERG cost of €2,000/household.
8 1 dirham (MAD) = 0.09272 euro (€) exchange rate at 04/12/2014
40
2.3 THESOLAR‐PERGORIGIN,DEVELOPMENTANDFEATURES
The technical definition and financial arrangements of the Solar‐PERG were based on the evaluation
of a previous programme, called PPER (Rural Electrification Pilot Programme), which was the first
attempt at establishing a programme in the field of off‐grid rural electrification in Morocco. It
electrified 1,500 dwellings in 30 different villages from 3 provinces between 1996 and 2001. After
that, the Solar‐PERG was established as a fee‐for‐service model in which the management of the
projects would be delegated to private energy service companies (ESCO) in a public‐private‐
partnership with the ONEE [164, 165]. The concessions to the ESCOs were made through several
tenders covering different regions of Moroccan territory. There were 4 different tenders between
2002 and 2005, whose awards are detailed in Table 5 and Figure 15:
Table 5: Solar‐PERG concessions and achievements
TENDER ESCO SHSs
OBJECTIVE SHSs
INSTALLED9 PROVINCES
OFF‐PERG Various ‐ 5,387 2002 ‐ PERG I TEMASOL 16,000 16,000 (100%) 4
2003 ‐ PERG II SUNLIGHT POWER MAROC 12,000 6,513 (54%) 3 BP SOLAR MAROC 4,000 950 (24%) 1
2004 ‐ PERG III TEMASOL 37,000 7,609 (21%) 20
2005 ‐ PERG IV ISOFOTON 34,500 13,600 (39%) 13 TEMASOL 5,500 1,500 (27%) 5
TOTAL Solar‐PERG 109,000 46,172 (42%) 46
TOTAL Solar‐PERG + others 51,559
The installation process was carried out according to the chronological scheme showed in Figure
14:
Figure 14: Solar PERG chronological scheme for the annual SHS installed
9 Some of the figures are approximate.
1500385 976 1308 1218
5070
83229533
5248
26911658
50
3929
45395132
0
2000
4000
6000
8000
10000
12000
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
PERG ISOFOTON
PERG other ESCOs
Before PERG
Number of SHS installed
Chapter 2: The Moroccan PV Rural Electrification Programme
41
Figure 15: Distribution of the Solar‐PERG concessions between the different ESCOs
Figure 16: Solar‐PERGISO local agencies distribution. The different colours indicate the covered area by each local agency
Morocco has a surface of 446,550 km2 (we consider the international recognition of Morocco
without the Western Sahara territory), so the mean geographical density of SHSs belonging to
Solar‐PERG corresponds to 0.1 SHS/km2. This extremely low geographical density of systems has
been one of the barriers that the ESCOs had to face.
42
In the operative frame, the ESCOs were responsible for the marketing, sales, installation and the
operation & maintenance of the SHSs in accordance with the following principles:
The SHS cost is subsidized 90% by the utility. The remaining 10% is paid by the user through
a fee collected by the ESCO.
There were different kinds of SHSs (Table 6), depending on PV power and service charges,
whose choice corresponded to the users.
The user signs a subscription contract with the ONEE, and a second contract with the ESCO
and the ONEE for the O&M service.
The delay in installing the SHS is 2 weeks from signing the contract and paying the
subscription fee.
The SHS ownership remains with the ONEE utility.
The ONEE inspects the new installed SHSs. If favourable, the ESCO will issue an invoice.
Table 6: Different SHSs offered in the Solar‐PERG programme
TENDER PV power Services User connection fee in € and (MAD), taxes
included
Monthly O&M fee in € and (MAD), taxes
included
PERG I&II
50 Wp 4 lamps + 1 socket (12 V)
69 (700) 6 (65)
75 Wp 6 lamps + 1 socket (12 V)
167 (1,800) 9 (96)
100 Wp 8 lamps + 1 socket (12 V)
287 (3,100) 12 (129)
PERG III&IV
75 Wp 4 lamps + 1 socket (12 V)
83 (900) 6 (65)
200 Wp 4 lamps + 3 socket (12 V) + 1 fridge
370 (4,000) 14 (150)
Figure 17 PERG III&IV standard 75 Wp SHS scheme and components description
Chapter 2: The Moroccan PV Rural Electrification Programme
43
Despite the variety of SHSs, almost 100% of the SHSs installed in phases I and II were 50 Wp power
systems and 75 Wp for the phases III and IV (the smaller systems), which means that, in general,
users prefer low costs systems.
The O&M contract establishes the user and ESCO obligations for a period of 10 years, which are
detailed in Table 7:
Table 7: Clauses of the O&M contract for the user and the ESCO
USER ESCO
Respect of the SHS use rules
Payment of the O&M fee every month
Payment of surcharges when there is payment delay
Contact the ESCO when failure or malfunction of the SHS
Allow entry to the house to the ESCO technicians
Train the user to use the SHS
Collect the O&M fees
Visit each SHS every 6 months for preventive maintenance
Repair the SHS failures or malfunctioning within 48 hours after user claim
Pick up (dismantling) the SHS after 3 months of non‐payment of the O&M fee
It is worth mentioning that the ESCO BP‐SOLAR, concessioner of 4,000 SHSs in 1 province
(Chichaoua), that finally installed less than 1,000 SHSs, used a prepayment system for collecting the
monthly maintenance fees, based on a rechargeable electronic card that users had to take to the
ESCO staff, and after recharging, to insert it into the charge controller. There was no feedback
about the performance of the prepayment system since BP‐SOLAR was the first ESCO to abandon
the programme because of economical imbalances.
2.4 THEISOFOTON‐PERGPROGRAMME
The study of this PhD is based on the experience of the ESCO called ISOFOTON, marked in green in
Figure 14, which installed 13,600 SHSs between 2006 and 2008 in 13 different provinces, as shown
in Figure 15.
The Solar‐PERGISO region is geo‐morphologically characterized to be located, partly, in a
mountainous area (50% of the region is covered by 3 mountain ranges: the Medium Atlas, the
Grand Atlas and the Antiatlas), and partly by wide desert areas (Table 8). These features give rise to
difficult accessibility in the region and a wide dispersion of villages and households.
Table 8: Geomorphological distribution of the region
PERG‐ISOFOTON
surface Mountains Hills Desert Plain
km2 214,531 109,636 2,990 79,148 22,757
% 100% 51.1% 1.4% 36.9% 10.6%
The extremely low geographical density of SHSs was a remarkable obstacle for the ISOFOTON‐PERG
development. The average density of SHSs in the region was 0.068 SHSs/km2, which means that
there is 1 SHS per 14.7 km2. There are just two provinces, Al Kalaa des Sraghna and Beni Mellal,
44
whose geographical density is more than 0.4 SHSs/km2. In the vast majority of the region, the
density is less than 0.1 SHS/km2, coinciding with the most mountainous and desert areas.
ISOFOTON deployed a structure to manage the programme for each of its two phases:
Marketing, sales and installation phase (3 years)
O&M phase (10 years)
This management structure was made up of the headquarters and warehouse in Casablanca and 9
local agencies dispersed throughout the Solar‐PERG region. The staff was made up of executive
managers, accountants and administrative employees in the headquarters in addition to
commercial and technical staff in the local agencies.
Table 9 and Figure 16 summarize the distribution of the 13,600 SHSs in the different provinces and
indicate the surface and the geographical density of the systems. The local structure for the O&M
phase was made up of 9 local agencies, 43 employees and 19 vehicles. It should be noted that,
although 13,600 SHS were installed during the 3 first years of the programme, after the installation
phase, that figure was reduced to 13,449 due to the cancellation of some contracts because of lack
of payment. Thus, the O&M phase was developed for that latter figure.
Table 9: Summary of the O&M structure location (Local Agencies) in the different provinces of the PERG programme. The provinces’ areas and the installed SHSs are also indicated.
Provinces Province Capital
Area km2
Number of SHSs
Density (SHS/km2)
Local Agency location
TOTAL ‐ 214,531 13,600 0.063 9
Ben Slimane Ben Slimane 2,760 889 0.311 Ben Slimane
Errachidia Errachidia 59,585 968 0.016 Errich
Beni Mellal Beni Mellal 6,638 2,754 0.410 El
Ksiba
Azilal Azilal 9,800 1,817 0.185 Azilal
Al Haouz – Marrakech
Taghnaout 7,883 868 0.109 Ait Ourir
Al Kalaa des Sraghnas
Al Kalaa des Sraghnas
10,070 4,445 0.437 Ben Guerir
Ouarzazate – Zagora
Ouarzazate 55,298 845 0.015 Ouarzazate
Taroudant Taroudant 16,500 697 0.042 Taroudant
Tiznit – Guelmim – Assa‐Zag
Tiznit 45,997 317 0.007 Tiznit
The choice of the location of the local agencies by the ESCO management staff was down to logistic
and administrative reasons. This is why some of the agencies were located in the capital of the
provinces, close to the ONEE’s bureaus, banks and regional government offices. Nevertheless, other
agencies were based in rural community centres to be closer to the PERG users, such as in
Errachidia, Al Kalaa des Sraghnas, Al Haouz or Beni Mellal.
Chapter 2: The Moroccan PV Rural Electrification Programme
45
The local agency serves both as the executive office and warehouse. One administrative employee
is in charge of the administrative tasks and remains permanently in the agency. The SHS' spare
parts are stocked in the warehouse, where the O&M technicians pick them up for the maintenance
and return the failed components from the in‐the‐field SHSs. The O&M teams are made up of two
technicians and one vehicle.
2.4.1 THEISOFOTON‐PERGSHS
The SHSs installed by ISOFOTON were mainly the 75 Wp power system kind. Just 30 of the 13,600
systems were of the 200 Wp typology. The 75 Wp SHS components are summarized in Table 10.
Table 10: 75W Solar‐PERGISO SHS component description
Qty Description Picture Qty Description Picture
1
75 Wp monocrystalline photovoltaic module
1 15 A PWM charge controller
1 150 Ah C20 modified SLI battery (12 V)
3 7WDC LC lamps
1 11WDC LC lamp
The SHS was sized for an autonomy of 5 days (tender condition), which means that considering 150
Ah as nominal capacity (Cnom), and a designed depth of discharge DOD = 40%, the design load was Ld
= 12 Ah/day, which corresponds approximately to the use of all the charges for 2 hours every day.
The SHS kit comprised a schematic manual for the user. It was a poster in Arabic installed close to
the charge controller attached to the indoor wall (Figure 18).
2.4.2 THEISOFOTON‐PERGPHASES
2.4.2.1 MARKETINGANDSALES
The commercial strategy to sell the SHSs was based on three approaches: the collective marketing;
the door to door sales; and the institutional approach.
In the first case, the collective marketing was carried out in the local markets (the so‐called souks)
organized once each week in the Centre of the Rural Communities10. A commercial team, by means
10 A Rural Community is a small region that comprises several villages and has an Administrative Center. Each Moroccan Province is made up of several Rural Communities, or Prefectures for the urban cities.
46
of a prototype of the SHSs (Figure 19), promoted the Solar‐PERG programme and tried to get
subscription contracts.
The door to door consisted of the commercial teams visiting the rural dwellings in order to get to
know to the future customers. This sales method required a great deal of effort to move to the
dwellings, which supposed a high economic cost. The O&M technicians used to do the door to door
sales when they visited the villages for the maintenance actions.
The institutional approach was based on the contact with the local authorities to get the necessary
support for the Solar‐PERG promotion (Figure 21).
These three commercial approaches were dependent on each other. For example, it is very usual in
the rural communities of Morocco for decisions not to be made at the individual level, but within
the collective sphere. In general, a family does not decide to install an SHS if the other neighbours
decide not to do the same thing. For this reason, the door to door was effective only when all the
inhabitants were previously convinced by the officers from the municipal or regional governments.
Even then, the Solar‐PERG programme had a generally negative response from the rural population
as they wanted to be electrified by the electrical grid, and not by means of solar systems. So, the
support of the local authorities was very important, in those cases in which these authorities were
not against the solar electrification.
However, despite the big efforts made by the ESCO in terms of commercial activity, the number of
SHSs installed remained well below the initial target (13,600 against 34,500 SHSs). Moreover, the
PV electrification was considered by the population as a temporary solution, waiting for the
definitive grid electrification, which currently is being carried out. This great gap between the
objective and the real achievement can be considered as a paradigmatic case regarding the
weakness of the assumptions on which the PVRE programmes are based.
2.4.2.2 INSTALLATION
After the subscription of a new customer and the signing of the contract, the ESCO delivered the
new contracts to the provincial office of the ONEE to be signed by the utility. In few days the ESCO
picked up the signed contracts from the ONEE and had a delay of 15 days to make the installations.
The installations were planned by the ISOFOTON local agency (LA) manager and supervised by the
headquarters staff. The SHS kits were stored in the local agency. Each morning, the technician
teams departed from the LA with a vehicle together with the solar kits to be installed and the list of
new customers.
The installation follows the ONEE reference prescriptions in terms of quantity and quality of the
components (Figure 22). In fact, in each province, an ONEE technical team went every month to the
rural villages for the commissioning of the new installed SHSs (Figure 20).
The installers, after finishing the installation, trained the users, often women and children, in the
use of the SHS, the meaning of the charge controller indication lights, and the procedures for
paying the O&M monthly fees and how to warn the ESCO when the SHS fails or malfunctions.
Chapter 2: The Moroccan PV Rural Electrification Programme
47
Finally, the SHS kit also included a record sheet in which the ESCO must register the maintenance
visits, indicating the date of the visit and the incidents that occurred.
2.4.2.3 O&M
The O&M period of a SHS began when the installation was accomplished. During the first 3 years,
ISOFOTON deployed a structure to cover all the activities: commercial, installation and O&M. When
the installation phase was finished, the structure was adjusted to just the O&M activity.
The maintenance comprised both the preventive and the corrective maintenance (PM and CM).
The preventive maintenance (PM) consists of checking the SHS performance. The battery must be
filled with distilled water if necessary, the PV module cleaned, the electric connections checked and
failed lamps replaced. The PM is a deterministic process as each SHS must be checked every 6
months, according to the Solar‐PERG rules. The maintenance technicians recorded the date of the
visit on the maintenance record sheet.
The corrective maintenance (CM) is carried out after prior notification by the user when she/he
notices a problem in the SHS operation. There was a free phone number, but they usually
contacted the local agency or the technicians directly when they visited the weekly markets. Then,
the technicians went to the dwelling, within 48 hours, to repair the system or replace the failed
components and return to start the SHS. The corrective visits were also recorded on the
maintenance record sheet.
The fee collection was carried out during the maintenance visits, in the local agency, or mainly in
the weekly markets organized in the centres of the rural communities (r), the souks. These
traditional souks attract most of the surrounding rural population and are the best places to meet
the SHS users, collect the monthly fees and replace failed lamps that users bring from their
dwellings. Note that lamps are the only SHS components that can be replaced in the souks.
The maintenance technicians are in charge of collecting the fees in the souks every week. They
spend the morning at the souk and the afternoon is dedicated to the maintenance activity in the
surrounding villages.
In some regions, there was a remarkable problem with the delay in payments, which habitually
obliged to the ESCO staff to go to the villages, dismantle some systems and even to take legal
action against the customers that did not allow to entry to the houses to take away the system.
2.4.2.4 MANAGEMENT
The management refers to the organization that the ESCO uses to manage the programme. It
involves the headquarters staff and resources, the flow of information between the customers‐local
agencies‐headquarter, the project and economic balances, forecasting, ONEE communication,
reports, etc.
All the staff of the ESCO ISOFOTON corresponding to the headquarters represented about 20% of
the total and evolved in the first 5 years from 14 people between 2006‐2008 to 11 and 8 in the
years 2009 and 2010 respectively.
48
The ESCO developed an ad hoc software tool to manage the programme that consisted of an
extensive database in which all data corresponding to user identification, dates of contract
signature, installation, fee payment, maintenance, stock, etc, were recorded.
Figure 18: User manual. It consists of a schematic poster including information on the SHS operation, warnings and use recommendations
Chapter 2: The Moroccan PV Rural Electrification Programme
49
Figure 19: Marketing of the Solar‐PERGISO programme carried out by the ISOFOTON staff in a souk (local market) in the Zagora province. The SHS prototype was used to show the system and explain its
operation
Figure 22: Outdoor and indoor installation stages of a SHS in the Errachidia province
Figure 20: ONEE inspector Figure 21: Meeting of the management staff of
ISOFOTON with the Assa‐Zag province authorities
50
2.5 SOMECOMMENTSABOUTTHESOLARPERGDEVELOPMENT
Apart from the success of the PERG programme in terms of achieved objectives, the Solar‐PERG did
not achieve the initial goals (only 42% of SHS were installed) and the private stakeholders involved
had to face to some extrinsic difficulties:
The expected objectives as regards the number of SHSs that must be installed were not
achieved because of lack of potential customers.
The reduction in the number of SHSs had a negative impact in the O&M management
whose costs were significantly increased.
The PERG programme developed by means of grid connections became strong competition
for the Solar‐PERG as people preferred the power grid instead of the SHSs and local
authorities supported it, in terms of financing.
The public‐private‐partnership (ppp) on which the fee for service model was based,
devolved the Solar‐PERG promotion tasks to the ESCOs, whose corporate images were very
weak, as regards the rural population. They may have known the ONEE (the National
Utility) but they showed distrust towards the ESCOs.
The SHS cost increased dramatically during the period 2006‐2008 due to prices of many
raw materials increasing considerably, such as the silicon (the main component of the PV
modules), the lead (the main component of the batteries) and the copper (the main
component of the electric wires).
The Solar‐PERG contract signed between the ESCOs and the ONEE was very unfavourable
for the ESCOs, due, for example, to the lack of price revision or the economic
compensation clauses.
Although these problems have been specific of the PERG programme and they cannot be
generalized to other experiences, it is worth mentioning that these kinds of problems are intrinsic
to the public–private‐partnership projects and they may happen in any stage of the programme.
As a result of the aforementioned comments, most of the ESCOs have been forced to leave the
programme due to financial imbalances in the management of the O&M phase. In a few regions,
some local technicians and subcontractors continue to operate the Solar‐PERG customers and their
SHSs. In many others they have been completely abandoned.
Nowadays most of the dwellings electrified by the Solar‐PERG are being connected to the national
power grid, thus, it is predictable that in a short time, the grid will cover almost 100% of the
Moroccan countryside and the SHSs will become obsolete.
2.6 THEISOFOTON‐PERGDATABASE
The experimental work of this thesis has been based on the data taken from the Solar‐PERGISO, in
particular from the maintenance and cost databases that the ESCO drew up during the first five
years of the programme development. These databases were established through real data
extracted from the day‐to‐day activity as feedback for the management of the programme.
Chapter 2: The Moroccan PV Rural Electrification Programme
51
The advantage that the author was part of the ISOFOTON management staff during these five
years, has allowed, on the one hand, full access to the databases and on the other, to have the
necessary know‐how and capabilities to properly interpret the collected data for further analysis.
2.6.1 THEMAINTENANCEDATABASE
It was made up of all kind of maintenance incidents such as failures of the SHS components, repairs,
device replacements or preventive actions. Every maintenance activity recorded had the date of
the activity, the complete SHS location data (personal data of the customer, contract number,
name and code of the village, rural community and province), a description of the maintenance
activity and all possible devices repaired or replaced (detailing the serial number of the new and
replaced devices) and the name of the technicians that carried out the action.
The ESCO used an ad‐hoc management software elaborated by CEGID [166] to manage all the
Solar‐PERGISO data. The maintenance database was integrated into the software functions.
Between the programmes began at the end of 2005 and November 2010 the maintenance
database had cumulated more than 80,000 maintenance inputs out of the 13,600 SHSs installed.
The compiling of the database was made in accordance with the following description:
The maintenance technicians visiting the SHSs, either because of the preventive
maintenance schedule or after the user failure warnings (corrective maintenance). During
the visit, the technicians made an inspection of the SHS operation and diagnosed the
possible faults. All this information is written in a maintenance datasheet as shown in
Figure 23. So, after every maintenance visit, a maintenance datasheet is generated.
The maintenance datasheets are transmitted to the headquarters administration to record
the maintenance actions onto the database.
The corrective inputs are checked and validated with another database: the spare‐part
stocks management, which the ESCO details in parallel within the overall management of
the programme.
2.6.2 THECOSTSDATABASE
It comes from the economic and financial management of the ESCO during the same period. From
these data the ESCO carried out the accounting of the company, so it is a complete and detailed
database compiled from the real costs of the the Solar‐PERGISO.
52
Figure 23: Maintenance datasheet model used by the ISOFOTON technicians after maintenance activities
CHAPTER 3
RELIABILITY ASSESSMENT OF SHS
COMPONENTS
54
3 RELIABILITYASSESSMENTOFSHSCOMPONENTS
3.1 INTRODUCTION
The reliability of the SHS components is a key factor in the design of the sustainable maintenance
structures of the PVRE programmes. However, perhaps because of the intrinsic difficulties in
gathering data in decentralised frameworks, available literature does not offer real data, thus
impeding the qualification of the reliability. Moreover, manufacturers do not usually provide any
information on failure rates or mean time to failure of the devices, only lifetime estimations, for
example the number of switch on/off cycles that a lamp can resist, the characteristic life in cyclic
use of batteries, or the annual power loss rate of the PV modules. However this kind of information
is based mainly on laboratory experiments and cannot be transferred to a programme of thousands
of devices in operation and, most importantly, where other factors are involved in their
performance, for example the user factor.
In fact, what is relevant in PVRE programmes with thousands of SHSs and long maintenance periods
is to know how the SHS components fail and how frequently they do so. This information is useful
for spare parts forecasting which is one of the pillars that allows optimized maintenance structures
to be designed. To cover this deficiency, this work has carried out a reliability study based on the
maintenance data obtained from the 5 years of operation of the Moroccan PERG programme.
The source of the data corresponds to the ISOFOTON ESCO, that has more than 80,000 corrective
and preventive maintenance data inputs, collected between October 2005 and June 2010.
The questions about which of the SHS’s components break down together with the frequency will
be answered by analyzing the time distribution of failures of every SHS component, using concepts
of reliability engineering and by determining the reliability function R(t), the failure rate λ(t) and the
Mean Time To Failure (MTTF).
3.2 RELIABILITYANALYSIS
3.2.1 SHScomponentsandfailureclassification
The description of the SHS components is summarized in Chapter 2.4.1 and Table 10.
3.2.1.1 Photovoltaicmodule
The PV module corresponds to a 36 series‐associated monocrystalline cells with a 12 VDC nominal
rated voltage. These modules usually have a very high reliability index and generally few problems
are associated with them. Failures in PV modules can be linked, generally, to a poorly‐made
electrical contact or a flaw in the by‐pass diode [167]. It must be noted that the module problems
are frequently related to a difference between the peak power value shown on its label and that
attained in experimental practice. In any case, this problem does not involve a failure in the
operating system. The expected faults in PV modules are as follows:
Chapter 3: Reliability Assessment of SHS Components
55
Diode failures. This failure can cause a malfunction in the solar module thus cutting off the
operation of some or all PV cells. If a PV module does not work for few days, the battery will not be
charged and the electricity supply will not be available. After some days of an inoperative solar
module, the battery self‐discharge can give rise to a deep discharge and it will be irreversibly
damaged. This battery failure is known in reliability engineering as a secondary failure, as it is
caused by the failure of another component (main failure). This kind of PV module failure is usually
repaired by replacing the damaged diode; hence, it is a repairable failure.
Broken PV module. Hail, heavy storms, vandalism, etc, can cause PV module breakage and,
therefore, it is a catastrophic failure.
Thermographic defects. There are sometimes hotspots in the solar cells, and even in the
interconnections between cells (bus), as a result of defects in the manufacturing process, which can
be detected by infrared thermographic cameras. The affected cell becomes reverse biased and
dissipates power in the form of heat [168, 169], which can destroy the PV module.
3.2.1.2 Chargecontroller
The charge controller uses a Pulse Width Modulation (PWM) system to regulate the charge and
discharge of the battery from the PV module toward the loads. Its maximum admissible current is
15A during charge and discharge. This device protects the battery by keeping it working within a
prescribed voltage range for an optimal use. It also shows the state of charge (SOC) of the battery
by means of LEDs located at the front of the device, which shows the SOC battery level. The LEDs
also warn of system malfunctioning, usually by showing a red LED when a deep battery discharge,
overload or a short circuit occurs. The charge controller is an electronic device, so its faults occur
randomly [167]. This means that the failure rate is constant with time. This behaviour is usually
described by exponential distributions of failures, which will be explained later. The failures in this
device will be non‐repairable (catastrophic failures).
3.2.1.3 Battery
The battery is a 12V modified Starting Lighting Ignition (SLI) lead‐acid battery which is
manufactured in Morocco and its technical report shows a capacity of C20 = 150 Ah (at 1.8V
minimum discharge voltage per cell and at 20ºC).
The lead‐acid battery lifetime is limited by its ageing effects, leading to decreasing capacity and
decreasing efficiency, giving rise to higher inner resistance or even to total breakdowns. Sudden
failures (catastrophic) can occur in batteries but they are less significant than failures through
continuously ongoing processes. The main causes of ageing are: anodic corrosion, sulphatation,
degradation of the separator, growth of dendrites and loss of inner surface in the negative
electrode [170]. Then, the ageing effect causes degradation failures. According to the standard IEC
60896‐11:2002(E) [171], the lifecycle of the battery is considered before its residual capacity drops
below 80% of its nominal capacity. However, in the real case of field trials, a residual capacity of
less than 80% may be a satisfactory battery performance for some users. Some studies indicate that
in an SHS with 3 – 4 days of theoretical autonomy, battery degradation will become noticed by the
user (in the sense of less availability of energy) when the useful ampere‐hour (Ah) have decreased
up to one‐third of the nominal battery capacity [172]. The user behaviour with regard to the SHS
operation will be closely linked to the battery cycle life.
56
3.2.1.4 Lowpowerconsumptionlamps
The SHS includes three 7WDC lamps and one 11WDC lamp. These devices are made up of a
fluorescent tube and electronic ballast. The life time for lamps is usually measured as the maximum
number of cycles (switch on/off) that lamps can resist. The Universal Technical Standard for Solar
Home Systems [173] has fixed this resistance to at least 5,000 cycles. It may be noted that, unlike
the rest of components, lamps have a discrete operation. They do not work continuously, but by
cycling. However, we do not consider this difference for the reliability analysis and we will use the
time variable instead of the cycle parameter. The expected failure types in lamps are, on the one
hand, the random electronic failures in the ballast, and on the other hand, the ageing of the
fluorescent tube.
3.2.1.5 Electricalkit
The SHS electrical installation is made up, in addition to the devices described above, of wires, light
switches, connection box, bulb sockets, a DC plug, etc. These components may also be the cause of
system failures as a result of manufacturing defects or installation mistakes. However, we do not
consider these failures because of a lack of data in the database, but we are aware of the
significance of what this SHS failure causes and on the need to study it in more detail.
3.2.2 Thesourceofdata
The database has been updated daily from the corrective and preventive maintenance activities
carried out by the ESCO technicians. It includes details on the failures of batteries, PV modules,
charge controllers and low power consumption (LC) light lamps for every SHS. These failures are in
most cases catastrophic failures, but we must take into account the following considerations:
The PV module failures resulting from diode breakdowns are considered repaired failures,
and not catastrophic failures.
The batteries replaced by ageing effects will be treated as catastrophic failures.
Before applying the reliability analysis, it was necessary to arrange the database by carrying out a
data debugging to remove the invalid inputs, such as mistakes in dates, erroneous PV identification
codes, or non‐representative samples resulting from insufficient data. The database’s figures, after
debugging, are shown in Table 11. It is worth noting that the number of SHSs considered in the
study is still high (7,595 after debugging).
Chapter 3: Reliability Assessment of SHS Components
57
Table 11: Recap of the maintenance database after debugging
Database Data inputs after debugging
Number of SHSs 7,595
Corrective & preventive Maintenance data 44,070
Failures
Batteries 714
PV modules 20
Charge controllers 433
7 W lamps 2,337
11 W lamps 755
We have worked with a very large sample in which there are 44,070 maintenance inputs related to
failures, as well as survivors (devices that have not failed during the period considered).
3.2.3 Reliabilityconcepts
The operating life of each component can be determined based on the failure database. After 5
years of operation, there are some components which have failed (failure data) and others which
have survived (the so‐called suspended or right censored data). The failure and suspended data can
be used to determine a probability density distribution (pdf) of failures, hereinafter referred to as
failure distribution f(t), from which we obtain the cumulative distribution function F(t) [174, 175]:
t
dttftF0
)()( (1)
F(t) is the probability that a component will fail before time=t. On the other hand, the reliability
function R(t) can be defined as the probability of a component surviving for a time interval. It is
given by the complementary expression of the cumulative distribution function F(t):
)(1)( tFtR (2)
The failure rate λ(t) is the frequency with which a system or component fails. Its function
represents the conditional probability of failure in the interval (t , t + dt) of that component, given
that there was no failure before time ≤ t. It can be expressed as number of components failing per
time unit. Its mathematical expression is:
)(
)()(
tR
tft (3)
58
Finally, the Mean Time to Failure (MTTF) can be defined as the expected value of time until failure.
It measures the average time between failures with the assumption that the failed system is not
repaired.
0
)( dttftMTTF (4)
3.2.4 Distributionfit
One of the most successful models used in reliability engineering is the Weibull distribution
because of its versatility in fitting many different failure models. The Weibull probability density
function is shown in Table 12.
Depending of the shape parameter β value, the trend of λ(t) will be decreasing for β<1; constant for
β=1; and increasing for β>1. Once f(t) is known, the other reliability functions ‐ λ(t), R(t), and MTTF ‐
can be obtained as shown in Table 12, where:
)
11(
is the Gamma function )(x for )
11(
x
When β comes close to 1, the reliability distribution R(t) approaches an exponential function and
the failure rate becomes constant (λ(t)= λ). This distribution is usually a good fit for electronic
devices, which follows a random model of failures independently of time. The exponential reliability
functions are also detailed in Table 12, where γ is the location parameter and means that the
failure distribution begins at t = γ. Note that if γ=0, then MTTF=1/λ, and R(t) for t=MTTF is:
368.0)( 1 etR . This means that the survival probability for t=MTTF and γ=0 is 36.8% [176].
On the other hand, if Weibull’s scale parameter β≈3.5, the failure model approaches the Normal
distribution. It means that there is a dominant failure mechanism, for example ageing, even if other
mechanisms intervene in the causes of the failure. The Normal functions appear in Table 12, where
θ represents the mean and σ is the standard deviation. In this case, the survival probability for t =
MTTF is 50%, and the mean θ will correspond to MTTF [175].
Chapter 3: Reliability Assessment of SHS Components
59
Table 12: Expressions of the failure distribution f(t), the failure rate λ(t), the reliability function R(t) and the mean time to failure MTTF for the Weibull, the Exponential and the Normal distributions. Note that
Exponential and Normal are specific cases of the Weibull distribution
Function Weibull (α, β, ϒ)
Exponential (α=1/λ, β=1, ϒ)
Normal (θ, σ)
f(t)
)(
1)()(t
ettf )()( tetf
2)(2
1
2
1)(
t
etf
λ(t) 1)()(
tt
dte
e
tt t
t
0
)(2
1
)(2
1
2
2
2
11
2
1
)(
R(t)
)(
)(t
etR )()( tetR dtetR
t t
0
)(2
1 2
2
11)(
MTTF )1
1(
MTTF
1MTTF dtetMTTF
tt 2)(2
1
0 2
1
Parameters
α: scale parameter
β : shape parameter
γ : location parameter
λ : failure rate
γ : location
parameter
θ : mean
σ : standard deviation
3.2.5 Failuredistributionfit
In order to get the best fit for an experimental failure distribution, the failure and suspended data
need to be put in order and the cumulative probability calculated. The accuracy of this distribution
can be improved by calculating the median ranking of cumulative percentages. This approximation
can be given by the Bénard estimation [174]:
4,0
3,0
n
iri
(5)
Where ri is the median rank for each failure, i is the ith order failure value and n is the sample size.
The median ranks are an estimate of the unreliability for each failure.
After the ranking process, the data will be ready to be plotted looking for the best fit. We will
determine how well the data fit an assumed distribution by using some of the many statistical
indices that measure the goodness of fit. One of these methods is the least square test. The
goodness of fit as derived by this method is called the correlation coefficient (ρ). The closer the
value ρ is to 1, the better the fit [174].
60
Once the reliability distribution is defined, the characteristic parameters can be obtained for every
distribution, and then, the reliability equations will be solved.
3.3 ANALYSISOFTHERESULTS
3.3.1 Distributionfitting
Different fit distributions have been tried for each SHS’s component, obtaining the following
outcomes:
i. The charge controller has the best fit with the one parameter (γ=0) exponential
distribution. Figure 24 shows the exponential fit. The two external lines mark the
confidence bounds of 95%.
ii. LC lamps have the best fit with a two‐parameter exponential distribution. Figure 24 shows
the 7WDC LC lamp fit, with a confidence level of 95%. The result is that the failure rate is
λ=5.96%/year. Note that the straight line does not start in coordinate (0, 100), but begins at
a time before zero (γ= ‐0.294 years). This fact can be interpreted because of the first points
appearing at the beginning of the failure distribution on the plot paper follow a different
distribution, which may be due to an early failure period (β<1). However, its impact on the
fitting result is imperceptible, since the correlation coefficient shows a very high value close
to 1. As regards the 11WDC lamp, it shows the same behaviour as the 7WDC lamp. It has a
location parameter γ=‐0.288 years and the failure rate figure is 5.97%/year. The two‐
parameter exponential fit in lamps, in contrast to the one‐parameter exponential charge
controller fit, can be explained by the fact that the failures in lamps present a residual
infant mortality. As shown in the graph, this period is very short, which indicates an
acceptable quality control made by the manufacturer.
Figure 24: Left: Failure distribution for the charge controller; Right: Failure distribution for 7WDC LC lamp. Both devices fit an exponential function (logarithmic scale on the y‐axis). In the case of the charge
controller, the exponential distribution is a one‐parameter function. For lamps, the distribution fits a two‐parameter exponential model. Both show a very good correlation coefficient (ρ) and a low uncertainty for
95% confidence bounds.
iii. The battery has the best fit using the normal distribution. This is coherent with the fact that
the main cause of failure is ageing. The correlation coefficient is perceptibly lower than the
precedent ones, but its figure remains very close to 1. However, there is a range of initial
failures which do not fit the normal distribution. In Figure 25, where F(t) is represented
Chapter 3: Reliability Assessment of SHS Components
61
instead of R(t), we can see that the failures until t~1.4 years, out of the Normal fit straight
line, have a different tendency. By trying a mixed Weibull distribution, shown in Figure 25,
we successfully fit the distribution until t=1.4 years with a shape parameter β figure of less
than 1. This means that the failure rate during this period decreases over time, which is to
say, the failures are the result of an infant mortality. In what follows, we will maintain the
Normal distribution as the best fit, although the first year behaviour has forced us to carry
out a more detailed analysis which is presented in Chapter 4.
Figure 25: Left: Normal fit of battery failure distribution. The Normal probability plot on the y‐axis represents the cumulative distribution function F(t); Right: Weibull fit. A slope change can be appreciated in the fit distribution line in t≈1.4 years. The shape parameter β in this stretch line is <1, hence, the failure rate has a decreasing tendency. It is important to note that the failure distribution does not fit the Normal function exactly in the first period until 1.4 years. After that, the Normal has a high goodness of fit and the correlation coefficient (ρ) presents a figure very close to 1 for the adjustment of all of failures altogether
iv. Finally, the PV module's reliability evaluation has been achieved from the data detailed in
Table 13:
Table 13: PV module failure figures: Left: figures from the maintenance database; Right: some failure information gathered from the maintenance technicians
PV failures declared in the database
Number of failures
PV failures declared by the maintenance technicians
Number of failures
Replacement but unidentified failures
20 Diode failures 3
Broken PV modules without replacement
5 Breakage of the module through natural causes
9
Unidentified failures. No replacement
15 Breakage of the module through human causes (vandalism)
1
Sum 40 Hot spots at the junctions between cells
6
62
There have been 20 replacements of PV modules resulting from catastrophic failures. In addition,
another 20 failures have been declared even though they have not been replaced. Otherwise, after
an interview with some of the ESCO maintenance technicians, we found that other different types
of PV failures have occurred. The diode failures and hot spots in the cell bus were usually repaired
“informally” by the technicians in the field (they access the cell bus through the tedlar layer, and
then they weld it). The broken PV modules were not replaced, sometimes the users’ request a
termination of the contract, perhaps because the users do not want to assume the obligation of
paying for a new PV module when the breakage was the result of human misuse.
After the evaluation of these figures, we have concluded that there is not enough information to
characterize PV module failures (we only have 40 failure inputs). The evaluation of the failure rate
for the PV modules will need more details on the causes of the failure and an in‐the‐field peak
power degradation and thermographic analysis. An in‐depth analysis on this is presented in Chapter
4.
3.3.2 Reliabilityfunctionsofcomponentsandsystem
The parameters (σ, θ) for Normal fit and (γ, λ) for Exponential distribution have been calculated and
are shown in Table 14. We see elevated goodness of fit coefficients (ρ) for each of the fit
distributions proposed.
Table 14: Parameters of normal and exponential reliability functions, correlation coefficients and MTTF of the SHS components with 95% confidence bounds
Parameter BATTERY CHARGE
CONTROLLER 7W LAMP 11W LAMP
Reliability
Normal
θ (years) 5.46 ‐ ‐ ‐
σ (years) 2.27 ‐ ‐ ‐
Exponential
λ (% / year) ‐ 3.67 5.96 5.97
γ (year) ‐ 0 ‐0.294 ‐0.288
Goodness of fit Correlation
coefficient (ρ) 0.9762 0.9973 0.9939 0.9954
MTTF (years).
95% confidence bound
5.5
± 3.4%
27.2
± 9.5%
16.5
± 4.0%
16.5
± 7.0%
The R(t) and λ(t) functions have been determined from the parameters in Table 14 and equations
from Table 12. We can see in Figure 27 that lamps and charge controller reliabilities are greater
than battery reliability after the 2nd and 4th operating years respectively. Table 14 shows that the
Chapter 3: Reliability Assessment of SHS Components
63
two lamps have an identical failure rate; (λ≈5.9%/year) being a higher value than the charge
controller (3.67%/year). The battery failure rate, however, increases over time, typical behaviour
when an ageing process is predominant.
The reliability of the system has been calculated according to the following series model diagram
(Figure 26):
Figure 26: Block diagram representing the SHS series reliability model made up of 7 independent components. It is assumed that lamps work in a series model, because if just one lamp fails, one of the
household rooms will not have lighting, hence the system will have failed
It is assumed that the SHS is made up of 7 independent components. The system fails when one of
the components fails. The main goal of an SHS is to provide energy to the loads (lamps and small
household appliances). If the PV module or charge controller does not work, the battery will
become damaged through lack of charge or/and deep discharge. If the battery capacity crashes,
there will be no energy available to feed the charges, hence, the system fails. As regards the lamps,
they are not working in series within the system, but we have assumed that when one of the lamps
fails, because of the lack of service in the room where this lamp worked, then the system fails.
Usually, when 1 lamp fails, a wide area of the dwelling will have an absence of lighting, and we have
considered this fault as an overall failure of the system. Hence the proposed SHS model operates
according to a series of system lamps.
As regards PV module reliability, it is considered to be close to 1 [177] in order to calculate the SHS
reliability function as the product of the individual component probabilities of survival [178]:
RSHS(t) = ΠRi(t) = RPV(t) RBAT(t) RCC(t) R7WL(t) R7WL(t) R7WL(t) R11WL(t) (6)
The RSHS(t) function is plotted in Figure 27. It shows an exponential tendency and a very negative
steep slope resulting from the battery function effect. On the other hand, the SHS series failure rate
λSHS(t) function is the sum of the individual component failure rate, as shown in Figure 28:
λSHS(t) = ΣRi(t) = λPV(t) + λBAT(t) + λCC(t) + λ7WL(t) + λ7WL(t) + λ7WL(t) + λ11WL(t) (7)
PV module
RPV(t)
11WDC Lamp
R11WL(t)
7WDC Lamp
R7WL(t)
Pb‐acid Battery
RBat(t)
Charge Controller
RCC(t)
7WDC Lamp
R7WL(t)
7WDC Lamp
R7WL(t)
64
Figure 27: Charge controller, battery, 7 & 11 W lamps, and series system (SHS) reliability functions
Figure 28: Charge controller, battery, 7 & 11 W lamps and series SHS failure rates
Finally, the MTTF figures for every component are shown in Table 14. This parameter has been
calculated by taking into account a 95% confidence boundary [179]. Note that the battery is the
component with the lowest MTTF value (5.5 years ±3.4%) which is in accordance with its reliability
and failure rate functions. On the other hand, the most reliable component is the charge controller
(27.25 years ±9.5%). Finally, the lamps have a very similar MTTF value between them (16.5 years
±4% for 7W lamps and 16.5 years ±7% for 11W lamps). It is important to note that the MTTF
concept has a different meaning according to the distribution model chosen. In the case of the
Chapter 3: Reliability Assessment of SHS Components
65
battery, whose failure distribution fits a Normal model, 5.5 years is the time in which 50% of
batteries will have failed. In the case of the charge controller, the MTTF figure means that 36.8% of
devices will have survived after 27.25 years. The case of the lamps, whose distribution model is a
two‐parameter exponential function, is similar to that of the charge controller, except that the
location parameter γ intervenes in the MTTF mathematical expression in accordance with the
equation from Table 12. Therefore 36.8% lamps will fail before 16.5 years for both 7 and 11WDC
lamps.
As regards the accuracy of the calculated MTTF, it can be observed that the confidence bounds are
very close (less than 10%), therefore, their values have a low uncertainty.
Some authors [180] have studied the mean lifetime of charge controllers and solar batteries based
on standard reliability level electronic parts belonging to charge controllers. These studies have
concluded with MTTF results of between 30 – 40 years for charge controllers and 6 – 10 years for
solar batteries. These theoretical results, based in exponential distributions, are significantly higher
than the experimental results shown in this work, but they may serve as a comparative reference
for the MTTF ranges achieved in our study.
3.4 APPLICATIONEXAMPLE
The reliability, and therefore the accumulated cost, of a PVRE programme is directly linked to the
material’s repairs and replacements when some of the devices fail. The ESCO is forced to draw up a
forecast for the maintenance period in order to calculate the optimal stock of spare parts, the
number of technical teams and how many vehicles will be necessary, among other things. Then, an
application example of the resulting reliability functions is proposed in order to determine the
annual stock of spare parts required for a hypothetical 100,000 SHS programme with a 10‐year
maintenance period. The results, in terms of number of units of the spare‐part stock per year, is
shown in Table 15:
Table 15: Maintenance period forecast for a 100,000 SHS PVRE programme with 10 years of maintenance. Figures represent the device‘s units required per year
Year 1 2 3 4 5 6 7 8 9 10
Charge Controllers
3,670 per year
7W Lamps 17,880 per year
11W Lamps 5,970 per year
Batteries 2,700 5,910 10,834 16,704 21,677 23,497 21,801 18,82 16,618 16,855
As shown in Table 15, charge controllers and lamps have a constant failure rate, unlike the battery’s
spare parts, which changes every year according to the normal distribution of failures. The annual
evolution of the quantities of spare parts is represented in Figure 29:
66
Figure 29: Annual evolution of the spare‐part requirements for a 100,000 SHS PVRE Programme with 10 years of maintenance
3.5 CONCLUSIONS
Through this reliability study of the Solar‐PERGISO programme, the failure distribution of every SHS
component has been evaluated in order to obtain its reliability function R(t), its failure rate λ(t) and
its MTTF. The results achieved show the following conclusions:
Charge controller and light lamp failure distribution can be established by an Exponential
function. The 2 types of lamps (7 and 11 WDC) show an identical behaviour as regards their
reliability function and failure rate and MTTF parameters.
Battery failure distribution is better established by a Normal function. Although the failures
in the first 1.4 years do not fit the normal model exactly, the whole failure distribution has a
high goodness of fit and it presents a correlation coefficient close to 1. In these first 1.4
years, failure distribution fits a Weibull model with a scale parameter β of less than 1;
hence the failure rate in this period has a decreasing tendency, corresponding to infant
mortality causes.
As regards the PV modules analysis, the maintenance database does not give enough
information about the failure mechanisms of this component. The failures found were: 3
damaged diodes, 10 frontal glass breakages and 6 hotpots at the junctions between cells.
The resulting R(t) and λ(t) functions have been shown for each component and for the
whole system. It is important to note that battery is the main limiting factor as regards the
reliability of the system, since its reliability figures are much lower than those of the lamps
or charge controller.
The MTTF results show, on the other hand, that the charge controller is the most reliable
component (about 27.2 years ±9.5%) and the least reliable is the battery (5.5 years ±3.4%),
while 7WDC and 11WDC LC lamps have a similar MTTF value (16.5 years ±4% for 7WDC lamps
and ±7% for 11WDC lamps). In these results we realize again that the battery has a low
MTTF value as opposed to those of the other components.
‐
5
10
15
20
25
0 1 2 3 4 5 6 7 8 9 10
Battery Charge Controller7W Lamp 11W Lamp
Nº of spare parts / year x 103
Chapter 3: Reliability Assessment of SHS Components
67
These results allow the maintenance structure in PVRE programmes to be characterized. The
calculation of the spare‐parts stock over a period of 10 years for a 100,000 SHS programme has
been shown as an example. It can also be very helpful when a quality improvement process needs
to be carried out. This study shows that an improvement in quality of the battery could increase the
system’s reliability if the battery performance reaches that of the lamps or charge controller.
Finally, the peculiarities of the study results regarding the low reliability of the batteries and the
few failures of the PV modules have been the cause of a greater in‐depth analysis of these two
components, which is detailed in the next Chapter.
68
CHAPTER 4
IN-THE-FIELD ASSESSMENT OF
BATTERIES AND PV MODULES
RELIABILITY IN THE PERG PROGRAMME
70
4 IN‐THE‐FIELDASSESSMENTOFBATTERIESANDPVMODULERELIABILITYINTHEPERGPROGRAMME
4.1 INTRODUCTION
The reliability study presented in Chapter 3 has shown that lamps and charge controllers have a
constant yearly failure rate of 6.0% and 3.7% respectively. Corresponding MTTF values are 27 and
17 years. However, the battery, affected by ageing factors, presented a variable failure rate and its
mean time to failure (MTTF) was 5.5 years.
A further analysis of the failure database showed that it only included the completely dead
batteries that required replacement by new ones. International technical standards consider that
lead‐acid batteries are dead when the remaining capacity drops below 80% of their initial capacity.
Nevertheless, in PVRE, batteries operate even when the remaining capacity is much lower than
80%, namely until the user perceives that the battery must be replaced. Consequently, further
studies to analyse the capacity degradation of the batteries and to establish their real lifetime and
reliability are required.
On the other hand, PV modules were not analysed in the previous reliability study because of the
very low failure data found in the database: just 20 failures out of 13,600 installed PV modules. This
low failure rate did not allow a proper reliability study to be carried out, but it indicated that PV
modules have a very high reliability as regards the other components.
This Chapter describes two in‐field assessments carried out in the Moroccan Solar‐PERGISO
programme to determine both, the capacity deterioration of the batteries and the quality status of
the PV modules when operating under real conditions in a sample of 41 SHSs from 6 provinces
(Figure 30). In 32 of these dwellings a datalogger has been installed to record the battery’s
operating parameters.
As already mentioned, the Solar‐PERGISO region is located partly in a mountainous area (50% of the
region is covered by mountains), and partly by wide desert areas. Climate varies between the
different areas, but the continental climate predominates with very hot summers and cold winters
(it becomes very dry and extremely warm during the long summer, especially in the southern
lowlands). In the mountainous regions rainfall can reach up to 350 mm per year and snow also falls
in winter. Precipitation in the south can reach 100 mm per year. Horizontal solar irradiation varies
between 4.7 and more than 5.5 kWh/m2/day as yearly average. This allows batteries and PV
modules to be tested under very different climatological conditions.
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
71
Figure 30: Moroccan PERG region divided into 12 provinces (shaded area). The table indicates the battery, datalogger and PV module sample distribution in the different provinces.
4.2 IN‐FIELDBATTERYTESTING
The battery used in the Solar‐PERGISO is a flat plate, lead‐acid, SLI (starting‐lighting‐ignition)
technology produced in Morocco (data sheet in Table 16). Note that this is the lowest cost battery
technology used in PV stand‐alone applications, and in this case, it reached a cost of 100 €/SHS
(0.06 €/Wh). On the other hand, the SHS's battery was sized for an autonomy of 5 days (tender
condition), which means that considering 150Ah as nominal capacity (Cnom), and a designed depth
of discharge DOD = 40%, it can be deduced that the design load was Ld = 12 Ah/day.
Table 16: Battery data sheet [181]
Storage capacity 150 Ah C20, at 20 °C and 10.8 V (1.8 V per cell) as final discharging voltage
Autonomy 5 days (DOD=40% and daily load Ld=12 Ah)
Electrolyte density 1.26 g/cm3 at 20 °C
The charge controller (CC) is a PHOCOS CML‐15 model, which has a pulse width modulation (PWM)
control including a temperature compensation algorithm. It protects the battery against deep
discharge cutting the load consumption when the battery reaches 11.4 V (at 25°C), as required by
Province BatteriesData‐
logger
PV
modules
Beni Mellal 14 12 0
Azilal 8 8 6
Marrakech 2 2 0
Al Haouz 2 1 0
Ouarzazate 11 9 23
Zagora 3 0 12
Total 40 32 41
72
the Solar‐PERGISO technical specifications imposed by the programme promoter (the ONEE). Other
features can be found in the manufacturer’s datasheet [182].
In order to analyse battery ageing rates, we have substituted existing batteries with new ones at 40
SHSs already in operation for more than 5 years. In this way, energy consumption habits must be
stabilized. 32 of these SHSs have also been equipped with the PHOCOS CX20 model charge
controllers [182], capable of recording past daily energy consumption values.
Several capacity tests have been carried out in these new batteries throughout their operating life
as detailed in Table 17.
Table 17: Different battery capacity tests achieved during their operation under real conditions
Test 1.1 1.2 2 3 4
Month 0
(as delivered by the manufacturer)
0 (after initial full charge)
6 12 18
Tests 2, 3 and 4 have been carried out by temporally collecting the batteries from the households
and putting them together on a testing stand (Figure 31) for around one week, during which the
SHS keeps working through a spare battery. Initial full charging was accomplished by means of
largely available domestic battery chargers, leaving the batteries for at least 12 hours in flotation
after the end of the charge. Then, each battery was discharged through two 50W halogen lamps.
This way, the discharging current, ID, was close to C20 (ID ≈ 2x50 W / 12 V = 8.3A). Discharging was
maintained until the battery voltage VB reached 10.8V. ID, VB, and ambient temperature was
manually recorded every 30 minutes. So, the accuracy of the measurement is about ± 4 Ah. As the
temperature affects the results, they have been corrected 0.5%/°C. So, we estimate an accuracy of
the result at about 6%. The measurements of the electrolyte density were also taken both before
and after carrying out the tests for each battery.
Finally, one of the most degraded batteries was opened up after Test 4, and the plates extracted for
direct visual inspection.
Figure 31: Left: Battery test stand for capacity testing. Batteries are connected to a resistive load that consists of two halogen lamps of 50W each; Right picking up the battery from one of the dwellings of the
sample
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
73
Figure 32 shows the voltage evolution of one of the batteries in Test 1.2. Note that the voltage
drops slowly during the discharging process but it falls quickly when voltage is close to 11.4 V,
which means that the DOD when the batteries reach the CC low voltage disconnection is practically
100%. This reveals that the protection threshold was incorrect and it was not protecting the
batteries, although, as will see below, this does not seem very relevant, since excessive discharging
rates are not common.
Figure 32: Voltage and energy curves of one of the battery discharging tests. The crosses above the voltage line represent the different readings taken during the test. The dashed line above the light grey area
represents the capacity extracted from the battery when the charge controller disconnects the battery at 11.4V. The dashed line above the thin and darker area shows the remaining capacity of the battery
between 11.4 and 10.8 V.
4.2.1 Capacityresults
Figure 33 shows the battery capacity histograms for the 40 batteries as delivered (Test 1.1) and
after the initial charge (Test 1.2). Figure 34 describes the time evolution of the capacity once the
batteries are in operation (Test 1.2, 2, 3 and 4). Table 18 summarizes the corresponding mean and
standard deviation values.
0
20
40
60
80
100
120
140
160
6.0
7.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00
Voltage(V)
Voltage (V) Energy (Ah)
Time (h)
Energy (Ah)
11.4 V10.8 V
74
Figure 33: Capacity distribution of batteries from tests 1.1 (after delivery by the manufacturer) and 1.2 (after initial full charge). Note that characteristic capacity distribution of test 1.1 is broader than that of
test 1.2 and its mean value is shifted to the left
Figure 34: Capacity representation of the entire battery sample on the Tests number 1.2, 2, 3 and 4. Note that from Test 2, the average capacity is situated below 80% as regards the nominal capacity
0%
20%
40%
60%
80%
100%
120%Measured Capacity / Nominal Capacity
Test 1.2 Test 4Test 3Test 2
18 months
40%
05
10
15
45%
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
105%
Test 1.1
Test 1.2
M d i / i l i
Number of bateries
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
75
Table 18: Corresponding capacity (C20) mean (μ) and standard deviation (σ) for the different tests
TEST μC20test/C20nominal (%) μ C20 (Ah) σ C20 (Ah)
1.1 84 126 15
1.2 92 138 11
2 76 114 16
3 65 97 25
4 62 94 25
The following comments apply:
Low mean and large spread capacity values of delivered batteries suggest, respectively, insufficient
‘formation’ of the plates and poor manufacturing quality. It is worth remembering that
incompletely formed plates contain not only proper active materials (lead dioxide on the positive
electrodes and sponge lead on the negative electrodes) but also remnants of other materials (PbO,
PbSO4) which lead to initial capacities that are below the nominal values. Moreover, these
remnants induce anomalous crystallization around them. Thus, this initial poor quality acts as a
seed for accelerated degradation. This quality problem is also seen in the broader dispersion of the
measured electrolyte density for the total battery set (see Figure 35).
Figure 35: Average electrolyte density distribution from the six cells of each battery in Test 1.2. Measurements were taken before (grey colour) and after (black) the capacity tests. The high dispersion
could be the result of poor manufacturing quality
0
2
4
6
8
10
12
1085
1095
1105
1115
1125
1135
1145
1155
1165
1175
1185
1195
1205
1215
1225
1235
1245
1255
1265
1275
1285
1295
1305
1315
After test
Before Test
Density (g/l)
Frecuency
76
The initial charge further helps the formation of the plates, leading to an increase in battery
capacity. However, half the specimen still shows capacities below 95% of the nominal value, which
is the recommended threshold for SHS battery acceptance (see the Universal Technical Standard
for Solar Home Systems [112]). Large capacity spread still persists.
Not surprisingly, subsequent observed degradation rates, with the batteries already in operation,
are very high. An experimental model of capacity degradation has been derived simply by
calculating the time that each battery is in use to reach the states corresponding to 80%, 70%, 60%,
and 50% of its nominal capacity. For each capacity state, there are some batteries that have
reached that state (it could be defined as "failures") and others that do not reach that state
("survivors") [174]. For instance, there are 21 batteries that reached the degradation of 70% of the
nominal capacity (0.7∙Cnom) at some point during the 18 months of the testing period ("failures"),
and 15 batteries that never reached this degradation ("survivors”).
Figure 36 shows that the unreliability function F(t) of the batteries that got 70% of their initial
capacity fits a Normal distribution. Furthermore, the mean value (or mean time to failure ‐ MTTF) of
each one of the Normal fit distributions at different capacities have been calculated (MTTF80%,
MTTF70%, MTTF60% and MTTF50%). Based on these averages, an experimental degradation function
has been extracted relating the MTTF and the capacity degradation (Figure 37).
Figure 36: Normal fit of the battery’s unreliability F(t), that is to say, the distribution of batteries that reach 70% of their initial capacity as observed in the in‐the‐field battery testing. The two contour lines indicate the 95% confidence boundary of the fit distribution. The correlation coefficient (ρ) shows how well the
linear regression model fits the data. In this case is very close to 1, indicating a good fit.
Failure at Cmeasured / Cinitial = 70%ρ = 0.93
UnreliabilityF(t) (%
)
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
77
Figure 37: Capacity tendency degradation of batteries extracted from the different capacity tests. When operation time reaches the MTTF = 5.5 years, the remaining capacity of the battery is just 18%. The two
contour lines indicate the 95% confidence boundary of the degradation function
The question of battery lifetime deserves further comment. Worldwide accepted standards [183,
184] indicate that batteries reach the end of their lifetime when the remaining capacity is below
80% of their initial capacity. In adhering to this figure, the degradation function derived here
implies that the SHS batteries concerned would have to be replaced before 1 year of operation.
However, in reality, batteries survive until the user complains about frequent blackouts. The Solar‐
PERGISO experience shows that, on average, this happens according to a MTTF = 5.5 years of
operation. As shown by the previously derived degradation model which corresponds to a
remaining capacity of the battery of around 18% of the nominal value. That is, international battery
standards and SHS user behaviour differ by factors between 4 and 6, when the remaining capacity
of the battery and lifetime are considered respectively. We think that the explanation of this rather
astonishing result relies on the fact that real energy consumptions are well below the standard
design values . Thus, most users are happy with its SHS even if it performs substantially below
specifications.
At this point, it is important to clarify that the capacity that remains in the battery when it has
0.18∙Cini does not necessarily match the available capacity when the battery operates within the
SHS, as evidenced below. Batteries at high capacity degradation levels have unexpected behaviours
due to the elevated internal resistance when current is flowing in the charge and discharge states,
and then, the charge controller’s algorithms are malfunctioning. That is the case when PV module
charges a degraded battery: the voltage in the terminals rises quickly because of a substantial
increase in the internal resistance, and it is interpreted by the charge controller as final charge
voltage, and it starts the floating charge mode even if the battery is not fully charged. Thus, the
charge of the battery by the ensemble PV module – CC does not reach the full charge and then, the
available capacity for the user is even lower than this 18% of Cini.
Finally, one of the most degraded batteries of the sample (it reached a capacity of less than
0.3∙Cnom) was inspected in the laboratory in order to check the actual state of the plates after
0%
20%
40%
60%
80%
100%
0 1 2 3 4 5 6 7 8 9 10
MTTF (years)
Capacity / nominal capacity (%)
MTTF = 5.5 years
Possible definition of death of battery: 18 % of nominal capacity
78
carrying out the Test 4. The electrolyte of the battery was completely removed and then the
container was opened and the positive and negative plates of the cells extracted.
The inspection showed that most of the positive active mass was lost (shedding effect) and was
deposited at the bottom of the cells (see Figure 38). The low physical resistance of the plates to the
mechanical loads occurred during the cycling operation can be the cause of the loss of active mass,
thus bringing about the dramatic decrease in battery capacity and its early death.
Figure 38: Loss of active mass in the positive plates in one of the cells of the battery
4.2.2 Observationsonenergyconsumption
After the analysis of the recorded data from the dataloggers it can be seen that:
Mean daily energy consumption is μload = 5.2 Ah/day, and the standard deviation σload= 4.18
Ah/day, which indicates that there is no standard load profile, however the real loads are
on average lower than the load of design (12 Ah/day).
Despite that, some users are affected by blackouts, associated with the low voltage
protection. This may happen on days in which energy consumption is exceptionally large. In
fact, disconnections at the most affected houses are probably related to consumption
surges during the weekend: 1/7 = 14%, which fits with the batteries that have suffered a
greater number of disconnections (see Figure 40(b)).
Dataloggers indicate that the average battery’s depth of discharge (DOD) ranges from
between 30% and 50%.
The state of charge (SOC) recorded by the dataloggers after sunset is, on average, 70%, while the
percentage of days in which the dataloggers indicate full charge is 74%. The results shown in Table
19 and the histogram in Figure 39 indicate that even if most batteries reach full charge every day,
the mean SOC after sunset is not 100%. Assuming that in general the loads start from the afternoon
onwards, it could be deduced that the charge controllers algorithms that are used to calculate the
SOC and the full charge state of the batteries are distorted by the battery degradation and do not
work properly.
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
79
Table 19: Statistical results of the SOC in the morning and in the afternoon and days in which batteries are fully charged
Figure 39: Distribution of days in which the batteries reach the full charge as a percentage
Given that the charge cycles of the batteries are characterized by low DOD (normal operation), with
sporadic high DOD and load disconnections (exceptional operation), it can be established that the
capacity degradation is related to both the capacity throughput [185], that is, the quantity of
energy that passes through the battery, and with the number of disconnections due to low battery
voltage that, according to the previous analysis, is not frequent but can dramatically affect the
health of the battery.
In principle, with other circumstances being equal (solar radiation, ambient temperature, charge
controller algorithms, etc.) the higher the energy consumption, the larger the battery degradation.
In fact, this can be observed in reality, despite the anomalous behaviour of the highly degraded
batteries analysed here. Figure 40 shows a) the average daily load (Ah) of each battery during the
18 months of operation; b) the percentage of days with at least one disconnection of the load due
to low battery voltage; and c) the remaining capacity of the batteries after 18 months of operation
ranked from least to most. The eight batteries in dark are those whose remaining capacity are
equal to or lower than 50% of the Cnom
SOC morning
(%) SOC afternoon
(%) Battery full
charged days (%)
Mean (μ) 66 70 74
Median 67 71 83 Standard Deviation (σ) 11 9 25
Mode 61 71 99
0%
5%
10%
15%
20%
25%
30%
35%
20% 30% 40% 50% 60% 70% 80% 90% 100%
Days with full charged battery(%)
Battery frecuency
θ = 74% σ = 25%
80
Figure 40: Bars in the same vertical position correspond to the same battery; a) Average daily load(Ah); b) Percentage of days with low voltage disconnections; (c) Remaining capacity of batteries after 18 months of
operation measured in Test 4. In dark, the 8 most degraded batteries (less than 50% capacity)
The data represented in Figure 40 (a), (b) and (c) can be merged in a mathematical linear
combination such as z=Ax+By, where x represents the percentage of days of low battery
disconnections, y the average daily load (in percentage as well) and z the capacity degradation. A
and B are two parameters calculated for the best linear regression (A = 0.42; B = 0.58) (see Figure
41).
0
5
10
15
a) Daily average load energy (Ah)
0%
5%
10%
15%
20%
b) Days of low battery disconnections (%)
0%
20%
40%
60%
80%
100%
30 24 09 22 36 16 03 02 15 40 21 01 13 06 28 10 11 39 08 38 23 04 29 12 37 14 26 27 31
Code of each battery from the sample
c) Capacity Test 4 (CT4/Cnom)
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
81
Figure 41: Relationship between the degradation of the batteries (CT4 / Cnom) and the combination of both the percentage of days of low battery disconnections (x) and the average daily load percentage (y) with
respect to a normalized load of 20 Ah. A and B are two parameters calculated for the best linear regression when compared with battery degradation. The results show that A = 0.42 and B=0.58
These results suggest that battery's degradation is affected by the combination of both the normal
and the exceptional operation roughly in the same proportion according to the values of A and B.
The goodness of fit is supported by a R2 = 0.494, which is a representative value when social
behaviours are involved, as is the case in SHS where the users are not only consumers, but also
managers of the systems.
4.3 IN‐THE‐FIELDPV‐MODULETESTING
The PV module model is an ISOFOTON IS‐80S, consisting of 36 monocrystalline silicon cells and, at
the moment of the testing, they had been working for a period of 6.15 years on average.
The testing method consisted of in‐the‐field measuring of the I‐V curve of the PV modules by means
of a capacitive load [186]. This I‐V curve has been extrapolated to standard test conditions (STC) to
extract the peak power of the PV modules. Then, this actual peak power has been compared with
the power of the flash report provided by the manufacturer as a part of the quality control carried
out at the end of the manufacturing process.
During the test, the on‐plane effective irradiance, Geff, and cell temperature, Tc [187], have been
measured from a coplanar reference PV module [188, 189], of the same model as that of the
sample. Thus, uncertainty due to thermal, angular and spectral responses is not an issue. As shown
in Figure 42, after cleaning both modules and waiting for cell temperature stabilization (both
modules must reach similar temperature values), the capacitive load test is carried out when the
effective irradiance is above 800 W/m2 [189] in order to minimize uncertainty.
Linear regression:R² = 0,494
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
0% 20% 40% 60% 80% 100% 120%
Ax+By
Capacity in Test 4 / nominal capacity
82
Figure 42: Outdoor measurement equipment. The PV module below is one of the sample modules, and the upper one is the reference module. Both are stabilized in temperature before testing and they are installed in the same plane. The calibrated cell is used to check that the effective irradiance Geff is greater than 800
W/m2 when carrying out the test
The main statistics of the results are summarized in Table 20 and Figure 43, where ΔIm* is the
variation of the maximum current with respect to that of the flash report and ΔPm* is the maximum
power variation with regard to the same report.
Table 20: Statistics of the PV module degradation, in STC conditions, related to the data from the manufacturer flash report after 6.15 years of operation
ΔIm*(%) ΔPm*(%)
Mean (μ) ‐4.8 ‐6.7
Median ‐5.0 ‐6.7
Standard deviation (σ) ‐1.6 ‐2.0
The test shows a mean reduction of PM* in 6.7%, and the standard deviation σ = 2.0%.
Reference PV module
Sample PV module
Calibrated cell
Capacitive load &
oscilloscope box
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
83
Figure 43: Distribution of the measured loss of power of the 41 PV modules after 6.15 years of operation
We can assume that the mean annual power (PM*) degradation corresponds to 1.1%. However, PV
modules can experience a premature degradation after the first hours of exposure to solar
radiation. The possible early degradation is included in this yearly rate, since degradation in the first
days of operation was never measured. Considering an early degradation in terms of maximum
power PM* between 0% and 4% [190], we can conclude that the mean yearly degradation goes
from 0.4% to 1.1%, which is consequent with other reported experiences [191, 192].
Inspection of hotspots has been carried out with a thermographic camera (model Infracam FLIR
E60). The results show that only one PV module presented temperature variations (ΔT) between
cells higher than 20 °C. That PV module had a ΔT of around 30°C, reaching a hot‐spot temperature
of 86°C (see Figure 44).
Figure 44: Thermal image of the rear side of a PV module showing a hot cell 30°C higher than the other surrounding cells of the module
0
1
2
3
4
5
6
7
8
9
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0
Freq
uen
cy (nºmodules)
Loss of power (%)
Mean = 6.7%Standard deviation = 2.0%
≈30 °C
84
It has been observed, as well, some visual defects in a few PV modules, such as browning in the
encapsulation ethylene‐vinyl‐acetate (EVA) layer [193, 194], or defects in small areas of the anti‐
reflective coating in one cell [169], but because of its low frequency they have no statistical
relevance in this study.
4.4 CONCLUSIONS
In order to analyse the battery degradation process, a sample of 40 batteries installed in the Solar‐
PERGISO has been periodically tested over a period of 18 operation months. The main results are:
i. On average, the capacity drops to 60% of the initial capacity after eighteen months of
operation. In less than six months the batteries have reached a remaining capacity of less
than 80% of the nominal capacity, the threshold usually used to define the battery lifetime,
which is not the case for PVRE users.
In spite of this fast degradation, past studies based on the O&M database show that
batteries keep working for much longer (MTTF=5.5 years) until the users perceive that the
SHS does not satisfy their needs and ask for the replacement of the battery.
Correlating these two results, a model has been proposed to calculate the remaining
capacity that leads to user dissatisfaction, which is 18% of the initial capacity for this
particular programme.
ii. Based on current recorded data, it has been determined that there is no a standard load
profile, but loads are in general very low as regards the storage capacity of the batteries.
The mean load consumption has been μload=5.2 Ah/day and the standard deviation σload=4.2
Ah/day. It must be noted that the design load was much higher (12 Ah/day), which could
suggest that battery degradation would have been more accelerated if both design and real
loads had been closer. This leads to an operation normally based on a high SOC, with
sporadic events of low battery disconnections. A model that correlates these two types of
operation with the battery capacity degradation has been proposed.
iii. The reasons for this fast degradation of the battery capacity could be as follows:
Bad manufacturing quality of batteries. The in‐the‐field testing has exhibited a rapid
degradation of batteries even working at low loads. Moreover, they have shown a wide
dispersion in terms of capacity and density of electrolyte. Ultimately, the visual inspection
of the plates from one of the most degraded batteries has shown the dramatic loss of
active mass in the positive plate which suggests a very low physical resistance of the plates
The behaviour of degraded batteries (with capacities of less than 0.8∙Cnom) is difficult to
predict, which makes it very complex to adapt the algorithms of the charge controllers.
The threshold of the Solar‐PERGISO charge controller, to protect the battery against over
discharge, allows a DOD close to 100%, which is completely incorrect, although this does
not seem to be very relevant, since excessive loads are not common
Chapter 4: In‐Field Assessment of Batteries and PV Modules Reliability in the PERG Programme
85
The results and conclusions reported in this Chapter could lead to the question of the convenience
of using local manufactured batteries in rural electrification programmes. It is assumed that
manufacturing quality depends only on the quality process and raw materials used and not on the
country, but it is also true that quality involves an increase in prices, and therefore, this must be
adapted to the local markets. However, successful experiences have taken place in Brazil and
Bolivia where local batteries have been used in PVRE programmes (according to author's own
sources). Thus, the use of local batteries in general must not be excluded, but compliance with the
minimum quality standards should be tested.
As regards the PV modules, a set of 41 mono‐crystalline modules have been tested in the field to
assess their state of quality, resulting in a mean power degradation rate of between 0.4% and 1.1%
per year, which matches other experiences reported in the bibliography. Defects related to
hotspots, broken diodes, browning and other defects are almost negligible. Hence, silicon PV
modules show good reliability behaviour, especially when compared with the other SHS devices,
such as batteries, lamps or charge controllers.
86
CHAPTER 5
CHARACTERIZATION OF THE
OPERATIONAL & MAINTENANCE COSTS
88
5 CHARACTERIZATIONOFTHEOPERATIONAL&MAINTENANCECOSTS
5.1 INTRODUCTION
As mentioned above, most PV rural electrification projects based on solar home systems (SHSs) and
fee for service concept [50, 114] have failed because real operation and maintenance (O&M) costs
have been larger than initially expected [120, 160, 158]. Fees lower than the real cost produces
serious financial imbalances, making O&M unfeasible and leading to the abandonment of SHSs by
the ESCOs.
In fact, despite many programmes and subsequent evaluations having been carried out since the
1970s [17, 66, 115, 195, 196, 197, 198, 199, 200], real O&M costs are hardly reported at the
available literature [201], making difficult the task of designing new SHSs programmes with
appropriate maintenance and management structures.
This Chapter presents an assessment and evaluation of the operation and maintenance costs of the
Solar‐PERGISO programme, with the aim of characterizing its cost structure. Based on the data
extracted from the 5‐year operational costs of the ESCO, the programme has been analyzed to take
out the most relevant economical aspects involved in the O&M phase as well as the comparative
appraisal between the 3 main activities: installation, O&M and management.
Remember that the Solar‐PERGISO rules provided that the ESCO must guarantee the SHS for a period
of 10 years, during which it must repair or replace the damaged components. It is also responsible
for collecting the monthly fees that the users must pay for the maintenance service. These fees are
established by the ONEE utility at 4.9 €/month/SHS (excluding VAT), that it is equivalent to 59.0
€/year/SHS. This fee will remain unchanged over the 10 years of maintenance service.
5.2 COSTANALYSIS
We will distinguish 3 main activities (see Figure 45): installation, O&M and general management.
The installation refers all the work and activities required to install the SHSs, as well as the purchase
of equipment and the marketing. The operation and maintenance of the systems requires the
technical maintenance of the SHSs (including spare parts) and the collection of user’s fees.
The general management (ESCO headquarters, management staff, etc) is linked to the others, so it
can be considered as an indirect cost. However, the management has been taken into account as
an independent activity in this study.
The different costs, such as taxes, banking fees, insurances, staff training, office supplies,
contingences fees, financial expenses, transports, customs, etc, are included in these 3 activities
according to their involvement in each one.
Chapter 5: Characterization of the Operational & Maintenance costs
89
Figure 45: Solar‐PERGISO programme activities
It has been necessary to assign every unit cost from the accounting database to the different
activity levels as represented in Figure 45. The cost allocation of the first 5 years of the Solar‐
PERGISO programme according to the different activities classification are shown in Figure 46 and
Table 21: from 2006 to 2008 the activity was mainly devoted to the installation of the SHSs, and
2009 ‐ 2010 to the operation and maintenance service. Obviously, O&M was also carried out from
2006 to 2008 for already installed SHSs.
The total expenses in these 5 years reached the amount of €12.5 million, distributed as shown in
Figure 46. Note that we have considered every expense involved in the development of the
programme, taking into account all operative and financial costs before amortization.
Figure 46: Distribution of actual costs in the first 5 years of programme
0 €
100 €
200 €
300 €
400 €
500 €
600 €
700 €
800 €
900 €
2006 2007 2008 2009 2010
Equipements
Installation
Marketing
Fees collection
Maintenance & Spare parts
General management
Year
€/SHS
End of the installation phase
90
Table 21: Solar‐PERGISO cost balance (units in €/SHS). Note the elevated costs of the O&M activities in 2009 and 2010, where just the cost of collecting the monthly fees represents almost half of the fee collected
Item 2006 2007 2008 2009 2010
Equipment 478 461 454 ‐ ‐
Installation 87 84 81 ‐ ‐
Marketing 94 80 64 ‐ ‐
Fee collection 12 10 8 26 24
Maintenance & Spare parts 15 15 16 33 40
General management 112 54 36 23 18
Total (€/SHS) 798 704 659 82 82
Given the failure rate of the SHS components in this programme (see Chapter 3), and considering
that the total number of SHSs in the O&M phase (13,449) remains practically fixed, it is reasonable
to suppose that the O&M costs in 2010 are representative of the following years. Therefore, we can
calculate the whole cost of the programme after the 10‐year period of O&M just by making the
hypothesis that the yearly discount rate will be similar to the inflation rate in the coming years.
In this way, the Solar‐PERGISO, whose completion year will be in 2018, should have an overall cost of
€21.2 million, which when referring to all the installed systems is €1,574/SHS.
We can see in Figure 47 that the installation costs are similar to the O&M costs for the whole
programme period, and that the major costs are the initial equipment (29.4%) in the installation
phase, and the maintenance activity including spare parts (26.5%).
Figure 47: Overall cost distribution of the Solar‐PERGISO programme for 13,449 SHSs and 1.008 MWp installed (considering 75 Wc/SHS). Percentage distribution of costs for each group of activities
O&M Management9.4%
Maintenance26.5%
Fee Collection14.9%
Equipments29.4%
Marketing5.0%
Installation5.7%
Installation Management
9.1%
Before set‐up
Management (18.5%)
Installation (40.1%)
O&M (41.4%)
After set‐up
Chapter 5: Characterization of the Operational & Maintenance costs
91
5.2.1 Installation
We must consider that the equipment costs, during the installation phase, was influenced by two
important facts: 1) the prices of the PV modules went up considerably as compared to the previous
years, reaching more than €3.5/Wp (€262/SHS) in the 2006‐2008 period; 2) the market price of lead
shot up reaching limits greater than 4 times its cost in 2005, which directly affected the battery
costs, in which the cost of the lead is 50% , reaching €0.75/Ah (or €1.51/Wp). So, the purchase price
of the PV kits was around €6.2/Wp (€465/SHS). Note that, at the photovoltaic market current prices
of 2015 (around €0.8/Wp for "small size" PV modules), the cost of this PV kit would be around
€3.7/Wp (€277/SHS). However, this dramatic reduction in PV module cost means just an 11.6%
decrease in the cost of the programme, showing that the cost of PV module is not the key point in
decentralized rural electrification.
5.2.2 O&M
Maintenance includes both spare parts and the maintenance structure. Its cost represents 26.5% of
the overall programme cost, as observed in Figure 47, and it can be expressed as an annual 9.01%
of the equipment investment (€41.7/SHS∙year). This figure is so far from other figures found in
some publications [155, 156, 157], where the maintenance cost is estimated at 1 – 3% per year of
the investment in equipment.
Costs involved directly in the maintenance are shown in Figure 48. We see that the cost of the
spare parts is the most important (€22.9/SHS∙year), especially battery, which represents
€19.25/SHS∙year (according to MTTF = 5.5 years [18]), followed by lamps: €2.93/SHS∙year (MTTF =
16.5 years).
Figure 48: Maintenance cost structure (note that fee collection cost is not included)
The second largest cost of the maintenance is the maintenance structure (€14SHS∙year). This
structure refers to the direct costs of this activity related to staff, offices, stores, vehicles, fuel,
€0.95
€3.86
Battery €19.25
Charge C. €0.61
Lamps €2.93
D. water €0.11
General Maintenance
Structure €3.19
Local Maintenance
Structure €10.81
‐ €
5 €
10 €
15 €
20 €
25 €
Equipments (spare parts)
Maintenance structure
Transports Other costs
€/SHS/year Total maintenance cost:
€41.7/SHS/year
54.9% 9.3%2.3%33.6%
% of the total maintenance cost
92
telephone, etc. These costs are divided between the local structures close to the SHSs, as local
agencies, technical staff, etc; and the general structure located in the ESCO headquarters. Over 75%
of costs are attributed to the local maintenance structure (€10.81/SHS∙year), versus the general
maintenance structure (€3.19/SHS∙year). This data confirms again that the decentralized character
is a very important factor in a PVRE programme: for example, the cost of fuel is as high as
€5.5/SHS∙year, and the annual distance per SHS travelled by the O&M vehicles is 57 km/SHS∙year.
Distilled water (€0.11/SHS∙year) is associated to the open lead battery used in this programme.
However, the cost of the maintenance linked to the distilled water for the batteries is 30% of the
total cost of the battery maintenance (the part of the overall maintenance cost intended for the
battery, which includes the spare parts, a part of maintenance structure, transport and other costs),
and represents 6% of the overall cost of the programme (€9.5/SHS∙year). This activity requires the
SHSs to go at least once a year, and recommendable once every 6 months. This opens the door to
evaluating the convenience of using “free maintenance” batteries, which do not require this
practice.
Within the maintenance activity, the cost of transport refers to the transport of spare parts to
supply the local stores, plus the import of goods which are acquired from outside of the country.
Under "other costs" we refer to the documentation (maintenance forms), financial expenses and
other contingencies.
Another of the major costs of the programme is the fee collection activity (14.9% of the total cost –
or €23.4/SHS∙year ‐ as shown in Figure 47). The method of carrying out this activity is based on the
daily presence of the ESCO staff in the main rural communities from each region, coinciding with
the days in which the local markets (souks) are organized, and demands a great effort in human
capital and mobility, which justifies its high cost.
In addition there is another circumstance which makes the activity even more expensive: the
management of non‐payment. When the user does not pay the monthly fee for more than 3
months, the ESCO agents must go to the user’s dwelling in order to collect the arrears, or even to
rescind the subscription contract and remove the PV system. This activity is very delicate and it
further increases the cost of the fee collection work. After the end of the installation phase, in
2009, the ESCO rescinded 151 customer contracts because of non‐payment of monthly fees.
Considering all of the O&M costs over the whole duration of the project (2006 – 2018), we can get
the average yearly cost of the O&M: €76.03/year∙SHS, just €59.09/year∙SHS being the yearly user
fees. Making a cash‐flow balance for a 5% constant annual discount rate, and given a ideal
collection rate of 100%, we will reach a total deficit of €3.4 million for the O&M activity over the
duration of the whole project.
In order to evaluate the accumulative costs of the main SHS components during the whole duration
of the programme, Figure 49 shows the component cost of installation as well as their replacement
when they fail (initial installation + spare parts).
Chapter 5: Characterization of the Operational & Maintenance costs
93
Figure 49: Detail of the general costs during the whole duration of the programme. The equipment costs are made up both of the initial installation and the spare parts of the maintenance activity. Figures in
brackets detail the cost per SHS.
From Figure 49 it is shown that the most important cost of the programme is not the PV module,
but the battery and the general management (both 18.5%). The PV cost of the module, of course, is
significant, but it accounts for just 15.5% of the overall cost. Considering 2015 PV market prices, the
PV module would mean only 4.36% of the cost of the programme.
5.2.3 Management
The relevance of the general management activity within the cost structure (18.5% of the overall
cost as shown in Figure 47 and Figure 49) must be highlighted. The ESCO had designed the
management structure for a 34,500 SHSs programme as initially planned. The lack of potential
customers and the electric grid expansion achieved by the ONEE, dramatically limited the number
of SHSs installed. This fact suggests that the size of the PVRE programmes must be big enough to
support the high cost of decentralized management structures.
5.2.4 Energycost
Finally, we can reach a figure of the electricity cost by calculating the electricity available for the
users for the whole duration of the project. Taking into account that the daily average radiation on
the tilted surface is around 5.5 kWh/d/m2 and considering the performance loses (75%), we obtain
an available overall production of 15.19 GWh for the 13,449 SHSs over 10 years, leading to a cost of
€1.39/kWh ( not so far from the figures of other programmes, e.g. India: US$0.65 – 1.35/kWh [202],
Zambia: US$1.6 – 2.1/kWh [203] or some African countries: US$0.45 – 1.30/kWh [20]). On the
other hand, the tariffs for on‐grid electricity in Morocco goes from €0.083/kWh to €0.137/kWh
18.5%
11,9%
14.9%
5.0%
5,7%
5.5%
2.7%
1.8%
18.5%
15.5%
0% 5% 10% 15% 20%
General management
O&M (without s. parts)
Fees Collection
Marketing
Installation
Miscellaneous
Lamps
Charge controller
Battery
PV moduleINITIAL INSTALLATION + SPARE PARTS (€243/SHS)
(€292/SHS)
(€28/SHS)
(€43/SHS)
(€86/SHS)
(€91/SHS)
(€79/SHS)
(€234/SHS)
(€188/SHS)
(€291/SHS)
94
(2015 prices [121]) according to the quantity consumed, having an initial subscription fee of €227
and a monthly fixed fee of €0.75 [162].
5.3 SENSITIVITYANALYSIS
Figure 50 shows that both, the variation in the battery and PV module costs, have the most impact
on the cost of the total programme. This analysis has been carried out by varying just the cost of
the components, without changing any other parameter. It is remarkable that battery affects
slightly more than the PV module. An 80% variation in the cost of the battery means a 15%
variation in the overall cost of the programme . In the case of lamps and charge controllers, the
variation in costs has much less impact. Note that the fuel for the ESCO vehicles has more influence
than lamps and charge controllers in the sensitivity analysis of costs.
Figure 50: Sensitivity analysis of the SHS component costs and fuel belonging the Solar‐PERGISO programme
Figure 51 represents the cost variation of the programme regarding the variation in the MTTF value
in lamps, batteries and charge controllers, without changing their costs. Obviously, the tendency is
that by increasing reliability, the overall cost of the programme decreases. We can see that battery
reliability has more influence than lamps or charge controllers on the overall cost of the
programme: a 30% increase in battery MTTF leads to a reduction in the programme cost of 5.5%.
‐20%
‐15%
‐10%
‐5%
0%
5%
10%
15%
20%
25%
‐90% ‐60% ‐30% 0% 30% 60% 90% 120%
BATTERY
PV MODULE
FUEL
LAMPS
CHARGE CONTROLLER
∆G
loba
l PE
RG
Cos
t
∆ components cost
Chapter 5: Characterization of the Operational & Maintenance costs
95
Figure 51: Sensitivity analysis regarding the reliability variation of the SHS components
Increasing reliability means increasing the cost of the kit components. Therefore, the impact on the
overall cost depends on the device’s cost/reliability relationship.
We can see in Figure 52 the cost/MTTF relationship of each device for keeping the programme’s
overall cost unchanged. This means, for example, if the battery MTTF decreases by 60% regarding
the MTTF figure, and its cost varies by ‐77.5%, the programme’s overall cost would not change.
These cost/MTTF relationships of the SHS components will help us to assess whether a reliability
variation can positively or negatively vary the programme’s overall cost depending on the
component costs that were considered.
Figure 52: Relationship between cost and MTTF in order to keep the overall cost of the programme constant when the MTTF varies. Example: the red dot in the upper right corner indicates a battery price 40% higher than the original, whose MTTF would be 80% longer, which means that the overall cost of the
programme would be lower than by using the original battery
‐120%
‐100%
‐80%
‐60%
‐40%
‐20%
0%
20%
40%
60%
80%
100%
‐100% ‐80% ‐60% ‐40% ‐20% 0% 20% 40% 60% 80% 100% 120%
∆ component MTTF
∆co
mpo
nent
cos
t
BATTERY
CHARGE CONTROLLER
LAMPS
‐15%
‐10%
‐5%
0%
5%
10%
15%
20%
‐90% ‐60% ‐30% 0% 30% 60% 90% 120%
∆
∆G
loba
l PE
R C
ost
BATTERY
CHARGE CONTROLLER
LAMPS
96
For example, it is evident that a higher quality battery will be more expensive, but in addition it
implies a longer life cycle, a greater reliability, and a lower maintenance cost. If the battery used at
the beginning in the Solar‐PERGISO is replaced by a different one with a price 40% higher than the
original, and its MTTF is 80% longer, the overall cost of the programme will be less than by using
the original battery, as shown in Figure 52.
5.4 INFLUENCEOFTHESHSSPATIALDENSITY
The spatial density of SHSs will largely determine the design of the maintenance structure, and will
directly affect some unit costs, such as staff, fuel, vehicles, transport of spare parts, the number of
local agencies and stores, etc.
A management cost analysis of the Solar‐PERGISO has been carried out regarding each local agency,
taking into account the number of SHSs managed by each agency, in addition to the agency staff
and goods, the surface of the local region and its geomorphologic features.
Figure 53 shows that decreasing the SHS density, the management structure cost increases fitting
an exponential function. This is due to the fact that general management costs increase rapidly
when the SHS’s density is very low. On the one hand fixed costs are spread among a smaller
number of SHSs, and on the other hand, the dispersion and inaccessibility of the systems increases
the variable costs.
Figure 53: Management local structure cost per SHS as regards the SHS density for each region. The geomorphologic features have been considered
From this cost/density distribution model, a sensitivity analysis can be carried out to know how the
SHS density affects the overall cost of the programme.
Figure 54 shows the variation of the overall cost of the programme when the SHS density changes
around the density figure. It fits an exponential function. The fact that this variation does not fit a
y = 16.291x‐0.226
R² = 0.8397
0 €
10 €
20 €
30 €
40 €
50 €
60 €
0.000 0.100 0.200 0.300 0.400 0.500
Annual real cost of the local structure / SHS (€/SHS/year). Data 2009 ‐ 2010
SHS density (SHS/km2)
€/SHS/year
Chapter 5: Characterization of the Operational & Maintenance costs
97
linear function has a great significance on the decentralized rural electrification and will be a major
factor when designing a PVRE programme.
Figure 54: Sensitivity analysis of the PERG according to the variation in the SHS density
5.5 APPLICATIONEXAMPLE
An application exercise is presented here to illustrate the influence of the results of this Chapter in
the design of PVRE programmes. We will imagine a hypothetical programme with 3 different
characteristics as regards the Solar‐PERGISO.
1) The cost of PV modules is reduced by half.
2) The number of SHSs does not vary, but the programme’s surface will be 10 times smaller than the Solar‐PERGISO area.
3) The battery MTTF will be double that of the current one and its cost will be 75% higher than indicated in the Solar‐PERGISO. It is an open battery that needs distilled water.
Table 22 summarizes the features of the Solar‐PERGISO and the example:
Table 22: Distinguishing features of Solar‐PERGISO and application example programmes
Case Parameter Solar‐PERGISO Application example
1 PV module cost (€/Wp) 3.35 1.675
2 SHS density (SHS/km2) 0.068 0.68
3 Battery MTTF (years) 5.46 10.92
Battery cost (€/Wp) 1.31 2.29
‐10%
‐5%
0%
5%
10%
15%
0.000 0.100 0.200 0.300 0.400 0.500
SHS density (SHS/km2)
0.068 SHS/km2
∆G
loba
l PV
RE
Cos
t
98
The overall programme costs resulting from applying the modification of each of the parameters
(cases 1 to 3) and all of them together (case 4), are summarized in Table 23:
Table 23: Resulting figures (in €/SHS) after applying the 4‐case features. The percentages indicate the cost variation as regards the original costs
Case
Total cost (€/SHS) Installation cost (€/SHS) O&M cost (€/SHS) Management cost (€/SHS)
Example Δ cost /
PERG Example
Δ cost /
PERG Example
Δ cost /
PERG Example
Δ cost /
PERG
PERG 1,574 0.0% 631 0.0% 651 0.0% 291 0.0%
1 1,452 ‐7.7% 509 ‐19.3% 651 0.0% 291 0.1%
2 1,434 ‐8.9% 603 ‐4.6% 541 ‐16.9% 290 ‐0.3%
3 1,472 ‐6.5% 706 11.8% 472 ‐27.5% 294 0.9%
4 1,211 ‐23.1% 555 ‐12.0% 361 ‐44.5% 294 1.0%
It can be shown that case 4 achieves a reduction of 23.1% of the original overall cost. The increasing
of the SHS density (case 2) mainly affects the O&M, reducing its cost by 16.9%. The reduction in the
PV module cost (case 1) just affects the installation activity, and the new battery (case 3) increases
the installation cost by 11.82% but reduces the O&M by 27.50%. The management cost does not
vary more than 1.0%.
For case 4, the distribution of costs is shown in Figure 55. We highlight the following aspects:
The major cost of the programme is not the battery (18.3%) nor the PV module (10%), but the management (24.3%). The halving of the cost of the PV module and the use of a battery with a cost/reliability relationship as we have chosen, is the reason why the cost of the programme is reduced. Even though the installation cost increases, the O&M cost decreases because the number of spare parts, mainly the battery, has been greatly reduced.
We also see that the management cost changes from 18.5% to 24.3%. Management is practically a fixed cost, and its reduction depends on increasing the number of SHSs in the programme. By keeping the number of systems in this example and reducing the maintenance costs, the relative cost of management will increase. This fact implies that it is necessary to improve the design of the maintenance and management structures, which will be the objective of the following Chapter, and to implement extensive rural electrification programmes.
Chapter 5: Characterization of the Operational & Maintenance costs
99
Figure 55: Details of the overall costs of the application example as regards the SHS component costs
The cost of energy in this application example has been reduced from €1.3/kWh to €1.0/kWh, and
the maintenance cost is reduced from €76.0/year∙SHS to €45.4/year∙SHS. The example has an
economic profitability of €1.8MM over the programme life.
5.6 CONCLUSIONS
The Solar‐PERGISO programme has been analyzed in order to identify the different costs that have
been involved in its development. Based on the real data costs of the first 5 years of the
programme we have obtained the overall cost for 10 years of maintenance, detailing each activity.
The overall programme cost reaches €21/Wp (or €1,574/SHS), where 40.1% of this cost
corresponds to the installation phase (€631/SHS); 41.4% to the O&M activity (€652/SHS) and 18.5%
to the general management (€291/SHS). The main conclusions reached in this paper are as follows:
Around 50% of the overall cost is invested during the installation phase, and the other 50% during the O&M period.
The O&M of the systems (maintenance, spare parts and fee collection) reaches €76.0/SHS∙year. This figure is further higher than usually considered in photovoltaic maintenance and it is not covered by user’s fees, causing unsustainable financial balances.
The PV module represents just 15.5% in the overall cost (€243/SHS), versus 18.5% of the battery (€292/SHS), so the battery has to be considered as the most expensive component in decentralized PV rural electrification.
The maintenance of the open lead batteries leads to the frequent addition of distilled water, whose overall cost means 6% of the overall cost of the programme (€9.5/SHS∙year).
The SHS dispersion and inaccessibility plays an important role in the cost structure, given by a mean SHS density of 0.068 SHS/km2. This feature affects the maintenance cost. For example, the cost of fuel in this programme represents €5.5/SHS∙year and the annual rate of distance per SHS travelled by the O&M vehicles reaches 57 km/SHS∙year.
24,3%
8,7%
14,2%
4,4%
7,2%
7,1%
3,5%
2,3%
18,3%
10,0%
0% 5% 10% 15% 20% 25% 30%
General management
O&M (w/o spare
parts)
Fees Collection
Marketing
Installation
Miscellaneous
Lamps
Charge controller
Battery
PV module
INITIAL SH
S INVESTEMEN
T + SPARE PARTS
% of the global programme cost
100
The energy delivered by the SHSs, expressed as available electricity for customers has been calculated, reaching a cost of €1.3/kWh.
Finally, we have shown an application example that demonstrates how by taking into account the
results of this analysis, the design of the PVRE programmes can be improved. Therefore, this study
opens the door to the creation of a design tool for costs to formulate future PVRE programmes.
CHAPTER 6
DESIGN OF DECENTRALIZED
MAINTENANCE STRUCTURES IN
PHOTOVOLTAIC RURAL
ELECTRIFICATION
102
6 DESIGNOFDECENTRALIZEDMAINTENANCESTRUCTURESINPHOTOVOLTAICRURAL
ELECTRIFICATION
6.1 INTRODUCTION
It is usual when designing a PVRE programme that sizing the SHS, according to local or international
standards, is often one of the issues most concentrated on, followed by the establishment of the
financial terms. As regards the latter, the incomes from the users play a decisive role when
establishing the fees to be paid for the maintenance service. As has been already mentioned, fees
are usually calculated according to what users pay for traditional lighting (candles, kerosene,
batteries recharging, etc), which is around US$ 3‐10 /month [17, 204, 205], an amount that in many
cases is not enough to cover the ESCO O&M costs.
As it has been shown, the main cause of high maintenance costs is the decentralisation factor that
has been often ignored by the promoters of electrification. In fact, decentralization makes the O&M
costs unknown and uncertain (travelling to repair an SHS can be ten times more expensive than the
repair itself), depending on aspects such as the geographical density of the SHSs, their reliability,
road access, the different local costs (personnel, vehicles, fuel, taxes, etc).
In this regard, the present Chapter aims to develop an ad‐hoc tool for the design of maintenance
structures in decentralised areas where PVRE programmes are going to be implemented, looking
for the minimization of the O&M costs. A mathematical optimization tool, modelled with GAMS
[206], one of the most powerful algebraic modelling languages, and solved with the CPLEX
optimiser [207], has been developed and applied to the Solar‐PERGISO programme in order to
compare the results.
The required input data to create the model has been defined together with several variables and
restrictions. An objective function, whose optimization criteria is the minimum cost of the O&M
activity, is calculated, obtaining the following outputs:
‐ composition of the maintenance structure (number of technicians and vehicles),
‐ location and quantity of local agencies (local maintenance headquarters),
‐ scheduling of the preventive maintenance and fee collection,
‐ the overall cost of the activity.
A prototype model has been implemented and validated in two provinces of the Solar‐PERGISO
region to show the usefulness of the tool when the data on the O&M costs and the reliability of the
SHS is available.
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
103
6.2 BASELINEDATA
Throughout the contract signed by the three parties (ESCO, ONEE and user), the ESCO committed
itself to maintaining the systems for a period of 10 years, in accordance with the following terms:
The ESCO has to repair or replace every defective or malfunctioning SHS component, within
48 hours after being notified by the user (corrective maintenance).
The ESCO must visit every SHS at least once each 6 months to check the state of the SHS
and to fill the battery with distilled water (preventive maintenance).
The user has to pay the ESCO a monthly fee of €4.9 (taxes not included) corresponding to
the maintenance service.
The ESCO has to maintain a minimum O&M local structure to ensure the aforementioned
service.
The local O&M structure deployed by the ESCO was presented in Chapter 2 and it is shown here for
reasons of clarity (Table 24). In all, the local structure was made up of 9 local agencies, 43
employees and 19 vehicles.
Table 24: Summary of the O&M structure location (local agencies) in the different provinces of the Solar‐PERGISO programme. The provinces’ areas and the SHSs installed are also indicated.
Provinces Province Capital
Area km2
Number of SHSs
Density (SHS/km2)
Local Agency location
TOTAL ‐ 214,531 13,452 0,062 9
Ben Slimane Ben Slimane 2,760 857 0,311 Ben Slimane
Errachidia Errachidia 59,585 959 0,016 Errich
Beni Mellal Beni Mellal 6,638 2,723 0,410 Ksiba
Azilal Azilal 9,800 1,809 0,185 Azilal
Al Haouz – Marrakech
Taghnaout 7,883 862 0,109 Ait Ourir
Al Kalaa des Sraghnas
Al Kalaa des Sraghnas
10,070 4,396 0,437 Ben Guerir
Ouarzazate – Zagora
Ouarzazate 55,298 841 0,015 Ouarzazate
Taroudant Taroudant 16,500 689 0,042 Taroudant
Tiznit – Guelmim – Assa‐Zag
Tiznit 45,997 316 0.007 Tiznit
The provinces are administratively divided in several rural communities (R), comprising a rural
centre (r) and a number of dispersed villages (V).
6.3 METHODOLOGY
The steps to build and run the modelling tool are described here. It is based on a mixed integer
linear optimisation model. The input of the tool is made up of a set of parameters with which
certain associated variables are calculated. An objective function is optimised according to a set of
constraints that must be satisfied. Figure 56 shows the schematic running of the tool:
104
Figure 56: Modelling tool scheme. The inputs describe the situation in the field and the outputs are the results of the modelling tool according to the optimization function and the set of restrictions.
The model will consider at least one local agency in the province located in the capital or in one of
the rural community centres (variable rBL ). The first objective that the model must meet is the
location of the local agency (agencies). Each rural community will be assigned to a local agency
(variable , 'r rBA ) in such a way that the SHSs in the rural community will only be attended to by
technicians from the associated agency.
The second element to be determined will be the number of vehicles associated to each local
agency. They are required for the O&M technicians to get to the villages and souks and one vehicle
has been assigned for every two technicians. Each local agency will hold at least one vehicle
(variable rNCR ).
The model is developed taking into account what has been described in Chapter 6.2 and the
following work dynamic:
On the workday, the O&M teams depart early in the morning from the local agency in the
vehicle with two possible destinations: a) the rural dwellings for maintenance work; b) one
of the souks for fee collection (and maintenance in the community of the souk, if
necessary). Figure 57 summarizes the workday scheme. If option a), the team will go to the
rural dwellings according to a forecasted planning whether PM or CM for repairs. If option
b), the team will move to the souk. There, at least one of the technicians will remain and
the other one can carry out maintenance tasks in the villages of the rural community, if
necessary. When the work of the day is ended, they return to the local agency.
OPTIMIZATION FUNCTION
and
RESTRICTIONS
OUTPUTS
‐ Local agencies: quantity and location
‐ O&M structure: number of technicians and vehicles
‐ Schedule of preventive maintenance visits and fees collection
‐ Global cost
INPUTS
‐ Number of SHSs and location
‐ Road network (distances)
‐ Main Rural Centers location
‐ Number of villages and location
‐ Time needed for displacements
‐ Time for maintenance intervention
‐ Time devoted for fee collection
‐ Local markets (souks) schedule and location
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
105
Figure 57: O&M teams workday scheme
The technician’s daily work must comprise the travelling time (departure from the local
agency and return) in addition to the maintenance action time. In no case it should exceed
the workday.
As regards the souks, not all of them will be visited for fee collection, but just those where
PERG users usually frequent (defined by parameter ,r db ). The time devoted to the souk
work is expressed by parameter ,r dtb .
The time necessary to undertake a maintenance activity (tas), either preventive or
corrective (since arriving to the dwelling until the departure) is also defined. Travel and
time for maintenance activities allow the daily work of the technicians to be calculated,
which is not permitted to exceed the workday (dailyt ).
6.3.1 Inputparametersandassociatedvariables
The optimisation model is designed to be used in a particular province that consists of a network of
nodes representing the capital of the province and several rural communities (R), which includes
some small villages (V). Around each village, there are few dispersed dwellings where a number of
SHSs are installed.
The model will run for a given planning period or "planning horizon" (D). To avoid problem
dimensions, this planning period will not be a complete year, but the period in which at least one
visit to each rural community must be carried out. Because of the level of service quality committed
to, every SHS must be visited for preventive maintenance twice a year. So, each rural community
should be visited at least once every six months. However, being realistic, as there is corrective
maintenances and fees must be collected, the assumption will be that each rural community has to
be visited every two months. Then, the proposed planning period will be two months,
corresponding to 56 working days.
MORNING AFTERNOON EVENING
LOCAL AGENCY
Departure of O&M teams
SOUK
VILLAGES LOCAL AGENCY
PM and CM Maintenance
Fee collection
Return of O&M teams
106
1,...,RR Rural communities in the considered province.
1,...,VV Villages in each rural community.
1,...,DD Days to consider in the simulation horizon time.
The transport network consists of paved roads that link the main towns (almost all the rural
community centres), and tracks to reach the small villages. Distances and mean speed according to
the road type are used to calculate the travel time. Figure 58 shows a schematic example of one of
the Solar‐PERGISO provinces.
Figure 58: Example of a nodes network. Each black spot represents a rural community centre. Segments outline the paved roads linking the centres
The inputs parameters are described in Table 25:
Table 25: Input parameters
rnv
Number of villages in the rural community rR .
,v ra
Element of a 0‐1 matrix such that it is equal to 1 if village vV belongs to the rural community rR and 0 otherwise.
vnshs
Number of SHSs in the village vV .
, 'r rdist
Distance between the rural centres , 'r r R .
, 'r rtd
Time needed for travelling between the rural centres , 'r r R .
'rdist
Average of distances from the rural centre of the rural community rR to each of its villages vV .
'rtd
Average time for travelling within the same rural community rR .
tas Time needed to attend to a solar home system.
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
107
,r db
Element of a 0‐1 matrix such that it is equal to 1 if there is a market (souk) in the rural community rR on day d D and 0 otherwise.
,r dtb
Time devoted to the market (souk) located in the rural community rR on day d D .
numc Maximum number of vehicles available to be distributed among the local agencies.
dailyt Length of technician’s workday.
rcmc
Cost of locating a local agency rR .
rcnc
Cost of assigning a team (vehicle and two technicians) to the possible local agency located in the rural community rR .
ctr Travelling cost per unit of distance.
From the previous setting, parameters described in Table 26 are obtained:
Table 26: Parameters obtained according to the inputs introduced
vnsys
Number of SHSs to be attended to during the planning horizon (proportional part of
the total SHSs to be visited), computed as 2365v v
Dnsys nshs
''rdist
Average of distance assigned to a SHS in the rural community rR , computed as
| 1
'''
vr
r rr
vv a
dist nvdist
nsys
V
''rtd
Average time devoted to attend to an SHS in the rural community rR , (including
travelling time) computed as
| 1
'''
vr
rr
vv a
td nvtd tas
nsys
V
After setting the input parameters, the model variables are defined according to Table 27:
Table 27: Model variables. They represent the decisions to be taken
rBL 0‐1 variable which equals 1 if a local agency is located in the rural community rR and 0, otherwise.
, 'r rBA 0‐1 variable which equals 1 if a possible local agency located in rR attends to the rural community 'r R and 0, otherwise.
rNCR
Number of vehicles assigned to the possible local agency located in the rural community rR .
, ',r r dBR 0‐1 variable which equals 1 if the rural community 'r R is visited from the possible local agency located in the rural community rR on day d D and 0, otherwise.
',r dNSR Number of solar home systems in the rural community 'r R attended to day d D .
, ',r r dNCT Number of vehicles travelling to the rural community 'r R from a possible local
108
agency located in the rural community rR on day d D .
, ',r r dTM Time spent in the rural community 'r R coming from the possible local agency located in the rural community rR on day d D .
6.3.2 Modelassumptions
6.3.2.1 Travelscheme
For reasons of simplicity, it has been assumed that to reach a village (V) it is always necessary to
pass through the rural centre, which is also supposed to be placed in the geographical centre of the
rural community. Data on the exact location of the different villages (nνr) are not available, they are
assumed to be dispersed throughout the rural community around the geographical centre at an
average distance (dist'r) (see example in Figure 59). Moreover, the model will consider that
travelling from a village (νr) to another within the same rural community (ν'r) has to be done by
passing through the centre.
Figure 59: Assumed rural communities and villages distribution
Furthermore, it will be assumed that the travelling to rural communities from the local agencies are
round‐trips, i.e., not configuring routes. The main reason to do so is that when computing costs
because of corrective maintenance, it is very plausible that each rural community must be visited
directly at least once within the planning period.
6.3.2.2 Correctivemaintenance
As a corrective maintenance is a stochastic event, it cannot be planned in advance. However,
thanks to the SHS reliability study (see Chapter 3), the average percentage of failed SHS
components per month is known. The optimisation model plans only the preventive maintenance
visits, and incorporates the corrective actions as part of the preventive maintenance just by adding
to the corresponding schedule the expected number of corrective actions to be carried out within
the planning period. The optimisation model provides a daily schedule that considers the corrective
Rural Community Centre.
Circles represent thedist’r distance to thevillages(nvr).
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
109
maintenance by forcing at least one visit to each village every two months within the planning
period. For example, if a corrective maintenance is required in a certain village, due to the
established level of service quality, it must be carried out within 48 hours, and all preventive
maintenance scheduled in this village for the following days will be carried out the day of the
corrective one, and other tasks should be rescheduled.
6.3.2.3 Criteriaandobjectivefunction
The model is developed under the criterion, firstly, of giving a certain level of service quality of the
maintenance. Previous hypotheses are assumed in order to ensure that with the resources and cost
obtained it will be possible to carry out the maintenance operations with the level of quality
assumed by the contract. So, these hypotheses and the service conditions will be included in the
model as hard constraints (constraints that must be adhered to by any feasible solution). Then, cost
will be the criterion to be minimised, assuming a fixed level of service. Total cost is made up of the
cost of locating local agencies, the cost of teams (vehicles + technicians) and the cost of travelling:
Costs related to the location of local agencies, such as office renting, human resources and
other operational costs (it includes a fixed cost per province and a variable cost per number
of local agencies established):
r rr
cmc BL
R
Costs related to the number of teams assigned to each local agency (it includes the annual
fixed costs of the vehicle as insurance and maintenance, and the salaries and some
expenses of the two technicians):
r rr
cnc NCR
R
Costs related to travelling (fuel), made up of travel covered from the local agencies to rural
communities and from rural communities to villages:
, ' , ', ' ',, ' '
2 2 ''r r r r d r r dr r d r d
ctr dist NCT ctr dist NSR
R D R D
Then, the function to be optimised is as follows:
, ' , ', ' ',, ' '
min[ 2 2 '' ]r r r r r r r r d r r dr r r r d r d
cmc BL cnc NCR ctr dist NCT ctr dist NSR
R R R D R D
6.3.3 Constraintdefinition
The constraints defined must guarantee that the service is provided with a given level of quality and
the schedule is robust enough to be adapted in real operations. Besides the assumptions included
at the beginning of this section, it is considered that two preventive maintenance calls are made to
each SHS per year. A proportional number of SHSs will be considered in the planning period model
(in our case, two months D=56).
So, the main constraints included in the model are as follows:
1) At least one local agency must be located in the province:
110
1rr
BL
R
2) Each rural community 'r R must be visited from one and only one local agency.
, ' 1, 'r rr
BA r
R
R
3) A rural community 'r R is assigned to a possible local agency only if this is established, and,
if that is the case, it could be attended to day d D .
, ', , ' , , ' , Dr r d r r rBR BA BL r r d R
4) If there is a souk on day d D , in the rural community 'r R , then it must be visited.
, ', ', , ' ,r r d r dr
BR b r d
R
R D
5) All the SHSs included in a rural community 'r R and contemplated in the planning horizon
must be visited:
, , ' , 'r d v r vd v
NSR a nsys r
D V
R
6) On day d D , the SHSs of a rural community 'r R can be visited only if that rural
community is visited on that day
, , ' , ','
, , Dr d v r v r r dv r R
NSR a nsys BR r d
V
R
7) Vehicles can be assigned to a rural community if there is a local agency located in that rural
community.
,r rNCR numcBL r R
8) The number of vehicles used for travelling from a local agency to a rural community 'r R on
day d D is limited by the number of vehicles assigned to the local agency.
, ', , , ' ,r r d rNCT NCR r r d R D
9) The time spent in the rural community r' ϵ R on day d ϵ D is the maximum from among the
time spent in the souk and the time spent doing SHSs maintenance. For rural communities where a local agency is located, it is not necessary to take into account the souk time since
users are attended to directly by the local agency staff.
, ', , , ',(1 ) (1 ), , ' ,r r d r d r r r dTM tb BL M BR r r d R D
, ', ', , ','' (1 ), , ' ,r r d r r d r r dTM td NSR M BR r r d R D
10) The time spent in the rural community 'r R by all the vehicles displaced there, plus the
travelling time to the rural community of all the vehicles (round‐trip) must be less than the
workday of the technicians.
, ', , ' , ', , ',2 , , ' ,r r d r r r r d r r dTM td NCT dailyt NCT r r d R D
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
111
11) The total time spent on day d D by the teams assigned to a local agency is at most the
length of their workday.
, ' , ', , ','
, ,r r r r d r r d rr
td NCT TM dailytNCR r d
R
R D
Together with these constraints, a set of conditions to improve the convergence of the optimisation
algorithms is included. The model is implemented in GAMS and solved with the CPLEX optimiser.
6.4 MODELAPPLICATION
To apply the proposed model, two real cases in the provinces of Azilal and Al Kalaa des Sraghnas
from the Moroccan Solar‐PERGISO programme are set out. The results will be compared to the real
maintenance structure deployed by the ESCO and the real costs associated.
6.4.1 Example1:Azilal
From Table 28 to Table 30 the input parameters in the case of Azilal are summarized.
Table 28: Rural community parameters of the Azilal province
(R) Rural communities vnsys 'rdist (km)'rtd
(min)rnv ,r db
(Souk)
0 Azilal (Capital) 22 0 0 0 1(Thursday)
1 Afourer 124 4.1 8 2 0
2 Agoudi N'lkhair 361 7.5 15 9 0
3 Ait Abbas 22 8.3 17 6 1(Friday)
4 Ait Bououli 80 11.1 22 5 0
5 Ait Mazigh 1 6.9 14 3 1(Monday)
6 Ait M'hamed 8 13.0 26 1 0
7 Ait Taguella 43 6.0 12 5 0
8 Ait Tamlil 3 12.8 26 12 0
9 Anergui 10 10.5 21 2 0
10 Beni Hassan 23 6.1 12 1 0
11 Bin El Ouidane 80 6.8 14 1 0
12 Bni A'yat 19 6.4 13 8 0
13 Bzou 3 8.2 16 1 0
14 Foum Jamaa 8 5.3 11 2 0
15 Imlil 55 5.4 11 2 0
16 Isseksi 10 7.8 16 3 1(Friday)
17 Moulay Aissa Ben Driss 71 6.9 14 2 0
18 Ouaouizeght 18 5.3 11 3 1(Wednesday)
19 Ouaoula 1 8.1 16 6 1(Wednesday)
20 Rfala 5 7.5 15 1 0
21 Tabante 66 10.3 21 1 0
22 Tabaroucht 90 5.9 12 2 0
23 Tamda Noumarcid 2 7.3 15 6 1(Thursday)
112
24 Tanante 16 6.9 14 1 1(Tuesday)
25 Taounza 8 5.9 12 3 0
26 Tidili Fatouaka 349 5.0 10 2 0
27 Tilougguite 9 12.0 24 12 1(Saturday)
28 Timoulilte 302 4.1 8 3 0
29 Zaouiat ahansal 22 16.7 33 11 1(Monday)
Table 29: Time parameters for Azilal
Time needed to attend to a solar home system ( tas ) 20 minutes
Time devoted to the market located in the rural community ( ,r dtb ) 4 hours
Maximum time allowed in a workday (dailyt ) 9 hours
Table 30: Eligible costs based on real expenses in Azilal. Associated costs means other secondary expenses linked to the main concept (i.e. telephone and fax costs of the local agency)
Concept (comprising associated costs) Annual unit cost (€)
Local agency 3,521
Agency head 6,589
Administrative employee 3,068
O&M technician 4,295
Vehicle (type VAN) 3,462
Vehicle (type 4x4) 6,402
Vehicle fuel consumption (€/100 km)11 5.31
Other inputs are the distances (distr,r' expressed in km) and travel times (tdr,r'. expressed in minutes)
between the different rural communities (R).
6.4.1.1 Results:
Table 31 summarizes the results of the model optimization:
11 Average fuel prices between 2006 ‐ 2010 in Morocco
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
113
Table 31: Optimization model results compared to the actual data for Azilal
Output parameters Model results ESCO real data
Local agency location ( rBL ) R=0 (1 local agency located in
AZILAL) 1 local agency located in
AZILAL
Vehicles ( rNCR ) 3 3
O&M technicians 4 4
Local structure costs (€/year) 48,011 48,011
Travel costs (fuel) (€/year) 7,257 8,687
O&M annual cost (€) 55,268 56,698
The results show that both the model solution and ESCO real data are similar (O&M annual costs
differ by 2.5%, which is not significant), what means that the ESCO probably deployed an optimized
structure in this province.
As regards the corrective maintenance, the model leads to a result through which, after assigning
all the preventive maintenance activities, there will be around 283 hours per year available for
corrective maintenance activities. According to the previous reliability study, during the 10 years of
maintenance, the highest number of corrective maintenance activities will happen during the sixth
year, in which the failure rate of the batteries reaches its maximum (see Table 32). If lamps are
replaced in the souks, then the number of corrective maintenance activities over the sixth year
corresponds to 397 batteries + 62 charge controllers = 459 CM actions. Whether the time dedicated
to the maintenance is 20', around 153 hours will be necessary, less than the available 283 hours,
according to the model results. For the other years during the maintenance period, the availability
for CM will be even larger.
Table 32: failure forecasting for the SHS components according to the reliability study. During the 6th year the failure rate of batteries reaches its maximum. Batteries and charge controllers are replaced in the user
dwelling while lamps are replaced in the souk.
Year 1 2 3 4 5 6 7 8 9 10
Batteries 8 62 186 286 369 397 361 305 272 278
Charge controllers 12 39 62 62 62 62 62 62 51 24
TOTAL 20 101 248 348 431 459 423 367 323 302
6.4.2 Example2:AlKalaadesSraghnas
In the case of the province of Al Kalaa des Sraghnas, with 55 rural communities and 4,396 SHSs, the
results of the model optimization are shown in Table 33, taking into account the same time
parameters defined in Table 29:
114
Table 33: Optimization model results compared to the actual data for Al Kalaa des Sraghnas
Output parameters Model results ESCO real data
Local agency location ( rBL ) R=18 (1 local agency located in
JAAFRA) 1 local agency located in
BEN GUERIR
Vehicles ( rNCR ) 4 5
O&M technicians 6 8
Local structure costs (€/year) 59,170 66,875
Travel costs (fuel) (€/year) 13,413 23,280
O&M annual cost (€) 72,583 90,155
The results of the model optimization indicate a lower annual maintenance cost of 19.5% as regards
the real ESCO data, due to the reduction of 1 maintenance team and the optimization of
maintenance travelling, in addition, the local agency has been relocated (Figure 60).
Figure 60: Al Kalaa des Sraghnas province map. The subdivisions show the different rural communities. The arrow indicates the movement of the local agency from Ben Guerir (ESCO location) to Jaafra (model
location)
As regards the CM, there will be around 346 hours per year available for corrective maintenance
activities. The highest number of corrective maintenance activities will also happen during the sixth
year (see Table 34). The number of corrective maintenance activities over the sixth year
corresponds to 1,076 batteries + 167 charge controllers = 1,243 CM actions. Around 414 hours will
Chapter 6: Design of Decentralised Maintenance Structures in Photovoltaic Rural Electrification
115
be necessary, more than the available time, according to the model results (346 hours are enough
to make 1,040 CM actions). As shown in Table 34, only the 5th, 6th and 7th years have more than
1,040 CM to carry out, thus the maintenance structure calculated by the model will be able for the
remaining maintenance period. Just in these 3 critical years, it will be necessary to extend the
number of maintenance teams from 3 to 4. That means that in these 3 years the costs of two
technicians and 1 vehicle must be added to the cost structure, which has been considered within
the resulting costs shown in Table 33.
Table 34: failure forecasting for the SHS components according to the reliability study in Al Kalaa des Sraghnas. In years 5th to 7th the failure rate of batteries reaches its maximum. Batteries and charge
controllers are replaced in the user dwelling. Lamps are replaced in the souk.
Year 1 2 3 4 5 6 7 8 9 10
Batteries 31 158 507 777 1002 1076 985 836 745 755
Charge controllers 43 98 167 167 167 167 167 167 125 70
Total 74 256 674 944 1169 1243 1152 1003 870 825
6.5 CONCLUSIONS
A model based on a mixed integer linear optimisation has been introduced with the aim of
estimating costs and designing maintenance structures for PV rural electrification programmes.
Constraints included in the model ensure a determined operability and level of service quality for
maintenance. The objective function defined must minimise the associated costs of:
‐ Local agencies
‐ Vehicles and technicians
‐ Maintenance and fee collection displacements
Based on the Solar‐PERGISO, the usefulness of the tool has been illustrated using two of the
provinces belonging to the programme.
The results of the application show in one case that the model solution matches the real ESCO data
in that province (Azilal), which suggests that the ESCO optimized the maintenance structure and
costs in that case. In the other province (Al Kalaa des Sraghnas), the model has optimized the
maintenance structure reducing by 1 the number of maintenance teams (2 technicians and 1
vehicle) for 7 of the 10 years of the maintenance period; it has relocated the local agency to a
better location and it has optimized maintenance travel. Thus, the cost of the O&M in this province
has been reduced by 19.5%, which suggests that the ESCO had deployed and oversized structure.
Throughout these results it has been illustrated that it is possible to design O&M structures in PVRE
programmes on the basis of the knowledge of the reliability parameters of the SHSs and the
operating costs of the programme.
116
CHAPTER 7
CONCLUSIONS AND FUTURE RESEARCH
118
7 CONCLUSIONSANDFUTURERESEARCH
7.1 CONCLUSIONS
PV technology plays an important role in the solution of the overall lack of access to energy. It is
expected that 250 million people will get access to electricity by means of solar home systems
before 2030.
Large PV rural electrification programmes currently taking place in many countries have shown
problems of sustainability in the maintenance phase as O&M costs are systematically larger than
expected, leading the private operators (ESCOs) to leave the programmes because of negative
financial balances. The cause of these concerns is that PVRE programmes are generally formulated
on the basis of assumptions that are not in line with reality.
This PhD has studied a real PVRE programme developed in Morocco with more than 13,000 SHSs
with the aim of analyzing the real factors involved in operation and maintenance, such as the
reliability of the SHSs operating under real conditions and the actual costs of the O&M phase. The
excellent opportunity for the author to have had full access to the detailed data of maintenance
and costs of the Moroccan programme developed by the ESCO ISOFOTON (the Solar‐PERGISO) for
five years, provides the opportunity, for the first time, to contrast the real data of the PVRE with
classic assumptions.
The work has been structured in two axes: the reliability study of the SHSs and the cost
characterization of the O&M phase.
Through the reliability study, the failure distribution of every SHS component has been evaluated
on the basis of the real failures extracted from the maintenance database that the ESCO drew up
during the first 5 years of operation of the programme. The following conclusions of the study are
highlighted:
Charge controllers and lamps have showed a failure distribution established by exponential
functions, as applied to electronic devices, in which failures happen randomly. The 2 types
of lamp (7 and 11WDC) have shown an identical behaviour as regards their reliability
function, failure rate and MTTF parameters.
The battery failure distribution has been defined by a Normal function, which is more
adapted to devices affected by aging factors. Although the failures in the first 1.4 years do
not fit the Normal model exactly, the whole failure distribution has shown a great goodness
of fit and presents a correlation coefficient close to 1. In these first 1.4 years, the failure
distribution fits a Weibull model with a scale parameter β of less than 1, which means that
the failures are the result of infant mortality.
As regards the PV modules analysis, the Solar‐PERGISO maintenance database does not give
enough information on the failure mechanisms of this component. The failures found were:
Chapter 7: Conclusions and Future Research
119
3 damaged diodes, 10 frontal glass breakages and 6 hotpots at the junctions between cells.
This information has not been enough to apply the reliability study but it can be argued
that the PV module failure data prove that they are very reliable compared to the other
components, with a minimal impact on the SHS series reliability.
The MTTF results have proved that the charge controller is the most reliable component
(about 27.2 years ±9.5%), 7W and 11W LC lamps have a similar MTTF value (16.5 years ±4%
for 7W lamps and ±7% for 11W lamps) and the least reliable component is the battery,
whose MTTF = 5.5 years ±3.4%.
As battery is the main limiting factor as regards the reliability of the system, and PV module
reliability has not been possible to asses, two in‐field degradation tests of both batteries and PV
modules have been carried out to analyze the behaviour of these components operating under real
conditions, in which user behaviour is involved in the degradation processes.
A sample of 40 batteries installed in the Solar‐PERGISO has been periodically tested over a period of
18 months in order to analyse the capacity degradation process of the battery. The main results are
as follows:
On average, the capacity drops to 60% of the initial capacity after eighteen months of
operation. In less than six months the batteries have reached a remaining capacity of less
than 80% of the nominal capacity, the threshold usually used to define the battery lifetime,
which is not the case for the Solar‐PVREISO users.
In spite of this fast degradation, reliability studies show that batteries keep working for
much longer (MTTF=5.5 years) until the users perceive that the SHS does not satisfy their
needs and ask for the replacement of the battery.
Correlating these two results, a model has been proposed to calculate the remaining
capacity that leads to user dissatisfaction, which is 18% of the initial capacity for this
particular programme.
Based on current (A) recorded data, it has been determined that there is no a standard load
profile, but loads are in general very low as regards the storage capacity of the batteries.
The mean load consumption has been μload=5.2 Ah/day with a standard deviation σload=4.2
Ah/day. It must be noted that the design load was much higher (12 Ah/day), which could
suggest that battery degradation would have been more accelerated if both design and real
loads had been closer. This leads to an operation normally based on a high SOC, with
sporadic events of low battery disconnections. A model that correlates these two sorts of
operation with the battery capacity degradation has been proposed.
The reasons for this fast degradation of the battery capacity could be as follows:
Bad manufacturing quality of batteries. The in‐the‐field testing has shown a rapid
degradation of batteries even working with low loads. Moreover, they have shown wide
dispersion in terms of capacity and density of the electrolyte. Ultimately, the visual
inspection of the plates from one of the most degraded batteries has shown the dramatic
120
loss of active mass in the positive plate which suggests a very low physical resistance of the
plates.
The behaviour of degraded batteries (with capacities of less than 0.8∙Cnom) is difficult to
predict, which makes it very complex to adapt the algorithms of the charge controllers.
The threshold of the charge controller to protect the battery against over discharge allows
a DOD close to 100%, which is completely incorrect, although this does not seem to be very
relevant, since excessive loads are not common.
As regards the PV modules, a set of 41 mono‐crystalline modules have been tested in the field to
assess their state of quality, resulting in a mean power degradation rate of between 0.4% and 1.1%
per year, which matches other experiences reported in the bibliography. Defects related to
hotspots, broken diodes, browning and other defects are almost negligible. Hence, silicon PV
modules show good reliability behaviour, especially when compared with the other SHS devices.
As regards the second pillar of the thesis, a characterisation of the Moroccan Solar‐PERGISO costs
has been achieved. Based on the real data costs of the first 5 years of the programme, the overall
cost for 10 years of maintenance has been obtained, detailing each activity (installation, O&M and
management). The overall programme cost reached €1,574/SHS , where 40.1% of this cost
corresponds to the installation phase (€631/SHS); 41.4% to the O&M activity (€652/SHS) and 18.5%
to the general management (€291/SHS). The main conclusions extracted are as follows:
Around 50% of the overall cost is invested during the installation phase, and the other 50% in the O&M period.
The O&M of the systems (maintenance, spare parts and fee collection) reaches €76/SHS∙year . This figure is further higher than usually considered in photovoltaic maintenance and it is not covered by user fees, causing unsustainable financial balances. In the case of the Solar‐PERGISO the annual fee was €59/SHS , significantly lower than the O&M unit costs.
The PV module represents just 15.5% in the overall cost (€243/SHS), versus 18.5% of the battery (€292/SHS), so battery has to be considered as the most expensive component in decentralized PV rural electrification.
The maintenance of the open lead batteries leads to add distilled water frequently, whose global cost means 6% of the overall programme cost (€9.5/SHS∙year).
The SHS dispersion and inaccessibility plays an important role in the cost structure, given by a mean SHS density of 0.068 SHS/km2. This feature affects the cost of maintenance. For example, the cost of fuel in this programme represents €5.5/SHS∙year.
The energy delivered by the SHSs has been calculated, expressed as available electricity for customers, reaching a cost of €1.3/kWh .
This PhD work has concluded with the proposal of a mathematical tool based on a mixed integer
linear optimization created with the aim of designing maintenance structures for PV rural
electrification programmes. The proposed model comprises a set of parameters and variables used
to define an objective function, which depends on a set of constraints to be satisfied. The objective
function must minimize the associated costs of:
‐ Local agencies
‐ Vehicles and technicians
Chapter 7: Conclusions and Future Research
121
‐ Maintenance and fee collection displacements
Based on the Solar‐PERGISO, the usefulness of the tool has been illustrated by applying it in two of
the provinces belonging to the programme.
In one case the model has come up with a solution that matches the real ESCO data in that province
in terms of the size of the structure and costs. In the other case, the model has optimized the
maintenance structure reducing by 1 the number of maintenance teams, has relocated the local
agency and has optimized the maintenance displacements. Thus, the cost of the O&M in this
province has been reduced by 19.5%.
These results illustrate that it is possible to design O&M structures in PVRE programmes based on
the availability of the reliability parameters of the SHSs and the operating costs of the programmes.
7.2 FUTURELINESOFRESEARCH
This research work has tried to open the door to the design of maintenance structures for
decentralized rural electrification. The criteria evaluated in this study as regards the reliability of
the SHSs and the characterization of the O&M costs, both on the basis of the Moroccan PVRE
programme has been useful to understand that the sustainability foundations that PVRE promoters
currently show weaknesses. Thus it is necessary to extend this analysis to other experiences with
the aim of universalising the results and being able to propose a paradigm of decentralized rural
electrification. In this line of work, the following areas of research are proposed:
The creation and application of friendly tools able to gather the data relating the reliability
and cost for the new programmes that will be developed. The goal is to make the collection
of data easier in order to extend the feedback in PVRE.
The development, application and analysis of results of new fee collecting systems, such as
the prepayment cards or the "pay‐as‐you‐go" model, with the aim of adapting the user
payment to the new technologies, already assumed for the rural population (for example
the payment through the mobile phone), in addition to the reduction in the management
cost of fee collection in PVRE programmes.
To establish new patterns for PVRE sizing taking into account that batteries degrade until
ranges of 18% of the initial capacity. Moreover, new in‐the‐field studies of batteries
working under real conditions could be very useful to extend the results of this PhD. The
definition of a standardized cycling model of batteries specifically for PVRE could be useful
for the improvement of quality and reliability.
Finally, as well as international standards have been developed to ensure the quality of the
SHSs and the good practises in the installation phase, it would be desirable the
development of an O&M standard for PVRE to guaranty the sustainability of long period
maintenance phases.
122
PUBLICATIONS GENERATED DURING
THIS PhD
124
PUBLICATIONSGENERATEDDURINGTHISPhD
Papers in international journals:
Carrasco LM, Narvarte L, Peral A, Vázquez M. Reliability of a 13,000‐SHS photovoltaic rural electrification programme. Prog. Photovolt: Res. Appl. 2013, 21. p.1136–1145 [Impact Factor: 9.696; Q1]
Carrasco LM, Narvarte L, Lorenzo E. Operational costs of A 13,000 solar home systems rural electrification programme, Renewable and Sustainable Energy Reviews, April 2013, Volume 20. p. 1‐7 [Impact Factor: 5.510; Q1]
Carrasco LM, Narvarte L, Martínez‐Moreno F, Moretón R. In‐field assessment of batteries and PV modules in a large photovoltaic rural electrification programme, Energy, 1 October 2014, Volume 75. p. 281‐288 [Impact factor: 4.159; Q1]
Gago Calderón A, Narvarte L, Carrasco LM, Serón Barba J. LED bulbs technical specification and testing procedure for solar home systems, Renewable and Sustainable Energy Reviews, January 2015, Volume 41. p. 506‐520 [Impact Factor: 5.510; Q1]
Carrasco LM, Narvarte L. Electrificación rural fotovoltaica "Solar Home Systems". Fiabilidad y costes de mantenimiento. "Era Solar", v. null (n. 173); 2013 p. 26‐29, pp.. ISSN 0212‐4157.
Papers in international congresses:
Guest lecture:
Carrasco LM, Narvarte L. Reliability issues and cost structure in the 13,000 SHS rural electrification programme in Morocco. 3rd Symposium Small PV Applications ‐ Rural Electrification and Commercial Use, June 2013, Ulm, Germany, p. 270‐275
Oral:
Carrasco LM, Narvarte L. Maintenance characterization of a 13,000 SHS PV program in Morocco. 2nd Symposium Small PV Applications ‐ Rural Electrification and Commercial Use, June 2011, Ulm, Germany, p. 46‐51
Carrasco LM, Narvarte L. Fiabilidad y costes de mantenimiento en un programa de electrificación rural de 13.000 solar home systems. XV Congreso Ibérico y X Iberoamericano de Energía Solar. Vigo, Galicia, Junio 2012, Vigo, España.
Carrasco LM, Narvarte L. Operational costs and reliability in a large rural electrification programme based on solar home systems. 28th European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) 2013 Proceedings, p. 3831 ‐ 3835. Paris, France.
Carrasco LM, L. Narvarte, A. Peral, Reliability Analysis of a 13,000 SHS PV Rural Electrification Programme in Morocco, 26th European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) 2011 Proceedings, p.4044 ‐ 4047. Hamburg, Germany
Publications generated during the PhD
125
Gago Calderón A, Narvarte L, Carrasco LM, y Díaz Martínez M. LED bulb lamps technical specification and testing procedure for solar home systems. 3rd Symposium Small PV‐ Applications Rural Electrification and Commercial Use, June 2013, Ulm, Germany.
126
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