Willingness to Pay for Renewable Energy - CEDRO -...

Willingness to Pay for Renewable Energy the Case of the Lebanese Residential and Commercial Sectors

A UNDP-CEDRO Publication October 2015

DISCLAIMER

The contents of this document are the sole responsibility of its authors, and do not necessarily reflect the opinion of the United Nations Development Programme, who will not accept any liability derived from its use.

Willingness to Pay for Renewable Energy: the Case of the Lebanese Residential

and Commercial Sectors

Authors Hassan HarajliCarla NassabJessica Obeid

Supporting Authors

Leila Dagher

Fabiana Gordon

UNDP-CEDRO Project, Lebanon

American University of BeirutDepartment of Economics, Lebanon

Imperial CollegeStatistical Advisory Service, UK

Acknowledgement

The UNDP-CEDRO Project would like to thank both the Government of Spain and the European Union for the donation of funds that enabled the CEDRO project from its first three phases to its current fourth phase. This study has been funded through both these kind contributions.

Copyright © UNDP / CEDRO – 2015

Reproduction is authorized provided the source is acknowledged and provided reproduction is not sold. The United Nations Development Programme (UNDP) is the UN’s principle provider of development, advice advocacy and grant support. With 131 country offices, it has long enjoyed the trust and confidence of government and NGOs in many parts of the developing as well as the developed world. It is typically regarded as a partner rather than as an adversary, and its commitment to uni-versal presence proved especially useful in post – conflict situation and with states that have been otherwise isolated from international community.

For further information:

United Nations Development Programme, www.undp.org.lb <http://www.undp.org.lb> CEDRO, www.cedro-undp.org <http://www.cedro-undp.org>

Note: The information contained within this document has been developed within a specific scope, and might be updated in the future.

1. Introduction and Context ....................................................................................... 8

2. The Lebanese Electricity System ............................................................................ 9

2.1 The Dual Mode and Hybrid RE Architecture .......................................................... 10

3. Willingness to Pay for Renewable Energy: Descriptive Analysis and Results ......... 12

3.1 Introduction ........................................................................................................... 12

3.1.1 The Lebanese Residential Sector ............................................................................ 12

3.2.1 The Lebanese Commercial Sector ......................................................................... 24

4. Willingness to Pay for Renewable Energy; Regression Analysis ............................ 33

4.1 Scenarios and WTP Outcome for the Residential Sector ....................................... 33

4.2 Scenarios and WTP Outcome for the Commercial Sector ...................................... 34

4.3 Regression Analysis; Methodology and Output ..................................................... 35

4.3.1 Methodology .......................................................................................................... 35

4.3.2 Residential Sector Results....................................................................................... 35

4.3.3 Commercial Sector Results .................................................................................... 36

5. Policy Implications and Conclusion........................................................................ 38

5.1 Income, Revenue and Expenditure on Electricity ................................................ 38

5.2 Residential Sector Implications............................................................................. 40

5.3 Commercial Sector Implications............................................................................ 41

5.4 Concluding Remarks .............................................................................................. 42

REFERENCES........................................................................................................... 53

Contents

Figure 2.1 Electricity demand and supply for four selected days in 2009Figure 2.2 Block diagrams of the PV and wind hybrid facilitiesFigure 2.3 PV system, storage, diesel genset, utility and load schematicFigure 3.1 Distribution of 600 samples vs. actual population distribution in LebanonFigure 3.2 Sample vs. Population urban and rural distributionFigure 3.3 Distribution of sample family number vs. actual numberFigure 3.4 Age distribution of the random surveyFigure 3.5 Percentage (%) of married people from sampled residentsFigure 3.6 Percentage distribution of sampled married residents’ number of childrenFigure 3.7 Distribution of education level of sampled residentsFigure 3.8 Percentage distribution (%) of employment/other status of the interviewed residentsFigure 3.9 Distribution of income groups of sampled residentsFigure 3.10 Distribution (%) of dwelling characteristics of surveyed residents Figure 3.11 Distribution of sampled residents w.r.t. housing ownershipFigure 3.12 Lebanese citizen’s perspective on the current energy situationFigure 3.13 Percentage of surveyed Lebanese household experiencing daily blackoutsFigure 3.14 Distribution of hours of blackouts experienced by surveyed Lebanese householdsFigure 3.15 Energy security reaction/responses of surveyed people in times of blackoutFigure 3.16 Distribution (%) of Ampere capacity to cover blackout periods by surveyed householdsFigure 3.17 Distribution of backup generation coverage of blackout hours Figure 3.18 Monthly payments to backup generator by surveyed householdsFigure 3.19 Distribution (%) of monthly payments to utility (EDL) as paid by surveyed householdsFigure 3.20 Percentage of surveyed citizens using air conditioning and their level of dependenceFigure 3.21 Degrees of dependence on electric heating from surveyed citizensFigure 3.22 Knowledge of renewable energy systems of surveyed citizensFigure 3.23 Percentage (%) distribution on perspectives of surveyed citizens’ w.r.t. space availabilityFigure 3.24 Percentage of surveyed citizens with renewable energy system installedFigure 3.25 Percentage (%) of those involved as members in an environmental organization

List of TablesTable 3.1 Statistics on monthly rent payments for diesel gensets capacityTable 4.1 WTP outcomes for four scenarios in the residential sectorTable 4.2 WTP outcomes for four scenarios in the commercial sectorTable 4.3 Main variables of significance and their directional relationship with WTP for WTP-L1 and WTP-L2Table 4.4 Main variables of significance and their directional relationship with WTP for WTP-U1 and WTP-U2Table 4.5 Main variables of significance and their directional relationship with WTP for WTP2 and WTP3Table 4.6 Main variables of significance and their directional relationship with WTP for WTP5Table 5.1 Monthly expense on securing power (in USD) for companies

List of Figures

Figure 3.26 Percentage (%) of the 600 residents surveyed with family members or themselves active in the RE sectorFigure 3.27 Residential sector’s comfort and trust in government management of money transfersFigure 3.28 Percentage distribution of reasons for zero bidsFigure 3.29 Percentage distribution of reasons for zero bidsFigure 3.30 Percentage (%) distribution of surveyed companies according to Lebanese regionsFigure 3.31 Composition, in percentage (%), of the commercial sector institutions surveyedFigure 3.32 Percentage distribution of the number of employees of surveyed institutionsFigure 3.33 Percentage distribution space (in m2) of surveyed institutionsFigure 3.34 Percentage of institutions with or without a maintenance teamFigure 3.35 Percentage of institutions ownership’s standingFigure 3.36 Distribution of relative economic wellbeing of surveyed institutionsFigure 3.37 Percentage distribution of respondents’ views on the current energy situationFigure 3.38 Percentage distribution of power cuts per dayFigure 3.39 Percentage distribution of backup source during EDL blackoutsFigure 3.40 Percentage distribution of power capacity from gensets during blackoutsFigure 3.41 Distribution of coverage of gensets during blackoutsFigure 3.42 Distribution (in percentage) of payment for backup gensetsFigure 3.43 Percentage distribution of EDL monthly payments of surveyed institutionsFigure 3.44 Percentage distribution of surveyed institutions dependence and degree of dependence on air conditioningFigure 3.45 Percentage distribution of surveyed institutions dependence and degree of dependence on electric heatingFigure 3.46 Percentage distribution of “knowledge” levels on RE systemsFigure 3.47 Percentage of surveyed institutions who undertook EEMsFigure 3.48 Percentage distribution of respective EEMs undertaken by surveyed institutionsFigure 3.49 Distribution of willingness to undertake EEMsFigure 3.50 Commercial sector’s comfort and trust in government management of money transfersFigure 3.51 Percentage distribution of reasons for zero bids in commercial sectorFigure 5.1 Percentage of total energy expenditures from income in the residential sector for electricity provisionFigure 5.2 Percentage of total energy expenditures from income in the residential sector pertained to electricity provisionFigure 5.3 Percentage of total annual revenues spent on energy for subsample of 39 companiesFigure 5.4 Total annual subsidies to Electricite´ du Liban (EDL) and % of total annual revenues share

8

The Lebanese government has set itself a target of achieving twelve percent of its energy mix from renewable energy sources by 2020, a pledge set by the Lebanese Council of Ministers in 2009 and reaffirmed in the 2009 Copenhagen Climate Change Summit and in the Ministry of Energy and Water’s (MEW) Policy Paper of 2010 (Aoun et al., 2013). The UNDP-CEDRO project has undertaken several resource assessments to identify the possible renewable energy sources, such as the Wind Atlas and the National Bioenergy Strategy, which can be utilized for Lebanon to meet this objective. Appraising residential and commercial customers’ willingness to pay (WTP) for renewable energy can better tailor policies and programs to support the development of renewable energy sources for these specific sectors. Contingent valuation (CV) studies have been the focus of research to estimate the percentage of customers wanting to join renewable energy (RE) programs and illicit the willingness to pay (WTP) for RE or RE attributes either through premium or absolute payments. Results from CV studies shed light on the willingness to support various renewable energy targets or goals, and to assess the significance of various economic, social, and attitudinal attributes and characteristics individuals hold which may influence WTP. This information will help to introduce better policies that could enhance WTP for RE delivered power.

Eliciting the willingness to pay of the Lebanese residential and commercial sectors for renewable energy power has to take account of, within the survey questionnaire, the existing unreliability (and thus complexity) of the Lebanese electricity sector. In response to the severe blackouts, consumers rely heavily on off-grid distributed (backup) diesel generators during blackout periods (Dagher and Ruble, 2010). The approach adopted to address this issue is through offering several distinct cases within the surveys/questionnaires themselves in both the residential and commercial sectors, respectively. These cases have to take into account what can be possible with distributed renewable energy systems (electricity-producing) integrated in households and/or institutions that face “unreliable” electricity supply from the national utility. The major possibility or constraint for integrating RE systems is whether or not the RE can completely displace the diesel self-generator (or other means of securing power in times of blackouts) or simply only reduce the use of diesel fuel (or other) back-up source.

The UNDP-CEDRO project commissioned a survey that undertook the sampling of six hundred residential and two hundred commercial institutions across the country to illicit their willingness to pay (WTP) for renewable energy sources, both renewable energy located within their vicinity and under their ownership, and/or purchased from the national grid where the national utility delivers “green” energy to their respective offices.

The report is divided into five chapters:

• Chapter 2: Overview of the current Lebanese electricity system and the subsequent architecture of distributed renewable energy

• Chapter 3: Descriptive results and analysis of the survey for the residential and commercial sectors

• Chapter 4: Regression analysis literature review, methodology, scenarios and results for the residential and commercial sectors

• Chapter 5: Policy implications and conclusion

1 Introduction and Context

9

Lebanon’s electricity sector is in a dire situation given the demand-supply deficit and the large technical and non-technical losses (approximately 35%) in the electricity network. These problems have led to daily blackouts averaging six hours for the entire country, which the Lebanese economy mostly counters with diesel back-up self-generation (MEW, 2010). The shock population increase in Lebanon, by at least one million (i.e., a quarter of its population) due to the Syrian refugee crisis, has further exacerbated the energy demand situation.

The blackouts vary across the year, with the most marked difference between supply and demand in the peak summer months, as shown in Figure 2.1. In Figure 2.1, one typical day from each season is selected and the difference between daily supply and demand is shown. In all the identified days, generation is performing significantly below its nominal capacity of 2300+ MW. In August 2015, demand for energy exceeded 3000 MW (Business News, 2015).

2 The Lebanese Electricity System

Figure 2.1 Electricity demand and supply for four selected days in 2009 (courtesy of EDL)

August 4, 2009 May 4, 2009

November 4, 2009 February 4, 2009

Peak demand hours differ across the year. The summer months are characterized by a constant peak from 9:00-10:00 a.m. onwards until approximately 9:00 p.m., while winter months are characterized by double peaking times, once in the late morning and once during late evenings. In spring, the demand increases fairly smoothly from the early hours of morning and peak towards noontime, remaining stable with a slight further peak during the night.

10

The introduction of renewable energy systems in Lebanon is not a simple relationship to measure, given the existence of blackouts and the need for diesel-back up generation to cover these blackout hours. However understanding the technical capabilities, requirements, and limitations of various types, sizes and configurations of renewable energy generation in such an environment is vital to communicate to anyone thinking of purchasing RE systems for their homes and/or institutions.

Replacing diesel-backup generation or complimenting them, along with the national electricity grid, with renewable energy resources, requires intelligent and yet often more complex designs. For example, in the context of the UNDP-CEDRO Project, the PV and microwind (or hybrid) systems designed and implemented had a “dual-mode architecture” (with capacities ranging from 1.2 – 5 kWp) whereby they worked both as stand-alone systems when there were power cuts, and then grid-connected systems when power was present from the grid. Figure 2.2 shows this configuration. For small systems, integrating renewable energy with battery storage offers a possible solution to displacing the diesel gensets, especially that the batteries can be recharged from the national grid as well as from the panels or the turbines, and can be set to offer at least two days of autonomy. This system will be more expensive than a normal grid-tied system due to the presence of batteries, charge controller, and a dual-mode inverter, yet manageable given the potential displacement of the diesel genset.

2.1 The Dual Mode and Hybrid RE Architecture

Figure 2.2 Block diagrams of the PV and wind hybrid facilities (Vallvé et al., 2012)

Although the Lebanese Ministry of Energy and Water (MEW) published its strategy for the power sector in June 2010, aiming to provide round the clock electricity by post-2014, and enabling the currently subsidized sector to yield profits to the Lebanese government (GoL) post-2015 (MEW, 2010), this realization has not been fulfilled and is expected to subject to several years of delay. The roadmap delivered by MEW constitutes several action plans which target all sides of an electricity system; demand and supply, existing and new generation, transmission and distribution, control and tariffs, and legal and regulatory frameworks, including the corporatization of Electricite du Liban (EDL). The policy paper reiterates the GoL’s pledge to source twelve percent of electricity supply from renewable energy sources by 2020, and the focus of the renewable energy targets indicated within the Policy Paper was on onshore wind power, hydropower, and waste-to-energy, with indirect emphasis on distributed generation through the enabling of the “net metering” program.

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The PV generator or the microwind turbine (DC output turbine) is connected through a battery charge controller with maximum power point tracking to a 48 V DC bus bar. Direct current (DC) electricity is stored in the battery first, and then converted to AC current in the dual i-mode bidirectional sinusoidal inverter. This particular type of inverter can operate autonomously in voltage control mode as well as in current control mode synchronized with the grid when the grid is powered. An automatic transfer switch ensures electrical safety with respect to the grid at all times. The building’s priority load is satisfied in the first instance from the microgenerators and the battery. If the generation exceeds the priority load, then other loads are satisfied, and when/if all the loads are satisfied and the generation is still in excess, the surplus is exported to the grid via the current “net metering” arrangement.

For larger systems envisioned in the commercial sector, including batteries becomes prohibitively expensive (depending on the institutions’ load characteristics), and therefore a grid-connected system is required whereby the integration of renewable energy sources interacts with both the national grid when electricity is on, and with the diesel generation when blackouts exist.

This RE system may lead to a better outcome in terms of reducing the cost of energy to respective institutions. The general schematic for such a system, assumed to be a PV system (as the solar irradiance is best aligned to the commercial sector’s working hours), is shown in Figure 2.3.

Figure 2.3 PV system, storage, diesel genset, utility and load schematic

The schematic or architecture for the PV system requires integration within the Lebanese energy con-text, where the system must synchronize with existing diesel-generators at respective institutions when utility electricity is absent, and then to synchronize with utility power once the power is present. The availability of battery storage is optional and depends on the size of the required RE system and the institutions’ loads, the respective financial costs and benefits of having backup storage, and the type of the institution, where in some cases such as hospitals, for example, uninterrupted supply of power to certain loads cannot be compromised. Battery storage can also be utilized for the objective of catering for the 10-20 seconds time lag between the interruption of utility power supply and the turning on of diesel generators. On occasions where the load is not too large, such as in small companies, the diesel gensets can be sacrificed for battery storage. In other words, if an office requires a significant amount of power, battery storage should be avoided (due to excessive costs for obtaining a large battery bank) and synchronization between the RE and the genset is required, whereas when an office is small, the diesel genset can be sacrificed for battery storage.

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3 Willingness to Pay for Renewable Energy: Descriptive Analysis and Results

The UNDP-CEDRO project commissioned a survey that undertook the sampling of six hundred residential and two hundred commercial institutions across the country to illicit their willingness to pay (WTP) for renewable energy sources, both renewable energy located within their vicinity and under their ownership, and/or purchased from the national grid where the national utility delivers “green” energy to their respective offices. The actual surveys used were in Arabic, yet a translated version in English can be found in Annex 1 for both the residential and the commercial sectors.

The survey design had to create simplicity and clarity from a very complex situation that dictated the integration of renewable energy systems in the Lebanese grid and had to capture a sufficient sample from the Lebanese residential and commercial sectors that enables representation of these sectors at large.

3.1 Introduction

The survey followed a stratified random sampling method where the geographical spread and gender distribution (i.e., female/male) strove to follow national statistics as best as possible.

The percentage distribution of the six hundred residential sector samples that where obtained from six Lebanese Mohafazat (regions) are indicated in Figure 3.1. They are compared to the actual population distribution of Lebanon according to CAS (2009).

3.1.1 The Lebanese Residential Sector

3.1.1.1 Geographic and Demographic Representability

Figure 3.1 Distribution of 600 samples vs. actual population distribution in Lebanon (adopted from CAS)

40%

20%

12%

11%

11%

6%

Mount Lebnaon North Bekaa Beirut South El naba4eh

Distribution of 600 samples across the Leb.Mouhafazat

2009 distribution of Leb.population across the Mouhafazat

43%

17%

12%

11%

10%

7%

Mount Lebnaon North Bekaa Beirut South El naba4eh

13

Samples obtained fall close to the actual distribution of the population and therefore can confidently be considered representative of the population with respect to the geographical spread. Figure 3.2 indicates the distribution of the sample with respect to urban vs. rural concentrations. The sample slightly over-represented urban areas and under-represented the rural ones.

Figure 3.2 Sample vs. Population urban and rural distribution (Source: ESCWA www.escwa.un.org/popin/members/lebanon.pdf)

With respect to gender, the sample targeted 50% males and 50% females, close to the 48.8% males and 51.2% gender distribution in Lebanon.

Concerning the distribution of the number of family members, Figure 3.3 illustrates that the collected sample of 600 residents correlated, randomly, with the overall expected (actual) distribution of family members, although some variation between the values have resulted (given the random nature of the sampling). The mean recorded is 4.38 family members per household.

Figure 3.3 Distribution of sample family number vs. actual number (Source: www.pdslebanon.org)

Urban / Rural representation (%)

# of family members

14

With respect to age, the only condition was that the respondent had to be above the age of 18. The distribution of the 600 surveys is indicated in Figure 3.4.

Figure 3.4 Age distribution of the random survey

The majority of the sampled respondents were married, as shown in Figure 3.5, with eighty percent of the married respondents having three children or less (Figure 3.6).

66%

34%

Married Unmarried

Figure 3.5 Percentage (%) of married people from sampled residents

Figure 3.6 Percentage distribution of sampled married residents’ number of children

The education level obtained as revealed through those surveyed is indicated in Figure 3.7. Most of the surveyed respondents have either completed high school, have obtained a university bachelor degree, or have a higher university degree.

Age group

Number of children

15

Figure 3.7 Distribution of education level of sampled residents

Approximately 73.7% of those surveyed were employed, as shown in Figure 3.8, followed by unemployed category (including “house wife”), and students.

74%

4%

2%

15%

5%

Employed Unemployed Re-red House Wife Student

Figure 3.8 Percentage distribution (%) of employment/other status of the interviewed residents

With respect to income of the surveyed respondents, Figure 3.9 shows that relatively most of those surveyed have incomes ranging from $501-$1,000 per month, followed respectively through the increasing brackets, where approximately 42.3% of those surveyed have incomes reported to range from $1001-$2000 per month.

Figure 3.9 Distribution of income groups of sampled residents

Income bracket

16

Turning to dwelling characteristics, Figure 3.10 shows that 64.8% of those surveyed live in indepen-dent (i.e., separate) apartments in buildings, followed by 34.5% that live in independent houses. It is important to note that 54.3% of the respondents in the rural areas indicated they have an independent house, with 43.4% indicating they live in independent apartments in buildings, and only 2.3% indicated they live in villas. In the urban areas, 32.8% of respondents indicated they live in independent houses, while 66.6% live in independent apartments in buildings, and 0.5% of the respondents in “urban” areas reside in villas.

With respect to ownership, approximately 64.5% of those surveyed indicate they own their dwelling, followed by 20.8% indicating they are currently tenants, as shown in Figure 3.11.

3.1.1.2 Dwelling Characteristics

Figure 3.10 Distribution (%) of dwelling characteristics of surveyed residents

Figure 3.11 Distribution of sampled residents w.r.t. housing ownership

Relatively more people in rural areas own their dwelling (approximately 71.7%) compared to urban dwellers (approx. 63.7% own their dwelling). About 21.1% rent their premises in urban areas as op-posed to 17.4% in rural areas.

The survey asked respondents their views on the current energy situation, and the subsequent costs they face on securing their respective energy needs. Figure 3.12 begins this part of the survey through a general question about the opinion of the interviewee on the current electricity sector’s performance in Lebanon. The majority of respondents, totaling 87.5% of those surveyed, indicated that they view the current energy situation in Lebanon as being “poor” or “very poor.” This is expected given the short-coming of the electricity sector in the country (outlined briefly in Chapter 2).

3.1.1.3 Residential Energy Profiles and Attitudes

34%

1% 65%

Independent house Villa Apartment in independent building

21%

64%

15%

Rented Ownership Live with parents

17

Figure 3.12 Lebanese citizen’s perspective on the current energy situation

The majority of the interviewees indicated that they face daily blackouts where they reside (Figure 3.13), with a larger share of respondents facing more than nine hours of blackouts (Figure 3.14).

98%

2%

Yes No

Figure 3.13 Percentage of surveyed Lebanese household experiencing daily blackouts

Perspective on the current energy situation of Lebanon

Percentage (%) of respondent experiencing blackouts

12%

16%

24%

48%

Up to 3 hours Up to 6 hours Up to 9 hours More than 9 hours

Figure 3.14 Distribution of hours of blackouts experienced by surveyed Lebanese households

Percentage distribution of hours of blackouts per 24 hr day

18

When facing these blackouts, most of the interviewees (approximately 85.6%) indicated that they rent or own diesel genset power, followed by 8.5% of interviewees who indicated they have an uninterrupt-ible power supply (UPS) source. Figure 3.15 reveals that 2.5% of respondents have nothing to cover the blackouts while 0.5% of respondents indicated that they still use candles.

Figure 3.15 Energy security reaction/responses of surveyed people in times of blackout

Percentage distribution of surveyed responses to blackouts

Those who own or rent diesel genset power own and rent capacity in various sizes as shown in Figure 3.16. Five Amperes is the most common, followed by ten Amperes. Very few households have twenty Amperes or more.

Figure 3.16 Distribution (%) of Ampere capacity to cover blackout periods by surveyed households

More than half of the rented and/or owned backup power are able to completely cover the blackout hours, however a substantial share of respondents indicated that the rented/owned backup gensets do not or cannot cover the full blackout hours (Figure 3.17). This is not uncommon, for example, neighborhood gensets are turned off during late nighttime hours and in areas where blackouts exceed nine hours, “resting” the generator is often quoted.

Distribution (%) of Ampere capacity backup

19

5%

14%

22% 59%

25% of blackout hours 50% of blackout hours 75% of blackout hours 100% of blackout hours

Figure 3.17 Distribution of backup generation coverage of blackout hours

Backup generator coverage of blackout hours

The distribution of payments for the gensets ranges from as low as thirty dollars or less per month, to as high as 250 dollars or more. Figure 3.18 lists this distribution.

Figure 3.18 Monthly payments to backup generator by surveyed households

What is telling in Lebanon is that the payments for genset capacity are not uniform across similar am-perage capacity. In other words and according to the findings of the survey, five Amperes, for example, are rented for thirty dollars in some cases and 140 dollars in other cases, as shown in Table 3.1, with a standard deviation of 28.9 dollars. The same holds for all other categories of power capacity rented. An important and yet not unexpected finding is that most payments for genset power occurs in capacity and not in actual power consumed. The Ministry of Energy and Water in Lebanon tries to regulate the private distributed power generator sector by setting the ceiling in which power, in kWh, can be sold. However, most of the respondents in the survey revealed they purchase power capacity, usually in steps of five Amperes.

Monthly payments for backup generator

(%)

20

Figure 3.19 shows the monthly payments of interviewees for the national grid operator, EDL. Most of the payments range from 20 – 60 dollars per month.

Figure 3.19 Distribution (%) of monthly payments to utility (EDL) as paid by surveyed households

With respect to air conditioning and electric heating, two requirements that demand a lot of energy to power, Figure 3.20 and Figure 3.21 show that in Lebanon, most residents, as revealed by the survey, depend on air conditioning in summer and electric heating in winter.

Figure 3.20 Percentage of surveyed citizens using air conditioning and their level of dependence

Monthly payments for utility (EDL) electricity

62%

38%

Yes No air condi-oning

15%

27%

28%

30%

Very li(le Moderate Considerably Extremely

Percentage (%) surveyed using air conditioning Percentage (%) of degrees of dependenceon air conditioning

Table 3.1 Statistics on monthly rent payments for diesel gensets capacity

Number Min ($) Max ($) Median ($) Mean ($) Std. Deviation

5 Amps 409 30.0 140.0 60 69.3 28.9

10 Amps 141 40.0 250.0 120 121.9 51.0

15 Amps 21 60.0 300.0 200 178.6 90.0

20 Amps 12 80.0 400.0 120 176.7 106.9

30 Amps 7 140.0 850.0 300 381.4 299.4

Invalid 7

21

Figure 3.21 reveals the dependence on electric heating is not as significant as air conditioning. This can be expected in a Mediterranean country like Lebanon. Furthermore, this has been verified in the UNDP/GEF (2014) publication, where it is indicated that 57% of the residential sector rely on diesel fuel for heating, while 31% rely on electricity.

24%

35%

24%

17%

Very li(le Moderate Considerably Very much

Figure 3.21 Degrees of dependence on electric heating from surveyed citizens

Respondents were asked about their respective knowledge on renewable energy systems. Figure 3.22 shows the results. More than half the respondents indicated they have “poor” to “very poor” knowledge on RE systems while 28% indicated that they have “good” to “excellent” knowledge. The importance of awareness with respect to renewables is revisited in Chapter 4.

3.1.1.4 Residential Renewable Energy Perspectives

Figure 3.22 Knowledge of renewable energy systems of surveyed citizens

Knowledge of renewable energy systems

Percentage (%) of degrees of dependenceon on electric heating

22

Most of those surveyed indicated that space is not an issue for renewable energy systems, shown in Figure 3.23. Slightly more of the respondents living in rural areas than those living in urban areas indi-cated their belief that they have sufficient space for RE systems on their respective roofs (78.3% versus 73%). Approximately 12.7% of urban dwellers and 19.6% of rural ones indicated that they do not know if the space they have suffices for RE systems.

Figure 3.23 Percentage (%) distribution on perspectives of surveyed citizens’ w.r.t. space availability

Figure 3.24 indicates that most of the interviewees do not have any renewable energy system installed, followed by those who indicated that they have a solar hot water (SHW) system. Only one respondent indicated the availability of an electricity-producing RE system on their roof.

Figure 3.24 Percentage of surveyed citizens withrenewable energy system installed

Space Availability for Renewable Energy Systems Percentage (%) with renewable energy installated

Figures 3.25 and 3.26 show that the majority of the respondents is not actively involved, nor are they aware of close family members being actively involved, in environmental non-governmental organiza-tions (NGOs) or in any renewable energy association.

1%

99%

Member Non-‐member

Figure 3.25 Percentage (%) of those involved as members in an environmental organization

2%

98%

Yes No

Figure 3.26 Percentage (%) of the 600 residents surveyed with family members or themselves

active in the RE sector

74%

13%

13%

yes I don't know No

0%

97%

3%

yes Non Only SHW System

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A set of questions in the survey targeted the respondents’ attitude toward the Lebanese government and their attitude and/or opinion on the actual survey being implemented. For those who responded with a lot of zero values, known as protest bids, the reasons for this were also requested and recorded. Figure 3.27 reveals the responses of interviewees on their respective comfort in terms of the government handling and managing any money transfers for RE support.

3.1.1.5 Residential Sector Attitude on Government and Survey

Figure 3.27 Residential sector’s comfort and trust in government management of money transfers

Almost half the respondents indicated that they are “fairly ok” or “highly ok” with the option that the government manages any transfer of funds for RE, while 32% were against this option, and 18.8% indifferent.

For those who answered mostly zero values for the WTP for RE scenarios in the survey, a follow-up question as to the reason for this “zero” value was requested. The answers are shown in Figure 3.28.

Figure 3.28 Percentage distribution of reasons for zero bids

How comfortable are you with the Lebanese government managing thismoney tranfer and RE support? (%)

Reasons for zerobids

Most of those with zero bids indicated they have done so because they are uninterested in the subject and in renewable energy, followed by the declaration that the government should pay to secure a more sustainable energy resource. Approximately eleven percent indicated that they will not venture into RE because, according to their respective perception, RE does not secure 24-hour electricity.

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Figure 3.29 Percentage distribution of reasons for zero bids

5%

14%

9%

72%

Did not understand the survey Did not believe in the survey Showed protest behavior Normal

Respondents’ attitudes to the survey

Two hundred surveys were sent to the commercial sector inquiring about their willingness to pay for renewable energy in Lebanon and seeking to find some basic “company” information and profiles. The companies surveyed where spread also across the country, as shown in Figure 3.30.

3.2.1 The Lebanese Commercial Sector

3.2.1.1 Company Characteristics

The surveyed sub-sectors within the commercial sector are outlined in Figure 3.31. Most of the sectors fall within the services and commerce groups, followed by agricultural, educational and health-related institutions.

Figure 3.30 Percentage (%) distribution of surveyed companies according to Lebanese regions

36%

32%

14%

10%

8%

Mount Lebnaon Beirut Bekaa South North

Distribution of survey across the Lebanese Mohafazat

Figure 3.29 indicates the general perspective of the interviewee in regards to the survey. Most of those surveyed have shown a normal understanding and attitude towards the survey, however approximately twenty-eight percent either did not understand the survey well enough, did not believe in it, and/or showed protest behavior. Given that surveys on renewable energy are relatively new in the Lebanese context, this attitude can be expected.

25

Figure 3.31 Composition, in percentage (%), of the commercial sector institutions surveyed

Commercial entity surveyed type

The majority of the surveyed institutions are characterized in having twenty employees or less, and therefore can be considered to be small-to-medium sized enterprises, as indicated in Figure 3.32. The mean number of employees amounted to thirty-three, while the median amounted to fourteen employees.

Figure 3.32 Percentage distribution of the number of employees of surveyed institutions

The office-space areas surveyed are distruted in accordance to Figure 3.33. The mean space, in square meters, is approximately 1255 m2, while the median is approximately 450 m2.

Figure 3.32 Percentage distribution of the number of employees of surveyed institutions

Number of employees per surveyed institution

Distribution of area (in meters-squared) of surveyed institutions

26

The majority of the surveyed institutions indicated that they do not have a maintenance team, as shown in Figure 3.34. With respect to ownership, approximately 55.5% of the offices are rented and 45.5% are owned (Figure 3.35).

Obtaining the budget balance of companies was practically impossible, where 80.5% refused to answer the question related to their respective annual turnover, and 81% refused to answer the question related to annual profits. The only question that hints at their economic standing is related to a comparison between revenue and expenses, shown in Figure 3.36, and even 7.5% refused to answer that question.

Figure 3.36 Distribution of relative economic wellbeing of surveyed institutions

Comparison of revenues and expenses

40%

60%

Yes No

Figure 3.34 Percentage of institutionswith or without a maintenance team

Figure 3.35 Percentage of institutions ownership’s standing

Percentage of institutionswith a maintenance team

Percentage of institutionseither renting or owning their premises

44%

56%

Rented Ownership

Similar to the residential survey, the interviewed personnel within the institutions (mostly General Managers) were asked about their perspective on the current energy situation in Lebanon. Figure 3.37 reveals the results, and similar to Lebanese residential citizens, most of respondents viewed the situation as “poor” or “very poor.”

3.2.1.2 Commercial Energy Profiles and Attitudes

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Figure 3.37 Percentage distribution of respondents’ views on the current energy situation

Perspective on the current energy situation in Lebanon

All the respondents indicated that their respective institutions face daily power cuts, as shown in Figure 3.38, with most indicating that they face more than nine hours of daily blackouts, which often means the entire working hours without government supplied electricity.

Figure 3.38 Percentage distribution of power cuts per day

Hours of blackouts per 24 hour day

Most companies either owned backup gensets (approximately 57%) or rented genset capacity (approximately 38.5%).

Figure 3.39 Percentage distribution of backup source during EDL blackouts

What does your institution have to cover the blackout periods?

The mean rented capacity was indicated to be approximately 98.6 Amperes, yet the median indicated is approximately 50 Amperes. The distribution of owned or rented diesel power is shown in Figure 3.40.

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Figure 3.40 Percentage distribution of power capacity from gensets during blackouts

Most of the power capacity obtained from gensets covers all the required working hours, as indicated in Figure 3.41. This can be attributed to the fact that power is needed mostly during the day, unlike the residential sector where nighttime hours of power is also requested yet not always delivered.

How many amperes do you have as backup power?

4%

13%

83%

50% of blackout hours 75% of blackout hours 100% of blackout hours

Figure 3.41 Distribution of coverage of gensets during blackouts

Extent to which backup covers blackouts

Figure 3.42 indicates the payments transferred to secure power from gensets. The mean payments for this backup service amounted to 869 dollars per month, while the median value stands at 450 dollars per month.

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Figure 3.42 Distribution (in percentage) of payment for backup gensets

Breakdown distribution of monthly payment amount (USD) for backup generator

Similar to the residential sector, payments to operate or secure the diesel gensets are not uniform within each of the categories. For example, the cost of securing ten Amperes ranges from 100 – 150 dollars, while the cost for twenty Amperes ranges from 100 – 450 dollars, and that for thirty Amperes ranges from 150-650 dollars.

Payments to the national utility, EDL, are shown in Figure 3.43. The mean payments are approximately 463 dollars while the median value is 350 dollars.

Figure 3.43 Percentage distribution of EDL monthly payments of surveyed institutions

The majority of the surveyed institutions are dependent on air conditioning in the summer, with the majority indicating that they are dependent to considerable degree (Figure 3.44).

Breakdown distribution of monthly payment amount (USD) EDL electricity

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Figure 3.44 Percentage distribution of surveyed institutions dependence and degree of dependence on air conditioning

Dependence on electric heating is less pronounced than air conditioning, as can be shown in Figure 3.45.

68%

32%

Yes No

Figure 3.45 Percentage distribution of surveyed institutions dependence and degree of dependence on electric heating

Percentage of Institutions usingelectric heating in winter

Percentage distribution of degree of dependence on electric heating

1%

25%

28%

20%

26%

Not at all Very Li-le Moderately Considerably Very much

94%

6%

Yes No

Percentage of Institutions using air conditioning in summer

Percentage distribution of degree of dependence on air conditioning in summer

1%

21%

31%

47%

Very li(le Moderately Considerably Very much

Knowledge on renewable energy technologies fared relatively better than the residential sector’s knowledge, yet only slightly. Approximately forty-three percent of those interviewed indicated a “poor” to “very poor” knowledge, as shown in Figure 3.46, while thirty-nine percent of respondents answered that they have “good” to “excellent” knowledge of RE systems.

3.2.1.3 Commercial Renewable Energy Perspectives

Figure 3.46 Percentage distribution of “knowledge” levels on RE systems

Knowledge on renewable energy systems

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Only one institution indicated that it has an-electricity producing RE system installed, with the majority having no RE system whatsoever. With respect to energy efficiency measures (EEMs), statistics of the survey paint a better picture, as shown in Figure 3.47.

Approximately seventy percent of the surveyed institutions undertook some kind of EEM. The measures undertaken are indicated in Figure 3.48. Lighting represents the lion’s share, with approximately 55.9% of those surveyed indicating they have changed their lighting to more efficient products. Behavioral change and window double glazing follows. It is interesting to note that even equipment upgrades were implemented by some agencies taking into consideration the equipment’s energy performance.

70%

30%

Yes No

Figure 3.47 Percentage of surveyed institutions who undertook EEMs

Energy efficiency measures undergone?

Figure 3.48 Percentage distribution of respective EEMs undertaken by surveyed institutions

A follow-up question on whether the institutions are willing to undertake energy efficiency measures was asked, and the positive responses are shown in Figure 3.49. Approximately 60.5% of those sur-veyed said they are willing to undergo EEMs, a finding that should resonate within policy maker’s plans for this sector.

Energy efficiency measures undertaken

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Figure 3.49 Distribution of willingness to undertake EEMs

Willingness to undergo energy efficiency measures

In the commercial sector, trust in the government to handle any money transfer is lower than that in the residential sector (compare Figure 3.27 with Figure 3.50). As shown in Figure 3.50, approximately fifty percent of those surveyed indicated their negative views on the government handling money transfers, with approximately twenty-nine percent indicating a more favorable view. 20.5% seemed indifferent to the government handling or not handling any money transfers to the RE sector.

3.2.1.4 Commercial Sector Attitude on Government and Survey

Figure 3.50 Commercial sector’s comfort and trust in government management of money transfers

Figure 3.51 shows the distribution of percentages of the reasons given for zero bids. Similar to the residential sector’s reasons for “zero” responses, most of the reasons for the “zero bids” given by the commercial sector respondents was due to their respective lack of interest in RE or their view that the government should step in to support and pay for RE systems.

Figure 3.51 Percentage distribution of reasons for zero bids in commercial sector

Furthermore, approximately forty-six percent of those in the commercial sector who mostly answered zero for the WTP for RE also indicated that they do not believe in the survey’s objectives, while eleven percent showed protest behavior.

Comfortability with the Lebanese government managing the money transfer for RE support

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4 Willingness to Pay for Renewable Energy: Regression Analysis

Four dependent variables (additional WTP per month) were considered for the residential sector that best reflected the technical options (see Chapter 2) of integrating renewable energy systems in the residential sector, both under the current electricity situation and under a situation where national grid electricity is provided on a 24-hour basis. These scenarios are (Dagher & Harajli, 2015):

1- WTP L1: WTP for RE if RE (with battery storage) is procured locally (local system means installed on one’s own roof) that caters for most of your electric needs, reducing your energy costs, yet will not be able to displace your diesel generator especially if you rely on electric heaters in winter and air conditioning in summer.

2- WTP L2: WTP for RE if RE (with battery storage) is procured locally, and the RE system can completely satisfy your load requirements and displace the diesel self-generator and reduce utility bills from the national utility

3- WTP U1: WTP for RE if RE power is procured from the national grid, yet electricity cuts remain in the country and the household must thus keep renting/operating their diesel generators.

4- WTP U2: WTP for RE if RE power is procured from the national grid, yet electricity by the grid (utility) in the country is provided 24 hours a day and therefore there is no longer the need for a backup diesel generator.

Table 4.1 indicates the results obtained on WTP for RE.

4.1 Scenarios and WTP Outcome for the Residential Sector

This chapter highlights the outcome of the regression analysis for both the residential sector and the commercial sector. It sets out to find which independent or explanatory variables impact the dependent variables (i.e., WTP for RE under the various scenarios). The chapter relies and summarizes two publications: Dagher and Harajli (2015) and Harajli and Gordon (2015).

Table 4.1 WTP outcomes for four scenarios in the residential sector (Dagher and Harajli, 2015)

Variable Mean Std. Error of Mean

Median Std. Deviation

Min Max % zero answers

WTP-L1 29.48 1.166 20.00 28.568 0 120 28.9%

WTP-L2 54.12 1.654 50.00 40.525 0 300 11.5%

WTP-U1 24.79 1.172 20.00 28.703 0 120 34.9%

WTP-U2 59.50 2.076 50.00 50.863 0 400 13.5%

The monthly median willingness to pay for renewable energy is approximately twenty dollars when diesel-generation is not completely displaced (only reduced fuel use, WTP-L1), and fifty dollars when diesel-generation can be completely eliminated (WTP-L2). In both cases, the means (averages) of the second option are higher than the first option. The median WTP for renewable energy is similar for the decentralized renewable energy systems (or “locally” procured) and those procured by renewable energy through the national grid. This shows no strong preference to “locally” sourced renewable energy as one would have expected given the current state of electricity.

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Five dependent variables (WTP per month additional to the utility bill) were considered that best reflected the technical options (see Chapter 2) of integrating renewable energy systems in the commercial sector, given the range of company sizes and their respective energy demand and assuming both the current electricity situation and a situation where national grid electricity is provided on a 24-hour basis. These scenarios are (Dagher & Harajli, 2015): 1- WTPL1: WTP for RE if RE (with battery storage) is procured from a local system (local system means

installed on one’s own roof) that caters for most of your electric needs, reducing your energy costs, and can also displace your diesel generator if the company does not rely on electric heaters and air conditioning. If the company relies on air conditioning and electric heating, a diesel genset will have to remain in place.

2- WTPL2: WTP for RE if RE (with battery storage) is procured from a local system, and the RE system can completely satisfy your load requirements and displace the diesel self-generator and reduce utility bills from the National Utility.

3- WTPL3: WTP for RE if RE (without battery storage) is procured from a local system, and the system can only reduce the costs of utility electricity and the diesel generator, yet not displace them entirely.

4- WTPU1: WTP for RE if RE power is procured from the national grid, yet electricity cuts remain in the country and the company must thus keep renting/operating their diesel generators.

5- WTPU2: WTP for RE if RE power is procured from the national grid, yet electricity by the grid (utility) in the country is provided 24 hours a day and therefore there is no longer the need for a backup diesel generator.

The first three scenarios are attributed to “local” RE systems, while WTP U1 and WTP U2 consider RE power procured through the national utility. Table 3 indicates the findings of the respondents in terms of the mean, median, standard deviation and percentage of zero answer outcomes.

4.2 Scenarios and WTP Outcome forthe Commercial Sector

Table 4.2 WTP outcomes for four scenarios in the commercial sector (Harajli and Gordon, 2015)

Table 4.2 shows the importance of reliability in power systems; if the renewable energy system displaces the diesel generator, WTP will increase. As a matter of fact, approximately thirty-six percent of those who have answered zero to any of the scenarios indicated that the reason for this is the lack of reliability and/or the ability of the RE system to guarantee 24 hours of electricity a day. The rest of the “zero” bids were due to disinterest in RE systems (32% of those presenting a zero bid), the government’s role in paying for RE (19.3% indicated that the government should pay for RE), and the lack of ownership of the company premises (5.5% of those presenting a zero bid).

The regression analysis in the next section focuses on three main scenarios: WTPL2, WTP L3, and WTPU2. WTPL1 and WTPU1 were omitted from the analysis because of a high “zero response” rate, indicating strongly that, for WTPL1, paying for an RE system that does not displace a diesel generator and cannot cater for the air conditioning and electric heating loads would not be a rewarding option, as is the case of paying more for RE power coming from the grid if 24-hour electricity is not guaranteed and diesel genset power would still be required as illustrated in WTPU1.

Scenario Mean St. error St. dev. Median % zero answers

WTPL1 229.8 41.0 578 0 52.0%

WTPL2 558.6 94.0 1330 200 36.5%

WTPL3 453.7 71.9 1016 200 33.0%

WTPU1 210.0 57.3 809 0 54.5%

WTPU2 612.9 118.9 1680 200 26.0%

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4.3 Regression Analysis: Methodology and Output

The methodology employed is referred to in Dagher and Harajli (2015) and Harajli and Gordon (2015). The methodology for this type of data is Tobit Regression also known as Censored Regression. Refer-ences on this methodology can be found in Greene (2003), Tobin (1958), Long (1997), Lee and Zeng (1999), and Cong (2000).

4.3.1 Methodology

4.3.2 Residential Sector Regression Results

Seven independent variables impact WTP for RE for both cases, WTP L1 and WTP L2. These indepen-dent variables, with their consequent signs are included in the Table 4.3 below:

Table 4.3 Main variables of significance and their directional relationship with WTP for WTP-L1 and WTP-L2

Table 4.3 indicates that there is a relationship between the above indicated variables and WTP. When the relationship is positive, this means that, for example, the more a household pays for genset rent and/or utility electricity, or the more awareness on RE systems and/or trust in government, the more the householder will be WTP for RE. Furthermore, owning the apartment is also crucial, given that those who are renting their apartments/houses are less willing to pay for RE. With respect to demo-graphic variables, age (D5) appears to be influential on WTP. The negative sign of the coefficient indi-cates that the younger the respondent, the more, on average, is his/her WTP.

The only difference between the two scenarios is the independent variable “dependence on air con-ditioning,” where in WTP-L2 it was significant and positively related. This is expected because it is only in WTP-L2 where we indicate to the surveyed individual that the RE can cover all his/her end-use elec-tricity needs.

For the utility delivered power, Table 4.4 indicates, similarly, the variables that impact WTP and the direction of the relationship. However in this case, the two cases (WTP U1 and WTP U2) are separated; the cases are not similar with respect to their relation to the indicated independent variables.

Independent variable Relationship to WTP

Monthly payment to backup generator +

Utility monthly payment +

Knowledge on renewable energy +

Dependence on electric heating +

Trust in government +

Age -

Ownership of property status +

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Table 4.4 Main variables of significance and their directional relationship with WTP for WTP-U1 and WTP-U2

Results for WTP for RE from the national grid, shown in Table 4.4, show less common significant vari-ables between each other than when comparing the two “local” cases in Table 4.3. WTP for RE from the grid when the energy security is not provided (i.e., 24-hour electricity is absent) annuls the importance of payments to diesel gensets, and as expected WTP for RE is highly significant when energy security is provided in WTP U2. This wasn’t the case in the locally installed RE systems. An explanation can be the respondent’s feeling of control in the locally sourced RE, where, maybe, the respondent may think that controlling loads can enable the effectiveness of RE to the extent of illuminating the diesel backup genset (Dagher and Harajli, 2015).

The respondents that depend more on air conditioning in summer and who are told that the RE can completely satisfy this energy demand, are WTP more. If this demand cannot be met except by diesel gensets, then those respondents that depend more on air conditioning are WTP, on average, less.

4.3.3 Commercial Sector Results Results for the commercial sector are presented in accordance with the three selected scenarios, WTP2, WTP3 and WTP5 in Tables 4.5 and 4.6. Only the statistically significant variables are indicated with their directional relationship. Details of the values of the coefficients can be viewed in Harajli and Gordon (2015). Furthermore, the approach adopted in Harajli and Gordon (2015) differs slightly from Dagher and Harajli (2015) in that the significance levels targeted the various levels or scale for each variable. For example, in the “comfortability with government,” significant testing occurred on each level from the “1: not at all, to 5: very,” so that Level 2 was compared to Level 1, Level 3 with Level 2, and so forth. In Table 4.5 below, we indicate significance at any level within each important variable. Readers can re-fer to Harajli and Gordon (2015) for details on the significance values within the scales of the variables themselves.

Table 4.5 Main variables of significance and their directional relationship with WTP for WTP2 and WTP3

Independent variable WTP U1 Relationship to WTP WTP U1 Relationship to WTP

Monthly payment to backup generator

Insignificant +

Utility monthly payment + +

Dependence on air conditioning Insignificant +

Dependence on electric heating + +

Trust in government + +

Age - Insignificant

Independent variable WTP2 Relationship to WTP WTP3 Relationship to WTP

No. of employees + +

Approximate working area Insignificant +

Ownership + +

Monthly payment to backup generator

+ Insignificant

Utility monthly payment + +

Trust in government + +

Willingness to undergo energy efficiency (EE) measures

+ Insignificant

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Number of employees and approximate working area can be viewed as proxies for income generation, the latter of which was not answered by the commercial respondents due to confidentiality concerns. Ownership is also important, meaning that the probability of having RE systems installed is higher on properties owned by the commercial institution in question.

Results of statistically significant variable of the final scenario, WTP5, are shown in Table 4.6.

Table 4.6 Main variables of significance and their directional relationship with WTP for WTP5

WTP5 assumes a reliable electricity system and that RE is purchased from the grid with a premium above the monthly fees paid to the utility (Harajli and Gordon, 2015).

Independent variable WTP2 Relationship to WTP

No. of employees +

Approximate working area Insignificant

Ownership +

Monthly payment to backup generator +

Utility monthly payment +

Trust in government +

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5 Policy implications and Conclusion

5.1 Income, Revenue and Expenditure on Electricity

This chapter sets out the policy recommendations that can be inferred from the surveys undertaken for the residential and commercial sectors. However before discussing these recommendations, an expected and yet major finding is related to the expenditures of current Lebanese citizens and companies on energy provision.

For the residential sector, a significant amount of income is earmarked to secure the electricity and hot water (given that water is mostly heated through an electric boiler in Lebanon) needs of a household. Lebanese consumers pay, on average, approximately 10.4% of their income on electricity including both the utility bill and the backup generator bill (taking the median values shown in Chapter 3 as indicators). This value can be considered as conservative, because heating costs and national annual budget transfers to EDL (Lebanon’s national utility) are not considered. Under one UK definition, “a fuel poor household is defined as one which needs to spend more than 10% of its income on all fuel use and to heat its home to an adequate standard of warmth” (Energy UK, 2014). Approximately fifty percent of Lebanese citizens pay more than ten percent of their income on electricity in Lebanon, as shown in Figure 5.1, and therefore approximately half the Lebanese can be considered, on average, fuel poor.

Figure 5.1 Percentage of total energy expenditures from income in the residential sector for electricity provision (Dagher and Harajli, 2015)

If the indirect costs of annual government revenues transferred to EDL are accounted for, as shown in Figure 5.4, assuming a mean annual value of transfers from 2008-2012 of $1.669 billion and the statistic that the residential sector consumes approximately 45.7% of total electricity consumption and that the average household in Lebanon has 4.38 members (see Chapter 3), the percentage of total individual income devoted to electricity provision of the sampled survey is shown in Figure 5.2, keeping the original percentage that excludes EDL (i.e., Figure 5.1 data).

Survey sample identity

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IEA statistics; http://www.iea.org/statistics/statisticssearch/report/?&country=SYRIA&year=2011&product=ElectricityandHeat

Figure 5.2 Percentage of total energy expenditures from income in the residential sector pertained to electricityprovision (including EDL budget transfers)

Survey sample identity

Including EDL transfer raises the average percentage of income spent on electricity in Lebanon for the residential sector to 16.64%. In this case, approximately 78.2% of Lebanese citizens pay more than ten percent of their income on electricity provision, a harsh statistic.

With respect to the commercial sector, the monthly cost of securing electricity requirements, from both back-up gensets and the national utility grid is given again, summarized, in Table 5.1.

Table 5.1 Monthly expense on securing power (in USD) for companies

From the commercial survey of two hundred companies, only thirty-nine companies indicated their actual annual revenues, and a comparison between these select companies’ annual energy costs and annual revenues shows that the former constitute approximately twenty percent of the latter, as shown in Figure 5.3. The median recorded (of the percentage payment share from revenues on energy provision) was approximately nine percent.

Mean Median Std. dv. Total monthly cost

Diesel Genset 870 450 1368 1320

Utility electricity 463 350 527 813

Figure 5.3 Percentage of total annual revenues spent on energy for subsample of 39 companies

Percentage of total annual revenues expended on energy

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The share of payments for energy provision in the residential and commercial sectors is significant - to say the least. For the residential sector, the social implications of this cost are profound. Put into context, the UK has approximately 2.28 million people defined as “fuel poor” or living in “fuel poverty.” Given the current number of households in the UK, this means that approximately 10.4% of the UK population is considered fuel poor compared to 50% of the Lebanese population if we exclude EDL transfers and 78.2% if we include these transfers. Many of the strategies and policies in the UK are focused solely on targeting this “fuel poor” group and alleviating them above this energy red line. For the commercial sector, paying for energy provision is translated into reduced profits, employment, and investment.

Although the international oil price have dropped significantly by mid-2015, easing the pressures on Lebanese household expenditures as outlined above, protecting Lebanese citizens from future increases in oil prices should be a strategic, urgent and vital objective that the Government of Lebanon must focus on through the diversification of energy and power sources and the moving away from fuel oil, heavy fuel oil, and diesel oil towards natural gas and renewables.

5.2 Residential Sector Implications

Tobit regressions for the four WTP measures in the residential sector yielded interesting results. The overarching finding is the critical impact of the unreliability of the electricity sector, and consequently the existence of backup diesel generators, on the willingness to pay for renewable energy. Across most scenarios, the more consumers pay for diesel generators the higher their willingness to pay for renewable energy, particularly when the latter can displace the need for gensets completely. The median monthly that are willing to be transferred to securing renewable energy systems, if these systems displace diesel gensets, are considerably higher than estimates from the literature. Bigerna and Polinori (2014), for example, indicated that values for WTP for RE range from 0.74 – 28.9 euros per month in Europe and 0.85 – 22.5 euros per month in the USA. In Lebanon, when RE is integrated without displacing the genset, the median WTP for RE power was shown to be approximately twenty dollars, within the European and US ranges. Yet a considerably higher value of fifty dollars per month was indicated in the residential sector if the complete displacement of the genset is enabled via RE power. Similarly, higher monthly utility bills result in higher WTP amounts. Designing green power programs that can ultimately lead to displacing the diesel generators have a better chance of success and attracting more funding. This calls for further projects that demonstrate the various storage technologies available. Valuable documentation on various storage technologies and their current and future prospects can be found in the OECD/IEA (2014) and IRENA (2012).

The variables on “familiarity with renewable energy systems” and “age” were also dominant, indicating the need to invest more in awareness raising on renewable energy systems, targeted in particular with the relatively younger generation. The awareness of renewable energy and the translation on WTP was shown in many studies such as Bigerna and Polinori (2014). Extensive programs for school children, university students, and the general public is required on a continual basis to increase the willingness of this young generation to create the required change towards a more sustainable energy system.

Renting or owning a home plays a role as well for the “locally” procured RE systems, as expected, where ownership means, on average, more WTP for RE. Introducing tailored incentives and/or policies for the renting (and/or leasing) community would help in involving this sector, as would campaigns to show the flexibility in relocating RE systems. Introducing labeling energy performances of buildings, whether buildings for sale or rent, and augmenting these with tax or rebate incentives for higher efficiency homes can push renewables further for both market segments (i.e., the sale and leasing markets). Importance of labeling for homes in the rental and sales market has been demonstrated in several research papers, such as in Kahn and Kok (2014), where it was found that a sub-category of homes in

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California with a green label obtain a small premium relative to otherwise comparable, non-labeled homes. The UK Energy Saving Trust (EST) indicated in one study that “an energy efficient home will not only command higher rental value and boost chances of a property being rented, but can also increase the value of a home by an average of £3,350 when it comes to being sold” (EST, 2008).

Perception on “trust in government” is the final variable showing significance across all scenarios. This is a strong message to the Lebanese government to improve its management of the sector if it is serious about achieving its twelve percent RE target by 2020. As discussed in Section 5.1, Lebanese citizens and businesses pay too much for the provision of electricity. Figure 5.4 shows the percentage of annual revenues collected by the government of Lebanon that is transferred back to the national utility, EDL. Between 15-25% of national revenues are channeled to secure energy from fuel oil. To gain trust from the citizens, “trust” that would translate to better opportunities for renewable energy, the government needs to overhaul the management and the current condition of the sector as a whole.

Figure 5.4 Total annual subsidies to Electricite´ du Liban (EDL) and % of total annual revenues share (El-Fadel et al., 2010, updated to 2012)

5.3 Commercial Sector Implications

The major finding in this commercial survey shows, likewise, the importance of alleviating current expenditure trends on energy provision in Lebanon and consequently the design of the RE system and its limitation needs to be well thought out and communicated. These current expenditures on electricity burdening the Lebanese commercial sector offer an opportunity for renewable energy technologies on condition that diesel gensets are removed through RE systems. The two scenarios (WTPL2 and WTPU2) in the commercial sector that assumed the removal of backup diesel gensets are also the scenarios that indicate a statistically significant correlation between increasing payments to genset rent and higher WTP for RE. This is a good indication for smaller offices that rent or own diesel genset power, which account for approximately 65.5% of the sampled survey (equating to having 50 Amperes or less in diesel genset rent capacity). This is due to the fact that designing RE systems with battery storage (that are charged from both the RE system and the grid) that completely displace diesel genset rent capacity could be an economically feasible option for smaller load requirements, especially in areas like Beirut, Lebanon’s capital city, where power cuts are only three hours per day. However for larger offices, the scenario of WTPL2 which assumes the complete displacement of diesel genset becomes unrealistic. The scenario under WTPL3 is the more realistic scenario in this case, where the RE would reduce the diesel fuel use within a genset (under the condition of safeguarding the minimum efficiency of the operating genset), or enable the option of working a smaller genset, yet cannot displace a genset completely. For this scenario, demonstration projects that showcase (and communicate) and detail the expenses versus the savings achievable are required, and this is part of what the UNDP-CEDRO project will be undergoing through the expected implementation of more than seven RE sites of at least 200

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Amperes. This can be further ascertained in the fact that approximately sixty-one percent of those interviewed in the commercial sector have indicated average to below average knowledge on renewable energy systems. Given the relative complexity of the RE system required, much ground work is required to raise awareness related to the benefits of RE for the commercial sector.

On a project level, a contractor who targets companies that own their premises and that have a relatively larger number of employees and space, will find that they tend to be more willing, on average, to pay more for RE. Communicating the easement of installation and relocation of renewable energy systems can assist in promoting RE within the leasing market of commercial companies, as would tailored policies that incentivize RE within the leasing sector. Again energy labeling, as discussed in Section 5.2, can assist in this regards.

Policies should be set to specifically target the commercial sector and raise this sector’s involvement in renewable energy. The parallels between solar resource availability and load profiles make this an important objective to follow. Moreover, “trust in government” to handle the transfer of funds was also a statistically significant explanatory variable across all scenarios. This calls for transparency, clarity, and accountability in government policies in the energy sector. This has not been the case so far in Lebanon, as aforementioned.

5.4 Concluding Remarks

The report has laid out a methodology for evaluating Lebanese citizens’ and businesses’ willingness to pay (WTP) for renewable energy capacity and/or power within the difficult national electricity situation existing in the country. Lebanon is characterized by daily blackouts. Hence, the ability and limitations of renewable energy power, whether procured locally or through the national grid, has to be well communicated so that willingness to contribute towards greening the electricity sector under realistic conditions can be ascertained.

The combination of environmental economics tools and energy policy is showcased, for the first time, in the Lebanese context. The finding of this report can be utilized by both decision-makers for better policies that encourage renewable energy in the country, and on a project level where it was shown how different designs of renewable energy systems, especially their ability to displace diesel gensets, translate to enhanced opportunity. Renewable energy offers a possibility for Lebanese citizens to rise above the fuel poverty line caused by their expenditures on electricity from diesel gensets and from the national grid, particularly because the levelised costs of many renewables are less than that of diesel gensets and less than the average costs of what the present utility, EDL, pays for energy generation and distribution.

The perception held of the electricity sector has been shown to be mostly “very poor” or “poor,” and the importance of government competence and management have been emphasized. Therefore if the benefits of renewable energy can be further highlighted and marketed as a pathway towards reducing the burdens of electricity costs, then an extensive and more significant update can be realized.

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Residential and Commercial Sector Survey

ANNEX 1

Introduction (RESIDENTIAL)Lebanon uses relatively costly fuel oil and heavy diesel oil to generate most of its power. Lebanese householders pay, on average, $c9.4/kWh for their electricity, however the government subsidizes this at least 3-2 times, i.e., it pays at least $c26 kWh, and often more, to cover its costs through the national treasury which itself is replenished through various taxes that the government collects. Moreover, there is a large demand-supply deficit that the government wishes to close, and is considering to do so though several conventional and renewable energy sources. This survey aims to ask your WTP for RE sources given the current situation.

Background information 1 How do you judge the current Lebanese energy

situation in Lebanon? (Circle)

2 Do you have or experience black-outs where you live?

3 How many hours per day (i.e., per 24 hours) are the blackouts?

4 Do you own or rent a diesel generator to cover the blackout period?

5 How many Amperes do you have of backup power?

6 To what percentage does the backup generator provide power during blackouts?

7 How much do you pay, on average and per month for your backup generator?

1 2 3 4 5Very poor Poor Average Good Excellent

Yes NoGo to 3 Go to 8

Very few (exact no?)Up to 3 hoursUp to 6 hours Up to 9 hours More than 9 hours


Up to 5 AmperesUp to 10 AmperesUp to 15 Amperes Up to 20 AmperesOver 20 Amperes (exact no?)

%25 of blackout hours%50 of blackout hours%75 of blackout hours%100 of blackout hours

< 30 USD50 - 30 USD70 - 50 USD 90 - 70 USD110 – 90 USD130 - 110 USD150 - 130 USDMore than 150 USD? Please state exact amount if possible

44

8 How much do you pay, on average, per month, on your EDL utility bill?

9 How well do you think your knowledge is about renewable energy?

10 Do you have a RE electricity source installed?

11 If yes, what renewable energy system is it and what capacity?

12 What year was it installed (exact year)?

13 Does it come with storage for times of blackouts?

14 Does the RE system, with storage, cover demand all the time (with EDL)?

15 If the RE system does not satisfy all your power, do you still use a back-up diesel?

16 How much did you pay for your RE system?

17 What is the average annual O&M cost for your RE system?

18 How much do you depend on air conditioning for cooling in summer?

Valuation SectionThe below questions are aimed to illicit your willingness to pay (WTP), per month, additional to your current EDL electricity bill, to fund a RE source, keeping in mind that the paid funds will go to an independent Renewable Energy Fund managed by a specialized team yet under the authority of the Ministry of Energy and Water and the Ministry of Finance, given the below cases.

Up to $20$20 - $40$40- $60 $60 - $80$80 - $100$100 - $120$120-$140$140-$160$160-$180$180-$200> $200


Yes No Only SHW systemGo to 11 Go to 18 Circle

System Capacity (KW/Amperes)PV systemMicrowindHybridOther (please state)



Yes No

Up to 2000$4,000$ - 2,000$6,000$ - 4,000$ 8,000$ - 6,000$10,000$ - 8,000$12,000$ - 10,000$More than 12,000$

$0 - $50 $50 - $250 $250 - $500$500 - $750 $750 - $1000> $1,000

1 2 3 4 5Not at

allVery little

Moderately Considerably Very much

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19 Local system; The RE system (with battery storage), together with electricity from the national grid, can satisfy all your demand, except the demand for air conditioning in times of blackouts. AC during blackouts will have to be supplied by diesel self-generation if desired.

Please circle

> 120? Please state ____________________

20 Local system; The RE system with battery storage, together with electricity from the national grid, can satisfy all your demand. The diesel self-generation is removed.

Please circle

> 120? Please state ____________________

21 Utility scale: How much additional income are you WTP, per month, on your utility bill, to fund large RE sources secured through the network, if the current blackouts you face still exist and are met through your private diesel generator?

Please circle

> 120? Please state ____________________

22 Utility scale: How much additional income are you WTP, per month, on your utility bill, to fund large RE sources secured through the network, if electricity is provided to you by EDL on a 24 hr basis?

Please circle

> 120? Please state ____________________

23 Is there a time limit for the additional payments indicated above?

24 If there is a time limit, how much time do you see yourself paying the additional monthly payments?

25 If you are WTP, how comfortable are you with the Lebanese government managing this money transfer and RE support?

26 If you are NOT WTP, why not?

$0 $5 $10 $20 $30$40 $50 $60 $70 $80$90 $100 $110 $120

$0 $5 $10 $20 $30$40 $50 $60 $70 $80$90 $100 $110 $120

$0 $5 $10 $20 $30$40 $50 $60 $70 $80$90 $100 $110 $120

$0 $5 $10 $20 $30$40 $50 $60 $70 $80$90 $100 $110 $120


Up to 1 yearUP to 2 yearsUp to 3 yearsUp to 4 yearsUp to 5 yearsOther? Specify please?

1 2 3 4 5Not at all Not really Neutral Fairly ok Highly ok

with it

They are expensiveThey are not reliableThey cannot guarantee power in times of blackoutsThey don’t interest meI don’t think I can afford to pay for themThe government should pay for securing RE, not II would rather pay to secure 24 hours of electricity first then think of RE energyI don’t own the place where I liveOther? Please specify

46

Socio-economic characteristics1 Gender MALE FEMALE

2 How many family members reside with you (including yourself)?

3 How many children do you have (if married)?

4 Age

5 FORMAL EDUCATION: (Tick where appropriate)

6 Are you a member of any environmental group and/or a renewable energy association?

YES…. NO….

7 Do you or any member of your family have any connections with RE sources in Lebanon, i.e. have you or family member ever worked or are working in the business of promoting RE source?

YES…. NO….

8 Employment

9 In which District (Caza) in Lebanon do you currently reside?

10 In what space do you live?

11 Do you have ownership of the property or are you renting (or other)?

12 What is your monthly personal income (USD), after taxes, from all sources? Please note that this is strictly confidential and anonymous information, only to be used for statistical purposes. (Please tic one)

NonElementary SchoolCompleted High SchoolUniversity/College first degree levelUniversity higher degree (MSc./PhD)Technical School

EmployedUnemployedRetired Full-time home makerStudentOther (please specify)

Independent houseVillaApartment in independent buildingOther?

RentedOwnershipLive with parents Other?

< 5001000 – 5001500 – 10002000 – 15002500 – 20003000 – 25003500 – 30004000 - 35004500 –40005000 – 4500> 5000

47

To be filled after completing interview

• Do I think the interviewee understood the contingent valuation exercise (Yes/No)?

• On a scale from 1 to 5, was the interviewee annoyed by the interview (1 being not annoyed at all, and 5 being very annoyed)?

• Does the interviewer think the respondent? o Did not understand the survey (please check); o Did not believe in the survey (please check);o Showed protest behavior (please check);o Other (please specify); __________________________________________________

• Was there a presence of a third party during the interview (Yes/No)?

• Comments on specific questions? _______________________________________________

• Date of field visit (day/month/year)? ____________________________________________

• Time to complete interview (hours, such as 1.5)? __________________________________

48

Introduction (COMMERCIAL)Lebanon uses relatively costly fuel oil and heavy diesel oil to generate most of its power. The Lebanese commercial sector pays, on average, $c9.5/kWh for their electricity, however the government subsidizes this at least 3-2 times, i.e., it pays at least $c26 kWh, and often more, to cover its costs through the national treasury which itself is replenished through various taxes that the government collects. Moreover, there is a large demand-supply deficit that the government wishes to close, and is considering to do so though several conventional and renewable energy sources. This survey aims to ask your WTP for RE sources given the current situation.

Background information 1 How do you judge the current Lebanese energy

situation in Lebanon? (Circle)

2 Do you have or experience black-outs at this institution?

3 How many hours per day (i.e., per 24 hours) are the blackouts?

4 Does this institution own or rent a diesel generator to cover the blackout period?

5 Are you a member of any environmental group and/or a renewable energy association?

6 To what percentage does the backup generator provide power during blackouts? I.e., does the generator cover all or part of the blackout hours?

7 How much do you pay, on average and per month for your backup generator?

8 How much do you pay, on average, per month, on your EDL utility bill?



Very few (exact no?)Up to 3 hoursUp to 6 hours Up to 9 hours More than 9 hours


Up to 10 AmperesUp to 20 AmperesUp to 30 Amperes Up to 40 AmperesOver 50 Amperes (exact no?)

%25 of blackout hours%50 of blackout hours%75 of blackout hours%100 of blackout hours

< 100 USD200 - 100 USD300 - 200 USD 400 - 300 USD500 – 400 USD600 - 500 USD700 - 600 USDMore than 700 USD? Please state exact amount if possible

Up to $100$100 - $200$200- $300 $300 - $400$400 - $500$500 - $600$600-$700$700-$800$800-$900$900-$1000> $1000 (exact amount?)

49

9 How well do you think your institution is informed or has knowledge about renewable energy?

10 Do you have a RE electricity source installed?

11 If yes, what renewable energy system is it and what capacity?

12 What year was it installed (exact year)?

13 Does it come with storage (i.e., batteries) for times of blackouts?

14 Does the RE system, with storage, cover demand all the time (with EDL)?

15 If the RE system does not satisfy all your power, do you still use a back-up diesel?

16 How much did you pay for your RE system?



19 Has your institution done any energy efficiency measures to reduce the amount of energy consumed?

20 If yes, what measures have been undertaken? (you can tick more than one)

Yes No Only SHW systemGo to 11 Go to 18 Circle

System Capacity (KW/Amperes)PV systemMicrowindHybridOther (please state)


Yes No

Up to $5000$5,000 - $10,000$10,000 - $15,000 $15,000 - $20,000$20,000 - $30,000$30,000 - $40,000$40,000 - $50,000More than $50,000 (exact amount?)



$0 - $100 $100 - $200 $200 - $300$300 - $400 $400 - $500> $500 (exact amount)?

1 2 3 4 5Not

at allVery little

Moderately Considerably Very much

Yes No

Lighting changeWall Insulation Window double glazingOther shadingEquipment upgradeBehavioral influence

Other (please specify)?

50

Valuation SectionThe below questions are aimed to illicit your institution’s willingness to pay (WTP), per month, additional to your current EDL electricity bill, to fund a RE source, keeping in mind that the paid funds will go to an independent Renewable Energy Fund managed by a specialized team yet under the authority of the Ministry of Energy and Water and the Ministry of Finance, given the below cases.

21 Local system; The RE system (with battery storage), together with electricity from the national grid, can satisfy all your demand, except the demand for air conditioning in times of blackouts. AC during blackouts will have to be supplied by diesel self-generation if desired.

> 1200? Please state ____________________

22 Local system; The RE system with battery storage, together with electricity from the national grid, can satisfy ALL your demand. The diesel self-generation is removed.

Please circle (per month additional payment)

> 1200? Please state ____________________

23 Utility scale: How much additional income are you WTP, per month, on your utility bill, to fund large RE sources secured through the national network, if the current blackouts you face still exist and are met through your private diesel generator?


> 1200? Please state ____________________

24 Utility scale: How much additional income are you WTP, per month, on your utility bill, to fund large RE sources secured through the network, if electricity is provided to you by EDL on a 24 hr basis?


> 1200? Please state ____________________

25 Is there a time limit for the additional payments indicated above?

26 If there is a time limit, how much time do you see yourself paying the additional monthly payments?

27 If you are WTP, how comfortable are you with the Lebanese government managing this money transfer and RE support?

28 If you are WTP, will you also be willing, and to what extent, to undergo energy consumption measures, some of which are listed in question 20, at your own expense?

$0 $50 $100 $200 $300$400 $500 $600 $700 $800$900 $1000 $1100 $1200

$0 $50 $100 $200 $300$400 $500 $600 $700 $800$900 $1000 $1100 $1200

$0 $50 $100 $200 $300$400 $500 $600 $700 $800$900 $1000 $1100 $1200

$0 $50 $100 $200 $300$400 $500 $600 $700 $800$900 $1000 $1100 $1200


Up to 1 yearUP to 2 yearsUp to 3 yearsUp to 4 yearsUp to 5 yearsOther? Specify please?

1 2 3 4 5Not at all Not really Neutral Fairly ok Highly ok

with it

1 2 3 4 5Not at

all Least costly

measures only

To a considerable

extent

All required measures

Highly ok with it

51

29 If you are NOT WTP, why not?

Socio-economic characteristics1 Institution type (see characterization table)

2 Number of employees?

3 Approximate working area (m2)?

4 Location (exact location/caza & rural / urban)

5 Is your institution a member of any environmental group and/or a renewable energy association?

YES…. NO….

6 Do you have a maintenance and services team? YES…. NO….

7 Do you have ownership of this property or are you renting (or other)?

8 What is your company’s annual turnover, after taxes, from all sources? Please note that this is strictly confidential and anonymous information, only to be used for statistical purposes. (Please tic one)

They are expensiveThey are not reliableThey cannot guarantee power in times of blackoutsThey don’t interest meWe don’t think I can afford to pay for themThe government should pay for securing RE, not I

We would rather pay to secure 24 hours of electricity first then think of RE energyWe don’t own the place where we workOther? Please specify

RentedOwnershipOther?

< 50,00050,000 – 100,000100,000 – 150,000150,000 – 200,000200,000 – 250,000250,000 – 300,000300,000 – 350,000350,000 – 400,000400,000– 450,000450,000 – 500,000> 500,000 (exact amount?)

52

To be filled after completing interview

• Do I think the interviewee understood the contingent valuation exercise (Yes/No)?

• On a scale from 1 to 5, was the interviewee annoyed by the interview (1 being not annoyed at all, and 5 being very annoyed)?

• Does the interviewer think the respondent? o Did not understand the survey (please check); o Did not believe in the survey (please check);o Showed protest behavior (please check);o Other (please specify); __________________________________________________

• Was there a presence of a third party during the interview (Yes/No)?

• Comments on specific questions? _______________________________________________

• Date of field visit (day/month/year)? ____________________________________________

• Time to complete interview (hours, such as 1.5)? __________________________________

53

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