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Transcript of Devoll Hydro Power (DHP), Albania
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
page 1
CLEAN DEVELOPMENT MECHANISM
PROJECT DESIGN DOCUMENT FORM (CDM-PDD)
Version 03 - in effect as of: 28 July 2006
CONTENTS
A. General description of project activity
B. Application of a baseline and monitoring methodology
C. Duration of the project activity / crediting period
D. Environmental impacts
E. Stakeholders‟ comments
Annexes
Annex 1: Contact information on participants in the project activity
Annex 2: Information regarding public funding
Annex 3: Baseline information
Annex 4: Monitoring plan
Annex 5: Information regarding stakeholders
Annex 6: Notification letter to the Albanian DNA and UNFCCC secretariat/CDM prior
consideration
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
page 2
SECTION A. General description of project activity
A.1. Title of the project activity:
Devoll Hydropower (DHP), Albania
Document version: PDD, version 01
Completion date: 22 July 2011
A.2. Description of the project activity:
Devoll Hydropower (DHP), Albania (hereinafter referred to as the “proposed project activity” or the
“project”) involves the installation of 3 accumulation reservoir hydro power plants (HPP Moglice – HPP
Kokel – HPP Banja) in a cascade development utilizing the hydropower potential of the Devoll river,
Albania. The planned total installed capacity of the project is 272 MW1. The project is expected to
generate around 789 GWh2 electricity per annum which will be supplied to the Albanian grid. The
generated electricity will be supplied to the national grid via newly constructed transmission lines. HPP
Moglice will be connected to Elbastan, the main hub in the southern primary grid, via 48.2 km long 220
kV3 double circuit line via HPP Kokel. HPP Kokel will be connected via the 220 kV
4 transmission line
from HPP Moglicë to Elbasan. HPP Banja will be connected to Cerrik sub-station in the secondary grid
by a 12.5 km long 110 kV5 single circuit line.
1*Note: The main technical and financial data of Devoll Hydropower (DHP) Project used in the PDD are from the
Feasibility Study Report (FSR), Revision November 2010, based on which the investment decision was taken as well
as from the Devoll Hydropower Project Design Basis Report, dated 07/07/2011 which indicates the most recent
technical data. There are small differences between the technical data of DHP at the time of the investment decision
and the most recent ones, however, those have no impact on the project concept and additionality. Therefore, it can
be accepted that the most recent technical data are also valid and applicable at time of the investment decision. In
order to demonstrate that the input values used in the PDD have not materially changed from the investment decision
(as per paragraph 54 of the EB38 report), the differences between the data are outlined in the PDD. The FSR of DHP
project and all other cited technical documents in the PDD are prepared by Norconsult, a leading Norwegian
engineering company having proven experience in developing power plants worldwide. 1 DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 2 and Design Basis Report, dated 07/07/2011,
pages 12-13. For clarity, there are two small turbines with installed capacity of 1.2 MW at HPP Moglice and HPP
Banja which utilize the environmental flow. They are not productive but emergency release turbines for the night for
the environmental flow of the river. They will not be operated at the same time as the big turbines but only used
when the main turbines are out of operation (too little water or maintenance) in order to keep the minimum flow rate
in the river of 1 (-2) m3/s. 2 DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 2 and Design Basis Report, dated 07/07/2011,
pages 12-13 3 DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 3 and Design Basis Report, dated 07/07/2011,
pages 12-13 4 DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 3 and Devoll Hydropower Project, Design
Basis Report, dated 07/07/2011, page 13 5 DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 3 and Design Basis Report, dated 07/07/2011,
page 13
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
page 3
Under the existing scenario the electricity in Albania is delivered by the national grid which is dominated
by old HPPs which currently cannot cover the increasing electricity demand. The share of electricity
import is around 40%6 of overall power generation. Black-outs and cut-offs in the grid are frequently
observed, thus a considerable number of consumers rely on the service of stand-by generators which are
operated during the time when the grid cannot supply electricity in the required amount and/or quality.
This fact is taken into account as per the option to include off-grid power plants defined in the “Tool to
calculate the emission factor for an electricity system”. Since in recent years in Albania load shedding,
which refers to the existence of suppressed demand was widely observed, the condition of suppressed
demand was taken into consideration for the weights to calculate the CM Emission factor.
The project activity will generate renewable power with negligible GHG emissions which will displace
electricity otherwise supplied by the Albanian grid and fossil fuel fired stand-by generators.
The baseline scenario of the project activity is the same as the scenario existing prior to the start of the
implementation of the project activity.
The project includes the creation of 3 new reservoirs. For HPP Möglice the reservoir surface area7 is
7,210,000 m2 and the power density is 23.745 W/m
2, for HPP Kokel the reservoir surface area
8 is 710,000
m2 and the power density is 50.986 W/m
2, and for HPP Banja the reservoir surface area
9 is 14,110,000 m
2
and the power density is 4.578 W/m2. As the power density of HPP Banja is below 10 W/m², greenhouse
gas emissions from water reservoirs are accounted in the project activity. With an expected grid emission
factor of 0.4631 tCO2/MWh and a yearly production of 789 GWh10
, the project is expected to achieve
annual CO2 emission reductions of about 339,052 tCO2 and total reduction of 3,390,520 tCO2 over the 10
years crediting period.
The project will contribute to sustainable development of the local area and Albania as following:
Balance the electricity supply and demand gap (“suppressed demand”) thus reducing the
reliance on off-grid power generators and imports.
Creates new employment and infrastructure, especially in the commune of Gramsh, thus
contributing to economic growth, improved standard of live of the local people and poverty
alleviation. Around 2,000 people will be employed during the construction and operational
phases.
6 See information in Annex 3 provided by KESH j.s.c. – the Albanian Electro-Energetic Corporation and OST j.s.c –
the Albanian Transmission System Operator
7 DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 2 and Design Basis Report, dated 07/07/2011, page 94, table 5.3.1 Reservoir
8 DHP Project, Design Basis Report, dated 07/07/2011, page 85, table 5.2.1 Reservoir. At time of the investment
decision, the reservoir surface area of HPP Kokel was 850,000 m2
- DHP Project, Engineering Services –
Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010, page 2. The difference in the values of the
reservoir surface area have no impact of the power density of HPP Kokel, as in both cases the value is above 10
W/m², hence no greenhouse gas emissions from water reservoirs have to be considered according to ACM0002.
9 DHP Project, Engineering Services – Development Phase, FSR, Chapter 1, Introduction, page 6 and DHP Project,
Design Basis Report, dated 07/07/2011, page 74, table 5.1.1 Reservoir. 10
The net electricity generation is 781.1 GWh due to deduction of 1% for auxiliary services (as per the assumption
made in the Business Plan at the time of the investment decision)
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
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Applies modern and highly efficient turbines and generators. The power transmission will be at
high voltage to ensure low loses.
Know-how and personnel training on local level are also important benefits from the project.
Sets an important benchmark by attracting foreign investments in the Albanian energy sector
and improving the security and stability of the country‟s power system.
Compliance with all international standards and best available technologies and practices.
The project will be granted to the Albanian Government after the expiry of the Concession
Agreement.
A.3. Project participants:
Name of Party involved
(host)
Private and/or public entity(ies)
project participants
(as applicable)
Kindly indicate if the Party
involved wishes to be
considered as project
participant (Yes/No)
Albania (host Party) Devoll Hydropower Sh.A. (DHP) No
Austria EVN AG No
Norway Statkraft AS No
Devoll Hydropower Sh.A. (DHP) is an Albanian Joint Stock company owned by EVN AG 50%
(Austria) and Statkraft AS 50% (Norway). It has been established for the purpose of implementing a
hydropower scheme on the Devoll River (South Albania) within a Build, Own, Operate and Transfer
(BOOT) concession (CA) from Government of Albania. More information about DHP is available on its
website: www.dhp.al.
EVN Group is an international energy and environmental services company, with headquarters in Lower
Austria. It operates in 19 countries and has more than 8,500 employees. EVN supplies more than 3
million direct customers with electricity, gas, heat, water, waste water treatment, waste incineration and
related services. More information about EVN is available on its website: www.evn.at.
Statkraft is Europe's leader in renewable energy. The company develops and generates hydropower,
wind power, gas power and district heating and is a major player on the European energy exchanges.
Statkraft has more than 3,400 employees in more than 20 countries. More information about Statkraft is
available on its website: www.statkraft.com.
A.4. Technical description of the project activity:
A.4.1. Location of the project activity:
A.4.1.1. Host Party(ies):
Albania
A.4.1.2. Region/State/Province etc.:
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
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Prefectures of Elbasan and Korçë
A.4.1.3. City/Town/Community etc.:
Gramsh Commune
A.4.1.4. Details of physical location, including information allowing the
unique identification of this project activity (maximum one page):
The proposed project activity is situated in the central-eastern part of Albania, south of Shkumbin River
and within 50-70 km southern from Tirana. It includes the mountainous region of the Devoll Valley with
utilisation of the head of Devoll River, including tributaries between Maliq at elevation +810 m a.s.l. and
elevation +95 m a.s.l. downstream of Banja Dam.
Table 1: Geographical coordinates of the dams and power houses of DHP project
Name X Y Lon Lat
Moglice dam 452701.52311
4504843.628 20ー 26' 24.692" E 40ー 41' 35.284" N
Moglice power house 444228.91712
4510076.444 20ー 20' 22.033" E 40ー 44' 23.072" N
Kokel dam 440589.38613
4514001.183 20ー 17' 45.519" E 40ー 46' 29.429" N
Kokel power house 440460.73814
4514015.262 20ー 17' 40.027" E 40ー 46' 29.852" N
Banja dam 42139815
4535213 20ー 3' 57.245" E 40ー 57' 51.444" N
Banja power house 42096116
4535417 20ー 3' 38.458" E 40ー 57' 57.907" N
11
HPP 3, Devoll Hydropower, HPP Moglice, ACC Dam, Dam and Intake Area Plan, NOR 351002 12
HPP 3, Devoll Hydropower, HPP Moglice, Powerhouse, NOR 366002 13
HPP 2, Devoll Hydropower, HPP Kokel Dam, General Dam Area Plan, NOR 251001 14
HPP 2, Devoll Hydropower, HPP Kokel Dam, General Dam Area Plan, NOR 251001 15
HPP 1, Devoll Hydropower, HPP Banja/HEC Banja, Dam and HPP Banja/Diga DHE HEC BANJA, 2011/06/08,
MUL 1000 16
HPP 1, Devoll Hydropower, HPP Banja/HEC Banja, Dam and HPP Banja/Diga DHE HEC BANJA, 2011/06/08,
MUL 1000
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
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Figure 1: Map of Albania
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
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Figure 2: Layout of cascade HPP Moglice- HPP Kokel- HPP Banja (Devoll Hydropower Project)
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
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A.4.2. Category(ies) of project activity:
Sectoral scope1: Energy industries (renewable sources)
A.4.3. Technology to be employed by the project activity:
(a) The scenario existing prior to the start of the implementation of the project activity
Under the existing scenario the electricity in Albania is delivered by the national grid which is dominated
by old HPPs which currently cannot cover the increasing electricity demand. The share of electricity
import amounts to almost 40%17
of overall power generation. Black-outs and cut-offs in the grid are
frequently observed, thus a considerable number of consumers rely on the service of stand-by generators
which are operated during the time when the grid cannot supply electricity in the required amount and/or
quality. This fact is taken into account as per the option to include off-grid power plants defined in the
“Tool to calculate the emission factor for an electricity system”. Since in recent years in Albania load
shedding, which refers to the existence of suppressed demand was widely observed, the condition of
suppressed demand was taken into consideration for the weights to calculate the CM Emission factor.
(b) The scope of activities/measures that are being implemented within the project activity
The proposed project activity involves the installation of 3 accumulation reservoir hydro power plants
(HPP Moglice – HPP Kokel – HPP Banja) in a cascade development utilizing the hydropower potential
of the Devoll river, Albania.
The Devoll hydropower development comprises:
Upper Plant (HPP3) - HPP Moglicë18
HPP Moglicë utilises a head of 300 m along an about 22 km long stretch of Devoll River. The intake is
situated in the Moglicë reservoir created by the approximately 150 m high Moglicë Dam, planned as an
asphalt core rockfill dam. The reservoir surface area19
is 7,210,000 m2
and the power density is 23.745
W/m2. A headrace tunnel of length 10.7 km conveys the water to the powerhouse located underground on
the north bank of Devoll River. The tailrace tunnel is approximately 900 m long leading to the Kokel
reservoir created by the Kokel Dam. HPP Moglicë is equipped with two Francis units with a total
combined capacity of 171.2 MW and an average annual energy production of 445 GWh. An additional
small unit of 1.2 MW for minimum release has been planned to at the toe of the HPP Moglice dam which
utilizes the environmental flow. HPP Moglicë will be connected to Elbasan, the main hub in the southern
primary grid, by a 48.2 km long 220 kV double circuit line via HPP Kokel.
17
See information in Annex 3 provided by KESH j.s.c. – the Albanian Electro-Energetic Corporation and OST j.s.c
– the Albanian Transmission System Operator 18
DHP Project, FSR, Executive Summary, Revision Nov. 2010, pages 2-3 and DHP Project, Design Basis Report,
dated 07/07/2011, page 12
19
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 2 and Design Basis Report, dated 07/07/2011, page 94, table 5.3.1 Reservoir
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
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Middle Plant (HPP2) – HPP Kokel20
HPP Kokel utilises different heads from the Kokel reservoir created by the approximately 50 m high
Kokel Dam. The reservoir surface area21
is 710,000 m2
and the power density is 50.986 W/m2. The
powerhouse is located at surface at the toe of Kokel Dam. A 300 m long headrace tunnel conveys the
water from the reservoir via an embedded penstock to two Francis units with a total combined capacity of
36.2 MW. The estimated average annual energy production is 92 GWh. The middle plant is connected
via the 220 kV transmission line from HPP Moglicë to Elbasan.
Lower Plant (HPP1) - HPP Banja22
The lower plant, HPP Banja, utilises the head of 80 m along an approximately 16 km long stretch of
Devoll River. The intake is situated in the Banja reservoir next to the south bank abutment of Banja Dam,
designed as a clay core embankment dam (approximately 80 m high). The reservoir surface area23
is
14,110,000 m2
and the power density is 4.578 W/m2. The powerhouse and the tailrace outlet are situated
on the south bank. The layout is the same as the original Albanian plans for the project. The dam and
headrace tunnel was left half completed after the site was abandoned in the 1980‟s. The plant is equipped
with two Francis units with a combined capacity of 64.6 MW and an additional small unit of 1.2 MW for
minimum release. The estimated average annual energy production is 252 GWh. HPP Banja will be
connected to Cerrik sub-station in the secondary grid by a 12.5 km long 110 kV single circuit line.
The planned total installed capacity of the project is 27224
. The project is expected to generate around
78925
GWh electricity per annum, of which approximately 99% (781.1 GWh) will be supplied to the
Albanian grid, and the rest 1% will be used for auxiliary services.
As the power density of HPP Banja is below 10 W/m², greenhouse gas emissions from water reservoirs
are accounted in the project activity. With an expected grid emission factor of 0.4631 tCO2/MWh and a
yearly production of 789 GWh26
, the project is expected to achieve annual CO2 emission reductions of
about 339,052 tCO2 and total reduction of 3,390,520 tCO2 over the 10 years crediting period.
20
DHP Project, FSR, Executive Summary, Revision Nov. 2010, pages 2-3 and Devoll Hydropower Project, Design
Basis Report, dated 07/07/2011, pages 12-13
21
DHP Project, Design Basis Report, dated 07/07/2011, page 85, table 5.2.1 Reservoir 22
DHP Project, FSR, Executive Summary, Revision Nov. 2010, pages 2-3 and Devoll Hydropower Project, Design
Basis Report, dated 07/07/2011, page 13
23
DHP Project, Engineering Services – Development Phase, FSR, Chapter 1, Introduction, page 6 and DHP Project,
Design Basis Report, dated 07/07/2011, page 74, Table 5.1.1 Reservoir. 24
DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 2 and Design Basis Report, dated 07/07/2011,
pages 12-13. For clarity, there are two small turbines with installed capacity of 1.2 MW at HPP Moglice and HPP
Banja which utilize the environmental flow. They are not productive but emergency release turbines for the night for
the environmental flow of the river. They will not be operated at the same time as the big turbines but only used
when the main turbines are out of operation (too little water or maintenance) in order to keep the minimum flow rate
in the river of 1 (-2) m3/s. 25
DHP Project, FSR, Executive Summary, Revision Nov. 2010, page 2 and Design Basis Report, dated 07/07/2011,
pages 12-13 26
The net electricity generation is 781.1 GWh due to deduction of 1% for auxiliary services (as per the assumption
made in the Business Plan at the time of the investment decision)
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
CDM – Executive Board
page 10
The project activity will generate renewable power with negligible GHG emissions which will displace
electricity otherwise supplied by the Albanian grid and fossil fuel fired stand-by generators.
The main technical parameters of DHP are shown in the table below.
Table 2: Manufacture and technical indicators of the main equipment of the proposed project activity
Equipment/
Technical Parameters
Units Values
HPP Moglice
Turbine27
Type - Francis
Number turbines - 2
Orientation - Vertical
Maximum turbine output (one
unit in operation)
MW 90.2
Maximum turbine output (two
units in operation)
MW 171.2
Speed
rpm 428.5728
Expected lifetime29
years 50
Generator30
Orientation - Vertical
No of generators - 2
Nominal frequency Hz 50
Nominal generator output per
unit
MW 88.8
Maximum generator output per
unit
MVA 104.531
27
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 41, Table 10.6-3 Main data for turbines and DHP Project, Design Basis Report, dated 07/07/2011, page 117,
Table 5.3.19 Mechanical Works. For clarity, the additional small unit of 1.2 MW at HPP Moglice has not been
considered in the FSR from November 2010 but subsequently planned in the most recent Design Basis Report, dated
07/07/2011. 28
At time of the investment decision, the Turbine speed has been assumed at 428.7 rpm - DHP Project, Engineering
Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010, page 41, Table 10.6-3 Main
data for turbines 29
The expected lifetime of the components of the project equipment is based on experience of Norconsult with
similar HPPs already constructed 30
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 46, Table 10.6-9 Main data for generators and DHP Project, Design Basis Report, dated 07/07/2011, page 118,
Table 5.3.20 Electrical Works 31
At time of the investment decision, the Maximum generator power output has been assumed at 101 MVA - DHP
Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010, page 46,
Table 10.6-9 Main data for generators
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03
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Speed rpm 42832
Expected lifetime years 50
Main transformers33
Nominal power per unit MVA 104.534
Ratio kV 220/gen
Voltage +/-5%
Expected lifetime years 40
High voltage switchgear35
System voltage kV 220
Frequency Hz 50
Expected lifetime years 40
Dam36
Type
- Embankment dam with a centrally
placed asphalt concrete core
Height (m) 15037
Reservoir38
HRWL surface area km2 7.21
Plant Load Factor (PLF)39
30
HPP Kokel
Turbine40
32
At time of the investment decision, the Generator speed has been assumed at 428.7 rpm - DHP Project,
Engineering Services - Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010, page 46, Table
10.6-9 Main data for generators 33
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 48, Table 10.6-10 Main data for transformers and DHP Project, Design Basis Report, dated 07/07/2011, page
118, Table 5.3.20 Electrical Works 34
At time of the investment decision the Nominal power has been assumed at 101 MVA - DHP Project, Engineering
Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010, page 48, Table 10.6-10 Main
data for transformers 35
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 49, Table 10.6-7 Main data High voltage switchgear and DHP Project, Design Basis Report, dated 07/07/2011,
page 118, Table 5.3.20 Electrical Works 36
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 1 and DHP Project, Design Basis Report, dated 07/07/2011, page 94-95 37
At time of the investment decision, the Dam height has been assumed at 147 m - DHP Project, Engineering
Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010, page 1 38
DHP Project, Engineering Services – Development Phase, FSR, Chapter 10, HPP Moglice, Revision Nov. 2010,
page 2 and DHP Project, Design Basis Report, dated 07/07/2011, page 94, Table 5.3.1 Reservoir 39
The PLF of HPP Moglice is determined as the annual electricity output / (installed capacity*8760)*100%). The
total operating hours per year are 8760. Thus, the PLF = 445,000/(171.2*8760)*100%) = 30%. The PLF of HPP
Moglice is confirmed by Norconsult, the engineering company responsible for development of the FSR of DHP
project with issuance of a Confirmation letter, dated 05/07/2011 and is in compliance with the Guidelines for the
reporting and validation of plant load factors, EB48, Annex 11 40
DHP Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010,
page 22, Table 11.6-3 Main data for turbines and DHP Project, Design Basis Report, dated 07/07/2011, page 90,
Table 5.2.8 Mechanical Works
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Type - Francis
Number turbines - 2
Orientation - Vertical
Maximum turbine output (one
unit in operation)
MW 17.9
Maximum turbine output (two
units in operation)
MW 36.2
Speed rpm 300
Expected lifetime years 50
Generator41
Number of units - 2
Orientation - Vertical
Nominal frequency Hz 50
Nominal generator output per
unit
MW 17.6
Maximum generator output per
unit
MVA 20.842
Speed rpm 300
Expected lifetime years 50
Main transformers43
Nominal power per unit MVA 20.844
Ratio kV 220/gen
Voltage +/-5%
Expected lifetime years 40
High voltage switchgear45
System voltage kV 220
Frequency Hz 50
Expected lifetime years 40
Dam46
41
DHP Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010,
page 27, Table 11.6-7 Main data for generators and DHP Project, Design Basis Report, dated 07/07/2011, page 91,
Table 5.2.9 Electrical Works 42
At time of the investment decision, the Maximum generator power output has been assumed at 21.4 MVA - DHP
Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010, page 28,
Table 11.6-8 Main data for transformers 43
DHP Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010,
page 27, Table 11.6-7 Main data for generators and DHP Project, Design Basis Report, dated 07/07/2011, page 91,
Table 5.2.9 Electrical Works 44
At time of the investment decision, the Nominal power output has been assumed at 21.4 MVA - DHP Project,
Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010, page 28, Table
11.6-8 Main data for transformers 45
DHP Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010,
page 29, Table 11.6-9 Main data High voltage switchgear and DHP Project, Design Basis Report, dated 07/07/2011,
page 91, Table 5.2.9 Electrical Works
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page 13
Type
Half concrete gravity dam and half
asphalt faced rockfill dam and
Height 5047
Reservoir48
HRWL surface area km2 0.71
Plant Load Factor49
% 29
HPP Banja
Turbine50
Type - Francis
Number turbines - 3
Turbine unit 1&2
Orientation - Vertical
Maximum turbine output (one
unit in operation)
MW 32.851
Maximum turbine output (two
units in operation)
MW 64.6
Speed rpm 300
Expected lifetime years 50
Turbine unit 3
Type - Francis
Orientation - Horizontal
Maximum turbine output MW 1.252
Speed rpm 1000
Expected lifetime years 50
46
DHP Project, Engineering Services – Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010,
page 2 and DHP Project, Design Basis Report, dated 07/07/2011, page 86 47
At time of the investment decision, the Dam height has been assumed at 55 m - DHP Project, Engineering Services
– Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010, page 2 48
DHP Project, Design Basis Report, dated 07/07/2011, page 85, Table 5.2.1 Reservoir. At time of the investment
decision, the Reservoir surface area of HPP Kokel was 850,000 m2
- DHP Project, Engineering Services –
Development Phase, FSR, Chapter 11, HPP Kokel, Revision Nov. 2010, page 2. The difference in the values of the
reservoir surface area have no impact of the power density of HPP Kokel, as in both cases the value is above 10
W/m², hence no greenhouse gas emissions from water reservoirs have to be considered according to ACM0002. 49
The PLF of HPP Kokel = 92,000/(36.2*8760)*100%) = 29%. The PLF of HPP Kokel is confirmed by Norconsult,
the engineering company responsible for development of the FSR of DHP project with issuance of a Confirmation
letter, dated 05/07/2011 and is in compliance with the Guidelines for the reporting and validation of plant load
factors, EB48, Annex 11 50
DHP Project, Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010,
page 23, Table 13.9-2 Main data for turbines and DHP Project, Design Basis Report, dated 07/07/2011, page 81,
Table 5.1.8 Mechanical Works. 51
At time of the investment decision, the Maximum turbine power output (one unit in operation) was assumed at
32.1 MW - DHP Project, Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov.
2010, page 23, Table 13.9-2 Main data for turbines 52 The 1.2 MW turbine is not a productive but an emergency release turbine for the night for the environmental flow
of the river. It will not be operated at the same time as the big turbines but only used when the main turbines are out
of operation (too little water or maintenance) in order to keep the minimum flow rate in the river of 1 (-2) m3/s.
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Generator53
Number of units - 3
Generator unit 1&2
Orientation - Vertical
Nominal frequency Hz 50
Nominal generator output per
unit
MW 32.454
Maximum generator output per
unit
MVA 38.3
Speed rpm 300
Expected lifetime years 50
Generator unit 3 -
Orientation - Horizontal
Nominal frequency Hz 50
Nominal generator output MW 1.255
Maximum generator output MVA 1.4
Speed rpm 1000
Expected lifetime years 50
Main transformers56
Number of units - 3
Main transformers units 1&2
Nominal power per unit MVA 38.357
Ratio kV 110/gen
Voltage +/- 5%
Expected lifetime years 40
Main transformer unit 3 -
Nominal power MVA 1.3
Ratio kV Distr. voltage/gen
Voltage +/- 5%
Expected lifetime years 40
53
DHP Project, Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010,
page 29, Table 13.9-6 Main data for generators and DHP Project, Design Basis Report, dated 07/07/2011, page 82,
Table 5.1.9 Electrical Works 54
At time of the investment decision, the Nominal generator power output was assumed at 31.7 MW - DHP Project,
Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010, page 29, Table
13.9-6 Main data for generators 55
At time of the investment decision, the Nominal generator power output was assumed at 1.1 MW - DHP Project,
Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010, page 29, Table
13.9-6 Main data for generators 56
DHP Project, Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010,
page 30, Table 13.9-7 Main data for transformers and DHP Project, Design Basis Report, dated 07/07/2011, page
82, Table 5.1.9 Electrical Works 57
At time of the investment decision, the Nominal power was assumed at 37.3 MW - DHP Project, Engineering
Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010, page 30, Table 13.9-7 Main data
for transformers
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High voltage switchgear58
System voltage kV 110
Frequency 50
Expected lifetime years 40
Dam59
Type - Clay core embankment dam
Height m 80
Reservoir60
HRWL surface area km2 14.11
Plant Load Factor61
% 44
The tender documentation for selection of the supplier of the equipment is under elaboration and will be
based on Statkraft standard. The main equipment of Devoll Hydropower project will be imported. The
country from which the equipment will be imported will be known after the selection of the supplier.
In order to ensure appropriate collection and archiving of the data during the monitoring, the project
owner and the supplier of the equipment will provide training to the project operators of Devoll
Hydropower plant.
(c) The baseline scenario
The baseline scenario of the project activity is the same as the scenario existing prior to the start of the
implementation of the project activity.
A.4.4. Estimated amount of emission reductions over the chosen crediting period:
The project applies 10 years crediting period. The crediting period is expected to start on 01/07/2020.
The expected amount of emission reductions to be achieved by the project over the 10 years crediting
period are indicated in the table below:
Table 3: Estimation of emission reductions over the crediting period
58
DHP Project, Engineering Services – Development Phase, FSR, Chapter 13, HPP Banja, Revision Nov. 2010,
page 31, Table 13.9-8 Main data high voltage switchgear and DHP Project, Design Basis Report, dated 07/07/2011,
page 82, Table 5.1.9 Electrical Works 59
DHP Project, FSR, Executive Summary, Revision Nov. 2010, pages 2 and DHP Project, Design Basis Report,
dated 07/07/2011, page 74. 60
DHP Project, Engineering Services – Development Phase, FSR, Chapter 1, Introduction, page 6 and DHP Project,
Design Basis Report, dated 07/07/2011, page 74, Table 5.1.1 Reservoir. 61
The PLF of HPP Banja = 252,000/(64.6*8760)*100%) = 44%. The PLF of HPP Banja is confirmed by
Norconsult, the engineering company responsible for development of the FSR of DHP project with issuance of a
Confirmation letter, dated 05/07/2011 and is in compliance with the Guidelines for the reporting and validation of
plant load factors, EB48, Annex 11
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Years Annual estimation of emission reductions
in tonnes of CO2 e
01/07/2020 169,526
2021 339,052
2022 339,052
2023 339,052
2024 339,052
2025 339,052
2026 339,052
2027 339,052
2028 339,052
2029 339,052
30/06/2030 169,526
Total estimated reductions (tonnes of CO2 ) 3,390,520
Total number of crediting years 10
Annual average over the crediting period of
estimated reductions (tonnes of CO2 e)
339,052
Three HPP units will be put into operation in a phased manner, as following: HPP Banja on 01/07/2015,
HPP Moglice on 01/12/2017 and HPP Kokel on 01/10/2018.
All three power plants will be in operation most likely in middle of 2019. Taking into consideration that
it needs time to fill the storage, the commercial operation of all three hydro power plants is envisaged for
the middle of 2020.
A.4.5. Public funding of the project activity:
No public funding from parties included in Annex I of the UNFCCC has been involved in the proposed
project activity62
SECTION B. Application of a baseline and monitoring methodology
B.1. Title and reference of the approved baseline and monitoring methodology applied to the
project activity:
Applied methodology:
ACM0002: “Consolidated baseline methodology for grid-connected electricity generation from
renewable sources”, ver. 12.1.0
Related Tools:
62 The project owner presented declarations to the DOE that no public funding from parties included in Annex I has
been involved in DHP
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“Tool to calculate the emission factor for an electricity system”, ver. 02.1.0
“Tool for the demonstration and assessment of the additionality”, ver. 05.2
B.2. Justification of the choice of the methodology and why it is applicable to the project
activity:
The applicability of the methodology ACM0002: “Consolidated baseline methodology for grid-
connected electricity generation from renewable sources”, ver. 12.1.0 to the proposed project activity is
demonstrated in the table below:
Table 4: Justification of the applicability of the methodology ACM0002
Aplicability conditions of ACM0002
Characteristics of the project
activity
Fulfilment of applicability
criterion
This methodology is applicable to
grid-connected renewable power
generation project activities that:
(a) install a new power plant at a site
where no renewable power plant was
operated prior to the implementation
of the project activity (greenfield
plant);
(b) involve a capacity addition;
(c) involve a retrofit of (an) existing
plant(s); or
(d) involve a replacement of (an)
existing plant(s).
The proposed project activity
consists of the installation of
new grid connected renewable
power plants at a site where no
renewable power plant was
operated prior to the
implementation of the project
activity (greenfield plant).
Yes
The project activity is the installation,
capacity addition, retrofit or
replacement of a power plant/unit of
one of the following types: hydro
power plant/unit (either with a run-of-
river reservoir or an accumulation
reservoir), wind power plant/unit,
geothermal power plant/unit, solar
power plant/unit, wave power
plant/unit or tidal power plant/unit;
The proposed project activity is
the installation of new
hydropower plants.
Yes
In the case of capacity additions,
retrofits or replacements (except for
wind, solar, wave or tidal power
capacity addition projects which use
Option 2: on page 11 to calculate the
parameter EGPJ,y): the existing plant
started commercial operation prior to
The proposed project activity is
the installation of new
hydropower plants.
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the start of a minimum historical
reference period of five years, used for
the calculation of baseline emissions
and defined in the baseline emission
section, and no capacity expansion or
retrofit of the plant has been
undertaken between the start of this
minimum historical reference period
and the implementation of the project
activity;
Yes
In case of hydro power plants, one of
the following conditions must apply:
The project activity is
implemented in an existing
reservoir, with no change in
the volume of reservoir; or
The project activity is
implemented in an existing
reservoir, where the volume of
reservoir is increased and the
power density of the project
activity, as per definitions
given in the Project Emissions
section, is greater than 4
W/m2; or
The project activity results in
new reservoirs and the power
density of the power plant, as
per definitions given in the
Project Emissions section, is
greater than 4 W/m2.
The project activity includes the
creation of new reservoirs and
the power density of the power
plants is higher than 4 W/m2, as
following:
HPP Möglice - 23.745
W/m2
HPP Kokel - 50.986
W/m2
HPP Banja - 4.578
W/m2
Yes
The methodology is not applicable to
the following:
Project activities that involve
switching from fossil fuels to
renewable energy sources at
the site of the project activity,
since in this case the baseline
may be the continued use of
fossil fuels at the site;
Biomass fired power plants;
The proposed project activity is
the installation of new
hydropower plants and does not
involve switching from fossil
fuels to renewable energy
sources at the site of the project.
The proposed project activity is
Yes
Yes
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Hydro power plants that result
in new reservoirs or in the
increase in existing reservoirs
where the power density of
the power plant is less than 4
W/m2.
the development and installation
of a hydropower plant.
The project activity includes the
creation of new reservoirs and
the power density of the power
plants is higher than 4 W/m2, as
following:
HPP Möglice - 23.745
W/m2
HPP Kokel - 50.986
W/m2
HPP Banja - 4.578
W/m2
Yes
All applicability criteria of ACM0002, ver.12.1.0 have been fulfilled, hence the methodology is
applicable to the proposed project activity.
B.3. Description of the sources and gases included in the project boundary:
According to ACM0002, ver. 12.1.0, the spatial extent of the project boundary includes the DHP plants
and all power plants connected physically to the Albanian electricity grid to which the proposed project
is also connected.
In Albania, the national electricity grid is the unique transmission and distribution line, to which all
power plants in Albania are physically connected to.
Albanian Electro-Energetic Corporation (KESH j.s.c.) 63
, following the split of OST j.s.c and OSSH j.s.c.,
carries out only functions in the field of generation and Public Wholesale Supplier.
Transmission System Operator (OST j.s.c) 64
, has been established in December 2003, and carries out the
function of management and operation of the transmission system, including also the role of the
electricity market operator as a state owned company.
Distribution System Operator65
(OSSH j.s.c) has been established with a DCM No.862, on 20/12/2006 on
“Establishment of the company “Distribution System Operator” j.s.c Tirane” and carries out the
functions of the Distribution Operator and that of Public retail supplier. The majority stake of OSSH was
taken over by CEZ in March 2009 and was renamed to CEZ SHPËRNDARJE66
in October 2010.
63
http://www.kesh.com.al/ 64
http://www.ost.al/ 65
The company has been renamed to CEZ SHPËRNDARJE 66
www.cez.al
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Figure 3: DHP project boundary
The GHGs and emission sources included in or excluded from the project boundary are shown in the
table below:
Table 5: Emissions sources included in or excluded from the project boundary
Source Gas Included? Justification/Explanation
Base
lin
e
Grid electricity
production
including off-
grid generators
CO2 Included According to ACM0002 only CO2
emissions from electricity generation
shall be accounted.
CH4 Excluded According to ACM0002
N2O Excluded According to ACM0002
Pro
ject
Act
ivit
y
Hydro electric
electricity
production
CO2 Included As the power density of the HPP Banja
is below 10 W/m², greenhouse gas
emissions from water reservoirs have to
be considered according to ACM0002.
CH4 Excluded
N2O Excluded
B.4. Description of how the baseline scenario is identified and description of the identified
baseline scenario:
According to ACM0002, Version 12.1.0, the project activity is the installation of a new grid-connected
renewable power plant/unit, therefore the plausible baseline scenarios are the following:
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Alternative 1: The proposed project activity undertaken without being registered as a CDM project
activity.
Alternative 2: Construction of a fossil fuel fired power plant providing the same annual electricity
output.
Alternative 3: Construction of a renewable power plant other than hydropower providing the same
annual electricity output.
Alternative 4: Continuation of the current situation – providing the same amount of electricity by the
Albanian grid.
Alternative 1: The proposed project activity undertaken without being registered as a CDM project
activity.
Financial analysis of this alternative is presented in section B.5. The results show that the internal rate of
return of the proposed project without CDM revenue is 8.9% which is below the WACC benchmark of
10.9%, demonstrating that the project is not financially attractive, therefore Alternative 1 is not plausible
baseline scenario.
Alternative 2: Construction of a fossil fuel fired power plant providing the same annual electricity
output.
There are only two fossil fuel fired power plants serving the Albanian grid – TPP Fier with installed
capacity of 75 MW and TPP Vlora with installed capacity of 97 MW. TPP Fier was shut down in the
year 2008. TPP Vlora constructed in year 2009 has not been operational67
over the last two years due to
high prices of oil. Electricity production by TPP Vlora is not economically attractive and the power plant
serves as a cold reserve in the Albanian power system. Therefore, Alternative 2 cannot be considered as a
baseline scenario to the proposed project activity.
Alternative 3: Construction of a renewable power plant other than hydropower providing the same
annual electricity output.
Currently there are no other existing large scale renewable power plants in the Albanian power system
beside hydropower. Generation of annual electricity output by solar, wind, biomass and geothermal
energy sources as high as the proposed project activity is not realistic. Therefore, Alternative 3 is not
considered as a baseline scenario to the project activity.
Alternative 4: Continuation of the current situation – providing the same amount of electricity by the
Albanian grid.
This scenario is financially feasible, therefore the baseline scenario of the proposed project is the
delivery of the equivalent amount of annual power output from the Albanian national grid to which the
project will also be connected.
67 See Annex 3, Tables Net Electricity Production based on information from the Albanian Electro-Energetic
Corporation (KESH j.s.c.) http://www.kesh.com.al/ and Transmission System Operator (OST j.s.c) http://www.ost.al/
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In conclusion, the only realistic and reasonable baseline scenario to the project activity is Alternative 4,
providing the same amount of electricity by the Albanian grid.
The data used for calculating the baseline emissions is provided in Annex 3.
B.5. Description of how the anthropogenic emissions of GHG by sources are reduced below
those that would have occurred in the absence of the registered CDM project activity (assessment
and demonstration of additionality):
According to ACM0002, ver. 12.1.0, the additionality of the proposed project activity is demonstrated as
per the latest version of the “Tool for the demonstration and assessment of the additionality”, 05.2.
Step 1: Identification of alternatives to the project activity consistent with current laws and
regulations
Sub-Step 1a. Define alternatives to the project activity:
In absence of the proposed project, reasonable and credible alternatives that are in accordance with laws
and regulations include:
Alternative 1: The proposed project activity undertaken without being registered as a CDM project
activity.
Alternative 2: Construction of a fossil fuel fired power plant providing the same annual electricity
output.
Alternative 3: Construction of a renewable power plant other than hydropower providing the same
annual electricity output.
Alternative 4: Continuation of the current situation – providing the same amount of electricity by the
Albanian grid.
Sub-Step 1b. Consistency with appropriate laws and regulations:
Analysis of the identified alternatives which are in compliance with mandatory legislation and
regulations is presented below:
Alternative 1: The proposed project activity undertaken without being registered as a CDM project
activity.
Financial analysis of this alternative is presented below. The results show that the internal rate of return
of the proposed project without CDM revenue is 8.9% which is below the WACC benchmark of 10.9%,
demonstrating that the project is not financially attractive, therefore not plausible baseline scenario.
Alternative 2: Construction of a fossil fuel fired power plant providing the same annual electricity
output.
There are only two fossil fuel fired power plants serving the Albanian grid – TPP Fier with installed
capacity of 75 MW and TPP Vlora with installed capacity of 97 MW. TPP Fier was shut down in the
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year 2008. TPP Vlora constructed in year 2009 has not been operational68
over the last two years due to
high prices of oil. Electricity production by TPP Vlora is not economically attractive and the power plant
serves as a cold reserve in the Albanian power system. Therefore, Alternative 2 cannot be considered as a
baseline scenario to the proposed project activity.
Alternative 3: Construction of a renewable power plant other than hydropower providing the same
annual electricity output.
Currently there are no other existing large scale renewable power plants in the Albanian power system
beside hydropower. Generation of annual electricity output by solar, wind, biomass and geothermal
energy sources as high as by the proposed project activity is not realistic. Therefore, Alternative 3 is not
considered a reasonable and credible alternative.
Alternative 4: Continuation of the current situation – providing the same amount of electricity by the
Albanian grid.
This scenario is in compliance with current laws and regulations of Albania, therefore the baseline
scenario of the proposed project is the delivery of the equivalent amount of annual power output from the
Albanian national grid to which the project will also be connected.
Hence, Alternatives 4 is considered reasonable and credible alternative to the project which is in line
with relevant rules and regulations.
Step 2: Investment Analysis
Sub-step 2a: Determine appropriate analysis method
The CDM project activity and the alternatives identified in step 1 generate financial benefits other than
CDM related income, therefore the simple cost analysis (Option I) is not applicable.
The investment comparison analysis (Option II) is not used because the alternative to the CDM project is
delivery of electricity from the Albanian grid, which is outside the control of the project developers.
Thus, Option III, benchmark analysis is chosen as it represents the most appropriate option for assessing
the financial attractiveness of the project activity.
Sub-step 2b: Option III. Apply benchmark analysis
The financial analysis for the CDM DHP69
project fulfills all requirements set out in the Guidelines on
the Assessment of Investment Analysis (version 5.0) and is in accordance with the following issues:
General issues in calculation and presentation
68 See Annex 3, Tables Net Electricity Production based on information from the Albanian Electro-Energetic
Corporation (KESH j.s.c.) http://www.kesh.com.al/ and Transmission System Operator (OST j.s.c) http://www.ost.al/
69 The Excel spreadsheets of CDM DHP investment analyses are presented to the DOE for assessment
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The model reflects the period of expected operation of the underlying project activity (technical
lifetime).
Depreciations and other non-cash items relating to the project activity, which have been deducted
in estimating gross profits on which tax is calculated, have been added back to net profits for the
purpose of calculating the financial indicator (e.g. IRR, NPV)
Taxation has been included in the cash flows due to the fact that the benchmark is intended for
post-tax comparisons.
All input values used in the investment analyses are valid and applicable at time of the
investment decision which was taken on 22/12/2010 with the approval of the FSR and the
Business Plan by DHP Administration Council at its 4th Meeting. The Minutes of Meeting from
DHP Administration Council is presented to the DOE as evidence supporting the time of the
investment decision.
All expenditures which occurred prior to the date of the investment decision 22/12/2010 were
considered as sunk cost.
The residual value for DHP is zero as the ownership of the plant will be transferred for a price of
zero to the Albanian Government in 2091, as stipulated by the Concession Agreement.
Specific Guidance on the Calculation of Project IRR and Equity IRR
The cost of financing expenditures (i.e. loan repayments and interest) has not been included in
the calculation of the project IRR.
Seeing that the WACC is applied as a post- tax benchmark, the EBIT (earnings before interest
and tax) is used as a base for the calculation of income tax.
Selection and Validation of Appropriate Benchmarks
The financial model applies the weighted average costs of capital (WACC) as an appropriate
benchmark for the project IRR.
The applied benchmark is based on parameters that are standard in the market, considering
specific characteristics of the project type but not linked to subjective profitability expectations
or risk profiles of particular project developers.
The costs of equity are based on the Albanian values provided in Appendix A: Default
values for the expected return on investment of the Guidelines on the Assessment of
Investment Analysis, ver.05. The applicable value for the correct Group 1: Energy
Industries is 13%. Please note that this value is given in real terms, while the financial
model uses nominal values in EUR. Therefore, the 13% are corrected to 15.3% in
nominal terms, assuming EUR inflation of 2% which was the value used in the FSR of
DHP.
Seeing that the debt financing structure for the project was not available (no letter of
intent by any bank was made available), the cost of debt was assumed as the commercial
lending rate in Albania.
o The investment decision was taken on 22/12/2010 with the approval of the FSR
and the Business Plan by DHP Administration Council at its 4th Meeting FSR.
The latest available credit rate value to this date was the November 2010 value
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of the “Average monthly credit rates in EUR for the banking system” for
maturity over 5 years was 6.77%70
as published by the National Bank of Albania.
o The financial analysis in the FSR was done in EUR currency as the project‟s
main influencing factors (investment costs, debt/equity financing of the project,
etc.) are in EUR as well. The above mentioned Albanian credit rates in EUR are
therefore considered appropriate.
Based on the FSR71
, a 50% debt and 50% equity financing has been assumed for the WACC
calculation. This is also the default value provided by the Guidelines on the Assessment of
Investment Analysis, ver. 05
Based on the cost of equity and debt mentioned above and an income tax rate of 10%, the
benchmark WACC is calculated as 10.9%.72
Sub-step 2c: Calculation and comparison of financial indicators
The financial model calculates the project IRR using the inputs set out below. The inputs were valid and
applicable at the time of the investment decision which was taken with the approval of the FSR on
22/12/2010.
Traceable information for the sources of the input parameters is given in the table below as well as in the
investment analysis Excel spreadsheet. The main source is the Feasibility Study report (FSR). Some
input parameters are not explicitly mentioned in the FSR. In these cases, the source is the Financial Excel
model of the Business Plan, dated 17/12/2010 which was approved along with the FSR on 22/12/2010.
Table 6: Key assumptions for investment analysis
Input Unit Value Source Comment
Investment cost EUR 855,300,000 Financial model
of the Business
Plan, Spreadsheet
CAPEX
In the FSR only the
investment cost in
real value (base year
2010) is given (791
million EUR).
For the CDM
financial analysis,
70
The November 2010 value is lower than any comparable average value (e.g. average for 3 months (September-
November 2010) or 6 months (June-November 2010)). Hence, the November 2010 value is used as it is the most
conservative in terms of CDM.
http://www.bankofalbania.org/web/Time_series_22_2.php?crd=0,3,4,0,0,22&uni=201104291652492011429165213
04088&mode=alone&format=3&ln=2&id=146&p_id=1&agr_shfaq=tab&shfaq=0&periudha_nga=1172&periudha_
deri=1192&cregfld_bashkesi=167095,3487 71
FSR, Chapter 25 Financial Analysis, Figure 25.2-1, Page 5 72
The WACC calculation used the formula given in the Information Note “Default values for the expected return on
equity”, published by the CDM Meth Panel as Annex 14 to its 49th
meeting report. The hurdle rate can be calculated
as the weighted average cost of capital (WACC), which is the weighted average cost of obtaining finance in the form
of equity and debt. Mathematically, this is denoted as follows:
WACC = ke x re + kd x rd x (1 – T),
where T is the applicable tax rate, ke and kd are respectively the proportion of equity and debt, and re and rd are the
cost of equity and debt respectively.
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the annual
distribution of the
nominal investment
cost (considering a
EUR inflation rate of
2%) was taken from
the financial model.
Project life-time (years
of operation)
Years 77 Financial model
of the Business
Plan, Spreadsheet
FCF
The terms and
conditions for the
length of the
operation period are
defined in the
Concession
Agreement,
Paragraph 10.1.73
Start of operational
generation
Date 01/07/2015
01/12/2017
01/10/2018
Financial model
of the Business
Plan, Spreadsheet
Alternatives, cells
U62, U92 and
U122
HPP Banje
HPP Moglice
HPP Kokel
Installed capacity MW 272 FSR, Executive
Summary, Page 2
Annual gross generation GWh 789 FSR, Executive
Summary, Page 9
When all 3 plants are
operational
Losses (for auxiliary
services
% 1 Financial model
of the Business
Plan, Spreadsheet
Project
Assumptions, cell
D15
Base: gross
generation
Concession fee %
2%
4%
FSR, Executive
Summary, Page 9
Percentage of annual
generation
2015-2051
After 2051
Wholesale Power Price
(Base Load)
EUR/MWh From 93.6 (in
year 2015) to
124.2 (year
2030), after
2030
increased by
Financial model
of the Business
Plan, Spreadsheet
FCF, line 18
Nominal values from
Pöyry market report
(wholesale price
forecast)
73
Paragraph 10.1 of the Concession Agreement defines the minimum concession period of 35 years. After that, it
will be checked annually if either the “Production Achievement Event” (Definition on Page 18) or the “IRR
Achievement Event” (Page 14) has been fulfilled. These events refer to the definition of the “Required minimum
IRR“(10%, Page 19) and the „Contracted Production Volume“(59 TWh, Page 10). Only the 59 TWh net
generations can be reached in 2091 (operation period 2015-2091).
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EUR inflation
Optional value EUR/MWh 2.25 in 2008,
increased by
EUR inflation
rate
FSR, Executive
Summary, Page 9
Additional price due
to flexibility of
hydro power
generation
Administration costs EUR/MW 3,000 Financial model
of the Business
Plan, Spreadsheet
Project
assumptions, cell
D32
Value in year 2010,
then increased by
EUR inflation rate
OPEX EUR/MW 6,000 Financial model
of the Business
Plan, Spreadsheet
Project
assumptions, cell
D35/36
Value in year 2010,
then increased by
EUR inflation rate
Income tax % 10 FSR, Executive
Summary, Page 9
The FSR increases
the tax rate to 18% in
2016 which is not
based on any official
document. Therefore,
for the CDM
financial analysis the
10% has been used
for the whole project
period. This is
conservative as it
overestimates the
profits.
Depreciation % 5 FSR, Executive
Summary, Page 9
20 years of
depreciation
EUR inflation rate % 1.8 IMF World
Economic
Outlook, April
2011
Based on Guidelines
on the Assessment of
Investment Analysis
(version 5.0) this
source has to be used
for calculating the
expected return on
equity in nominal
terms. As the start of
project activity is
planned for 2011, the
average value of the
period 2012-2016
has been calculated.
This value is very
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similar to the FSR
where 2.0% is used.
Further detailed reference to the source and calculation of the input variables is given in the spreadsheet
“Input” of the Excel file of the financial analysis.
The resulting project IRR is below the WACC benchmark for a project of this type in Albania. The
contribution of the CER revenues improves the financial attractiveness of DHP project.
Table 7: Project IRR without CER revenues and the WACC benchmark
Project IRR without CER revenues 8.9%
WACC benchmark 10.9%
Sub-Step 2d: Sensitivity analysis
A sensitivity analysis of the project activity has been performed in order to test the robustness of the
calculations.
The variables “investment cost”, “electricity price” and “annual generation” constitute more than 20% of
either total project costs or total project revenues. Hence, they are subjected to variations of +/-10% and
+/– 5% in the sensitivity analysis. All other variables (e.g. O&M cost equals less than 5% of revenues)
are significantly below the 20% threshold and are therefore not considered in the sensitivity analysis.
The results of the variation are presented in this PDD and are reproduced in the associated spreadsheet.
Table 8: Variations of input parameters
IRR Sensitivity
Analysis 90% 95% 100% 105% 110%
Investment costs 9,6% 9,2% 8,9% 8,6% 8,3%
Generation volume 8,2% 8,5% 8,9% 9,2% 9,5%
Electricity price 8,2% 8,5% 8,9% 9,2% 9,5%
The following table indicates which change would be necessary to surpass the benchmark of 10.9%.
Table 9: Changes which would be necessary to surpass the benchmark
NPV=0 with WACC= 10,9% is fulfilled if the following parameters are changed from the original values
Investment 75%
Generation volume 131%
Electricity price 131%
In order to be above the benchmark, a reduction of the investment cost by 25% or an increase of the
revenues (either by generation volume or electricity price) by 31% would be necessary.
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All these scenarios are highly unrealistic to happen.
The project owners (Statkraft and EVN) as well as the engineering company Norconsult (which prepared
the FSR) have senior expertise to adequately estimate the investment cost as well as annual generation
for new hydro power plants.
The projected prices in the FSR have been derived from the Albanian market report prepared by Pöyry
Energy Consulting. Pöyry market forecast is based on a complex model using the fundamentals of the
electricity market for all European countries and is widely used and well-known among potential
investors and authorities in the SEE region.
The sensitivity analysis shows that in each sensitivity case examined it is very unlikely the change of the
parameters to surpass the benchmark. Therefore, the project activity is unlikely to become financially
attractive without the incentive from CDM.
According to the Guidance on the demonstration and assessment of prior consideration of the CDM74
,
CDM DHP project falls under the hypothesis of section II. Proposed project activities with a start date
from 2 August 2008. Following the definition for a starting date of a CDM project activity as defined in
the Glossary of CDM terms75
, the starting date of DHP will be in the future since no real action as
financial closure, ordering of major equipment, construction permit or start of construction has yet
begun. Nevertheless, on 29/09/2009 the project owner has sent a notification letter76
to the Albanian
DNA and UNFCCC secretariat informing about the intention to implement Devoll Hydropower project
in Albania under CDM/Prior consideration of CDM. With the notification letter the project owner
intended securing the CDM status of DHP project by demonstrating that the incentive from CDM was
considered at the earliest stage of the project implementation.
For the purpose of demonstrating the serious consideration of the incentive from CDM in the decision to
implement CDM DHP, implementation timeline of the project activity is presented below, based on
official, legal and other relevant documentation77
available prior the start of the project activity.
Date when the investment decision was made
The project participants made the investment decision to build CDM DHP on 22/12/2010 with the
approval of the FSR by DHP Administration Council at its 4th Meeting. The incentive from CDM was
seriously considered and indicated in the FSR78
.
Date when construction works started
74
Version 04, EB 62 75
http://cdm.unfccc.int/Reference/Guidclarif/glos_CDM.pdf 76
The Notification letter to the to the Albanian DNA and UNFCCC secretariat/Prior consideration of CDM is
presented in Annex 8 77
All official reliable evidences demonstrating that the incentive from CDM was seriously considered in the decision
to implement CDM DHP project and indicating that continuing and real actions were taken to secure the CDM status
of the project in parallel with its implementation have been compiled and presented to the DOE as supplementary
documentation to the PDD 78
FSR, Chapter 25 Financial Analysis, page 9, 25.6.1. CDM income
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Construction of the project activity has not yet started. The planned construction works commencement
date is in Q3 of 2012
Date of start-up (e.g. date when commercial production started)
Three HPP units will be put into operation in a phased manner, as following: HPP Banja on 01/07/2015,
HPP Moglice on 01/12/2017 and HPP Kokel on 01/10/2018.
All three power plants will be in operation most likely in middle of 2019. Taking into consideration that
it needs time to fill the storage the commercial operation of all three hydro power plants is envisaged for
the middle of 2020.
Table 10: Timeline of events and actions supported by reliable evidences indicating that the incentive
from CDM was seriously considered in the Devoll Hydropower project as well as that continuing and
real actions have been undertaken by the project participants to achieve CDM registration.
№ Date Evidences
1. 29/05/2007 Contract between EVN AG and ALLPLAN GmbH for development of PIN for
the potential CDM project HPP Devoll river, Albania
2. 06/09/2007 Minutes of Meeting of EVN AG representatives regarding the implementation of
Devoll Hydropower in Albania reporting the consideration of the incentive from
CDM.
3. 18/12/2007 PIN HPP Devoll elaborated for EVN AG by ALLPLAN GmbH
4. 14/04/2008 Minutes of Meeting of EVN AG representatives reporting on a discussion
regarding possibility for obtaining additional financing for Devoll Hydropower
project from CDM.
5. 26/05/2008 Minutes of Meeting of EVN AG representatives reporting that the Letter of No
Objection for the PIN of CDM Devoll Hydropower project is still pending to be
issued by the Albanian DNA.
6. 08/09/2008 Letter of No Objection for PIN Devoll Hydropower issued by the Albanian DNA
7. 19/12/2008 Concession Agreement relating to the design, financing, construction,
ownership, operation, maintenance and transfer of the Devoll river hydropower
project in the Republic of Albania between the Ministry of Economy, Trade and
Energy as Contracting Authority and EVN AG, Statkraft AS and Devoll
Hydropower S.h.a. as Co-concessionairs
8. 23/12/2008 Framework Agreement 46004121, dated 23/12/2008/12776 between EVN AG
and ALLPLAN GmbH for development of CDM PDD for HPP Devoll project.
9. No date
indicated in
the
document
Assignment and Assumption Agreement to the Framework Agreement 46004121
Position 50/dated 23/12/2008 and to the Vertraulichkeitsvereinbarung79
, dated
01/04/2008 – the CDM Project Agreement between EVN AG, ALLPLAN
GmbH and Devoll Hydropower Sh.A (DHP)
10. 29/09/2009 Notification letter to the Albanian DNA and UNFCCC secretariat for realization
of CDM Hydro Power Plant Devoll project in Albania under Clean Development
79 English translation: “Confidentiality agreement”
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Mechanism according to Article 12 of the Kyoto Protocol to the UNFCCC –
CDM Prior Consideration
11. 20/10/2009 Minutes of CDM Kick-Off Meeting for Devoll Hydropower project
12. 01/02/2010 E-mail from DHP informing the project participants about a personal meeting
with the Albanian DNA and the willingness of the DNA to support the
realisation of DHP project under CDM in Albania.
13. 11/2010 FSR of Devoll Hydropower, developed by Norconsult
14. 22/12/2010 Minutes of Meeting of the 4th Meeting Administration Council (AC), Devoll
Hydropower Sh.A. on which the FSR of DHP were approved – Investment
decision to proceed with DHP project.
15. July 2011 Contract with the DNV for validation of CDM DHP project
Step 3: Barrier analysis
This step is not applied
Step 4. Common Practice Analysis
Sub-step 4a. Analyse other activities similar to the proposed project
The Albanian grid is dominated by just few large hydro power plants located at the Drin river in the
North of Albania. However, the last built big hydro power plant - 600 MW HPP Koman dates back to
1986 when the former political system was still in place. HPP Koman was built and is still owned by the
state – the Albanian Power Corporation (KESH) and thus cannot be compared to the implementation of a
“new” HPP of similar size to be built by an international private consortium after having won a tendering
process and facing market uncertainties. Furthermore, the Devoll Hydropower plant is located on the
Devoll River in the South of Tirana.
Table 11: HPPs serving the Albanian grid80
№
Power Plant
Installed Capacity
(MW)
Year of Commissioning
1. HPP Bistrica 1 22.5 1948
2. HPP Lanabregas 5 1951
3. HPP Bistrica 2 5 1952
4. HPP Ulez 25 1954
5. HPP Shkopet 24 1963
6. HPP Vau Dejes 250 1975
7. HPP Fierza 500 1978
8. HPP Koman 600 1986
9. HPP Smokhtine 9.2 2004
80 Albanian Electro-Energetic Corporation (KESH j.s.c.) http://www.kesh.com.al/ and Transmission System
Operator (OST j.s.c) http://www.ost.al/
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10. HPP Gjanc 3.7 2005
11. HPP Bogove 2.5 2006
Currently another international investor plans to build a 52.9 MW HPP at the Drin river, which is also
developed as a CDM project activity.
Due to new support from the Albanian Government and the entry into force of the law no. 9663 of date
18.12.2006 “on concessions”, during 2007 and concessionary licenses have been granted for the
construction of a considerable number of hydropower plants with small or medium size capacities.
This new law is considered to be the main reason that some small HPPs were built or rehabilitated
recently, like Gjanc (3.7 MW; 2005); Bogove (2.5 MW; 2006) Smokthine (9.2 MW; 2004); Tervol (12
MW; 2009)81
etc.
As it can be seen from the table above, all recently built HPPs are small or medium sized with a
maximum capacity of 12 MW and thus not comparable with the 272 MW HPP Devoll Hydropower
project.
Sub-step 4b Discuss any similar options that are occurring
Since no similar project activities could be observed in Albania under Sub-step 4a this Sub-step is not
applicable and it can be concluded from this analysis that the proposed project is not a common practice.
It is therefore concluded that the proposed project activity is additional.
B.6. Emission reductions:
B.6.1. Explanation of methodological choices:
The emission reductions are calculated in accordance with the approved consolidated baseline
methodology ACM0002, Version 12.1.0.
The necessary data for calculating baseline, project and leakage emissions was provided by the following
official sources of Albania (see also Annex 3 of the PDD):
Korporata Elektroenergjetike Shiqiptare (KESH) and
The Transmission System Operator (OST)
Baseline emissions
Baseline emissions include only CO2 emissions from electricity generation in fossil fuel fired power
plants that are displaced due to the project activity. The methodology assumes that all project electricity
generation above baseline levels would have been generated by existing grid-connected power plants and
the addition of new grid-connected power plants. The baseline emissions are to be calculated as follows:
81 www.akbn.gov.al
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BEy = EGPJ,y x EFgrid,CM,y (6)
Where:
BEy = Baseline emissions in year y (tCO2/yr)
EGPJ,y = Quantity of net electricity generation that is produced and fed into the grid as a result of
the implementation of the CDM project activity in year y (MWh/yr)
EFgrid,CM,y = Combined margin CO2 emission factor for grid connected power generation in year y
calculated using the latest version of the “Tool to calculate the emission factor for an
electricity system” (tCO2/MWh)
Calculation of EGPJ,y
The calculation of EGPJ,y is different for (a) greenfield plants, (b) retrofits and replacements, and
(c) capacity additions. These cases are described next:
(a) Greenfield renewable energy power plants
If the project activity is the installation of a new grid-connected renewable power plant/unit at a site
where no renewable power plant was operated prior to the implementation of the project activity, then:
EGPJ,y = EGfacility,y (7)
Where:
EGPJ,y = Quantity of net electricity generation that is produced and fed into the grid as a result of
the implementation of the CDM project activity in year y (MWh/yr)
EGfacility,y = Quantity of net electricity generation supplied by the project plant/unit to the grid in year
y (MWh/yr)
Since the Devoll HPP is a Greenfield renewable energy project the equation under (a) of above is
applied.
Project Emissions (PEy):
For most renewable power generation project activities, PEy = 0. However, some project activities may
involve project emissions that can be significant. These emissions shall be accounted for as project
emissions by using the following equation:
(1)
Where:
PEy = Project emissions in year y (tCO2e/yr)
PEFF,y = Project emissions from fossil fuel consumption in year y (tCO2e/yr)
PEGP,y = Project emissions from the operation of geothermal power plants due to the release of
non-condensable gases in year y (tCO2e/yr)
PEHP,y = Project emissions from water reservoirs of hydro power plants in year y (tCO2e/yr)
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The procedure to calculate the project emissions from each of these sources is presented next.
Under the underlying project activity the project emissions PEFF,y and PEGP,y are not applicable and thus
0. The only source of project emissions might be from water reservoirs of hydro power plants (PEHP,y).
The equations for this kind of project emissions are described as follows:
Emissions from water reservoirs of hydro power plants (PHHP,y)
For hydro power project activities that result in new reservoirs and hydro power project activities that
result in the increase of existing reservoirs, project proponents shall account for CH4 and CO2 emissions
from the reservoir, estimated as follows:
(a) If the power density of the project activity (PD) is greater than 4 W/m2 and less than or equal to 10
W/m2:
(3)
Where:
PEHP,y = Project emissions from water reservoirs (tCO2e/yr)
EFRes = Default emission factor for emissions from reservoirs of hydro power plants in year y
(kgCO2e/MWh)
TEGy = Total electricity produced by the project activity, including the electricity supplied to the
grid and the electricity supplied to internal loads, in year y (MWh)
(b) If the power density of the project activity (PD) is greater than 10 W/m2:
PEHP,y = 0 (4)
The power density of the project activity (PD) is calculated as follows:
(5)
Where:
PD = Power density of the project activity (W/m2)
CapPJ = Installed capacity of the hydro power plant after the implementation of the project
activity (W)
CapBL = Installed capacity of the hydro power plant before the implementation of the project
activity (W). For new hydro power plants, this value is zero.
APJ = Area of the reservoir measured in the surface of the water, after the implementation of
the project activity, when the reservoir is full (m2)
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ABL = Area of the reservoir measured in the surface of the water, before the implementation of
the project activity, when the reservoir is full (m2). For new reservoirs, this value is zero.
The ex-ante calculations of the power densities (PD) (see section B.2.) of the different power plants of
the underlying project activity are summarized in the following table:
Table 12: Calculation of the power densities
Banja Kokel Moglice
HRWL surface area [km²] see Design Basis
Report 14 0.71 7.21
1,000,000
1,000,000 1,000,000
Installed capacity (see FSR)
[MW]
64.6
36.2
171.2
HRWL surface area [m²] 14,110,000
710,000 7,210,000
W installed
[W] 64,600,000
36,200,000 171,200,000
Power density calculated
[W/m²] 4.578 50.986 23.745
According to the applied methodology only project emissions for the HPP Banja have to be taken into
account. These project emissions are to be calculated with the formula described under (a) of above.
In the underlying PDD these project emissions for the HPP Banja are considered in the ex-ante
calculation of the estimated emission reductions.
For the HPPs Kokel and Moglice power densities of 50.986 and 23.745 W/m² were calculated. If the
power density is higher than 10 W/m² no project emissions have to be considered (see point (b) of
above). For the ex-ante calculation of the emission reductions it is assumed that from these HPPs no
project emissions will occur under this project activity.
All the parameters (capacities and surface areas) to recalculate the power densities annually throughout
the operational phase are monitored.
Leakage (Ly)
According to the methodology, no leakage emissions are considered. The main emissions potentially
giving rise to leakage in the context of electric sector projects are emissions arising due to activities such
as power plant construction and upstream emissions from fossil fuel use (e.g. extraction, processing,
transport). These emissions sources are neglected.
Emission reductions (ERy)
Emission reductions are calculated as follows:
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ERy = BEy – PEy (11)
Where:
ERy = Emission reductions in year y (t CO2e/yr)
BEy = Baseline emissions in year y (t CO2e/yr)
PEy = Project emissions in year y (t CO2e/yr)
A Combined Margin (CM) (see also the explanation under Baseline Emissions) consists of the
combination of Operating Margin (OM) and Build Margin (BM) according to the procedures
prescribed in the “Tool to calculate the emission factor for an electricity system (Version 02.1.0)”, which
in the following is named the “Tool”.
The developers are aware of the fact that the “Tool to calculate the emission factor for an electricity
system (Version 02.1.0) was amended in the EB meeting 61 but we refer to the point 24. of the Sixty-first
meeting report which stipulates:
24. For all revised methodologies and tools that were approved by the Board at this meeting, the DOEs
may upload not later than 3 February 2012 (24:00 GMT) for registration the project design documents
(PDDs) of project activities in which the previous version of an approved methodology or an approved
tool has been applied, in accordance with paragraph 36 of the “Procedure for the submission and
consideration of requests for revision of approved baseline and monitoring methodologies and tools for
large scale CDM project activities”.
Since we intend to get registered to project activity immediately after validation and are seeking to get
the Letter for Approval (LoA) in parallel from the DNA of Albania till the end of the year 2011 we apply
point 24 regarding the transition period for using previous versions of the “Tools” and “Methodologies”.
Sections taken from the “Tool” for explanation reasons are illustrated in italic letters.
The operating margin is the emission factor that refers to the group of existing power plants whose
current electricity generation would be affected by the proposed CDM project activity. The build margin
is the emission factor that refers to the group of prospective power plants whose construction and future
operation would be affected by the proposed CDM project activity.
This tool may be applied to estimate the OM, BM and/or CM when calculating baseline emissions for a
project activity that substitutes grid electricity, i.e. where a project activity supplies electricity to a grid
or a project activity that results in savings of electricity that would have been provided by the grid (e.g.
demand-side energy efficiency projects).
Under this tool, the emission factor for the project electricity system can be calculated either for grid
power plants only or, as an option, can include off-grid power plants. In the latter case, the conditions
specified in ”Annex 2 - Procedures related to off-grid power generation” should be met. Namely, the
total capacity of off-grid power plants (in MW) should be at least 10% of the total capacity of grid power
plants in the electricity system; or the total power generation by off-grid power plants (in MWh) should
be at least 10% of the total power generation by grid power plants in the electricity system; and that
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factors which negatively affect the reliability and stability of the grid is primarily due to constraints in
generation and not to other aspects such as transmission capacity.
In the underlying calculation of the GEF for the national grid of Albania off- grid power plants are
included. Under Step 4 of the Annex 2 of the “Tool” (see also Step 2 of the “Tool” and Annex 3
respectively) it is required that the total power generation by off-grid power plants (in MWh) amounts to
more than 10% of the total power generation by grid power plants in the electricity system for the year
the off- grid study was done. The off-grid study was done for the year 2007.
Note that this tool is also referred to in the Tool to calculate project emissions from electricity
consumption for the purpose of calculating project and leakage emissions in case where a project
activity consumes electricity from the grid or results in increase of consumption of electricity from the
grid outside the project boundary.
If during operation of the hydropower project a situation will occur, where electricity is taken from the
Albanian grid Scenario A; Option A1 of the “Tool to calculate baseline, project and/or leakage
emissions from electricity consumption (Version 01)” will be applied. However, this is currently
considered unlikely.
Project participants shall apply the following seven steps:
STEP 1. Identify the relevant electric power system.
STEP 2. Choose whether to include off-grid power plants in the project electricity system
(optional)
STEP 3. Select an operating margin (OM) method.
STEP 4. Calculate the operating margin emission factor according to the selected method.
STEP 5. Identify the cohort of power units to be included in the build margin (BM).
STEP 6. Calculate the build margin emission factor.
STEP 7. Calculate the combined margin (CM) emissions factor.
STEP 1. Identify the relevant electric power system.
For determining the electricity emission factors, a project electricity system is defined by the spatial
extent of the power plants that are physically connected through transmission and distribution lines to
the project activity (e.g. the renewable power plant location or the consumers where electricity is being
saved) and that can be dispatched without significant transmission constraints. If the project electricity
system is located partially or totally in Annex-I countries, then the tool is not applicable.
The project electricity system is the national grid of Albania. The geographical boundary for the
determination of the baseline emissions is therefore defined as the national grid of Albania and direct
emissions from all generation sources serving the grid with inclusion of off-grid plants.
Similarly, a connected electricity system, e.g. national or international, is defined as an electricity
system that is connected by transmission lines to the project electricity system. Power plants within the
connected electricity system can be dispatched without significant transmission constraints but
transmission to the project electricity system has significant transmission constraint. If a connected
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electricity system is located partially or totally in Annex-I countries, then the emission factor of that
connected electricity system should be considered zero.
Electricity transfers from connected electricity systems to the project electricity system are defined as
electricity imports and electricity transfers to connected electricity systems are defined as electricity
exports.
Electricity is imported to the project electricity system (national grid of Albania) from connected
electricity systems (national grid of Greece, Kosovo/Serbia and Montenegro)82
. According to the source
ENTSOE.EU83
(see also attached baseline data in Annex 3 of the PDD) there are also exports from the
national grid to the above mentioned connected electricity systems.
For the purpose of determining the build margin (BM) emission factor, the spatial extent is limited to the
project electricity system, except where recent or likely future additions to transmission capacity enable
significant increases in imported electricity. In such cases, the transmission capacity may be considered
a build margin source.
For the purpose of determining the operating margin (OM) emission factor, one of the following options
should be used to determine the CO2 emission factor(s) for net electricity imports (EFgrid,import,y) from a
connected electricity system within the same host country(ies):
(a) 0 tCO2/MWh, or
(b) The weighted average operating margin (OM) emission rate of the exporting grid, determined as
described in step 3 (d) below; or
(c) The simple operating margin emission rate of the exporting grid, determined as described in step
3 (a), if the conditions for this method, as described in step 2 below, apply to the exporting grid;
or
(d) The simple adjusted operating margin emission rate of the exporting grid, determined as
described in step 3 (b) below.
For imports from connected electricity systems located in Annex-I country(ies), the emission factor is 0
tons CO2 per MWh.
For both, electricity imports from the Annex I country Greece and non Annex I countries Kosovo/Serbia
and Montenegro the emission factors are considered 0 tCO2/MWh (see Option (a) from above).
Electricity exports should not be subtracted from electricity generation data used for calculating and
monitoring the electricity emission factors.
Exports were not subtracted from the electricity generation for calculation of the Combined Margin (CM)
Grid Emission Factor.
Step 2: Choose whether to include off-grid power plants in the project electricity system (optional)
82 https://www.entsoe.eu/resources/data-portal/exchange/
83 https://www.entsoe.eu/resources/data-portal/exchange/
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Project participants may choose between the following two options to calculate the operating margin
and build margin emission factor:
Option I: Only grid power plants are included in the calculation.
Option II: Both grid power plants and off-grid power plants are included in the calculation.
Option I corresponds to the procedure contained in earlier versions of this tool. Option II allows the
inclusion of off-grid power generation in the grid emission factor. Option II aims to reflect that in some
countries off-grid power generation is significant and can partially be displaced by CDM project
activities, e.g. if off-grid power plants are operated due to an unreliable and unstable electricity grid.
Option II requires collecting data on off-grid power generation as per Annex 2 and can only be used if
the conditions outlined therein are met. Option II may be chosen only for the operating margin emission
factor or for both the build margin and the operating margin emission factor but not only for the build
margin emission factor.
Option II is chosen and the off- grid electricity generation is taken into account for both the calculation of
the build margin (BM) and the operating margin (OM) emission factor.
If Option II is chosen, off-grid power plants should be classified as per the guidance in Annex 2 in
different classes of off-grid power plants. Each off-grid power plant class should be considered as one
power plant j, k, m or n in the following steps, as applicable.
The classification as per the guidance in Annex 2 is applied accordingly. Each off-grid power plant class
is considered as one power plant. In total 23 UNFCCC classes were identified during the off-grid survey
(see guidance in Step 1.2 of the Annex 2 of the “Tool” in Annex 3 of the PDD). In the following table the
determined (during the off-grid survey) UNFCCC classes are summarized.
Table 13: Identified UNFCCC off -grid classes
Diesel CAP < 10 10 < CAP < 50 50 < CAP < 100 100 < CAP < 200 200 < CAP < 400 400 < CAP < 1000 CAP > 1000
Age (0-5)
Age (6-10)
Age (11-20)
Gasoline
Age (0-5)
Age (6-10)
Age (11-20)
Nominal capacity of off grid power plants in [kW]
The only generation technology applied by the surveyed off-grid plants is the reciprocant engine system
fuelled either by diesel or by gasoline (see also Annex 1 of the “Tool”). The diesel fuelled off- grid
plants covered all the seven capacity classes. The gasoline fuelled off-grid plants just covered the first
capacity class smaller than 10 kW.
According to Step 4 of Annex 2 of the “Tool” the following prerequisites for the inclusion of the off-
grid power plants have to be fulfilled:
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Step 4 of Annex 2: Assess the extent of off-grid power The effects of feeding additional electricity to the grid or saving electricity demand on off-grid
power plants connected to the system are associated with significant uncertainty. For this
reason, a significant amount of off-grid power should exist to include these plants in the grid
emission factor.
The inclusion of off-grid power plants in the grid emission factor is only allowed if one of the
following two conditions are met:
The total capacity of off-grid power plants (in MW) is at least 10% of the total capacity of
grid power plants in the electricity system; or
The total power generation by off-grid power plants (in MWh) is at least 10% of the total
power generation by grid power plants in the electricity system.
If one of these conditions is not met, then off-grid power plants cannot be included in the
calculation of the grid emission factor of the electricity system. Otherwise, proceed to next step.
There is an inconsistence in the underlined sections above, which has not been solved so far in the
revised “Tool to calculate the emission factor for an electricity system (Version 02.1.0) and (Version
02.2.0.).
The off- grid study for Albania was done for the year 2007. According to Step 3 of the “Tool” a single
calendar year within the 5 most recent calendar years prior to the time of submission of the CDM-PDD
for validation has to be used. By choosing the year 2007 this requirement is fulfilled.
The extrapolated off grid generation for the year 2007 (lower level of the 95% confidence interval)
amounted to 472,708 MWh. This is equal to 16.3% of the total power generation by grid power plants of
the Albanian grid in the year 2007. The total power generation for the year 2007 amounted to
2,892,974 MWh (including hydro power (2,829,512 MWh) and thermal power (63,462 MWh); without
imports) (see also Annex 3 of the PDD).
Since the installed capacity of all (sampled) off-grid power plants in operation amounts to 239 MW,
which is equal to 15.7 % of the total installed capacity of 1,523 MW both above mentioned requirements
are met.
Step 3. Select an operating margin (OM) method
The calculation of the operating margin emission factor (EFgrid,OM,y) is based on one of the following
methods:
(a) Simple OM, or
(b) Simple adjusted OM, or
(c) Dispatch data analysis OM, or
(d) Average OM.
Each method is described under Step 4.
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The simple OM method (option a) can only be used if low-cost/must-run resources84
constitute less than
50% of total grid generation in: 1) average of the five most recent years, or 2) based on long-term
averages for hydroelectricity production.
The dispatch data analysis (Option d) cannot be used if off-grid power plants are included in the project
electricity system as per Step 2 above.
Since hourly electricity generation data are not available neither option (b) nor option (c) are applicable.
Since low-cost/must run resources constitute more than 50% of total grid generation in average of the
five most recent years (see following table below) the Average Operating Margin (OM) method (option
(d)) is used.
The following table gives an overview about the electricity generation over the last 5 years were data
were available.
Table 14: Electricity generation of Albania for the most recent 5 years, where data were available
Sum of electricity generation in [MWh] 6,398,476 6,684,154 6,245,682 6,921,539 7,451,723
Electricity Generation in MWh 2005 2006 2007 2008 2009
Sum Hydros / low cost-must run 5,072,489 5,363,873 2,829,512 3,832,831 5,201,015
Percentage 0.79 0.80 0.45 0.55 0.70
Sum Import 1,249,000 1,240,000 2,880,000 2,616,000 1,778,000
Percentage 0.20 0.19 0.46 0.38 0.24
Sum Thermal 76,987 80,281 536,170 472,708 472,708
Percentage 0.01 0.01 0.09 0.07 0.06
Percentage Low cost - must run 0.99 0.99 0.91 0.93 0.94
For the years 2007 to 2009 the electricity generation from the off- grid plants is taken into consideration.
The table shows that the low cost must run resources constitute by far more than 50% for all the 5 years.
In Albania there was just on thermal power plant (TPP FIER) based on the fossil fuel Residual Fuel Oil
in operation until 2007. All the off-grid power plants are either based on the fossil fuel diesel or gasoline.
For the Net Caloric Values (NCV) and the Emission Factors default values from IPCC 2006 V2 were
used. In order to stay conservative the lower values within the 95% confidence interval were taken into
account.
For the simple OM, the simple adjusted OM and the average OM, the emissions factor can be calculated
using either of the two following data vintages:
Ex ante option: If the ex ante option is chosen, the emission factor is determined once at the
validation stage, thus no monitoring and recalculation of the emissions factor during the
crediting period is required. For grid power plants, use a 3-year generation-weighted average,
based on the most recent data available at the time of submission of the CDM-PDD to the DOE
for validation. For off-grid power plants, use a single calendar year within the 5 most recent
calendar years prior to the time of submission of the CDM-PDD for validation.
84 Low-cost/must-run resources are defined as power plants with low marginal generation costs or power plants that
are dispatched independently of the daily or seasonal load of the grid. They typically include hydro, geothermal,
wind, low-cost biomass, nuclear and solar generation. If coal is obviously used as must-run, it should also be
included in this list, i.e. excluded from the set of plants.
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Ex post option: The year in which the project activity displaces grid electricity, requiring the
emissions factor to be updated annually during monitoring. If the data required to calculate the
emission factor for year y is usually only available later than six months after the end of year y,
alternatively the emission factor of the previous year (y-1) may be used. If the data is usually
only available 18 months after the end of year y, the emission factor of the year proceeding the
previous year (y-2) may be used. The same data vintage (y, y-1 or y-2) should be used
throughout all crediting periods.
For the calculation of the Average operating margin (OM) the ex ante option is chosen. The most recent
data, which were available from KESH and OST respectively, are from 2007 to 2009 (see also data
included in Annex 3 of the PDD). These data fit appropriately with the 2007 data of the off- grid study.
Step 4: Calculate the Operating Margin emission factor (EFOM,y) according to the selected method
In the following section at first the procedure for the calculation of the (a) Simple OM is described, since
the applied calculation of the (d) Average OM follows the same procedure. The only difference is the
inclusion of low cost/must run power plants under (d) Average OM.
(a) Simple OM
The simple OM emission factor is calculated as the generation-weighted average CO2 emissions per unit
net electricity generation (tCO2/MWh) of all generating power plants serving the system, not including
low-cost / must-run power plants/units.
The simple OM may be calculated:
Option A: Based on the net electricity generation and a CO2 emission factor of each power unit;85
or
Option B: Based on the total net electricity generation of all power plants serving the system and the
fuel types and total fuel consumption of the project electricity system.
Option B can only be used if:
(a) The necessary data for Option A is not available; and
(b) Only nuclear and renewable power generation are considered as low-cost/must-run power sources
and the quantity of electricity supplied to the grid by these sources is known; and
(c) Off-grid power plants are not included in the calculation (i.e., if Option I has been chosen in Step 2).
Option A - Calculation based on average efficiency and electricity generation of each plant
Under this option, the simple OM emission factor is calculated based on the net electricity generation of
each power unit and an emission factor for each power unit, as follows:
85
Power units should be considered if some of the power units at the site of the power plant are low-cost/must-run
units and some are not. Power plants can be considered if all power units at the site of the power plant belong to the
group of low-cost/must-run units or if all power units at the site of the power plant do not belong to the group of
low-cost/must-run units.
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(1)
Where:
EF grid,OMsimple,y = Simple operating margin CO2 emission factor in year y (tCO2/MWh)
EG m,y = Net quantity of electricity generated and delivered to the grid by power unit m in
year y (MWh)
EF EL,m,y = CO2 emission factor of power unit m in year y (tCO2/MWh)
m = All power units serving the grid in year y except low-cost / must-run power units
y = The relevant year as per the data vintage chosen in Step 3
Determination of EFEL,m,y
Since for the power units m NO accurate data of fuel consumption and electricity generation was
available, the emission factor (EFEL,m,y) was determined according to Option A2 of the “Tool”.
Option A2. If for a power unit m only data on electricity generation and the fuel types used is
available, the emission factor should be determined based on the CO2 emission factor of the fuel
type used and the efficiency of the power unit, as follows:
(3)
Where:
EFEL,m,y = CO2 emission factor of power unit m in year y (tCO2/MWh)
EFCO2,m,i,y = Average CO2 emission factor of fuel type i used in power unit m in year y (tCO2/GJ)
ηm,y = Average net energy conversion efficiency of power unit m in year y (ratio)
m = All power units serving the grid in year y except low-cost/must-run power units
y = The relevant year as per the data vintage chosen in Step 3
Where several fuel types are used in the power unit, use the fuel type with the lowest CO2 emission factor
for EFCO2,m,i,y..
Each off-grid power plant is operated just by one fossil fuel source (diesel or gasoline).
Determination of EGm,y
For grid power plants, EGm,y should be determined as per the provisions in the monitoring tables.
For off-grid power plants, EGm,y can be determined using one of the following options:86
86
Note that different options can be applied to different classes of off-grid power plants; however, the same option
should be applied to all (sampled) off-grid power plants within one class.
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Option 1. EGm,y is determined based on (sampled) data on the electricity generation of off-grid
power plants, as per the guidance in Annex 2.
Option 2. EGm,y is determined based on (sampled) data on the quantity of fossil fuels combusted
in the class of off-grid power plants m, as per the guidance in Annex 2, and the default
efficiencies provided in Annex 1, as follows:
(4)
Where:
EGm,y = Net quantity of electricity generated and delivered to the grid by power unit m in year y
(MWh)
FCi,m,y = Amount of fossil fuel type i consumed by power plants included in off-grid power plant
class m in year y (mass or volume unit)
NCV i,y = Net calorific value (energy content) of fossil fuel type i in year y (GJ/mass or volume
unit)
η m,y = Default net energy conversion efficiency of off-grid power plant class m in year y (ratio),
as per the default values provided in Annex 1
m = Off-grid power plant class considered as one power unit (as per the provisions in Annex
2 to this tool)
y = The relevant year as per the data vintage chosen in Step 3
i = Fossil fuel types used
The project participants provide the following clarification to the formula of above:
If all input parameters are applied according the formula above (taken from the valid “Tool”) with their
relevant units the following is obtained:
[MWh] = [tons] x [GJ/tons] x [ ]
[MWh] = [GJ]
Thus, in our point of view the right side of the formula has to be divided by 3.6 in order the transform
[GJ] into [MWh].
To clarify this issue ALLPLAN/denkstatt sent a letter to the CDM Executive Board on 30th November
2010.
ALLPLAN/denkstatt received a notification from the CDM Executive Board that the submitted Letter
regarding the minor technical errors in the Methodological “Tool” will be considered at EB 59.
At the EB 60 meeting the “Tool to calculate the emission factor for an electricity system” was revised.
The revised “Tool” (Version 02.1.0) was amended to allow the use of an operating margin emission
factor different form zero in case of connected electricity systems located in countries other than the
project host country. However, the technical errors and the inconsistency in Step 4 of Annex 2 of the
“Tool” notified by ALLPLAN/denkstatt have not been considered.
Since no off- grid power plants could be identified, where electricity generated is measured directly with
electricity meters, Option 1 could not be applied for the off-grid study.
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All sampled companies operating off-grid power plants provided the required data for calculation of
EGm,y according to the “corrected” Option 2 above. Thus this option was applied for the calculation of
the generated electricity by each off- grid power plant.
(d) Average OM
The average OM emission factor (EFgrid,OM-ave,y) is calculated as the average emission rate of all power
plants serving the grid, using the methodological guidance as described under (a) above for the simple
OM, but including in all equations also low-cost/must-run power plants.
For the project activity the Average OM calculation is applied. The following table below summarizes
the results of the calculation of the Average operating margin (OM) for the years 2007 to 2009 including
off-grid plants.
Table 15: Calculation of the (OM) Operating Margin emission factor for the years 2007 to 2009
Baseline (including imports) LCMR [MWh] Imports [MWh]
2007 5,709,512 2,880,000
2008 6,448,831 2,616,000
2009 6,979,015 1,778,000
19,137,358 7,274,000
EF AverageOM [tCO2/MWh]
0.0529
0.0503 6,921,539
0.0467 7,451,723
Total (2007-2009) = 20,618,944
Prepared by denkstatt GmbH
Emission factors for the National Grid of Albania
EF AverageOM [tCO2/MWh] Load [MWh]
0.0631 6,245,682
The generation-weighted average OM for the years 2007 to 2009 amounts to 0.0529 tonsCO2/MWh.
Step 5. Identify the group of power units to be included in the build margin
The sample group of power units m used to calculate the build margin consists of either87
:
(a) The set of five power units that have been built most recently, or
(b) The set of power capacity additions in the electricity system that comprise 20% of the system
generation (in MWh) and that have been built most recently88
.
87
If this approach does not reasonably reflect the power plants that would likely be built in the absence of the project
activity, project participants are encouraged to submit alternative proposals for consideration by the CDM Executive
Board. 88
If 20% falls on part capacity of a unit, that unit is fully included in the calculation.
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Project participants should use the set of power units that comprises the larger annual generation.
As a general guidance, a power unit is considered to have been built at the date when it started to supply
electricity to the grid.
Power plant registered as CDM project activities should be excluded from the sample group m.
However, If the group of power units, not registered as CDM project activity, identified for estimating
the build margin emission factor includes power unit(s) that is(are) built more than 10 years ago then:
(i) Exclude power unit(s) that is (are) built more than 10 years ago from the group; and
(ii) Include grid connected power projects registered as CDM project activities, which are
dispatched by dispatching authority to the electricity system.89
Capacity additions from retrofits of power plants should not be included in the calculation of the build
margin emission factor.
The three small Hydro Power Plants (HPPs) Bogove 2.5 MW (2006); Gjanc 3.7 MW (2005) and
Smokthine 9.2 MW (2004) were the only power plants built within the last ten years, where individual
net electricity generation data was available and thus taken into account for the Build Margin (BM)
calculation.
In “Small HPPs” (39,062 MWh) see table 16 below) a huge amount of very small HPPs are subsumed,
where no individual net electricity generation data was available. Some of those small HPPs have been
rehabilitated recently and others are older ones. In order to stay conservative in the calculation of the BM
emission factor all the small HPPs subsumed under “Small HPPs” are treated as newly built ones and
thus taken into account in the calculation of the BM.
Thus, applying Step 5 (a) of above the set of five power units that have been built most recently amount
to 39,062 MWh at maximum.
Applying Step 5 (b) of above, the set of power capacity additions in the electricity system that comprise
20% of the system generation (in MWh) and that have been built most recently amount to 2,603,000
MWh which is 46% of the system generation (including “Small HPP”; all the off- grid units and HPP
KOMAN). This set of power plants also includes power plants that are older than 10 years like some off -
grid power units and the HPP KOMAN (start of operation 1986).
According to the “Tool” the following procedure applies:
Power plants registered as CDM project activities should be excluded from the sample group m. If the
group of power units, not registered as CDM project activity, identified for estimating the build margin
emission factor includes power unit(s) that is (are) built more than 10 years ago then:
(i) Exclude power unit(s) that is (are) built more than 10 years ago from the group; and
(ii) Include grid connected power projects registered as CDM project activities, which are
dispatched by dispatching authority to the electricity system.
Following (ii) of above:
89 This information shall be provided by the host country.
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Since Albania so far does not have any existing grid connected power plant registered as CDM project
activity, not such a power plant could be included for the calculation of the BM emission factor.
Following (i) of above thermal and hydro power plants built before 1999 were excluded. The excluded
power plants are all off grid units (data vintages 2 and 3) (see also clarification below) and the HPP
Koman.
According to Step 1.2. of Annex 2 of the “Tool” the off-grid power plants were sub-divided into three
data vintages: plants with 0 to 5 years of operation, plants with 6 to 10 years of operation and plants with
11 to 20 years of operation (the oldest off grid power plant surveyed started operation in 1987).
Thus the second data vintage of the off-grid classes refers to a start of operation between 1998 and 2002,
which means that the off- grid power plants of these classes are partly younger and partly older than 10
years since the reference year for the Build Margin (BM) calculation is 2009.
Following the guidelines of the “Tool” only the off- grid plants only for the first data vintage were taken
into account for the calculation of the Build Margin (BM) emission factor.
The following table 16 summarizes the electricity generation of the finally considered set of power plants
for the calculation of the Build Margin (BM) emission factor 2009 according to the procedure from Step
5 of the “Tool” (see also Annex 3 of the PDD).
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Table 16: List of power plants taken into consideration for the BM calculation
Electricity generation in [MWh] 2009 Time of Comissioning
Small HPP 39,062 2009
Gjanc, Bogove, Smoktine 50,248 2004,2005,2006
Off Grid (Cap1, Fuel D; Age 1) 32,527 2003-2007
Off Grid (Cap1, Fuel G; Age 1) 13,131 2003-2007
Off Grid (Cap2, Fuel D; Age 1) 171,478 2003-2007
Off Grid (Cap3, Fuel D; Age 1) 3,419 2003-2007
Off Grid (Cap4, Fuel D; Age 1) 25,247 2003-2007
Off Grid (Cap5, Fuel D; Age 1) 29,349 2003-2007
Off Grid (Cap6, Fuel D; Age 1) 67,940 2003-2007
Off Grid (Cap7, Fuel D; Age 1) 26,466 2003-2007
Off Grid (Cap1, Fuel D; Age 2) 6,629 1998-2002
Off Grid (Cap1, Fuel G; Age 2) 1,066 1998-2002
Off Grid (Cap2, Fuel D; Age 2) 32,329 1998-2002
Off Grid (Cap3, Fuel D; Age 2) 1,820 1998-2002
Off Grid (Cap4, Fuel D; Age 2) 10,126 1998-2002
Off Grid (Cap5, Fuel D; Age 2) 8,849 1998-2002
Off Grid (Cap6, Fuel D; Age 2) 14,227 1998-2002
Off Grid (Cap7, Fuel D; Age 2) 22,944 1998-2002
Off Grid (Cap1, Fuel D; Age 3) 0 1988-1997
Off Grid (Cap1, Fuel G; Age 3) 493 1988-1997
Off Grid (Cap2, Fuel D; Age 3) 700 1988-1997
Off Grid (Cap3, Fuel D; Age 3) 242 1988-1997
Off Grid (Cap4, Fuel D; Age 3) 247 1988-1997
Off Grid (Cap5, Fuel D; Age 3) 1,668 1988-1997
Off Grid (Cap6, Fuel D; Age 3) 1,811 1988-1997
Koman (HPP) 2,040,982 1986
Fierza (HPP) 1,556,248 1978
Vau dejes (HPP) 1,084,358 1975
Shkopet (HPP) 100,787 1963
Ulez (HPP) 124,631 1954
Bistrice 2 (HPP) 35,100 1952
Lanabregas (HPP) 34,235 1951
Bistrice 1 (HPP) 135,364 1948
*IMPORTS 1,778,000
Vlora (TPP) 0
Fier (TPP) 0
Sum of electricity generation in [GWh] 5,673,723 *without Imports
Sum of electricity generation of the
sample group for the BM [GWh] 458,867
Percentage of the electricity generation of
most recently
built 5 Power Plants 8%
In terms of vintage of data, project participants can choose between one of the following two options:
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Option 1. For the first crediting period, calculate the build margin emission factor ex-ante based on the
most recent information available on units already built for sample group m at the time of CDM-PDD
submission to the DOE for validation. For the second crediting period, the build margin emission factor
should be updated based on the most recent information available on units already built at the time of
submission of the request for renewal of the crediting period to the DOE. For the third crediting period,
the build margin emission factor calculated for the second crediting period should be used. This option
does not require monitoring the emission factor during the crediting period.
Option 2. For the first crediting period, the build margin emission factor shall be updated annually, ex-
post, including those units built up to the year of registration of the project activity or, if information up
to the year of registration is not yet available, including those units built up to the latest year for which
information is available. For the second crediting period, the build margin emissions factor shall be
calculated ex-ante, as described in option 1 above. For the third crediting period, the build margin
emission factor calculated for the second crediting period should be used.
The Build Margin (BM) Emission factor was calculated ex-ante by choosing Option 1 from above.
Step 6. Calculate the build margin emission factor
The build margin emissions factor is the generation-weighted average emission factor (tCO2/MWh) of all
power units m during the most recent year y for which power generation data is available, calculated as
follows:
(13)
Where:
EFgrid,BM,y = Build margin CO2 emission factor in year y (tCO2/MWh)
EGm,y = Net quantity of electricity generated and delivered to the grid by power unit m in year y
(MWh)
EFEL,m,y = CO2 emission factor of power unit m in year y (tCO2/MWh)
m = Power units included in the build margin
y = Most recent historical year for which power generation data is available
The CO2 emission factor of each power unit m (EFEL,m,y) should be determined as per the guidance in
Step 4 (a) for the simple OM, using options A1, A2 or A3, using for y the most recent historical year for
which power generation data is available, and using for m the power units included in the build margin.
For off-grid power plants, EGm,y should be determined as per the guidance in Step 4.The calculation of
the CO2 -emission factor of the thermal power and the off-grid power plants required for the calculation
of the build margin (BM) was conducted by using option A2 of the step 4 (a) of the applied “Tool”
according to the formula as follows:
(3)
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The following table summarizes in detail the calculation of CO2 emissions taken into account for the
calculation of the Build Margin (BM) emission factor. The only fossil fuelled power plants in operation
in the year 2009 are off- grid power plants identified during the off- grid survey.
Table 17: Calculation of CO2- emissions of fossil power plants (including off- grid plants) taken into
account for the BM emission factor calculation
Relevant year
2009 A B C D E F G
i EGm FCi,m NCVi EFCO2,i ηm EFEL,m
Net Electricity Generation Fuel
Consumption
Net Calorific
Value
(Lower Value)
CO2 Emission
Factor
(Lower Value)
Average Net
Energy
Conversion
Efficiency
CO2 -
Emission
Factor
CO2
Emissions
(MWh) (t) (GJ/t) (tCO2/GJ) (%) (tCO2/MWh) (t-CO2)
Default
values from
Annex 1 of
the
"Electricity
Tool" F=Dx3.6/E G=AxF
1 Off Grid (Cap1, Fuel D; Age 1) Diesel 32,527 41.4 0.0726 0.28 0.933 30,362
2 Off Grid (Cap1, Fuel G; Age 1) Gasoline 13,131 42.5 0.0675 0.28 0.868 11,396
3 Off Grid (Cap2, Fuel D; Age 1) Diesel 171,478 41.4 0.0726 0.33 0.792 135,811
4 Off Grid (Cap3, Fuel D; Age 1) Diesel 3,419 41.4 0.0726 0.35 0.747 2,553
5 Off Grid (Cap4, Fuel D; Age 1) Diesel 25,247 41.4 0.0726 0.37 0.706 17,834
6 Off Grid (Cap5, Fuel D; Age 1) Diesel 29,349 41.4 0.0726 0.39 0.670 19,668
7 Off Grid (Cap6, Fuel D; Age 1) Diesel 67,940 41.4 0.0726 0.42 0.622 42,278
8 Off Grid (Cap7, Fuel D; Age 1) Diesel 26,466 41.4 0.0726 0.45 0.581 15,371
275,273
CO2 emissions from Power Plants
m
No. Name of Power Plant
Fuel Type
The column A of the table above shows the extrapolated electricity generation from the off-grid classes
(vintage 1). Column C shows the lower value of the Net Caloric Values (NCV) according to IPCC 2006.
Column D contains the lower value of the CO2 Emission Factors of different fossil fuels according to
IPCC 2006.
The CO2 Emission Factor of each power plant (EFEL,m) is calculated in column F by application of the
formula described under Step 6 of the “Tool” above. The CO2 Emissions (tonsCO2) are calculated in
column G by multiplication of F and A.
The summarized value of 275,273 tonsCO2 has to be divided by the electricity generation (MWh) of the
group of power plants determined under Step 5 of the “Tool” of above. The electricity generation of
these power plants amounts to 458,867 MWh.
Thus the calculated Build Margin (BM) emission factor amounts to 0.600 tonsCO2/MWh.
Step 7. Calculate the combined margin emissions factor
The combined margin emissions factor is calculated as follows:
(14)
Where:
EFgrid,BM,y = Build margin CO2 emission factor in year y (tCO2/MWh)
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EFgrid,OM,y = Operating margin CO2 emission factor in year y (tCO2/MWh)
wOM = Weighting of operating margin emissions factor (%)
wBM = Weighting of build margin emissions factor (%)
The following default values should be used for wOM and wBM:
Wind and solar power generation project activities: wOM
= 0.75 and wBM
= 0.25 (owing to
their intermittent and non-dispatchable nature) for the first crediting period and for
subsequent crediting periods.
All other projects: wOM
= 0.5 and wBM
= 0.5 for the first crediting period and wOM
= 0.25
and wBM
= 0.75 for the second and third crediting period,90
unless otherwise specified in the
approved methodology which refers to this tool.
Alternative weights can be proposed, as long as wOM + wBM = 1, for consideration by the Executive
Board, taking into account the guidance as described below. The values for wOM + wBM applied by
project participants should be fixed for a crediting period and may be revised at the renewal of the
crediting period.
The Tool also gives “Guidance on selecting alternative weights”:
The following guidance provides a number of project-specific and context-specific factors for developing
alternative operating and build margin weights to the above defaults. It does not, however, provide
specific algorithms to translate these factors into quantified weights, nor does it address all factors that
might conceivably affect these weights. In this case, project participants are suggested to propose
specific quantification methods with justifications that are consistent with the guidance provided below.
Given that it is unlikely that a project will impact either the OM or BM exclusively during the first
crediting period, it is suggested that neither weight exceed 75% during the first crediting period.
Factor Summary – Impact
on weights
Further Explanation
Project size (absolute or
relative to the grid size of the
system or the size of other
system capacity additions)
No change in weight
on basis of absolute
or relative size alone
Alternative weights on the basis of absolute
or relative project size alone do not appear
to be justified.
90 Project participants can submit alternative proposal, for revision of tool or the methodology or deviation from its
use, if weightage does not reflect their situation with an explanation for the alternative weights.
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Timing of project output Can increase OM
weight for highly off-
peak projects;
increase BM for
highly on-peak
projects.
Projects with output is mainly off-peak can
have a greater OM weight (e.g. solar PV
projects in evening peak regions, seasonal
biomass generation during off-peak
seasons), whereas projects with
disproportionately high output during on-
peak periods (e.g. air conditioning efficiency
projects in some grids) can have greater BM
weight.
Predictability of project output Can increase OM for
intermittent
resources in some
contexts.
Projects with output of an intermittent nature
(e.g. wind or solar projects) may have
limited capacity value, depending on the
nature of the (wind/solar) resource and the
grid in question, and to the extent that a
project’s capacity value is lower than that of
a typical grid resource its BM weight can be
reduced. Potential adjustments to the
OM/BM margin should take into account
available methods (in technical literature)
for estimating capacity value.10
Suppressed demand Can increase BM
weight for the 1st
crediting period.
Under conditions of suppressed demand that
are expected to persist through over half of
the first crediting period across a significant
number of hours per year, available power
plants are likely to be operated fully
regardless of the CDM project, and thus the
OM weight can be reduced.
For system management (nature of local electricity markets, planning, and actors) and other
considerations no guidance is available at present.
EFgrid,CM,y is calculated according to formula explained above taking weights wOM and wBM as 0.25 and
0.75 respectively due to the suppressed demand situation in Albania. The proof of suppressed demand
can be substantiated by the following documents (see
http://web.worldbank.org/WBSITE/EXTERNAL/COUNTRIES/ECAEXT/ALBANIAEXTN/0,,contentM
DK:22037104~pagePK:141137~piPK:141127~theSitePK:301412,00.html or Annual report Situation of
Energy Sector and activity of ERE for 2008, Table 1.5 page 28).
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The following table summarizes the calculation of the combined margin (CM) emission factor for the
electricity grid of Albania including off-grid power plants. Additional baseline information can be found
in Annex 3 of the PDD.
Table 188 Calculation of the Combined Margin (CM) emission factor for the years 2007 to 2009
Baseline (including imports) LCMR [MWh] Imports [MWh]
2007 5,709,512 2,880,000
2008 6,448,831 2,616,000
2009 6,979,015 1,778,000
19,137,358 7,274,000
w OM = 0.25
w BM = 0.75
Prepared by denkstatt GmbH
0.0529 0.5999
0.4631
Alternative (CM) EF y [tCO2/MWh]
Alternative weights
Emission factors for the National Grid of Albania
EF AverageOM [tCO2/MWh]
0.0467
20,618,944
EF BM,2009
Load [MWh]
7,451,723
0.0631 6,245,682
0.0503 6,921,539
Total (2007-2009) =
EF AverageOM [tCO2/MWh]
The ex-ante calculated combined margin (CM) emission factor amounts to 0.4631 tonsCO2/MWh.
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B.6.2. Data and parameters that are available at validation:
Data / Parameter: CapBL
Data unit: W
Description: Installed capacity of the hydro power plant before the implementation of the
project activity. For new hydro power plants, this value is zero.
Source of data used: Project site
Value applied: 0
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied
The project is newly built hydropower station. Therefore, based on the
methodology, for new hydro power plants, this value is zero.
Any comment: Since the project activity is a new hydro power plant this value is 0.
Data / Parameter: ABL
Data unit: m²
Description: Area of the reservoir measured in the surface of the water, before the
implementation of the project activity, when the reservoir is full (m2). For new
reservoirs, this value is zero.
Source of data used: Section 1.3 (Project components Water-flow: structures and changes) of the
WCD document
Value applied: 0 m² (Banja)
0 m² (Kokel)
0 m² (Moglice)
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
Measured from topographical surveys, maps, satellite pictures, etc.
Any comment: Since the all reservoirs are new ones, the applied values are 0.
Data / Parameter: EFRes
Data unit: kgCO2e/MWh
Description: Default emission factor for emissions from reservoirs
Source of data used: Decision by EB23
Value applied: 90 kgCO2e/MWh
Justification of the
choice of data or
description of
measurement methods
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and procedures
actually applied:
Any comment: -
Data / parameter: FCi,m,y
, (FCi,y
, FCi,j,y
, FCi,k,y
, FCi,n,y
and FCi,n,h
)
Data unit: Mass or volume unit (tons)
Description: Amount of fossil fuel type i consumed by power plant / unit m, j, k or n (or in
the project electricity system in case of FCi,y
) in year y or hour h
Source of data used: Figures provided by companies with off-grid plants during off- grid survey
Value applied: See collected questionnaires during off- grid survey
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
All the eligible questionnaires of the off-grid survey contain the amount of
fossil fuel consumed by off-grid power plant in tons or the survey year 2007.
Any comment: To calculate ex ante the OM and BM emission factor.
Data / Parameter: NCVi,y
Data unit: GJ per mass or volume unit (e.g. GJ/m³, GJ/ton)
Description: Net calorific value (energy content) of fossil fuel type i in year y
Source of data used: The following data sources may be used if the relevant conditions apply:
Data source Conditions for using the data
source
Values provided by the fuel
supplier of the power plants in
invoices
If data is collected from power plant
operators (e.g. utilities)
Regional or national average
default values
If values are reliable and documented
in regional or national energy
statistics / energy balances
IPCC default values at the lower
limit of the uncertainty at a 95%
confidence interval as provided in
Table 1.2 of Chapter 1 of Vol. 2
(Energy) of the 2006 IPCC
Guidelines on National GHG
Inventories
Off grid power plants are either operated with diesel or gasoline.
Value applied: Provided in Annex 3
Justification of the
choice of data or
description of
Application of IPCC default values.
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measurement methods
and procedures
actually applied:
Any comment: To calculate ex ante the OM and BM emission factor.
Data / Parameter: EFCO2,i,y
and (EFCO2,m,i,y
)
Data unit: tCO2/GJ
Description: CO2 emission factor of fossil fuel type i used in power unit m in year y
Source of data used: The following data sources may be used if the relevant conditions apply:
Data source Conditions for using the data
source
Values provided by the fuel
supplier of the power plants in
invoices
If data is collected from power plant
operators (e.g. utilities)
Regional or national average
default values
If values are reliable and documented
in regional or national energy
statistics / energy balances
IPCC default values at the lower
limit of the uncertainty at a 95%
confidence interval as provided in
Table 1.2 of Chapter 1 of Vol. 2
(Energy) of the 2006 IPCC
Guidelines on National GHG
Inventories
For the current project activity IPCC default values at the lower limit of the
uncertainty at a 95% confidence interval were used.
Value applied: Provided in Annex 3
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
Application of IPCC default values.
Any comment: To calculate ex ante the OM and BM emission factor.
Data / Parameter: EGm,y
, (EGy, EG
j,y, EG
k,y and EG
n,h )
Data unit: MWh
Description: Net electricity generated by power plant/unit m, k or n in year y
Source of data used: KESH; OST
Value applied: Provided in Annex 3
Justification of the
choice of data or
description of
measurement methods
and procedures
Official data of OST and KESH
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actually applied:
Any comment: To calculate ex ante the OM and BM emission factor.
Data / Parameter: GENimported
Data unit: MWh
Description: Electricity imported from connected electricity systems
Source of data used: ENTSOE
Value applied: Provided in Annex 3
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
Official data of ENTSOE!
https://www.entsoe.eu/resources/data-portal/exchange/
Any comment: To calculate ex ante the OM emission factor.
Data / Parameter: ηm,y and ηk,y
Data unit: -
Description: Average net energy conversion efficiency of power unit m or k in year y
Source of data used: Use either:
Documented manufacturer‟s specifications (if the efficiency of the plant is
not significantly increased through retrofits or rehabilitations); or
For grid power plants: data from the utility, the dispatch centre or official
records if it can be deemed reliable; or
The default values provided in the table below in Annex 1 (if available for
the type of power plant)
Since for the different off-grid power plants and other fossil fuelled thermal
power plants no accurate figures could be obtained, the default values from
Annex 1 of the underlying “Electricity Tool” are used.
Value applied: Provided in Annex 3
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
Default values determined in Annex 1 of the “Tool to calculate the emission
factor for an electricity system”
Any comment: Since no other data for efficiencies are available, IPCC default values were
applied.
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Data / Parameter: CAPm
Data unit: MW
Description: Total capacity of off-grid power plants included in off-grid power plant class
m
Source of data used: Survey on off-grid power plants, as per Annex 2
Value applied: See collected questionnaires during off- grid survey
Justification of the
choice of data or
description of
measurement methods
and procedures
actually applied:
All the eligible questionnaires of the off-grid survey contain the capacities of
the surveyed off- grid plants.
Any comment: Only applicable if Option II is chosen in Step 2 of this tool, which is the case
in the underlying project activity
B.6.3. Ex-ante calculation of emission reductions:
Ex-ante calculations of the envisaged Emission Reductions (ER) were made by using the DHP estimates
of electricity generations for the power plants Kokel, Banja and Moglice (see feasibility study report or
IRR calculation).
For the ex-ante calculation of emission reductions the following electricity generation data are taken into
account:
HPP Moglice 171.2 MW 445,000 MWh
HPP Kokel 36.2 MW 92,000 MWh
HPP Banja 64.6 MW 252,000 MWh
Sum 272 MW 789,000 MWh
In the DHP financial model, the annual generation of 789 GWh is reduced by 1% for losses (auxiliary
services). The CDM model as well as the ex-ante calculation has been updated accordingly.
DHP expects to deliver this net electricity generation to the national grid of Albania as soon as all three
power plants are in full operation. This is planned for July of 2020.
The start of commercial operation is envisaged with:
01/07/2015 for HPP Banja
01/12/2017 for HPP Moglice
01/10/2018 for HPP Kokel
Latest information of DHP to the start of operation are given as follows:
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All three power plants will be in operation most likely in middle of 2019. Taking in consideration that it
needs time to fill the storage the commercial operation of all three hydro power plants is envisaged for
the middle of 2020.
Since no leakage has to be considered according to the applied approved methodology ACM0002
(Version 12.1.0). Thus the emission reductions are calculated as follows:
ERy = BEy – PEy
Where:
ERy = Emission reductions in year y (t CO2e/yr)
BEy = Baseline emissions in year y (t CO2e/yr)
PEy = Project emissions in year y (t CO2e/yr)
The Combined Margin (CM) emission factor (including off grid plants according to the “Tool to
calculate the emission factor for an electricity system (Version 02.1.0))” for the national electricity grid
of Albania was calculated as described in the section B.6.1 of this document (see also Annex 3 of the
document).
As soon as all HPPs are in full operation the Baseline Emissions (BEy) are calculated as follows:
BEy = EGy x EFgrid,CM,y = 789,000 MWh x 0.99 x 0.4631 tonsCO2/MWh = 361,732 tonsCO2e/year
The only project emissions which have to be considered are those of Banja due to the “Emissions from
water reservoirs of hydro power plants (PEHP,y)” determined in the approved methodology ACM0002.
The calculation is done according to the following equation:
According to the formula above the project emissions (PEHP,y) for Banja amount to 252,000 x 90 / 1000 =
22,680 tCO2e/year.
Thus the ex-ante calculated emission reductions (ERy) amount to 361,732 – 22,680 = 339,052
tonsCO2e/year if the default emission factor for emissions from reservoirs of hydro power plants of
90 kgCO2e/MWh is applied.
For the sake of completeness it is mentioned here that DHP assigned SINTEF Energy Research in doing
a study with the title: “Overview of potential net greenhouse gas emissions from creating reservoirs in
the Devoll river, Albania”. This survey was finished on 05th of January 2010.
The net emissions from the reservoir of the hydro power plant of Banja in this study amount to 21.1
kgCO2e/MWh, which is by far lower as the default emission factor applied for the ex-ante calculation.
Thus DHP intends to revise this study by application of the latest figures for the reservoir of Banja in the
first year of crediting period at latest. If the revision of the study leads to a similar result and the
correctness is proved by a DOE during verification the final project emissions are calculated ex-post by
applying this value.
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B.6.4 Summary of the ex-ante estimation of emission reductions:
Table 19: Summary of ex-ante estimation of emission reductions
Year Estimation of
project activity
emissions
(tCO2eq)
Estimation of
baseline
emissions
(tCO2eq)
Estimation of
leakage
(tCO2eq)
Estimation of
overall emissions
reductions
(tCO2eq)
01/07/2020 11,340 180,866 0 169,526
2021 22,680 361,732 0 339,052
2022 22,680 361,732 0 339,052
2023 22,680 361,732 0 339,052
2024 22,680 361,732 0 339,052
2025 22,680 361,732 0 339,052
2026 22,680 361,732 0 339,052
2027 22,680 361,732 0 339,052
2028 22,680 361,732 0 339,052
2029 22,680 361,732 0 339,052
30/06/2030 11,340 180,866 0 169,526
Total (tonnes of CO2eq)
(crediting period =
10 years)
226,800 3,617,320 0 3,390,520
B.7. Application of the monitoring methodology and description of the monitoring plan:
B.7.1 Data and parameters monitored:
Data / Parameter: EGPJ,y = EGfacility,y
Data unit: MWh/yr
Description: Quantity of net electricity generation supplied by the project plant/unit to the
grid in year y
Source of data to be
used:
Measured by electricity meters and verified against balance bills
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
The annual net electricity delivered to the grid by the project activity is
estimated for the ex-ante calculation with:
HPP Moglice 171.2 MW 440,550 MWh
HPP Kokel 36.2 MW 91,080MWh
HPP Banja 64.6 MW 249,480 MWh
Description of
measurement methods
and procedures to be
applied:
Continuous measurement and at least monthly recording
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QA/QC procedures: The meters will be periodically checked according to the relevant national
electric standards and regulations; power supplied to the grid will be double
checked according to electricity sales invoices.
Any comment: Refer to B.7.2. Description of the monitoring plan
Data / Parameter: TEGy
Data unit: MWh/yr
Description: Total electricity produced by the HPP Banja considered having a power
density between 4 and 10 W/m², including the electricity supplied to the grid
and the electricity supplied to internal loads, in year y.
Source of data to be
used:
Measured by electricity meters and verified against balance bills
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
The annual net electricity delivered to the grid by the HPP Banja is estimated
for the ex-ante calculation with 252,000 MWh.
Description of
measurement methods
and procedures to be
applied:
Continuous measurement and at least monthly recording
QA/QC procedures: The meters will be periodically checked according to the relevant national
electric standards and regulations; power supplied to the grid will be double
checked according to electricity sales invoices.
Any comment: -
Data / Parameter: EGimported
Data unit: MWh/yr
Description: Quantity of net electricity imported from the national grid in year y (in times
when the power plant is not generating any electricity)
Source of data to be
used:
Measured by electricity meters and verified against balance bills
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
For the ex-ante calculation of the emission reductions the power supplied
from the grid to the project activity is estimated to be 0 MWh.
Description of
measurement methods
and procedures to be
applied:
Continuous measurement and at least monthly recording
QA/QC procedures: The meters will be periodically checked according to the relevant national
electric standards and regulations; power supplied to the grid will be double
checked according to electricity sales invoices.
Any comment: Refer to B.7.2. Description of the monitoring plan
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Data / Parameter: EFRes
Data unit: kgCO2e/MWh
Description: Emission factor for emissions from reservoirs
Source of data to be
used:
SINTEF study to be updated at the first year of crediting period at latest
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
To be calculated in the SINTEF study.
Description of
measurement methods
and procedures to be
applied:
New calculation once at the first year of crediting period.
QA/QC procedures: Proved by a DOE before or during first verification of the Monitoring Report.
Any comment: -
Data / Parameter: EFgrid,CM,y
Data unit: tCO2/MWh
Description: Combined margin CO2 emission factor for grid connected power generation in
year y calculated using the latest version of the “Tool to calculate the emission
factor for an electricity system (Version 02.1.0)”
Source of data to be
used:
Official data from KESH, OST and ENTSOE (imports)
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
The ex-ante calculated Combined Margin (CM) grid emission factor
(including off- grid power plants) amounts to 0.4631 tonsCO2/MWh.
Description of
measurement methods
and procedures to be
applied:
The Combined Margin (CM) grid emission factor (including off- grid power
plants) is calculated ex-ante for the first crediting period.
QA/QC procedures: -
Any comment: -
Data / Parameter: CapPJ
Data unit: W
Description: Installed capacity of the hydro power plant after the implementation of the
project activity.
Source of data to be
used:
Project site
Value of data applied
for the purpose of
calculating expected
emission reductions in
HPP Moglice 171,200,000 W
HPP Kokel 36,200,000 W
HPP Banja 64,600,000 W
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section B.5
Description of
measurement methods
and procedures to be
applied:
Check the generators‟ nameplates annually.
QA/QC procedures: -
Any comment: Refer to B.7.2. Description of the monitoring plan
Data / Parameter: APJ
Data unit: m²
Description: Area of the reservoir measured in the surface of the water, after the
implementation of the project activity, when the reservoir is full.
Source of data to be
used:
Project activity site
Value of data applied
for the purpose of
calculating expected
emission reductions in
section B.5
Banja Kokel Moglice
HRWL surface area [m²]
14,110,000
710,000
7,210,000
Estimated for the ex-ante calculation of the power density.
Description of
measurement methods
and procedures to be
applied:
Annual measured from topographical surveys, maps, satellite pictures, etc.
QA/QC procedures: -
Any comment: -
B.7.2. Description of the monitoring plan:
According to the approved methodology ACM0002 monitoring shall consist of metering the electricity
[kWh] generated by the project activity generating renewable energy. Emission reductions are calculated
by multiplying the generated electricity with the ex ante fixed Combined Margin (CM) emission factor
for the national grid of Albania (with the inclusion of fossil fuelled off-grid power plants) as determined
in this Project Design Document (PDD).
Since the monitoring of emission reduction will be achieved through the measurement of net electricity
generation, no special operational and management structure is needed apart from normal electricity
generation operational and management structure.
For the ex-ante calculation no electricity import to the project sites from the Albanian grid was
envisaged. If electricity imports occur under the project activity they will be monitored by an additional
electricity meter and will be subtracted from the net electricity generation supplied to OST.
The project emissions from water reservoirs of hydro power projects (PEHP,y) are calculated annually
after monitoring the total electricity produced by the HPP Banja. The power density of Banja is
envisaged to be between 4 and 10 W/m². Thus Project Emissions have to eb considered according to the
approved methodology ACM0002 Version 12.1.0.
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All measurements will be conducted with calibrated measurement equipment according to relevant
industry standards and the Albanian metering code. The quality control (QC) and quality assurance (QA)
of the metering is done as required in the above mentioned standards and codes..
Calibration of the energy meters will be carried out according to the same agreements..
The recorded data will be kept for at least two years after the end of the last crediting period.
For further detail see also attached monitoring plan in Annex 4.
B.8. Date of completion of the application of the baseline study and monitoring methodology
and the name of the responsible person(s)/entity(ies):
Contact information of the person(s)/entity(ies)
responsible for the application of the baseline
and monitoring methodology
Indicate if the person/entity is also a project
participant listed in Annex 1
Nevena Alexandrova
Climate Change Expert
Project Manager of the CDM DHP project
Energy and Environment Department
ALLPLAN GmbH
Schwindgasse 10, 1040 Wien
Tel: +43 (1) 505 37 07 22
Mobile: +43 676 842 22 52 22
Fax: + 43 (1) 505 37 07 27
E-mail: [email protected]
www.allplan.at
No
Christian Praher
Senior Consultant
denkstatt GmbH
denkstatt 1130 Wien, Hietzinger Hauptstraße 28
Tel.: +43 (0) 1 786 89 00 55,
Mobile: +43 (0)664 164 62 05
Fax: +43 (0)1 786 89 00 15
E-mail: [email protected]
www.denkstatt.at
No
Christian Steinreiber
Senior Consultant
Pöyry Management Consulting
Laaer-Berg-Strasse 43, 1100 Vienna, Austria
Mobile: +43 (0) 664 828 57 32
Fax: + 43 (0) 1 53605 165
No
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Email: [email protected]
www.poyry.com
SECTION C. Duration of the project activity / crediting period
C.1. Duration of the project activity:
C.1.1. Starting date of the project activity:
The starting date of DHP will be in the future since no real action as financial closure, ordering of major
equipment, construction permit or start of construction has yet begun. Nevertheless, on 29/09/2009 the
project owner has sent a notification letter91
to the Albanian DNA and UNFCCC secretariat informing
about the intention to implement Devoll Hydropower project in Albania under CDM/Prior consideration
of CDM. With the notification letter the project owner intended securing the CDM status of DHP project
by demonstrating that the incentive from CDM was considered at the earliest stage of the project
implementation.
C.1.2. Expected operational lifetime of the project activity:
The expected operational lifetime of the project activity is considered as 35 years corresponding to the
minimum concession period as per the clauses in the Concession Agreement with the Albanian
Government. The Agreement states that the “Concession shall expire when the accumulated energy
production has reached 59 TWh or the achieved IRR has reached 10%, whichever comes first”92
.
C.2. Choice of the crediting period and related information:
C.2.1. Renewable crediting period:
C.2.1.1. Starting date of the first crediting period:
Not applicable
C.2.1.2. Length of the first crediting period:
Not applicable
C.2.2. Fixed crediting period:
C.2.2.1. Starting date:
The crediting period is expected to start on 01/07/2020
91
The notification letter to the to the Albanian DNA and UNFCCC secretariat/Prior consideration of CDM is
presented in Annex 8 92
FSR, Chapter 25, Financial analyses, page 3, Concession Agreement
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C.2.2.2. Length:
10 years
SECTION D. Environmental impacts
D.1. Documentation on the analysis of the environmental impacts, including transboundary
impacts:
For the development phase of this project activity an Environmental and Social Impact Assessment
(ESIA) was done. The last version of the report, used for this chapter, is dated June 2011.
The Albanian Environmental legislation contains the requirements of Environmental Approval and the
preparation of Environmental Impact Assessment (EIA) for development projects, described in LAW No.
8990, dated 23/01/2003. Additionally to DHP meeting the required Albanian EIA requirements, the joint
venture partners of DHP have CSR policies which demand that international ESIA standards and
practices be applied.
In tune with present trends towards establishing sustainability in development interventions and as
required by DHP policy, the guideline principles developed by the International Hydropower Association
(IHA) from August 2009 have been used to support and improve the ESIA process.
The ESIA identifies and lists different categories of impacts:
Impacts Caused by Changes in River Hydrology and Morphology
Impacts Caused by Construction or Plant Location
Roads and Transmission Lines
Land and Geology
Climate and Air Pollution
Hydrology
Water Quality
Fish and Aquatic Ecosystems
Terrestrial Fauna
Terrestrial Vegetation
Nature Protection
The Environmental (and Social) Management Plan, ESMP, identifies the different responsibilities of the
parties involved: Devoll Hydropower Sh.A, the Central Government in particular represented by Ministry
of Environment, Forests and Water Administration, Regional and local governmental representatives,
Local (municipal and village) administration, Contractors and Sub-Contractors, and Independent experts
and NGO‟s.
D.2. If environmental impacts are considered significant by the project participants or the host
Party, please provide conclusions and all references to support documentation of an environmental
impact assessment undertaken in accordance with the procedures as required by the host Party:
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The Draft ESIA from June 2011 identifies physical and biological impacts. The most important impacts
of Devoll Hydropower Project are related to the changes in river flow in the different section of the river
and the secondary impacts of such changes (impacts on water use and aquatic biodiversity).
There are priority mitigation actions, which include:
Minimum flow release on dams (Moglicë Dam, Kokël Dam and Banja Dam)
Waste and water management in the project area and adjacent villages
Reforestation
Measures to reduce sediment flushing and erosion
Relocation of Lumaj and Nikollarë villages with full compensation
Replacement of roads and bridges
Loss of local access
Landscaping to repair scars to nature
Measures against dust, noise and air pollution during construction phase
Preventive excavation and removal of objects in cultural heritage sites, that will be flooded
(prehistoric burial sites)
Water related mitigation measures will focus on the protection of biodiversity and integrity of the
ecosystem in the impacted parts of the water system, and mitigate the potential damage to fisheries and
other water related use (irrigation, water supply, transport, etc.).
The most important mechanism for mitigation will be specific requirements for Minimum Flow Releases
(for MFR). The ESIA has given recommendations for MFR in the relevant river reaches.
The detailed ESMP to be developed when construction details and schedules are known will expand the
framework ESMP contained within this ESIA and address issues defined under IFC Performance
Standards relevant to environmental and social management planning including involuntary resettlement.
It will produce an ESMP manual with clear priorities and procedures for DHP to implement to ensure
compliance with international best practice.
The Environmental Management Plan will be divided into potential sub-programmes:
Reservoir Clearance and Filling Plan;
Water Quality Monitoring;
Fish Monitoring Plan;
Re-forestation Plan;
Construction Activities Environment Plan;
Operation Activities Environment Plan;
Transmission Line Environment Management Plan;
Roads Environment Management Plan.
Monitoring is one of the important elements of an ESMP and serves a number of functions including:
a) Providing a check on the implementation of proposed mitigation measures and ESMP
recommendations; and
b) Identifying corrective measures or the redesign of mitigation measures, if the originally planned
mitigation measures are not sufficiently effective.
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The monitoring will take place at different stages of the project lifetime.
a) Monitoring of construction work and construction facilities
b) Resettlement and compensation monitoring, and
c) Long term or operational monitoring
SECTION E. Stakeholders’ comments
E.1. Brief description how comments by local stakeholders have been invited and compiled:
Devoll Hydropower uses several different ways to invite Stakeholders comments:
1) Public Information Centre93
Since September 2010 DHP has operated a Public Information Centre (PIC) in Gramsh. Gramsh is the
main city in the project area and also the location of our site office from where site works are coordinated
(Land Access, ESIA, drilling works, field works).
The Public Information Centre serves as a centre where local direct and indirect project affected people
can inform themselves about all aspects related to hydropower in general, our project development as
well as on the current works and the project status. We explain relevant topics according to poster we
have composed for this purpose. We are also exhibiting a poster on CDM.
The PIC is open 4 days in a week, covering different daytimes and is staffed by male and female DHP
employee. Herewith we enable stakeholders to visit the PIC also in the evening hours and also ensure to
have a gender balanced opportunity to access the PIC.
Further the PIC serves as an accommodation for middle sized information meetings with local
government representatives.
2) Mobile Information Service94
Since December 2010 DHP have operated the so called Mobile Information Service (MIS). With the
same purpose as the PIC, the MIS is a mobile service where DHP serves the local communities that due
to distance, bad infrastructure or missing (public) transport is not able to visit the PIC in Gramsh. Until
February 2011 there have been approx. 10-15 sessions in distant villages in the project area. The MIS
will be conducted regularly and adapted to requirement for disclosure of new project information and
explanation purposes.
Same as the PIC, the MIS is staffed by male and female DHP employee.
3) DHP website95
93
Photos of DHP Public Information Centre are presented in Annex 6 94
Photos from meetings held in different communities by the DHP Mobile Information Service 95
Screenshot of DHP project website is presented in Annex 6
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A project website (http://www.dhp.al/) has been established, which give actual relevant information
about the project to the public.
Information about the CDM-project was also published e.g. via the website:
http://www.dhp.al/index.php?option=com_content&view=article&id=66%3Acdm-
project&catid=46%3Acdm-project&Itemid=65&lang=en
4) Meetings with local authorities
Continuously meetings with local and regional authorities are held, those were bilateral as well as
multilateral. The purpose of the meetings is the provision of information about the project and the project
progress, as well as provision of a platform for discussion of questions and concerns.
The main topic and focus of each of them is concerned with the establishment of project design area,
identification of the impacted land and commune or private property, local infrastructure and irrigation
channels.
5) Informative Round Table Meeting
DHP has introduced the “Informative Round Table Meeting” (IRTM) to have a platform for regular
formal meetings. To these meeting the heads of (sub)-prefectures, districts, municipality and communes
are invited.
The IRTM takes place every 2nd or 3rd month. So far DHP has conducted 2 sessions, the format of those
should be standardized.
Herewith DHP ensures to inform and engage the local government and decision makers closely enabling
them to fulfil their duties as elected representatives of the communities. Also we provide a platform
where issues and concerns can be raised and discussed in an early stage in order to handle them without
further complications.
6) Meeting central authorities
Continuously meetings with central authorities are held. The purpose of those meetings is the provision
of information about the project and the project progress, as well as provision of a platform for
discussion of questions and concerns. For different issues, different platforms/working groups have been
established. (PIU – formal representation of the Contracting Authority/METE; working group on
Replacement Infrastructure/representatives of a.o. MPW and METE.
7) Meetings (inter)national institutions, donor organisations and NGOs
DHP is continuously consulting the international community representatives by informing them on the
project and the conducted works.
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EU, UNDP, EBRD, Austrian Development Corporation, Swiss Development Corporation, SNV, GTZ,
KfW, OSCE, JICA, as well as approx. 20 others have been and will be regularly updated and cooperation
will be sought.
In September 2010 a local NGO called “Devolli 2010” was established and purpose of this establishment
is to replacement infrastructure between Banja dam and Gramsh was established. DHP sought immediate
dialogue with this NGO and have conducted several bilateral meetings. Further DHP has contributed to a
public hearing that was organised by this NGO.
8) Public Hearings
On 25th March 2010, DHP participated in the public hearing on the Strategic Environmental Assessment
(SEA) proposal for Energy Planning in the Devoll River. This event was organised in the Cultural House
in Gramsh by Ministry of Economy, Trade and Energy (METE) and it had numerous community
representatives as attendants. Photo of the public hearing is presented in Annex 5.
There will be a separate Public Hearing for the Draft Environmental and Social Impact Assessment
(ESIA) most likely in June 2011. For this the ESIA will be translated into Albanian language for the
interested public to prepare, comments will be collected and addressed properly.
Following this Public Hearing the raised comments will be addressed, which might lead to the need of
conducting some small additional studies and consultations. The results will be part of the final ESIA,
which expected to be finished in the 3rd
quarter of 2011. This will also include two important parts: the
Environmental and Social Management plan and the Resettlement Action plan.
E.2. Summary of the comments received:
During the numerous consultations with Stakeholders (local and central authorities, NGOs, residents) a
lot of comments were received. Mostly the project was warmly welcomed and seen as a very positive
opportunity for economic growth in the poor region.
The requests and comments received until March 2011 were considering:
Threat of losing accessibility (road from Banja dam to Gramsh, vehicle connection to Silare)
Employment possibilities
Expected pollution of the future lakeshore (since waste and wastewater in the area is thrown in
the river)
Fees for property inundation
Potential influence on irrigation and the water systems
Fear of traffic/noise/dust from the construction activities
Losing of key livelihoods (agriculture, fodder, medicinal plants, grazing, honey-bees, forests,
etc.).
These concerns will be included in the ESIA process, and treatment measures further elaborated in the
Social Management Plan, the Environment Management Plan, and the Resettlement Action Plan.
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E.3. Report on how due account was taken of any comments received:
DHP takes into account each single comment. Most comments fall into those categories listed below:
Replacement of the Road from Banja to Gramsh. The project will flood the road from Banja
to Gramsh. Local residents, depending on the road have past negative experiences with
relocation of this road, so there is doubt in the villages, what might happen with this road.
The solution presented from DHP in cooperation with the Albanian government is following:
According to the concessions agreement and as stated in various meetings and information
letters, DHP will compensate the value of the existing road that will be inundated, but the
responsibility for the decision and construction of the replacement infrastructure is with the
Government of Albania. DHP endorses/favours to achieve an acceptable solution for the local
community.
Property inundation: the Albanian government defines the rates for property inundation. DHP
is complying with Albanian and EU legislation in compensating the persons concerned. Further
to that DHP is supporting various measures to improve regional development.
Additional to that the project design has been changed resulting in the need of resettling only
approx. 40-50 houses instead of approx. 100 houses according to the initial project design.
Employment: DHP is aware of its important role of a major employer during construction time
in the region. In order to qualify local untrained personnel for potential work at the construction
site and the power project, DHP runs training courses prior to the start of the construction phase:
English courses and first aid training is done for local people. Another program will skill workers
as Welders, Brick layer, Driver until start of the construction phase.
Further to that DHP has received several requests for support from the communes, ranging from clearing
of roads up to reconstruction of drinking water facilities. Each request is being treated by DHP separately
depending on DHP´s own requirements, current local impact, awaiting and respecting activities and
official responsibilities by authorities for such matters.
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Annex 1
CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY
Organization: Devoll Hydropower Sh.A. (DHP)
Street/P.O.Box: Rruga Papa Gjon Pali II
Building: ABA Business Center, Office Nr. 1204
City: Tirana
State/Region:
Postcode/ZIP:
Country: Albania
Telephone: + 355 4 450 1 450
FAX: + 355 4 2400 734
E-Mail:
URL: http://www.dhp.al/
Represented by: Mr. Mario Niederwolfsgruber
Title: Chief Financial Officer
Salutation: Mr.
Last name: Niederwolfsgruber
Middle name:
First name: Mario
Department:
Mobile: + 355 69 408 2703
Direct FAX: + 355 4 2400 734
Direct tel: + 355 4 450 1 450
Personal e-mail: [email protected]
Organization: EVN AG
Street/P.O.Box: 2344 Maria Enzersdorf
Building: EVN Platz
City: Maria Enzersdorf
State/Region: Vienna
Postcode/ZIP:
Country: Austria
Telephone: +43 (0) 2236 200-121 79
FAX: +43 (0)2236 200-821 79
E-Mail: [email protected]
URL: www.evn.at
Represented by: Mr. Peter Layr
Title: Managing Director, Dr.
Salutation: Mr.
Last name: Layr
Middle name:
First name: Peter
Department: Managing Board
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Mobile:
Direct FAX: +43 (0) 2236 200 2030
Direct tel: +43 (0) 2236 200 12873
Personal e-mail: [email protected]
Organization: Statkraft AS
Street/P.O.Box: Lilleakerveien 6, P.O. Box 200 Lilleaker
Building:
City: Oslo
State/Region:
Postcode/ZIP: 0216
Country: Norway
Telephone: +47 24 06 78 91
FAX: +47 24 06 70 01
E-Mail: [email protected]
URL: www.statkraft.com
Represented by:
Title: President and Chief Executive Officer
Salutation: Mr.
Last name: Rynning-Tønnesen
Middle name:
First name: Christian
Department: Corporate Management
Mobile:
Direct FAX: +47 24 06 70 01
Direct tel: +47 24 06 79 00
Personal e-mail: [email protected]
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Annex 2
INFORMATION REGARDING PUBLIC FUNDING
No public funding from parties included in Annex I of the UNFCCC has been involved in the proposed
project activity96
96 The project owner presented declarations to the DOE that no public funding from parties included in Annex I has
been involved in DHP
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Annex 3
BASELINE INFORMATION
“Tool to calculate the emission factor for an electricity system (Version 02.1.0)”
Annex 1: Default efficiency factors for power plants
Used Electricity generation data for the years 2007 to 2009
Imports/Exports
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Import
GWh 2005 2006 2007 2008 2009
1 98 173 275 278 274
2 106 136 312 258 43
3 77 94 289 285 197
4 47 24 213 175 6
5 20 8 174 157 42
6 62 50 179 193 134
7 88 113 188 140 141
8 79 103 233 204 223
9 91 88 220 213 224
10 145 130 265 202 251
11 170 111 258 257 142
12 266 210 274 254 101
Summe 1249 1240 2880 2616 1778
Export
GWh 2005 2006 2007 2008 2009
1 78 58 16 21 40
2 112 43 1 12 81
3 102 97 0 0 36
4 63 104 2 14 162
5 89 115 7 19 79
6 64 59 0 2 17
7 44 10 2 16 6
8 25 29 0 9 4
9 55 28 0 8 9
10 48 32 2 16 23
11 31 43 8 33 39
12 15 21 12 35 37
Summe 726 639 50 185 533
Balance (pos=Import; neg=export)
GWh 2005 2006 2007 2008 2009
1 20 115 259 257 234
2 -6 93 311 246 -38
3 -25 -3 289 285 161
4 -16 -80 211 161 -156
5 -69 -107 167 138 -37
6 -2 -9 179 191 117
7 44 103 186 124 135
8 54 74 233 195 219
9 36 60 220 205 215
10 97 98 263 186 228
11 139 68 250 224 103
12 251 189 262 219 64
Summe 523 601 2830 2431 1245
https://www.entsoe.eu/resources/data-portal/exchange/
Electricity generation
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Net electricity production 2006
Inst. Capacity
MW Gross MWh
Aux.Ser.
MWh
Losses
MWh Net MWh
Hydro Production 1447.9 5,452,852 6,710 82,269 5,363,873
Drin River Cascade 1350 5,011,712 5,097 78,045 4,928,569
Fierza 500 1,939,718 2,698 30,220 1,906,800
Koman 600 2,119,750 1,087 32,955 2,085,708
Vau Dejes 250 952,244 1,312 14,870 936,061
Mat River Cascade 50 196,134 1,210 3,270 191,654
Ulez 25 106,754 501 1,675 104,578
Shkopet 25 89,380 709 1,595 87,076
Bistrica River Cascade 27.5 154,883 362 792 153,729
Bistrica I 22.5 123,606 266 636 122,704
Bistrica II 5 31,277 96 156 31,025
Other HPP 20.4 71,693 41 162 71,491
Selita 5 32,304 41 162 32,102
Gjanc+Bogove+Smokthine 15.4 39,389 39,389
Small HPP 18,430 18,430
Thermo Production (TPP Fieri) 75 92,630 10,960 1,389 80,281
TPP Fieri 75 92,630 10,960 1,389 80,281
Total Domestic Production 1522.9 5,545,482 17,670 83,658 5,444,154
Net electricity production 2007
Inst. Capacity
MW Gross MWh
Aux.Ser.
MWh
Losses
MWh Net MWh
Hydro Production 1447.9 2,868,364 7,124 31,728 2,829,512
Drin River Cascade 1350 2,532,504 4,904 28,195 2,499,404
Fierza 500 694,463 1,417 7,058 685,987
Koman 600 1,204,720 2,122 13,854 1,188,744
Vau Dejes 250 633,321 1,365 7,283 624,673
Mat River Cascade 50 138,145 1,760 1,589 134,797
Ulez 25 70,573 1,453 812 68,309
Shkopet 25 67,572 307 777 66,488
Bistrica River Cascade 27.5 127,881 417 1,471 125,993
Bistrica I 22.5 121,646 279 1,399 119,968
Bistrica II 5 6,235 138 72 6,025
Other HPP 20.4 67,110 43 473 66,594
Selita 5 33,951 43 473 33,435
Gjanc+Bogove+Smokthine 15.4 33,159 33,159
Small HPP 2,724 2,724
Thermo Production (TPP Fieri) 75 71,898 7,609 827 63,462
TPP Fieri 75 71,898 7,609 827 63,462
Total Domestic Production 1522.9 2,940,262 14,733 32,555 2,892,974
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Net electricity production 2008
Installed
Capacity
(MW)
Gross
Production
(MWh)
Auxiliary
Services
(MWh)
Losses in
Production
(MWh)
Net Production
(MWh)
Hydro Production 1447.9 3,849,896 4,693 12,371 3,832,831
Drini River Cascade 1350 3,441,046 3,184 9,937 3,427,925
Fierze 500 1,071,634 1,015 0 1,070,619
Koman 600 1,551,980 1,101 9,937 1,540,941
Vau Dejes 250 817,432 1,068 0 816,364
Mat River Cascade 50 171,703 1,061 928 169,714
Ulez 25 92,334 732 476 91,126
Shkopet 25 79,369 329 451 78,588
Bistrica River Cascade 27.5 139,405 403 973 138,030
Bistrica I 22.5 118,706 262 869 117,575
Bistrica II 5 20,699 141 103 20,455
Other HPP 20.4 54,998 45 534 54,419
Selita 5 35,768 45 534 35,189
Gjanc, Bogove, Smokthine 15.4 19,230 0 0 19,230
Small HPP 42,744 0 0 42,744
Thermo Production (TPP Fieri) 75 0 0 0 0
TPP Fieri 75 0 0 0 0
Total Domestic Production 1522.9 3,849,896 4,693 12,371 3,832,831
Net electricity production 2009
Installed
Capacity
(MW)
Gross
Production
(MWh)
Auxiliary
Services
(MWh)
Losses in
Production
(MWh)
Net Production
(MWh)
Hydro Production 1447.9 5,229,618 4,822 23,782 5,201,014
Drini River Cascade 1350 4,704,738 3,120 20,031 4,681,587
Fierze 500 1,557,357 1,110 0 1,556,248
Koman 600 2,062,050 1,037 20,031 2,040,982
Vau Dejes 250 1,085,330 973 0 1,084,358
Mat River Cascade 50 228,638 1,212 2,009 225,418
Ulez 25 126,116 389 1,096 124,631
Shkopet 25 102,522 822 913 100,787
Bistrica River Cascade 27.5 172,128 440 1,224 170,464
Bistrica I 22.5 136,742 256 1,123 135,364
Bistrica II 5 35,385 184 101 35,100
Other HPP 20.4 85,052 51 519 84,483
Selita 5 34,804 51 519 34,235
Gjanc, Bogove, Smokthine 15.4 50,248 0 0 50,248
Small HPP 39,062 0 0 39,062
Thermo Production (TPP Fieri) 172 0 0 0 0
TPP Fieri 75 0 0 0 0
TPP Vlora (New) 97 0 0 0 0
Total Domestic Production 1619.9 5,229,618 4,822 23,782 5,201,014
Source: Albanian Electro-Energetic Corporation (KESH j.s.c.) http://www.kesh.com.al/ and
Transmission System Operator (OST j.s.c) http://www.ost.al/
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Selection of the method to determine the operating margin (OM):
Electricity generation of the grid of Albania for the years 2005 to 2009 (with inclusion of off- grid
generation in the years 2007 to 2009)
Sum of electricity generation in [MWh] 6,398,476 6,684,154 6,245,682 6,921,539 7,451,723
Electricity Generation in MWh 2005 2006 2007 2008 2009
Sum Hydros / low cost-must run 5,072,489 5,363,873 2,829,512 3,832,831 5,201,015
Percentage 0.79 0.80 0.45 0.55 0.70
Sum Import 1,249,000 1,240,000 2,880,000 2,616,000 1,778,000
Percentage 0.20 0.19 0.46 0.38 0.24
Sum Thermal 76,987 80,281 536,170 472,708 472,708
Percentage 0.01 0.01 0.09 0.07 0.06
Percentage Low cost - must run 0.99 0.99 0.91 0.93 0.94
Due to the fact that low-cost/must run resources amount to more than 50% for the most recent 5 years
(2005 to 2009), where data was available the operating margin (OM) is calculated according to Option
(d) of Step 3 of the “Tool” the Average OM.
The calculation is provided for the years 2007 to 2009 as follows:
Electricity generation in [MWh] 2005 2006 2007 2008 2009 Date of comission
Gjanc,Bogovce, Smokthine 39,389 33,159 19,230 50,248 2004,2005,2006
off grid 1 32,527 32,527 32,527 2007-1987
off grid 2 13,131 13,131 13,131 2007-1987
off grid 3 171,478 171,478 171,478 2007-1987
off grid 4 3,419 3,419 3,419 2007-1987
off grid 5 25,247 25,247 25,247 2007-1987
off grid 6 29,349 29,349 29,349 2007-1987
off grid 7 67,940 67,940 67,940 2007-1987
off grid 8 26,466 26,466 26,466 2007-1987
off grid 9 6,629 6,629 6,629 2007-1987
off grid 10 1,066 1,066 1,066 2007-1987
off grid 11 32,329 32,329 32,329 2007-1987
off grid 12 1,820 1,820 1,820 2007-1987
off grid 13 10,126 10,126 10,126 2007-1987
off grid 14 8,849 8,849 8,849 2007-1987
off grid 15 14,227 14,227 14,227 2007-1987
off grid 16 22,944 22,944 22,944 2007-1987
off grid 17 0 0 0 2007-1987
off grid 18 493 493 493 2007-1987
off grid 19 700 700 700 2007-1987
off grid 20 242 242 242 2007-1987
off grid 21 247 247 247 2007-1987
off grid 22 1,668 1,668 1,668 2007-1987
off grid 23 1,811 1,811 1,811 2007-1987
Koman (HPP) 2,186,860 2,085,708 1,188,744 1,540,941 2,040,982 1986
Fierza (HPP) 1,870,021 1,906,800 685,987 1,070,619 1,556,248 1978
Vau dejes (HPP) 927,319 936,061 624,673 816,364 1,084,358 1975
Shkopet (HPP) 58,200 87,076 66,488 78,588 100,787 1963
Ulez (HPP) 104,578 68,309 91,126 124,631 1954
Bistrice 2 (HPP) 31,025 6,025 20,455 35,100 1952
Lanabregas (HPP) 30,089 32,102 33,435 35,189 34,235 1951
Bistrice 1 (HPP) 122,704 119,968 117,575 135,364 1948
Other HPPs 18,430 2,724 42,744 39,062
Fier (TPP) 76,987 80,281 63,462 0 0 1966/1983/2009
Vlora (TPP) 0 0 0 0
IMPORTS 1,249,000 1,240,000 2,880,000 2,616,000 1,778,000 (Source: https://w w w .entsoe.eu/resources/data-portal/exchange/)
Sum of electricity generation in [MWh] 6,398,476 6,684,154 6,245,682 6,921,539 7,451,723
Electricity Generation in MWh 2005 2006 2007 2008 2009
Sum Hydros / low cost-must run 5,072,489 5,363,873 2,829,512 3,832,831 5,201,015
Percentage 0.79 0.80 0.45 0.55 0.70
Sum Import 1,249,000 1,240,000 2,880,000 2,616,000 1,778,000
Percentage 0.20 0.19 0.46 0.38 0.24
Sum Thermal 76,987 80,281 536,170 472,708 472,708
Percentage 0.01 0.01 0.09 0.07 0.06
Percentage Low cost - must run 0.99 0.99 0.91 0.93 0.94
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Relevant year
2007 A B C D E F G
m i EGm FCi,m NCVi EFCO2,i ηm EFEL,m
Net Electricity
Generation
Fuel
Consumption
Net Calorific
Value
(Lower
Value)
CO2 Emission Factor
(Lower Value)
Average Net
Energy
Conversion
Efficiency
CO2
Emission
Factor
CO2 Emissions
(MWh) (t) (GJ/t) (tCO2/GJ) (%) (tCO2/MWh) (t-CO2)
Default
values from
Annex 1 of
the
"Electricity
Tool" F=Dx3.6/E G=AxF
1 Off Grid (Cap1, Fuel D; Age 1) Diesel 32,527 41.4 0.0726 0.28 0.933 30,362
2 Off Grid (Cap1, Fuel G; Age 1) Gasoline 13,131 42.5 0.0675 0.28 0.868 11,396
3 Off Grid (Cap2, Fuel D; Age 1) Diesel 171,478 41.4 0.0726 0.33 0.792 135,811
4 Off Grid (Cap3, Fuel D; Age 1) Diesel 3,419 41.4 0.0726 0.35 0.747 2,553
5 Off Grid (Cap4, Fuel D; Age 1) Diesel 25,247 41.4 0.0726 0.37 0.706 17,834
6 Off Grid (Cap5, Fuel D; Age 1) Diesel 29,349 41.4 0.0726 0.39 0.670 19,668
7 Off Grid (Cap6, Fuel D; Age 1) Diesel 67,940 41.4 0.0726 0.42 0.622 42,278
8 Off Grid (Cap7, Fuel D; Age 1) Diesel 26,466 41.4 0.0726 0.45 0.581 15,371
9 Off Grid (Cap1, Fuel D; Age 2) Diesel 6,629 41.4 0.0726 0.28 0.933 6,188
10 Off Grid (Cap1, Fuel G; Age 2) Gasoline 1,066 42.5 0.0675 0.28 0.868 925
11 Off Grid (Cap2, Fuel D; Age 2) Diesel 32,329 41.4 0.0726 0.33 0.792 25,605
12 Off Grid (Cap3, Fuel D; Age 2) Diesel 1,820 41.4 0.0726 0.35 0.747 1,359
13 Off Grid (Cap4, Fuel D; Age 2) Diesel 10,126 41.4 0.0726 0.37 0.706 7,153
14 Off Grid (Cap5, Fuel D; Age 2) Diesel 8,849 41.4 0.0726 0.39 0.670 5,930
15 Off Grid (Cap6, Fuel D; Age 2) Diesel 14,227 41.4 0.0726 0.42 0.622 8,853
16 Off Grid (Cap7, Fuel D; Age 2) Diesel 22,944 41.4 0.0726 0.45 0.581 13,326
17 Off Grid (Cap1, Fuel D; Age 3) Diesel 0 41.4 0.0726 0.28 0.933 0
18 Off Grid (Cap1, Fuel G; Age 3) Gasoline 493 42.5 0.0675 0.28 0.868 428
19 Off Grid (Cap2, Fuel D; Age 3) Diesel 700 41.4 0.0726 0.33 0.792 554
20 Off Grid (Cap3, Fuel D; Age 3) Diesel 242 41.4 0.0726 0.35 0.747 181
21 Off Grid (Cap4, Fuel D; Age 3) Diesel 247 41.4 0.0726 0.37 0.706 174
22 Off Grid (Cap5, Fuel D; Age 3) Diesel 1,668 41.4 0.0726 0.39 0.670 1,118
23 Off Grid (Cap6, Fuel D; Age 3) Diesel 1,811 41.4 0.0726 0.42 0.622 1,127
Fier Residual Fuel Oil 63,462 39.8 0.0755 0.375 0.725 45,997
Vlora (CCGT) Natural Gas 46.5 0.0543 0.6 0.326 0
0.0631
CO2 emissions from Power Plants
No. Name of Power Plant
Fuel Type
Relevant year
2008 A B C D E F G
m i EGm FCi,m NCVi EFCO2,i ηm EFEL,m
Net Electricity
Generation
Fuel
Consumption
Net Calorific
Value
(Lower
Value)
CO2 Emission Factor
(Lower Value)
Average Net
Energy
Conversion
Efficiency
CO2
Emission
Factor
CO2 Emissions
(MWh) (t) (GJ/t) (tCO2/GJ) (%) (tCO2/MWh) (t-CO2)
Default
values from
Annex 1 of
the
"Electricity
Tool" F=Dx3.6/E G=AxF
1 Off Grid (Cap1, Fuel D; Age 1) Diesel 32,527 41.4 0.0726 0.28 0.933 30,362
2 Off Grid (Cap1, Fuel G; Age 1) Gasoline 13,131 42.5 0.0675 0.28 0.868 11,396
3 Off Grid (Cap2, Fuel D; Age 1) Diesel 171,478 41.4 0.0726 0.33 0.792 135,811
4 Off Grid (Cap3, Fuel D; Age 1) Diesel 3,419 41.4 0.0726 0.35 0.747 2,553
5 Off Grid (Cap4, Fuel D; Age 1) Diesel 25,247 41.4 0.0726 0.37 0.706 17,834
6 Off Grid (Cap5, Fuel D; Age 1) Diesel 29,349 41.4 0.0726 0.39 0.670 19,668
7 Off Grid (Cap6, Fuel D; Age 1) Diesel 67,940 41.4 0.0726 0.42 0.622 42,278
8 Off Grid (Cap7, Fuel D; Age 1) Diesel 26,466 41.4 0.0726 0.45 0.581 15,371
9 Off Grid (Cap1, Fuel D; Age 2) Diesel 6,629 41.4 0.0726 0.28 0.933 6,188
10 Off Grid (Cap1, Fuel G; Age 2) Gasoline 1,066 42.5 0.0675 0.28 0.868 925
11 Off Grid (Cap2, Fuel D; Age 2) Diesel 32,329 41.4 0.0726 0.33 0.792 25,605
12 Off Grid (Cap3, Fuel D; Age 2) Diesel 1,820 41.4 0.0726 0.35 0.747 1,359
13 Off Grid (Cap4, Fuel D; Age 2) Diesel 10,126 41.4 0.0726 0.37 0.706 7,153
14 Off Grid (Cap5, Fuel D; Age 2) Diesel 8,849 41.4 0.0726 0.39 0.670 5,930
15 Off Grid (Cap6, Fuel D; Age 2) Diesel 14,227 41.4 0.0726 0.42 0.622 8,853
16 Off Grid (Cap7, Fuel D; Age 2) Diesel 22,944 41.4 0.0726 0.45 0.581 13,326
17 Off Grid (Cap1, Fuel D; Age 3) Diesel 0 41.4 0.0726 0.28 0.933 0
18 Off Grid (Cap1, Fuel G; Age 3) Gasoline 493 42.5 0.0675 0.28 0.868 428
19 Off Grid (Cap2, Fuel D; Age 3) Diesel 700 41.4 0.0726 0.33 0.792 554
20 Off Grid (Cap3, Fuel D; Age 3) Diesel 242 41.4 0.0726 0.35 0.747 181
21 Off Grid (Cap4, Fuel D; Age 3) Diesel 247 41.4 0.0726 0.37 0.706 174
22 Off Grid (Cap5, Fuel D; Age 3) Diesel 1,668 41.4 0.0726 0.39 0.670 1,118
23 Off Grid (Cap6, Fuel D; Age 3) Diesel 1,811 41.4 0.0726 0.42 0.622 1,127
Fier Residual Fuel Oil 39.8 0.0755 0.375 0.725 0
Vlora (CCGT) Natural Gas 46.5 0.0543 0.6 0.326 0
0.0503
CO2 emissions from Power Plants
No. Name of Power Plant
Fuel Type
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Relevant year
2009 A B C D E F G
m i EGm FCi,m NCVi EFCO2,i ηm EFEL,m
Net Electricity
Generation
Fuel
Consumption
Net Calorific
Value
(Lower
Value)
CO2 Emission Factor
(Lower Value)
Average Net
Energy
Conversion
Efficiency
CO2
Emission
Factor
CO2 Emissions
(MWh) (t) (GJ/t) (tCO2/GJ) (%) (tCO2/MWh) (t-CO2)
Default
values from
Annex 1 of
the
"Electricity
Tool" F=Dx3.6/E G=AxF
1 Off Grid (Cap1, Fuel D; Age 1) Diesel 32,527 41.4 0.0726 0.28 0.933 30,362
2 Off Grid (Cap1, Fuel G; Age 1) Gasoline 13,131 42.5 0.0675 0.28 0.868 11,396
3 Off Grid (Cap2, Fuel D; Age 1) Diesel 171,478 41.4 0.0726 0.33 0.792 135,811
4 Off Grid (Cap3, Fuel D; Age 1) Diesel 3,419 41.4 0.0726 0.35 0.747 2,553
5 Off Grid (Cap4, Fuel D; Age 1) Diesel 25,247 41.4 0.0726 0.37 0.706 17,834
6 Off Grid (Cap5, Fuel D; Age 1) Diesel 29,349 41.4 0.0726 0.39 0.670 19,668
7 Off Grid (Cap6, Fuel D; Age 1) Diesel 67,940 41.4 0.0726 0.42 0.622 42,278
8 Off Grid (Cap7, Fuel D; Age 1) Diesel 26,466 41.4 0.0726 0.45 0.581 15,371
9 Off Grid (Cap1, Fuel D; Age 2) Diesel 6,629 41.4 0.0726 0.28 0.933 6,188
10 Off Grid (Cap1, Fuel G; Age 2) Gasoline 1,066 42.5 0.0675 0.28 0.868 925
11 Off Grid (Cap2, Fuel D; Age 2) Diesel 32,329 41.4 0.0726 0.33 0.792 25,605
12 Off Grid (Cap3, Fuel D; Age 2) Diesel 1,820 41.4 0.0726 0.35 0.747 1,359
13 Off Grid (Cap4, Fuel D; Age 2) Diesel 10,126 41.4 0.0726 0.37 0.706 7,153
14 Off Grid (Cap5, Fuel D; Age 2) Diesel 8,849 41.4 0.0726 0.39 0.670 5,930
15 Off Grid (Cap6, Fuel D; Age 2) Diesel 14,227 41.4 0.0726 0.42 0.622 8,853
16 Off Grid (Cap7, Fuel D; Age 2) Diesel 22,944 41.4 0.0726 0.45 0.581 13,326
17 Off Grid (Cap1, Fuel D; Age 3) Diesel 0 41.4 0.0726 0.28 0.933 0
18 Off Grid (Cap1, Fuel G; Age 3) Gasoline 493 42.5 0.0675 0.28 0.868 428
19 Off Grid (Cap2, Fuel D; Age 3) Diesel 700 41.4 0.0726 0.33 0.792 554
20 Off Grid (Cap3, Fuel D; Age 3) Diesel 242 41.4 0.0726 0.35 0.747 181
21 Off Grid (Cap4, Fuel D; Age 3) Diesel 247 41.4 0.0726 0.37 0.706 174
22 Off Grid (Cap5, Fuel D; Age 3) Diesel 1,668 41.4 0.0726 0.39 0.670 1,118
23 Off Grid (Cap6, Fuel D; Age 3) Diesel 1,811 41.4 0.0726 0.42 0.622 1,127
Fier Residual Fuel Oil 39.8 0.0755 0.375 0.725 0
Vlora (CCGT) Natural Gas 46.5 0.0543 0.6 0.326 0
0.0467
No. Name of Power Plant
Fuel Type
CO2 emissions from Power Plants
Baseline (including imports) LCMR [MWh] Imports [MWh]
2007 5,709,512 2,880,000
2008 6,448,831 2,616,000
2009 6,979,015 1,778,000
19,137,358 7,274,000
EF AverageOM [tCO2/MWh]
0.0529
0.0503 6,921,539
0.0467 7,451,723
Total (2007-2009) = 20,618,944
Prepared by denkstatt GmbH
Emission factors for the National Grid of Albania
EF AverageOM [tCO2/MWh] Load [MWh]
0.0631 6,245,682
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Calculation of the Build Margin (BM) for the year 2009:
Electricity generation in [MWh] 2009 Time of Comissioning
Small HPP 39,062 2009
Gjanc, Bogove, Smoktine 50,248 2004,2005,2006
Off Grid (Cap1, Fuel D; Age 1) 32,527 2003-2007
Off Grid (Cap1, Fuel G; Age 1) 13,131 2003-2007
Off Grid (Cap2, Fuel D; Age 1) 171,478 2003-2007
Off Grid (Cap3, Fuel D; Age 1) 3,419 2003-2007
Off Grid (Cap4, Fuel D; Age 1) 25,247 2003-2007
Off Grid (Cap5, Fuel D; Age 1) 29,349 2003-2007
Off Grid (Cap6, Fuel D; Age 1) 67,940 2003-2007
Off Grid (Cap7, Fuel D; Age 1) 26,466 2003-2007
Off Grid (Cap1, Fuel D; Age 2) 6,629 1998-2002
Off Grid (Cap1, Fuel G; Age 2) 1,066 1998-2002
Off Grid (Cap2, Fuel D; Age 2) 32,329 1998-2002
Off Grid (Cap3, Fuel D; Age 2) 1,820 1998-2002
Off Grid (Cap4, Fuel D; Age 2) 10,126 1998-2002
Off Grid (Cap5, Fuel D; Age 2) 8,849 1998-2002
Off Grid (Cap6, Fuel D; Age 2) 14,227 1998-2002
Off Grid (Cap7, Fuel D; Age 2) 22,944 1998-2002
Off Grid (Cap1, Fuel D; Age 3) 0 1988-1997
Off Grid (Cap1, Fuel G; Age 3) 493 1988-1997
Off Grid (Cap2, Fuel D; Age 3) 700 1988-1997
Off Grid (Cap3, Fuel D; Age 3) 242 1988-1997
Off Grid (Cap4, Fuel D; Age 3) 247 1988-1997
Off Grid (Cap5, Fuel D; Age 3) 1,668 1988-1997
Off Grid (Cap6, Fuel D; Age 3) 1,811 1988-1997
Koman (HPP) 2,040,982 1986
Fierza (HPP) 1,556,248 1978
Vau dejes (HPP) 1,084,358 1975
Shkopet (HPP) 100,787 1963
Ulez (HPP) 124,631 1954
Bistrice 2 (HPP) 35,100 1952
Lanabregas (HPP) 34,235 1951
Bistrice 1 (HPP) 135,364 1948
*IMPORTS 1,778,000
Vlora (TPP) 0
Fier (TPP) 0
Sum of electricity generation in [GWh] 5,673,723 *without Imports
Sum of electricity generation of the
sample group for the BM [GWh] 458,867
Percentage of the electricity generation of
most recently
built 5 Power Plants 8%
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Relevant year
2009 A B C D E F G
i EGm FCi,m NCVi EFCO2,i ηm EFEL,m
Net Electricity Generation Fuel
Consumption
Net Calorific
Value
(Lower Value)
CO2 Emission
Factor
(Lower Value)
Average Net
Energy
Conversion
Efficiency
CO2 -
Emission
Factor
CO2
Emissions
(MWh) (t) (GJ/t) (tCO2/GJ) (%) (tCO2/MWh) (t-CO2)
Default
values from
Annex 1 of
the
"Electricity
Tool" F=Dx3.6/E G=AxF
1 Off Grid (Cap1, Fuel D; Age 1) Diesel 32,527 41.4 0.0726 0.28 0.933 30,362
2 Off Grid (Cap1, Fuel G; Age 1) Gasoline 13,131 42.5 0.0675 0.28 0.868 11,396
3 Off Grid (Cap2, Fuel D; Age 1) Diesel 171,478 41.4 0.0726 0.33 0.792 135,811
4 Off Grid (Cap3, Fuel D; Age 1) Diesel 3,419 41.4 0.0726 0.35 0.747 2,553
5 Off Grid (Cap4, Fuel D; Age 1) Diesel 25,247 41.4 0.0726 0.37 0.706 17,834
6 Off Grid (Cap5, Fuel D; Age 1) Diesel 29,349 41.4 0.0726 0.39 0.670 19,668
7 Off Grid (Cap6, Fuel D; Age 1) Diesel 67,940 41.4 0.0726 0.42 0.622 42,278
8 Off Grid (Cap7, Fuel D; Age 1) Diesel 26,466 41.4 0.0726 0.45 0.581 15,371
275,273
0.5999 tonsCO2/MWh
CO2 emissions from Power Plants
m
No. Name of Power Plant
Fuel Type
Calculation of the Combined Margin (CM):
Baseline (including imports) LCMR [MWh] Imports [MWh]
2007 5,709,512 2,880,000
2008 6,448,831 2,616,000
2009 6,979,015 1,778,000
19,137,358 7,274,000
w OM = 0.25
w BM = 0.75
Prepared by denkstatt GmbH
0.0529 0.5999
0.4631
Alternative (CM) EF y [tCO2/MWh]
Alternative weights
Emission factors for the National Grid of Albania
EF AverageOM [tCO2/MWh]
0.0467
20,618,944
EF BM,2009
Load [MWh]
7,451,723
0.0631 6,245,682
0.0503 6,921,539
Total (2007-2009) =
EF AverageOM [tCO2/MWh]
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Procedures related to off-grid power generation (following Annex 2 of the
“Tool”)
Excerpt from the “Tool” is marked in Italic.
The procedures in this annex serve to (a) identify those off-grid power plants that are eligible for
inclusion in the grid emission factor and to (b) collect the necessary data to include them in the
calculations of the operating and build margin emission factors of this tool.
Step 1: Obtain data on off-grid power generation
Data on off-grid power generation is usually not readily available and has to be collected to include off-
grid power generation in the grid emission factor. The collection of data on off-grid power generation
has two purposes: data is required to determine whether an identified power plant qualifies as .off-grid
power plant., as defined in the definitions section; and data is required to calculate the emissions and
electricity generation from off-grid power plants.
For this purpose, project proponents can conduct an own survey, or use existing data (if such data
provides the necessary information as outlined further below and if the existing data has the vintage as
required per this tool).
The project developer Energji ASHTA the owner of another CDM HPP project activity in Albania
assigned the VeVe Group, which is the Energji Ashta‟s local partner in Albania to conduct this off-grid
survey. Additionally Energji ASHTA assigned DATA TECHNOLOGY Betriebsberatungs GmbH & Co
KG (CEO: Univ.Prof. Dr. Marcus Hudec) with the Quality Assurance (QA) and Quality Control (QC).
Energji ASHTA and the project owners of Devoll share the costs for this off- grid study.
The collected data can be used in the following two ways:
(a) Direct use of data on a plant-by-plant basis: Include in the emission factor only those off-grid power
plants for which the necessary data is available or is collected. Ensure that the plants selected for
inclusion in the grid emission factor are reasonably representative for the overall off-grid power
generation in the electricity system97
;
(b) Statistical evaluation of the data based on sampling: Collect the necessary data for a representative
and appropriately stratified sample of off-grid power plants and infer the data to the entire electricity
system.
Document in the CDM-PDD which approach is followed.
In the above mentioned off-grid survey approach (b) was chosen. The whole off-grid survey consists of a
stratified sampling of off-grid power plants and a statistical extrapolation to the overall population.
97
For example, information on off-grid power generation could only be available for some sectors of the economy.
In this case, only the plants from these sectors may be included in the grid emission factor. However, in including
selected plants, no systematic bias should be introduced (e.g. by including only coal fired plants).
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The documentation of the whole off-grid study conducted by VeVe is available to the DOE on request.
As already mentioned above the whole statistical survey was accompanied for Quality Assurance (QA)
reasons by the Austrian statistic expert Univ. Prof. Dr. Marcus Hudec (DATA TECHNOLOGY
Betriebsberatungs GmbH & Co KG) in order to comply with international statistical standards and the
UNFCCC requirements determined in Annex 2 of the “Tool”. Marcus Hudec is member of the Council
of Statistics of Austria and head of the group responsible for statistical quality standards.
Step 1.1: Choose the data to be collected
Document which data is collected for each (sampled) off-grid power plant. Table 1 provides the
minimum data that must be collected for each (sampled) off-grid power plant p.
Table 1: Minimum data/information to be collected on each off-grid power plant p
In addition, other data may be collected, depending on how the requirements of this annex for inclusion
of an off-grid power plant p in the grid emission factor are assessed and on which options are used in
Step 3 of the tool to calculate the emission factor for a class of off-grid power plants m (Option A1, A2 or
A3) and the electricity generation by a class of off-grid power plants m (Option 1, 2 or 3). This may
include the following data:
All the input parameters summarized in Table 1 above are collected for each sampled off-grid power
plant during the field survey (see Questionnaire in English and Albanian language as Annexes to the
documentation of the whole off- grid study of VeVe, which is provided to the DOE on request).
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The design of the questionnaire has been developed in iterations of drafts and included extensive
pretesting to assure a highest standard of data quality according to the data collection process. The
questionnaire was utilized in personal interviews by a specially trained group of interviewers.
Table 2: Additional data that may be collected on off-grid power generation
Note that the same data collection approach should be applied to all off-grid plants in one sector (e.g.
industrial, commercial and residential sector).
The following input parameters summarized in Table 2 above are collected for each sampled off- grid
power plant during the field survey see Questionnaire in English and Albanian language as Annexes to
the documentation of the whole off- grid study of VeVe, which is provided to the DOE on request)
DATEstart,p since the off-grid power plants are also included in the build margin (see Step 1.2 of the
Annex 2 of the “Tool” below)
The conducted field survey showed that it was impossible for the respondents to provide the following
data of the Table 2 of above. These data were asked for in the Questions 21d and 21b of the
Questionnaire:
Question Q21d “teN calorific value of used fuel” (NCVp,i,y). None of the respondents did know
the exact value of the NCV. Thus, conservative default values (Source: IPCC 2006) were taken
into account.
Question Q21b “Energy produced from the off grid power plant (EGp,y)”.
None of the respondents could provide this data since no electricity meter are installed in the off-
grid power plans.
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Thus, the value for this data question has been calculated as product of Net calorific value (NCVp,i,y)
with the corresponding default efficiency factors for power plants m,y (see Annex 1 of above)) and
with the value of question Q21c „„Fuel quantity used (FCp,i,y)‟‟ divided by 3.6 in order to convert GJ
into MWh (corrected Option 2 of Step 4 of the “Tool”)
6.3
,,,,
,
ymyi
i
ymi
ym
NCVFC
EG
[MWh]
Where:
EGm,y = Net quantity of electricity generated and delivered to the grid by power unit m
in year y (MWh)
FCi,m,y= Amount of fossil fuel type i consumed by power plants included in off-grid
power plant class m in year y (mass or volume unit (tons))
NCVi,y = Net calorific value (energy content) of fossil fuel type i in year y (GJ/mass or
volume unit (GJ/ton))
ηm,y Default net energy conversion efficiency of off-grid power plant class m in year
y (ratio), as per the default values provided in Annex 1
m = Off-grid power plant class considered as one power unit (as per the provisions
in Annex 2 to this tool)
y = The relevant year as per the data vintage chosen in Step 3
i = Fossil fuel types used
This approach was used as already mentioned above since no questionnaire provided the directly
measured net quantity of generated electricity (EGm,y) requested for application of Option 1 of Step 4 of
the “Tool”. All questionnaires provided the amounts of fossil fuel consumed (FCi,m,y) by each off-grid
power plant during the year 2007. Thus EGm,y was calculated for all the UNFCCC off- grid classes
according to the corrected Option 2 of Step 4 of the “Tool”.
OMCp,y: This data set was not provided in the Questionnaire since for the 3rd
point of Step 2 of
Annex 2 point (c) was applied.
TEL: This data set was not provided in the Questionnaire since for the 3rd
point of Step 2 of
Annex 2 point (c) was applied. During the survey every company provided the tariff
class for the electricity purchased from the national grid of Albania (see also approach
described under Step 2 of Annex 2 of the “Tool”).
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Step 1.2: Define the classification of off-grid power plants
To facilitate data collection and calculations, off-grid power plants should be classified in different
classes of off-grid power plants. All off-grid power plants included in one class are considered as one
single power unit for the calculations in this tool.
Off-grid power plants should be classified according to their capacity (CAPp), fuel type (FUELp), and
type of technology (TECHp).
This classification was applied in the conducted off-grid survey (see documentation of the whole off-grid
study conducted by VeVe is available to the DOE on request).
Referring to the collected data from the questionnaires a theoretical maximum of 42 (7 x 1 x 2 x 3 = 42)
UNFCCC classes could be identified:
CAPp (question Q13 in the questionnaire), 7 different categories
TECHp (question Q8 in the questionnaire), 1 category
FUELp (question Q10 in the questionnaire), 2 categories
Age (question Q15 in the questionnaire), 3 categories
During the off grid survey just one technology was identified, namely the “Reciprocating engines”. The
off- grid power plants were either fuelled by diesel or by gasoline (FUELp). Gasoline was just used in
very small off- grid power plants (CAP < 10 kW).
Since the off- grid power plants are included also for the calculation of the build margin (BM) emission
factor the following age classes were defined based on the start date of operation (DATEstart,p) according
to Step 1.2 of Annex 2 of the “Tool”.
0 – 5 years of operation (reference year 2007)
6 – 10 years of operation (reference year 2007)
11 – 20 years of operation (reference year 2007)
The oldest off-grid power plant surveyed started operation in 1987.
If off-grid power plants are also included in the build margin, their vintage needs to be determined based
on the start date of operation (DATEstart,p). In this case, the classes have to be differentiated into three
data vintages: plants with up to five years of operation, plants with up to 10 years of operation and
plants with more than 10 years of operation.
Finally the following 23 UNFCCC classes separated into the data vintages required in the “Tool” were
identified:
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Diesel CAP < 10 10 < CAP < 50 50 < CAP < 100 100 < CAP < 200 200 < CAP < 400 400 < CAP < 1000 CAP > 1000
Age (0-5)
Age (6-10)
Age (11-20)
Gasoline
Age (0-5)
Age (6-10)
Age (11-20)
Nominal capacity of off grid power plants in [kW]
If default efficiencies, as provided in Annex 1 of this tool, are used to determine the emission factor for a
power plant (see Option A2 in Step 4 of this tool), the power plant classification provided in Annex 1
should be used. If the Options A1 and/or A3 in Step 4 of this tool are applied to determine the emission
factors for off-grid power plant classes, project participants may also use their own classification.
Since default efficiencies, as provided in Annex 1 of the “Tool”, are used to determine the emission
factor for each power plant (The sum of all off- grid power plants included in one UNFCCC class are
considered as one single power unit.) (see Option A2 in Step 4 of the “Tool”), the same power plant
classification provided in Annex 1 is used.
Step 1.3: Define the sectors for which data is collected
Define for which sectors (e.g. households, commercial sector) or industries data on off-grid electricity
generation is collected or whether data is collected for the whole economy. The project participants may
deliberately choose the sectors for which data is collected; however, the sectors should be clearly and
unambiguously defined (e.g. which size of companies or households, the geographical area covered, etc)
and the selection should include any systematic bias (e.g. by including only a sub-sector which uses only
coal as fuel while less carbon intensive fuels are used in other sub-sectors).
The survey was conducted as a probability survey, where the Business register of INSTAT was used as a
sampling frame. To achieve a maximum quality of the results a stratified sampling approach has been
chosen. The stratification is based on the economic activity and the size of the company which was
considered to be most appropriate for the off- grid survey.
As potential users of off-grid power plants private and state owned economic enterprises, public
institutions and households were identified. So the target population in the conducted survey was
determined to include all off-grid power plants used by enterprises, households and public institutions.
According to NACE Rev 1.1, there are 12 sections of economic activities to be considered. The size of
companies is divided in 4 groups: over 50 employees, 10 - 49 employees, 5 - 9 employees and 1 - 4
employees. In this way in total 48 strata are formed. The table below Active enterprises by Economic
Activities and Size, 2007 (Section A, B and P not-included) summarizes for each stratum, the number of
enterprises according to the economic activity and the size of companies.
The specific conditions of Albania (high cost of producing electricity because of high fuel prices) lead to
marginal use of off-grid power plants in households for non business purposes. Thus the household
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sector (NACE section P) was neglected and off-grid power plants used by families are not considered in
the off-grid survey.
Off-grid power plants used by the enterprises, operating in economic activities such as agriculture,
hunting and forestry (NACE section A) and fishing (NACE Section B) are excluded as well in the survey
since the type of activity refers to marginal off- grid power use as well. The excluded enterprises
represent less than 1% of the total number of enterprises.
The enterprises cover all sizes of economy and all geographical sector of Albania in order to avoid any
bias described in Step 1.3 of Annex 2 of the “Tool” above.
The following table summarizes the number of companies within different sectors. The companies are
located in all geographical areas of Albania. All the company data were provided by the official Statistic
Authority of Albania INSTAT to VeVe.
Active enterprises by Economic Activities and Size, 2007 (Section A, B and P not-included) Economic Activity (NACE Section)
Size of enterprises
50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 9 55 74 217 355
D-Manufacturing 233 557 629 6,631 8,050
E-Electricity, gas and water supply 32 31 19 30 112
F-Construction 107 829 735 2,749 4,420
G-Wholesale and retail trade 48 422 999 41,060 42,529
H-Hotels and restaurants 16 69 299 11,657 12,041
I-Transport, storage and communication 41 107 241 7,780 8,169
J-Financial intermediation 28 16 48 228 320
K-Real estate, renting and business
activities
55 186 241 3,815 4,297
M-Education 72 64 101 486 723
N-Health and social work 100 318 144 1,212 1,774
O-Other community, social and personal
service
52 139 184 3,586 3,961
Total 793 2,793 3,714 79,451 86,751
Source INSTAT
The selected enterprises in the table above were considered to represent best the overall population of
off- grid power plants in Albania, by application of the working assumption that each active enterprise at
least possesses on off-grid power plant.
Step 1.4: Establish the survey design and management scheme (applicable if a survey is used)
Document transparently the design and methodology of the survey, following best practices in survey
design and statistics. In doing so, the following guidance shall be applied:
The institution conducting the survey should have relevant experience with undertaking surveys;
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The whole off-grid study was conducted by the local consultant VeVe Group and local statistic
experts from the University of Tirana. For Quality Assurance (QA) reasons the whole statistical
survey was accompanied by the Austrian statistic expert Univ. Prof. Dr. Marcus Hudec (DATA
TECHNOLOGY Betriebsberatungs GmbH & Co KG) in order to comply with international
statistical standards and UNFCCC requirements.
Ensure a proper stratification within the geographical area of the electricity system and within
the different users of off-grid power generation (e.g. considering relevant differences between
sectors, household income, etc). To this end, it may be necessary to conduct a pre-survey to
collect information which sectors, companies or households typically use off-grid power plants;
See described stratification in Step 1.3 of above.
Sampling frame and Sampling units
Since the survey is a probability survey, for construction of the sample the existence of a
sampling frame was required. The sampling frame is the list/population (sampling units) from
which the samples will be drawn, it's (almost) never exactly equal to the target population.
In order to get a representative sampling the Business Register is used as sampling frame, which
is created and maintained by INSTAT (Institute of official statistics in Albania). The New
Business Register constitutes all non-agricultural active enterprises (public and private
enterprises and also public institutions) operating within the territory of Albania.
For the underlying survey conducted, the Business Register was considered the best registry for
economic enterprises in Albania.
The Business Register contains required information regarding:
Identification of enterprises as: identification code (NIPT), legal form, ownership,
name, address, contact details (phone, fax etc.)
Stratification variable as: main economic activity, size according number of
employees, geographic location
Demographic variable as: the date of foundation and the date of activity closure.
These variables are updated periodically by different INSTAT activities like: The activity status
(active or non-active), main economic activity, size according to employees, addresses, contact
details; phone, fax, mobile, e-mail). The economic activity of companies is based on the
Economic Activity Nomenclature, NACE Rev 1.1.
The sources for updating these variables are administrative registers or/and statistical survey.
Among administrative source there are: QKR (National Registering Center), DPT (General Tax
Office), file (card index) of VAT, annual account of enterprises, etc.
Among the statistical sources the following can be mentioned: Newly Created Enterprises
survey, Annual Structure Survey (ASN), quarterly survey (STS), Production Price survey (PPI),
and other surveys.
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The use of the Business Register was considered to be the most appropriate source for off-grid
survey usage since it minimizes the coverage errors.
Additionally, see also description of the stratification in Step 1.3 of above.
The results of the survey should be used to derive global estimates adjusted for their uncertainty
at a 95% confidence level in a conservative manner (using the upper or lower uncertainty bound
whatever is conservative);
In order to stay conservative the lower levels (according to the uncertainty at a 95% confidence
level as required in Annex 2 of the “Tool” of the finally extrapolated amounts of the off-grid
electricity generation of the identified UNFCCC classes were considered in the calculation of the
Combined Margin (CM) emission factor.
The methods used to collect data should strive to avoid any bias and should ensure random
sampling in the various strata;
By application of the sampling frame described above under Steps 1.3 and 1.4 any bias in data
collection is avoided.
The actual drawing of the random sample according to the details of the sampling scheme has
been performed within INSTAT applying a systematic random sampling scheme within strata.
Provide objective and transparent methods for data collection;
The data collection was done according to the following procedure:
Survey instrument
A first draft questionnaire according to the requirements of Annex 2 of the “Tool” was prepared
in October 2010. The VeVe team in collaboration with the Austrian experts have reviewed the
drafts and provided comments on the selection of questions. So the final questionnaire was
improved several times in order to correspond to the requirements of the UNFCCC.
Questionnaire Content
The questionnaire is organized in different sections:
Identifying questions: This group is composed by Id Questionnaire, Response Indicator,
Address of the enterprises and Characteristics of enterprises
The characteristics of every off-grid power plants disposable at the enterprise
The data regarding the usage of off-grid power plants in the years 2007 and 2008
Additionally the maintenance manner of off-grid-power plants was surveyed as well.
Pilot survey
The first draft of the questionnaire was tested through a pilot survey in 10 enterprises, including a
government institution (Ministry of Finance). The pilot test survey has been conducted from the
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well trained and experienced interviewers (enumerators) and it was monitored by the VeVe team.
The results of the pilot survey served for improvement of the questionnaires.
Interviewer recruiting and training
The field survey was conducted by 85 interviewers in total. 40 interviewers were employed in the
Tirana district and 45 interviewers for the field work in all the other Albanian districts. The
distribution was based on the number of the questionnaires per districts. (A training list of all the
interviewers can be provided by VeVe on request).
In total four supervisors for the supervising the field survey were hired. The interviewers and the
supervisors have been selected in close collaboration with INSTAT. The supervisors previously
have worked in other INSTAT surveys.
The interviewers and supervisor recruitment was done by INSTAT based on the criteria normally
applied for other enterprise surveys. As former INSTAT employees for the enterprises census all
the interviewers have previous experience in doing statistical surveys. Thus, the interviewers
know the enterprises (location; addresses...), which simplified the field survey and raised the
amount of filled out questionnaires.
In order to be familiar with the questionnaire and the manner it should be filled, the VeVe team
has organized training sessions before start of the field work. The training has been organized in
2 different sessions, one day each. The interviewers were divided in 2 groups. The first group
composed by the Tirana interviewers and the second session has included the rest of interviewers
from other districts. The training session was realized by the project team in collaboration with
INSTAT specialists.
The training laid a focus on the following 3 issues:
First issue: Gaining more knowledge regarding the survey and the questionnaire. During this
period the interviewers got information regarding the reasons for the survey and every question
in the questionnaire. Every interviewer got additional (explanatory) information to every single
question of the questionnaire.
Second issue: Role plays were done how to fill the questionnaire. After the interviewers were
familiar with the questions, the second period was an interactive communication (under the
supervision of VeVe staff), where the interviewers played the role of interviewers and the
respondents.
Third issue: The practice how to fill the questionnaires was discussed.
Field work
Collection of filled questionnaires has been done in every Albanian district. In average every
interviewer had to fill approx. 40 questionnaires during a period of 3 weeks, so they had to fill in
average 3 questionnaires per day.
The field survey has started by training interviewers on 26th January 2011 and lasted
approximately one month. Every Monday VeVe got in touch with the interviewers to get
feedback regarding the progress of the survey and the occurred problems during the survey.
The most frequent questions raised have been:
Missing the data label on the off-grid power plant
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Net Caloric Values figures of the fuels were not known by all the respondents.
No info regarding the energy generated by the off grid power plants during a year could
be provided.
There have been some cases where the interviewers had problems to collect the requested data,
especially in the state institutions, because they have asked for an official letter from the
company conducting the survey (VeVe), but these problems could be solved subsequently.
Ensure that appropriate procedures for data verification are in place, including relevant quality
assurance and quality control methods.
All the survey data were collected first in paper format by filled questionnaires. Afterwards the
data entry process on PC had to be conducted in order to be further elaborated by the statistical
computer program SPSS.
Before recording, a qualitative check of all the questionnaires was done in order to be sure that
they were filled properly and also according to some other standard procedures to support the
data entry.
The data entry process was done in Excel because for some categorical data during the recording,
the Excel gives the possibility for data validation.
At a later stage the data have been transferred into SPSS (version 17) using the standard
procedures offered by SPSS.
Also in the SPSS software VeVe has done quality check, e.g. the data range control for
categorical data.
Both electronic data and the whole off- grid survey were provided to the Client
(VERBUND/EVN) and to the Austrian statistic expert Univ. Prof. Dr. Marcus Hudec (DATA
TECHNOLOGY Betriebsberatungs GmbH & Co KG) for Quality Assurance (QA) and further
Quality Control (QC) in the following way:
Transparent documentation of all procedures and methods applied during the whole process
from the planning phase to the calculation of final results
SPSS – Syntax Files, which provide the documentation of all data transformation and
calculation steps
SPSS – System Files, which contain all data necessary for the examination of the derived
results and allows the reproduction of the results by an IE
DATA TECHNOLOGY Betriebsberatungs GmbH & Co KG conducted parallel a calculation
(extrapolation) of the provided SPSS data in and received the same results as VeVe.
The DOE should carefully evaluate and confirm that the survey was conducted in accordance with these
principles and best practices for conducting and evaluating surveys.
Step 1.5: Collect the data or use existing data sources
Collect the data or use relevant existing data sources. Exclude all plants for the sample for which not all
necessary data (as identified in Step 1.1 of this annex) could be collected.
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The following data were collected during the field survey:
Sample size
At the beginning of the survey a sample size of approx. 3,000 to 3,500 enterprises was considered
sufficient.
Sample allocation
With the chosen stratification, a proportional allocation was not practicable because of the very different
number of enterprises in the strata. Therefore for the sample allocation a disproportionate allocation was
chosen. Thus the number of enterprises in the strata is different.
The decision regarding the selection rate was:
All the companies having over 50 employees were selected.
14% of the companies having between 10 to 49 employees were selected.
9% of the companies having between 4 to 9 employees were selected.
2% of the small companies having between 1 to 4 employees were selected.
In practical terms not a strict proportion was applied but a minimum cell size in each stratum was
determined. A minimum sample size of 7 enterprises in each stratum was determined.
Assuming that the most important enterprises, so-called VIP enterprises, have been and still are
important users of off- grid power plants in periods of power cuts, the establishment of a specific stratum
for those enterprises was proposed. The stratum for the VIP enterprises includes enterprises that were
randomly selected under the first selection process and those that remained unselected at the beginning
and being selected after the first selection process subsequently.
Based on the Business Register of INSTAT it was possible to identify all the VIP enterprises at a later
stage of surveying. In total 274 VIP enterprises were sampled during the main sampling and 455 VIP
companies were sampled in a second step of the field survey. Thus in total 729 VIP companies were
surveyed (see also tables below).
Sample selection
The sample selection was conducted in two steps: (i) the selection of main sample (including the
randomly sampled VIP companies and (ii) the sampling of the missing identified VIP companies. The
process of sampling is shown graphically in Figure 1-1.
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In a first step, a sample of 3,121 enterprises was selected in an independent manner for all strata,
through usage of a systematic selection (see following table 1-2). This sampling is considered the main
sampling structure. In each stratum the samples are sorted according to districts to avoid a possible bias
due to non representative sampling-proportions from different regions.
Table 1-2. The structure of Main sampling (including VIP-enterprises and non-VIP-enterprises)
Economic Activity (NACE Section)
Size of company
50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 9 8 7 7 31
D-Manufacturing 233 77 56 132 498
E-Electricity, gas and water supply 32 7 7 7 53
F-Construction 107 116 66 54 343
G-Wholesale and retail trade 48 59 89 821 1,017
H-Hotels and restaurants 16 9 26 233 284
I-Transport, storage and
communication
41 14 21 155 231
J-Financial intermediation 28 7 7 7 49
K-Real estate, renting and business
activities
55 26 21 76 178
M-Education 72 9 9 9 99
N-Health and social work 100 44 12 24 180
O-Other community, social and
personal service
52 19 16 71 158
Total 793 395 337 1,596 3,121
At a second step, a new stratum (stratum 49) was created (inclusion of VIP companies from the main
sampling and VIP enterprises, which remained unselected in the first step (see table 1-4).
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Table 1-3: The distribution of VIP-enterprises to the strata within the main sample
Economic Activity (NACE Section)
Size of enterprises
50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 4 1 1 0 6
D-Manufacturing 50 5 0 0 55
E-Electricity, gas and water supply 5 0 0 0 5
F-Construction 55 15 0 1 71
G-Wholesale and retail trade 39 19 0 1 59
H-Hotels and restaurants 6 0 0 0 6
I-Transport, storage and
communication 19 1 1 0 21
J-Financial intermediation 25 1 0 0 26
K-Real estate, renting and business
activities 4 1 3 0 8
M-Education 1 0 0 0 1
N-Health and social work 2 0 0 0 2
O-Other community, social and
personal service 14 0 0 0 14
Total 224 43 5 2 274
Table 1-4: The structure of Strata 49, composed only by VIP-enterprise, not selected in the main sample
Economic Activity (NACE Section)
Size of enterprises 50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 0 5 0 1 6
D-Manufacturing 0 47 4 2 53
E-Electricity, gas and water supply 0 0 2 0 2
F-Construction 0 83 14 5 102
G-Wholesale and retail trade 0 168 48 20 236
H-Hotels and restaurants 0 2 0 0 2
I-Transport, storage and
communication
0 9 1 2 12
J-Financial intermediation 0 2 2 1 5
K-Real estate, renting and business
activities
0 15 5 10 30
M-Education 0 3 0 0 3
N-Health and social work 0 0 0 0 0
O-Other community, social and
personal service
0 4 0 0 4
Total 0 338 76 41 455
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Note: Step 1 and 2 has been conducted by INSTAT according to technical specification of VeVe Group,
because INSTAT doesn‟t make available to third parties any sampling frame.
At a third step, VeVe has reallocated all VIP-enterprises in one unique stratum (Stratum 49). Thus,
regarding the VIP-enterprises a census was reached with a selection probability of 1, independently of
the structure of the stratum.
In the main sampling 3,121 enterprises (including 274 VIP enterprises) were surveyed with the structure
presented in the table 1-3.
By analysis of the information provided in Tables 1-2, 1-3 and 1-4 a reallocation was done for non-VIP
enterprises in Table 1-5.
Table 1-5. The distribution of non-VIP-enterprises in Final sample (48 strata)
Economic Activity (NACE Section)
Size of enterprises
50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 5 7 6 7 25
D-Manufacturing 183 72 56 132 443
E-Electricity, gas and water supply 27 7 7 7 48
F-Construction 52 101 66 53 272
G-Wholesale and retail trade 9 40 89 820 958
H-Hotels and restaurants 10 9 26 233 278
I-Transport, storage and
communication 22 13 20 155 210
J-Financial intermediation 3 6 7 7 23
K-Real estate, renting and business
activities 51 25 18 76 170
M-Education 71 9 9 9 98
N-Health and social work 98 44 12 24 178
O-Other community, social and
personal service 38 19 16 71 144
Total 569 352 332 1,594 2,847
Table 1-6 shows the distribution of VIP enterprises according to size and activity (only for the stratum
49).
Table 1-6. The final distribution of VIP-enterprises by economic activity and size
Economic Activity (NACE Section)
Size of enterprises
50+
employees
10-49
employees
4-9
employees
1-4
employees
Total
C-Mining and quarrying 4 6 1 1 12
D-Manufacturing 50 52 4 2 108
E-Electricity, gas and water supply 5 0 2 0 7
F-Construction 55 98 14 6 173
G-Wholesale and retail trade 39 187 48 21 295
H-Hotels and restaurants 6 2 0 0 8
I-Transport, storage and
communication 19 10 2 2 33
J-Financial intermediation 25 3 2 1 31
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K-Real estate, renting and business
activities 4 16 8 10 38
M-Education 1 3 0 0 4
N-Health and social work 2 0 0 0 2
O-Other community, social and
personal service 14 4 0 0 18
Total 224 381 81 43 729
In a further step of surveying additionally 60 off- grid power plants were surveyed within 50 enterprises
(already covered during the survey. These off-grid power plants were taken into account subsequently.
Thus in total 3,636 (2,847 + 729 + 60) questionnaires were collected and data were taken into account.
For the extrapolation (determination of the extrapolation weights) the numbers of VIP companies were
deducted from the numbers of companies of the different strata representing the overall population. By
doing this the overall population is divided in a VIP and a non VIP part.
Step 2: Exclude plants that do not qualify as off-grid power plants
The exclusion of the enterprises, which do not possess an off- grid power plant, was done in the
following manner.
Referring to the question Q5 (Do you use an off grid power plant?) 1247 enterprises sampled do not use
off- grid power plants (see following table below). These samples were considered in the extrapolation as
follows:
No reduction of the number of samples for the calculation of the weights
No reduction of the size of the overall population (strata sizes remain unchanged)
the corresponding electricity generation value of these off grid plants was determined with
0 MWh.
The other non applicable samples (answering was refused at 97 companies; 274 companies surveyed in
2011 have already quit their activity; 147 companies were not found on the addresses provided by
INSTAT (97 + 274 + 147 = 518)).
These samples were considered in the extrapolation as follows:
Reduction of the number of samples for the calculation of the weights
No reduction of the size of the overall population (strata sizes remain unchanged)
Distribution of enterprises using of off-grid power plants
Q5. Do you use an off grid power
plant?
Frequency Percent
No 1,247 34.3
Yes 1,811 (+ 60) = 1,871 51.5
NA (Refused 97; Closed Activity
274; Not found 147)
518 14.2
Total 3,636 100.0
Exclusion of plants, not used during the year 2007
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Referring to the question Q15 (When you have started to use the off grid power plant?) 109 plants have
started the operation of the off- grid plant only in the year 2008. Thus these questionnaires were excluded
in the database for the year 2007.
After this exclusion 1,871- 109 = 1,762 questionnaires (= off- grid power plants) were eligible and
delivered values for electricity generated in the year 2007.
This step aims to exclude those power plants from the sample or other data source which cannot be
considered as off-grid power plants according to the definition provided above. To this end, exclude
those plants from the sample or other source of information for which one of the three following
conditions is not met:
GRIDp = true;
SWITCHp = true;
Whenever the grid is reliable and stable, the consumers purchase electricity only from the grid
and the off-grid power plant is not operating. This can be demonstrated in one of the following
ways:
(a) OMCp,y > TEL,p,y; or
(b) Log book data on the hours of operation of the off-grid power plant p and the quality and
availability of grid supply clearly shows that the plant only operated when the grid was not
reliable and stable; or
(c) Demonstrate that OMC > TEL once for all off-grid power plants included in a class of
offgrid power plants and a sector by showing that this condition generally applies to all
plants in the class and sector, e.g. using the fuel costs (e.g. official statistics or projections
on fuel prices), the efficiency of the plants in that class (e.g. using typical the default
efficiencies provided in Annex 1) and relevant information on electricity purchase costs in
the sector (e.g. statistics on electricity prices).
Exclusion of the plants, which are supplying the equipments not connected to the grid power
(GRIDp = true/false)
Through the question Q22 (Are all parts (electricity consumer equipment) of your company supplied by
the electricity grid?), it was possible to identify off- grid plants without a connection to the national grid
power system. There were 4 cases, which have to be excluded from the database because they are
supplying some equipment not connected to the grid power system.
Thus 1758 questionnaires are eligible under the off- grid survey and are considered for determination of
the extrapolation weights.
Exclusion of plants which are not able to switch from grid to off- grid and from off- grid to grid
(SWITCHp = true/false)
The plants which are not able to switch from grid to off- grid and from off- grid to the grid are easily
identified through the question Q23 (Can the company switch from grid to off-grid and from off-grid to
grid?). Based on this condition, all the remaining off- grid plants were eligible. Thus, no other off- grid
plant was excluded from the database.
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Proof that whenever the grid power system will be stable and reliable the consumers switch to the
grid power system because of lower cost.
The proof was conducted according to approach (c) of Step 2 of Annex 2 of the “Tool” in the following
manner:
1. In every questionnaire the tariff class (TEL) is given (€/kWhel) from the grid (see table about
tariffs in Albania below) (1 € = 140 LEK; 11 LEK/ kWh = 7.9c€/kWh).
2. default of the off- grid power plant (see default values for efficiencies according to Annex 1 of the
“Tool”
3. 1/default (kWh(PEC)/kWhel generated)
4. Conversion from kWh Primary Energy Content (PEC) into liters of fuel (l) by use of NCV of the
different fuels
5. Costs of Fuel in (€/l)
6. Calculation of specific costs of off- grid electricity (OMC) by multiplication of 4. with 5.
(€/kWhel)
7. Comparison of OMC (6.) and TEL (1.): OMC has to be higher than TEL
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CAP < 10 10 < CAP < 50 50 < CAP < 100 100 < CAP < 200 200 < CAP < 400 400 < CAP < 1000 CAP > 1000
default 0.28 0.33 0.35 0.37 0.39 0.42 0.45
1/default 3.57 3.03 2.86 2.70 2.56 2.38 2.22 kWh/kWhel
NCV Diesel
(lower value) 41.4 41.4 41.4 41.4 41.4 41.4 41.4 MJ/kg
Density 0.83 0.83 0.83 0.83 0.83 0.83 0.83 kg/l
34.362 34.362 34.362 34.362 34.362 34.362 34.362 MJ/l
9.55 9.55 9.55 9.55 9.55 9.55 9.55 kWh/l
needed Diesel
for 1 kWhel 0.37 0.32 0.30 0.28 0.27 0.25 0.23 [l]
Cost per l Diesel
*€/l+ (2007) 0.9 0.9 0.9 0.9 0.9 0.9 0.9 *€/l+
Costs per kWhel
*€/kWhel] 0.34 0.29 0.27 0.25 0.24 0.22 0.21 *€/kWhel]
Nominal capacity of off grid power plants in [kW]
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CAP < 10 10 < CAP < 50 50 < CAP < 100 100 < CAP < 200 200 < CAP < 400 400 < CAP < 1000 CAP > 1000
default 0.28 0.33 0.35 0.37 0.39 0.42 0.45
1/default 3.57 3.03 2.86 2.70 2.56 2.38 2.22 kWh/kWhel
NCV Gasoline 44.3 44.3 44.3 44.3 44.3 44.3 44.3 MJ/kg
Density 0.72 0.72 0.72 0.72 0.72 0.72 0.72 kg/l
31.896 31.896 31.896 31.896 31.896 31.896 31.896 MJ/l
8.86 8.86 8.86 8.86 8.86 8.86 8.86 kWh/l
needed gasoline
for 1 kWhel 0.40 0.34 0.32 0.31 0.29 0.27 0.25 [l]
Cost per l gasoline
*€/l+ (2007) 0.9 0.9 0.9 0.9 0.9 0.9 0.9 *€/l+
Costs per kWhel
*€/kWhel] 0.36 0.31 0.29 0.27 0.26 0.24 0.23 *€/kWhel]
Nominal capacity of off grid power plants in [kW]
The calculations summarized in the tables above show that OMCp,y > TEL,p,y for all the off-grid power
plants even if only the fuel costs are taken into consideration in order to be conservative. Thus no off-
grid power plant had to be excluded based on this condition.
At the end of the exclusion process the database composed of 1,762 – 4 = 1,758 eligible off- grid plants.
Step 3: Aggregate data according to classes of off-grid power plants
In the case of direct use of the data on a plant-by-plant basis (Option a in the introduction to Step 1),
allocate the collected data to the classes of off-grid power plants.
The electricity generation of the directly sampled off grid power plants in the year 2007 amounts to
174,000 MWh. The sum of the capacities of all the sampled off- grid power plants amounts to 239 MW.
These figures are just given for illustration. In the underlying off- grid study a statistical extrapolation for
the total population was performed (see following clause below).
In the case of a statistical evaluation of the data based on sampling (Option b in the introduction to Step
1), allocate the collected data to the applicable stratum. Use the results of the survey to derive global
estimates for the total population, for each class of off-grid power plants m, adjusting conservatively for
the uncertainty at a 95% confidence level.98
The extrapolation is done on strata level according to the procedure summarized in the following table:
Extrapolation weights for the 49 determined strata of the overall population
98 Note that this should not include power plants which did not qualify as off-grid following the procedures in Step 2.
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Population Sample Initial Non- Do not True
Strata Size Size Weight Contact qualify Sample Weight1 Dega = C And Size = 1 1 5 5 1.0000 0 0 0 1 4 1.25002 Dega = D And Size = 1 2 183 183 1.0000 3 20 8 0 152 1.20393 Dega = E And Size = 1 3 27 27 1.0000 0 1 1 0 25 1.08004 Dega = F And Size = 1 4 52 52 1.0000 1 4 2 0 45 1.15565 Dega = G And Size = 1 5 9 9 1.0000 0 1 1 0 7 1.28576 Dega = H And Size = 1 6 10 10 1.0000 1 1 0 0 8 1.25007 Dega = I And Size = 1 7 22 22 1.0000 1 1 1 0 19 1.15798 Dega = J And Size = 1 8 3 3 1.0000 1 0 1 0 1 3.00009 Dega = K And Size = 1 9 51 51 1.0000 1 7 1 0 42 1.214310 Dega = M And Size = 1 10 71 71 1.0000 1 10 1 0 59 1.203411 Dega = N And Size = 1 11 98 98 1.0000 1 3 0 0 94 1.042612 Dega = O And Size = 1 12 38 38 1.0000 2 3 0 0 33 1.151513 Dega = C And Size = 2 13 49 7 7.0000 0 0 0 0 7 7.000014 Dega = D And Size = 2 14 505 72 7.0139 2 4 4 0 62 8.145215 Dega = E And Size = 2 15 31 7 4.4286 0 0 1 0 6 5.166716 Dega = F And Size = 2 16 731 101 7.2376 1 4 8 0 88 8.306817 Dega = G And Size = 2 17 235 40 5.8750 1 0 0 0 39 6.025618 Dega = H And Size = 2 18 67 9 7.4444 0 1 0 0 8 8.375019 Dega = I And Size = 2 19 97 13 7.4615 0 0 0 0 13 7.461520 Dega = J And Size = 2 20 13 6 2.1667 0 0 0 0 6 2.166721 Dega = K And Size = 2 21 170 25 6.8000 0 1 1 0 23 7.391322 Dega = M And Size = 2 22 61 9 6.7778 0 1 0 0 8 7.625023 Dega = N And Size = 2 23 318 44 7.2273 0 0 1 0 43 7.395324 Dega = O And Size = 2 24 135 19 7.1053 1 4 0 0 14 9.642925 Dega = C And Size =3 25 73 6 12.1667 0 1 0 0 5 14.600026 Dega = D And Size = 3 26 625 56 11.1607 0 4 0 0 52 12.019227 Dega = E And Size = 3 27 17 7 2.4286 0 2 0 0 5 3.400028 Dega = F And Size = 3 28 721 66 10.9242 1 2 7 0 56 12.875029 Dega = G And Size = 3 29 951 89 10.6854 2 7 3 0 77 12.350630 Dega = H And Size = 3 30 299 26 11.5000 1 4 0 0 21 14.238131 Dega = I And Size = 3 31 239 20 11.9500 0 0 2 0 18 13.277832 Dega = J And Size = 3 32 46 7 6.5714 1 0 1 0 5 9.200033 Dega = K And Size = 3 33 233 18 12.9444 1 0 3 0 14 16.642934 Dega = M And Size = 3 34 101 9 11.2222 0 1 0 0 8 12.625035 Dega = N And Size = 3 35 144 12 12.0000 0 0 0 0 12 12.000036 Dega = O And Size = 3 36 184 16 11.5000 0 1 1 0 14 13.142937 Dega = C And Size = 4 37 216 7 30.8571 0 1 0 0 6 36.000038 Dega = D And Size = 4 38 6,629 132 50.2197 0 14 6 0 112 59.187539 Dega = E And Size = 4 39 30 7 4.2857 0 2 0 0 5 6.000040 Dega = F And Size = 4 40 2,743 53 51.7547 0 7 3 0 43 63.790741 Dega = G And Size = 4 41 41,039 820 50.0476 6 77 35 0 702 58.460142 Dega = H And Size = 4 42 11,657 233 50.0300 4 16 7 0 206 56.587443 Dega = I And Size = 4 43 7,778 155 50.1806 3 10 4 0 138 56.362344 Dega = J And Size = 4 44 227 7 32.4286 0 1 0 0 6 37.833345 Dega = K And Size = 4 45 3,805 76 50.0658 3 6 5 0 62 61.371046 Dega = M And Size = 4 46 486 9 54.0000 0 0 0 0 9 54.000047 Dega = N And Size = 4 47 1,212 24 50.5000 1 5 1 0 17 71.294148 Dega = O And Size = 4 48 3,586 71 50.5070 2 10 5 0 54 66.407449 Strata VIP 49 729 729 1.0000 55 37 33 1 603 1.2090
Total 86,751 3,576 739.4687 97 274 147 2 3056 875.5711
Strata Refused Closed
Since the estimation of the variances was not satisfying a reasonable strategy to improve the estimation
of variances is the collapsing of strata with few observations only. The collapsing was applied to the 4
economic sectors with least number of companies according to the scheme determined in the following
table.
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Number of eligible NON-VIP Companies in the Sample
50+
employees
10-49
employees
5 - 9
employees
1 - 4
employees
Mining and
quarrying
2 1 1 2 6
Manufacturing 141 49 38 70 298
Electricity, gas and
water supply
14 1 1 4 20
Construction 33 48 29 13 123
Wholesale and
retail trade
5 25 45 284 359
Hotels and
restaurants
6 5 14 131 156
Transport, storage
and communication
11 6 4 18 39
Financial
intermediation
0 6 2 1 9
Real estate, renting
and business
activities
23 11 9 26 69
Education 30 1 4 3 38
Health and social
work
65 8 5 11 89
Other community,
social and personal
service activities
14 10 10 34 68
344 171 162 597 1274Total
Size of company
total
Section of
Economic
Activity
Due to the collapsing of strata the weights had to be recalculated as for the collapsed strata extrapolation
is based on the total economic sector irrespective of the size of the company. The result of this
recalculation is summarized in the following table.
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Population Sample Initial Non- Do not True
Strata Size Size Weight Contact qualify Sample Weight1 Dega = C And Size = 1 1 343 25 13.7200 0 2 0 1 22 15.59092 Dega = D And Size = 1 2 183 183 1.0000 3 20 8 0 152 1.20393 Dega = E And Size = 1 3 105 48 2.1875 0 5 2 0 41 2.56104 Dega = F And Size = 1 4 52 52 1.0000 1 4 2 0 45 1.15565 Dega = G And Size = 1 5 9 9 1.0000 0 1 1 0 7 1.28576 Dega = H And Size = 1 6 10 10 1.0000 1 1 0 0 8 1.25007 Dega = I And Size = 1 7 22 22 1.0000 1 1 1 0 19 1.15798 Dega = J And Size = 1 8 289 23 12.5652 2 1 2 0 18 16.05569 Dega = K And Size = 1 9 51 51 1.0000 1 7 1 0 42 1.214310 Dega = M And Size = 1 10 719 98 7.3367 1 12 1 0 84 8.559511 Dega = N And Size = 1 11 98 98 1.0000 1 3 0 0 94 1.042612 Dega = O And Size = 1 12 38 38 1.0000 2 3 0 0 33 1.151513 Dega = C And Size = 2
14 Dega = D And Size = 2 14 505 72 7.0139 2 4 4 0 62 8.145215 Dega = E And Size = 2
16 Dega = F And Size = 2 16 731 101 7.2376 1 4 8 0 88 8.306817 Dega = G And Size = 2 17 235 40 5.8750 1 0 0 0 39 6.025618 Dega = H And Size = 2 18 67 9 7.4444 0 1 0 0 8 8.375019 Dega = I And Size = 2 19 97 13 7.4615 0 0 0 0 13 7.461520 Dega = J And Size = 2
21 Dega = K And Size = 2 21 170 25 6.8000 0 1 1 0 23 7.391322 Dega = M And Size = 2
23 Dega = N And Size = 2 23 318 44 7.2273 0 0 1 0 43 7.395324 Dega = O And Size = 2 24 135 19 7.1053 1 4 0 0 14 9.642925 Dega = C And Size =3
26 Dega = D And Size = 3 26 625 56 11.1607 0 4 0 0 52 12.019227 Dega = E And Size = 3
28 Dega = F And Size = 3 28 721 66 10.9242 1 2 7 0 56 12.875029 Dega = G And Size = 3 29 951 89 10.6854 2 7 3 0 77 12.350630 Dega = H And Size = 3 30 299 26 11.5000 1 4 0 0 21 14.238131 Dega = I And Size = 3 31 239 20 11.9500 0 0 2 0 18 13.277832 Dega = J And Size = 3
33 Dega = K And Size = 3 33 233 18 12.9444 1 0 3 0 14 16.642934 Dega = M And Size = 3
35 Dega = N And Size = 3 35 144 12 12.0000 0 0 0 0 12 12.000036 Dega = O And Size = 3 36 184 16 11.5000 0 1 1 0 14 13.142937 Dega = C And Size = 4
38 Dega = D And Size = 4 38 6,629 132 50.2197 0 14 6 0 112 59.187539 Dega = E And Size = 4
40 Dega = F And Size = 4 40 2,743 53 51.7547 0 7 3 0 43 63.790741 Dega = G And Size = 4 41 41,039 820 50.0476 6 77 35 0 702 58.460142 Dega = H And Size = 4 42 11,657 233 50.0300 4 16 7 0 206 56.587443 Dega = I And Size = 4 43 7,778 155 50.1806 3 10 4 0 138 56.362344 Dega = J And Size = 4
45 Dega = K And Size = 4 45 3,805 76 50.0658 3 6 5 0 62 61.371046 Dega = M And Size = 4
47 Dega = N And Size = 4 47 1,212 24 50.5000 1 5 1 0 17 71.294148 Dega = O And Size = 4 48 3,586 71 50.5070 2 10 5 0 54 66.407449 Strata VIP 49 729 729 1.0000 55 37 33 1 603 1.2090
Total 86,751 3,576 596.9448 97 274 147 2 3056 716.1880
Strata Refused Closed
The 1,758 eligible off-grid plants were allocated to the different UNFCCC classes defined under Step 1.2
of Annex 2 of the “Tool”.
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The general Hansen-Hurwitz estimation principle has been applied for the extrapolation of the sampled
data. For the calculation of the confidence intervals for UNFCC-Classes the estimation had to be applied
to each UNFCC-Class separately, leading to domain estimation which was applied. In fact this means
only observations belonging to the UNFCC-Class contribute in this case to estimation (see SPSS
documentation for details and formulas).
The results of the survey were used to derive global estimates for the total population, for each class of
off-grid power plants m, adjusting conservatively for the uncertainty at a 95% confidence level. The
results are summarized in the following table.
Energy produced from the off grid power plants within the determined 23 UNFCCC classes
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Lower Level Upper Level
Class 1 : Cap=1, Tech=1,
Fuel=D, Age=138,313 2,950 32,527 44,099 282
Class 2 : Cap=1, Tech=1,
Fuel=D, Age=29,963 1,700 6,629 13,298 79
Class 3 : Cap=1, Tech=1,
Fuel=D, Age=31,113 657 0 2,402 7
Class 4 : Cap=1, Tech=1,
Fuel=G, Age=119,636 3,316 13,131 26,141 197
Class 5 : Cap=1, Tech=1,
Fuel=G, Age=22,478 720 1,066 3,891 34
Class 6 : Cap=1, Tech=1,
Fuel=G, Age=31,539 534 493 2,586 14
Class 7 : Cap=2, Tech=1,
Fuel=D, Age=1203,883 16,522 171,478 236,287 392
Class 8 : Cap=2, Tech=1,
Fuel=D, Age=247,732 7,853 32,329 63,135 133
Class 9 : Cap=2, Tech=1,
Fuel=D, Age=35,500 2,448 700 10,301 24
Class 13 : Cap=3, Tech=1,
Fuel=D, Age=18,644 2,664 3,419 13,869 87
Class 14 : Cap=3, Tech=1,
Fuel=D, Age=23,338 774 1,820 4,856 50
Class 15 : Cap=3, Tech=1,
Fuel=D, Age=32,072 933 242 3,901 18
Class 19 : Cap=4, Tech=1,
Fuel=D, Age=135,931 5,448 25,247 46,615 120
Class 20 : Cap=4, Tech=1,
Fuel=D, Age=219,996 5,032 10,126 29,866 58
Class 21 : Cap=4, Tech=1,
Fuel=D, Age=32,594 1,197 247 4,942 10
Class 25 : Cap=5, Tech=1,
Fuel=D, Age=147,654 9,333 29,349 65,958 62
Class 26 : Cap=5, Tech=1,
Fuel=D, Age=223,052 7,241 8,849 37,255 34
Class 27 : Cap=5, Tech=1,
Fuel=D, Age=32,611 481 1,668 3,554 15
Class 31 : Cap=6, Tech=1,
Fuel=D, Age=1106,646 19,735 67,940 145,352 61
Class 32 : Cap=6, Tech=1,
Fuel=D, Age=234,497 10,335 14,227 54,766 32
Class 33 : Cap=6, Tech=1,
Fuel=D, Age=315,640 7,051 1,811 29,469 9
Class 37 : Cap=7, Tech=1,
Fuel=D, Age=196,181 35,544 26,466 165,896 19
Class 38 : Cap=7, Tech=1,
Fuel=D, Age=250,580 14,091 22,944 78,217 21
779,594 156,557 472,708 1,086,656 1758.0
Energy produced from off- grid power plants for the year 2007 in (MWh)
EstimationStandard
deviation
95%-Confidence intervall Unweighted
amount of
samples
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Step 4: Assess the extent of off-grid power
The effects of feeding additional electricity to the grid or saving electricity demand on off-grid power
plants connected to the system are associated with significant uncertainty. For this reason, a significant
amount of off-grid power should exist to include these plants in the grid emission factor.
The inclusion of off-grid power plants in the grid emission factor is only allowed if one of the following
two conditions are met:
The total capacity of off-grid power plants (in MW) is at least 10% of the total capacity of grid
power plants in the electricity system; or
The total power generation by off-grid power plants (in MWh) is at least 10% of the total power
generation by grid power plants in the electricity system.
If one of these conditions are not met, then off-grid power plants cannot be included in the calculation of
the grid emission factor of the electricity system. Otherwise, proceed to next step.
There is an inconsistence in the underlined sections from above, which was not solved in the revised
“Tool to calculate the emission factor for an electricity system (Version 02.1.0)”.
The off- grid study for Albania was done for the year 2007. According to Step 3 of the “Tool” data from
one single calendar year within the 5 most recent calendar years prior to the time of submission of the
CDM-PDD for validation has to be used. 2007 is within this timeframe, thus this requirement is fulfilled.
The extrapolated off grid generation for the year 2007 amounted to approx. 472,708 MWh (lower level
of the confidence interval). This is equal to 16.3% of the total power generation of power plants
connected to the Albanian grid in the year 2007. The total power generation for the year 2007 amounted
to 2,892,974 MWh (inclusive thermal power; without imports).
Since the installed capacity of all (sampled) off-grid power plants in operation amounts to 239 MW,
which is equal to 15.7 % of the total installed capacity of 1,523 MW both above mentioned requirements
are met.
Step 5: Assess the reliability and stability of the grid and that this is primarily due to constraints in
generation, and not to other aspects such as transmission capacity
It has to be demonstrated that the grid to which project participants have access is not reliable and not
stable and that this is primarily due to constraints in generation and not due to other issues, such as
limited transmission capacity. To this end, it needs to be demonstrated that
Shortages, blinks, black-outs, load shedding and/or large variations in frequency and voltage
ranges are common practice in the grid operation. Supporting evidence describing the number,
duration and extent of events related to instability and unreliability of the grid has to be
provided based on project participants or third parties statistics or surveys; and
This situation is primarily due to constraints in generation, and not to other aspects such as
transmission capacity.
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The reliability and stability of the grid was discussed between VeVe and OST (KESH). It was
demonstrated that the instability of the grid is (was) primarily due to constraints in generation, and not to
other aspects such as transmission capacity (see attached Letter of OST) below.
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Annex 4
MONITORING INFORMATION
DEVOLL HPP - MONITORING PLAN 2020 to 2030
Purpose
The monitoring plan is designed to monitor the parameters listed in B.7.1 of the PDD, which are required
for calculation of the actual Certified Emission Reductions (CERs) achieved by the underlying project
activity.
The Project activity requires the monitoring of the following items:
a) Net electricity generation by the project activity
b) The surface areas of the reservoirs of the power plants when full.
c) Installed Capacity of the power plants
d) Net electricity imports to the project activity, if any
Ad a) The monitoring of the net electricity generation by the project activity is described in detail
below.
Ad b) The surface areas of the reservoirs at the full water level will be measured and calculated yearly
by using the design schematics and area maps. Photographs of the reservoir at several key
locations will be taken when the project becomes operational to check whether the actual
reservoir does not deviate substantially from the design.
Ad d) No electricity imports is envisaged at the current stage of project development.
Monitoring framework
Objective
The objective of the present monitoring plan is to assure the complete, consistent, clear, and accurate
monitoring and calculation of the emissions reductions, within the DEVOLL hydropower boundaries,
during the crediting period.
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Boundaries
The boundaries of the project activity will remain constant during the entire crediting period as defined
in Section B.3.
Equipment to be used
The electric energy meters record net energy generation fed to the national grid every hour and stores the
data accumulatively.
The electricity measurement devices are chosen according to the requirements determined in the electric
metering code of Albania.
Installation Point of the Electric energy metering equipment
The exact installation points of all the electricity meters are not fixed so far, but it should be done similar
to the procedure described as follows:
Net Electricity exports of each HPP will be recorded and aggregated monthly at the sub-station at
the end of the transmission line connecting the HPPs to the grid.
Monitoring of generation and consumption of electricity should be performed on-site by e.g. a
bidirectional electricity meter, together with monitoring of exports directly after transformation
up to 220kV, the voltage used by the grid for transmissions.
The project proponent will keep all relevant receipts for electricity sales. These receipts (or
photocopies) will be made available to the auditor at verification.
The on-site data can be used to back-up the generation data from the aforementioned sub-station.
Electricity Meter Calibration
Regular calibration will be necessary for the monitoring equipment. The necessary calibration will be
performed according to the manufacturer‟s guidelines, or according to the applicable regulations (e.g. the
Albanian electric metering code), by a suitably skilled technician at the required frequency (at least once
a year). A certificate of calibration will be provided for each piece of equipment after completion.
The output meters will be jointly sealed after calibration.
Operational and management structure for monitoring the project activity
The following figure below outlines the operational and management structure, which the project
developer will implement to monitor emission reductions and any leakage effects generated by the
project activity.
An operational team will be formed which will be responsible for monitoring of all the aforementioned
monitoring parameters. This team will compose of a DEVOLL Plant Manager and a group of DEVOLL
Plant Engineers, who will be in charge of the monitoring processes. The group of DEVOLL Plant
Engineers under the supervision of the DEVOLL Plant Manager will be assigned for monitoring of
different parameters on a timely basis and will perform the recording and archiving of data in an orderly
manner.
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Internal monitoring reports will be forwarded to and reviewed by the DEVOLL Plant Manager on a
monthly basis in order to ensure the project activity follows the requirements of the monitoring plan.
Training of the monitoring personnel
Personnel, who carry out the monitoring functions, are trained continuously. New personnel have to
follow up a training program and are formed in the specific skills required to carry out the Monitoring
Plan. The training contains CDM knowledge, operational regulations, quality control (QC), data
monitoring requirements and data management regulations, etc.
The DEVOLL plant manager carries out regular refresher trainings. Minutes are made by the Plant
Manager after every training course.
Measuring procedure
1. Measuring and recording frequency
The Plant Engineers read the meter monthly, report it in a spreadsheet (see tables below) and store the
data separately from the electronically saved data.
The meter readings and data discharge of the monitoring month takes place at the last day of every
month.
The DEVOLL plant manager controls and verifies the monthly aggregated data of all three power plants.
Moglice Hydropower Plant
Year
Month Monthly Generation (MWh)
January
February
March
DEVOLL Plant
Manager
MOGLICE Plant Engineers
KOKEL Plant Engineers
BANJA Plant Engineers
Data Archiving Data Archiving Data Archiving
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April
May
June
July
August
September
October
November
December
Total
Kokel Hydropower Plant
Year
Month Monthly Generation (MWh)
January
February
March
April
May
June
July
August
September
October
November
December
Total
Banja Hydropower Plant
Year
Month Monthly Generation (MWh)
January
February
March
April
May
June
July
August
September
October
November
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December
Total
2. Verification and Quality Control (QC) of the measurement
The measurements are done according to national or international standards (like the ELECTRIC
METERING CODE of Albania). Currently DHP still negotiates the transmission network connection and
electric energy injection agreement with OST. This agreement will fulfil all requirements determined in
the metering code.
The person in charge of monitoring will verify the accuracy of the recorded energy data in the hydro
power plant. Data will need to be compared against the information of the commercial measurements
published by (OST).
The commercial measurement of exported energy to the grid, is combined with DEVOLL hydropower
plant, and is validated monthly by (OST or DHP). DEVOLL hydropower energy measurement should be
(nearly) equal to the commercial measurement. If the measurements are not exactly equal the smaller
figures are used to stay on the conservative side.
The net electricity generation from Moglice; Kokel and Banja HPP is obtained from the data reported by
the Plant Engineers. If the electricity measurements are disproportionate to the jointly commercial
measurement, the person in charge of monitoring process has to investigate a possible damage in the
meters and report the non conformance.
At each HPP site at least one back up electricity meter has to be kept in reserve.
3. Calculation of the Certified Emission Reductions (CERs)
The person in charge of monitoring calculates the Certified Emissions Reductions (CERs) for each year
of the crediting period in a spreadsheet, where the Grid Emissions Factor (GEF) is determined ex ante
according to Section B.6.1. The spreadsheet used may looks as follows:
Calculation of the Certified Emission Reductions (CERs) for DEVOLL HPP: fixed 10-years
crediting period
A B C D E
Year Annual validated
generation (MWh)
Emission factor
(ton CO2/MWh)
Baseline
emissions (ton
CO2)
Project
emissions
(ton CO2)
Emission
Reductions
(ton CO2)
A * B C - D
01/07/202
0
2021
2022
2023
2024
2025
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2026
2027
2028
2029
30/06/203
0
Sum
Data management
All data collected as part of monitoring plan should be archived electronically and be kept for at least 2
years after the end of the last crediting period.
Monitoring report
Monitoring reports for verification by a Designated Operational Entity (DOE) will be prepared on a
yearly basis as follows:
The DEVOLL plant manager will issue an annual monitoring report in line with CDM regulations and
the requirements of this monitoring methodology.
The monitoring report will contain a summary of the whole monitoring plan and will describe the
implementation of the monitoring plan in that particular year, present the relevant results and data and
calculate emission reductions for this period.
The report will include:
• Quality assurance (QA) reports for the monitoring equipment;
• Calibration reports for the monitoring equipment (including relevant standards and
regulations);
• Any maintenance and repair of monitoring equipment;
• The qualifications of the persons responsible for the monitoring and calculations;
• The tests performed and data obtained;
• Emission reduction calculations;
• A summary of the monitoring plan in that particular year;
• Any other information relevant to the monitoring plan.
The performance of the project activity will be reviewed and analyzed by the consultants on a regular
basis.
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Annex 5
INFORMATION REGARDING STAKEHOLDERS
Photos: DHP Public Information Centre, Gramsh
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Photos: Impressions from MIS (information meetings held in different communities
(clockwise: Cingar i Poshtem, Drize, Moglice and in Gjergjovine 2)
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Photo: Impression of the Public Hearing from March 25th
2010 in the Cultural House in Gramsh,
Albania
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Screenshot of DHP website
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Annex 6
NOTIFICATION LETTER TO THE ALBANIAN DNA AND UNFCCC SECRETARIAT/CDM
PRIOR CONSIDERATION
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