Jishanhu P D D

PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.

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



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SECTION A. General description of project activity

A.1 Title of the project activity:
>>
Project title: Jiangxi Duchang Jishanhu Wind Farm Project
PDD version: 2.0
Completion date PDD: 10/10/2008

A.2. Description of the project activity:
>>
Jiangxi Duchang Jishanhu Wind Farm Project (hereinafter referred to the proposed project) is located in
Duchang County of Jiujiang City in Jiangxi Province, China. The proposed project will be constructed
and operated by Jiangxi Zhongdiantou New Energies Co., Ltd.

With a period of 21 years in total, the proposed project will have a total installed capacity of 30MW
(1.5MW×20) contributing to power generation of 55,042MWh annually to Central China Grid through
Jiangxi Grid. The annual operation hours are 1835. By utilizing clean and renewable power, electricity
generated by the proposed project will replace the same amount of electricity generated by Central China
Grid which is dominated by fossil-fuel fired power. As a result, greenhouse gas emission reduction of
estimated 62,616tCO2e per year can be achieved.

The proposed project will not only provide clean electricity to grid but also contribute to sustainable
development of the host country by means of:
Providing reliable, zero-emitting renewable energy to Central China Grid
Contributing to local economic development through employment creation
Stimulating the growth of wind power industry in China
Decrease the GHG emission by reducing the electricity generation from the fossil-fuel fired power
plants, and also the emission of SOx, NOx and dust
Stimulating the development of local tourism industry
Improving people’s living standard

A.3. Project participants:
>>
The parties involved in the proposed project are shown in Table A-1:

Table A-1 Project participants
Name of Party involved Private and/or public entity(ies) Kindly indicate if the Party
(*)((host) indicates a host project participants (*) (as involved wishes to be considered as
Party) applicable) project participant (Yes/No)
Jiangxi Zhongdiantou New
P. R. China (host) No
Energies Co., Ltd
Germany KfW No

For more detailed contact information on participants in the project activities, please refer to Annex 1.



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A.4. Technical description of the project activity:

A.4.1. Location of the project activity:
>>

A.4.1.1. Host Party(ies):
>>
People’s Republic of China

A.4.1.2. Region/State/Province etc.:
>>
Jiangxi Province

A.4.1.3. City/Town/Community etc:
>>
Duchang County of Jiujiang City

A.4.1.4. Detail of physical location, including information allowing the
unique identification of this project activity (maximum one page):
>>
The project site is located in Duchang County, Jiujiang City, Jiangxi Province. The site location’s
approximate coordinates are east longitude of 116°09′32′′ and north latitude of 29°15′12′′.

Figure A-1 illustrates the location of the proposed project.



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Jiangxi Duchang Jishanhu
Wind Farm Project

Figure A-1 Map of the project location



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A.4.2. Category(ies) of project activity:
>>
The project activity falls within Sectoral Scope 1: Energy Industries.
- Electricity generation from wind power

A.4.3. Technology to be employed by the project activity:
>>
The proposed project utilises standard wind power technology which will be domestically manufactured.

The proposed project involves the installation of 20 wind turbines produced by Goldwind Science and
Technology Co., Ltd. with an individual capacity of 1500kW per unit adding up to a total installed
capacity of 30MW. The main specifications of the turbine are listed in Table A-2.

Table A-2 Technical specifications of employed turbine (Goldwind S77-1500kW)
Rotor Diameter 77m
Installation height 65m
Area swept 4657m2
Number of blades 3
Rotor Speed 9～17.3rpm
Operational data Cut-in wind speed 3m/s
Nominal wind speed 11.5m/s
Cut-out wind speed 22m/s
Ultimate wind speed 59.5m/s
Operation temperature -30～40℃
Generator Nominal output 1500kW
Rated voltage 690V
Frequency 50Hz
Rated speed 17.3rpm
Rated current 660A

The project entity has made arrangements for its staff to become familiar with the operation and
maintenance requirements of a wind farm.

All technologies utilized in the proposed project are domestically produced and there is no technical
transfer involved.

A.4.4 Estimated amount of emission reductions over the chosen crediting period:
>>
7*3 year renewable crediting period is chosen for the proposed project. Annual emission reduction of the
proposed project is estimated to be 62,616 tCO2e which totals in 438,312 tCO2e during the first crediting
period (from January, 2009 to December, 2015).

The estimation of the emission reductions in the crediting period is presented in Table A-3.

Table A-3 Estimation of emission reduction over the first crediting period



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Year Annual estimation of emission reductions in tones of CO2 e

01/01/2009 – 31/12/2009 62,616
01/01/2010 – 31/12/2010 62,616
01/01/2011 – 31/12/2011 62,616
01/01/2012 – 31/12/2012 62,616
01/01/2013 – 31/12/2013 62,616
01/01/2014 – 31/12/2014 62,616
01/01/2015 – 31/12/2015 62,616

Total estimated reductions (tCO2 e) 438,312
Total number of crediting years 7
Annual average over the crediting
period of estimated reductions 62,616
(tCO2e)

A.4.5. Public funding of the project activity:
>>
There is no public funding from Annex I countries available to the proposed project.

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:
>>
ACM0002: “Consolidated baseline methodology for grid-connected electricity generation from
renewable sources” , version 07, EB36;
“Tool to calculate the emission factor for an electricity system”, version 01, EB35;
“Tool for the demonstration and assessment of additionality”, version 05, EB39;

For more information regarding the methodology, please refer to the link:
http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html

B.2 Justification of the choice of the methodology and why it is applicable to the project
activity:
>>
The baseline methodology ACM0002 is applicable to the proposed project, because the proposed project
meets all the applicability criteria stated in the methodology:

The proposed project is a new wind power plant to supply the electricity capacity additions;
The proposed project does not involve an on-site switch from fossil fuels to a renewable source;
The geographic and system boundaries for the relevant electricity grid, the Central China Power Grid,
can be clearly identified and information on the characteristics of the grid is available.

Therefore, ACM0002 (version 07) has been applied to the proposed project.



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B.3. Description of the sources and gases included in the project boundary
>>
The spatial extent of the project boundary includes the project site and all power plants connected
physically to the Central China Grid. Central China Grid covers Henan Province, Hunan Province, Hubei
Province, Jiangxi Province, Sichuan Province and Chongqing Municipality.1

The sources and gases included in the project boundary are described in Table B-1 as follows:

Table B-1 Inclusion of gases and sources in the calculation of the emission reductions
Source Gas Included? Justification / Explanation
Fossil fuel- CO2 Yes Main emission source
fired Power Minor emission source. Excluded for
plants CH4 No
simplification. This is conservative.
Baseline connected to
the Central Minor emission source. Excluded for
China Power N2O No
simplification. This is conservative.
Grid
Excluded by the methodology for wind farm
CO2 No
Jiangxi projects
Project Duchang Excluded by the methodology for wind farm
CH4 No
Activity Jishanhu Wind projects
Farm Project Excluded by the methodology for wind farm
N2O No
projects

B.4. Description of how the baseline scenario is identified and description of the identified
baseline scenario:

>>
The proposed project activity is the installation of a new grid-connected wind power plant. As per
ACM0002: “Consolidated baseline methodology for grid-connected electricity generation from renewable
sources”, version 07, the baseline scenario is the following:

“If the project activity is the installation of a new grid-connected renewable power plant/unit, the baseline
scenario is the following: Electricity delivered to the grid by the project would have otherwise been
generated by the operation of grid-connected power plants and by the addition of new generation sources
as reflected in the combined margin (CM) calculations described in the “Tool to calculate the emission
factor for a electricity system.”

According to the above discussion, the equivalent electricity provided by the Central China Grid is
selected as the baseline scenario for the proposed project.

Parameters and data sources for determining the baseline scenario are listed in Table B-2:

1
http://cdm.ccchina.gov.cn/web/NewsInfo.asp?NewsId=2875



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Table B-2 Parameters and data sources for determining the baseline scenario
Parameter Value Source
- China Electric Power Yearbook 2002-
2007
- 2006 IPCC Guidelines for National
Baseline emission factor 1.1376 Greenhouse Gas Inventories：Volume 2
Energy
- China Energy Statistical Yearbook
2005-2007
Net electricity supplied to the
55,042MWh Feasibility Study Report
grid by the proposed project

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): >>

The proposed project is a public bid project. On February 08, 2007, local government sent out the bid
invitation document of the proposed project on. On the document, the government gave out the principle
on feed-in tariff, which was “the feed-in tariff of the project will be no more than 0.7855 RMB/KWh”.
After evaluating the financial situation of the project, the project owner found the project faced serious
investment barrier.

In order to overcome the barrier, the project owner got in touch with CDM Project Development Center
of CPCEC to discuss the possibility of CDM development intending to get the support from CERs sales.
According to the expected CDM development income analysis from CDM Project Development Center
of CPCEC on February 12, 2007, the CDM income will make compensation for the tariff to a degree of
0.083 RMB/KWh.

On February 26, 2007, a management meeting was held to discuss the bidding tariff for the proposed
project. Based on the principle on feed-in tariff in the bid invitation document and expected CERs sales,
all the participants reached a consensus to choose 0.78 RMB/KWh as the bidding tariff and to develop the
proposed project as a CDM project after winning the bid.

On April 19, 2007, the project owner won the bid, and 0.78 RMB/KWh was confirmed as the fixed feed-
in tariff. The project owner continued discussing with CDM Project Development Center of CPCEC
about the details of CDM application. On April 26, 2007, a report of CDM development financial
evaluation was made by CDM Project Development Center of CPCEC to calculate CDM revenue which
is a necessity to improve the financial situation of the project. On June 06, 2007, the CDM Development
Service Contract was signed between the project owner and CDM Project Development Center of CPCEC.
The design institute compiling the Feasibility Study Report (FSR) for the project has also fully considered
CDM incentives and revenue when compiling the FSR, which is reflected in the FSR, the main reference
for the construction and implementation of the project.

The construction of the proposed project started on November 26, 2007, which has been applied as the
starting date of the project activity.

In conclusion, during the decision-making process, the project proponent has seriously considered the
CDM revenue to overcome the investment barrier of the proposed project. The milestone of the proposed
project is shown in Table B-3:



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Table B-3 Milestone of the proposed project
Time Milestone
February 2007 Bid Invitation Document
February 2007 CDM development income analysis
February 2007 Management meeting
April 2007 Letter of acceptance for bidding
April 2007 CDM development finance evaluation report
June 2007 CDM development service contract
June 2007 Environment Impact Assessment
August 2007 Approval of EIA
August 2007 Feasibility Study Report
November 2007 Approval of the proposed project
November 2007 Construction works started

The additionality of the project activity is demonstrated using the steps described in the ‘Tool for the
demonstration and assessment of additionality’ (version 05).

Step 1. Identification of alternatives to the project activity consistent with mandatory laws and
regulations

Sub-step 1a: Define alternatives to the project activity

The methodological step requires a number of sub-steps, the first of which is the identification of realistic
and credible alternatives to the project activity. There are only a few alternatives that are realistic and
credible in the context of the Central China Power Grid:

Alternative 1: The proposed wind power activity undertaken without being registered as a CDM project
activity
Alternative 2: Thermal power generation resulting in the same amount of power delivery to the grid
Alternative 3: Power generation from other renewable power sources, such as hydropower plants,
biomass power plants or solar power plants
Alternative 4: Equivalent electricity service provided by the Central China Grid

The hydro power is unrealistic due to limited resources in Duchang County. The total exploitable hydro
resources in Duchang County is amounted to 1.8MW2, and average operation hour for hydro power plants
in Jiangxi Province in 2006 is 2730 hours3, which means it is difficult to develop a hydro power plant
with equivalent installed capacity based on limited hydro resources.
Due to technology development status and high cost for power generation, investments of solar power
and biomass project of equivalent installed capacity as the proposed project are far from being financial
attractive45.

2
http://218.65.3.188/dcx/bmgkxx/slj/fzgh/fzgh/200808/t20080803_14204.htm
3
China Electric Power Yearbook 2007
4
http://finance.people.com.cn/GB/1038/59942/59949/6294546.html
5
http://jjckb.xinhuanet.com/cjxw/2007-11/27/content_75467.htm



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Sub-step 1b: Consistency with mandatory laws and regulations

Considering the same annual electricity generation, the alternative baseline scenario for the proposed
project should be a thermal power plant with installed capacity of 15MW. According to Chinese power
regulations, fuel-fired power plants of less than 135MW are prohibited to construct in the areas covered
by large grids6. Therefore, Alternative 2 is not in compliance with Chinese regulations, and is not a
realistic and credible alternative.

For Alternative 1, the proposed project undertaken without being registered as a CDM project activity
satisfies China’s regulations.

For Alternative 4, equivalent electricity service provided by Central China Grid satisfies China’s
regulations.

Therefore, Alternative 1 and Alternative 4 comply with China’s regulations and will be analyzed in Step
2 as potential alternatives.

Step 2 Investment analysis

Sub-step 2a - Determine appropriate analysis method

The “Tool for the Demonstration and Assessment of Additionality” recommends three analysis methods.
They are simple cost analysis (option I), investment comparison analysis (option II) and benchmark
analysis (option III).

The proposed project produces economic benefits through the sales of electricity other than CDM related
income; therefore, the simple cost analysis cannot be taken. The investment comparison analysis is not
applicable to the proposed project because the alternative of the proposed project is “Equivalent
electricity service provided by the Central China Grid”, not a new investment project. Hence, the
benchmark analysis is chosen and the Internal Return Rate (IRR) is used to assess the financial viability
of the project activity.

Sub-step 2b - Options III: Apply benchmark analysis

The investment analysis is conducted through a calculation of the Internal Rate of Return (IRR) of the
project and IRR is compared with a benchmark stated on the Interim Rules on Economic Assessment of
Electrical Engineering Retrofit Projects, issued by the State Power Corporation of China. The Interim
Rules provide a guideline for projects in the electric power industry which state a minimum Internal Rate
of Return (IRR) of 8%7. This minimum IRR is of total investment and is a widely accepted standard for
projects in the power industry. Many of China’s power projects apply this benchmark IRR for financial
assessment and use it as a hurdle rate for investment in the power industry such as wind power projects,
hydropower projects, fossil fuel fired projects, transmission and substation projects.

6
Notice on Strictly Prohibiting the Installation of Fuel-fired Generators with Capacity of 135 MW or below issued by the
General Office of the State Council, decree no. 2002-6.
7
State Power Corporation of China. Interim Rules on Economic Assessment of Electrical Engineering Retrofit Projects. Beijing:
China Electric Power Press, 2003



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Sub-step 2c - Calculation and comparison of financial indicators

1) Parameters needed for calculation of IRR
According to the Feasibility Study Report of the proposed project, parameters needed for calculation of
IRR are as follows:

Table B-4 Parameters for calculation of IRR
Parameter Data Source
Installed capacity 30 MW Feasibility Study Report Page 14-1
Electricity delivered to grid 55,042 MWh Feasibility Study Report Page 14-1
Static total investment RMB 336,823,500 Feasibility Study Report Page 14-1
Long-term Loans Rate 7.83% Feasibility Study Report Page 14-1
Current Capital Loans Rate 7.29% Feasibility Study Report Page 14-1
Tariff(Including VAT) RMB 0.78 /KWh Letter of Acceptance for Bidding
Material Cost RMB 15/KW Feasibility Study Report Page 14-2
Salary and Welfare
RMB 80,000/employee/year Feasibility Study Report Page 14-2
Allowance
Number of Employees 15 Feasibility Study Report Page 14-2
Repair Cost 2009-2011 0.5% Feasibility Study Report Page 14-2
Rate 2012-2016 1.0% Feasibility Study Report Page 14-2
Depreciation Rate 6.67% Feasibility Study Report Page 14-2
Insurance Rate 0.25% Feasibility Study Report Page 14-2
Other Expenses RMB 35/KW Feasibility Study Report Page 14-2
VAT Rate 8.5% Feasibility Study Report Page 14-2
Extra VAT Rate 10% Feasibility Study Report Page 14-2
Income Tax Rate 25% Feasibility Study Report Page 14-2
Surplus Reserve Rate 10% Feasibility Study Report Page 14-2
Operation life 20 years Feasibility Study Report Page 14-1
Annual O&M 2009-2011 RMB 5.31 Million Excel Table for IRR Calculation
cost 2012-2016 RMB 7.04 Million Excel Table for IRR Calculation
Expected CERs price EUR 11/tCO2e Estimated Value

2) Comparison of the project IRR and the financial benchmark

In accordance with benchmark analysis, if the financial indicators of the proposed project, such as the
project IRR, are lower than the benchmark, the proposed project is not considered to be financially
attractive.

Table B-5 shows the project IRR with and without the income from CERs sale. Without the sales of
CERs, the project IRR is 6.51% which is lower than the financial benchmark. Thus the proposed project
is not financially attractive. Taking into account the CDM revenues, the project IRR is 8.02% which is
higher than the financial benchmark, and the proposed project becomes financially attractive.

Table B-5 Comparison of IRR with and without the income from CERs sale
Item Without CDM Benchmark With CDM
IRR 6.51% 8% 8.02%

Sub-step 2d - Sensitivity analysis



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For the proposed project, four parameters were selected as sensitive factors to check out the financial
attractiveness:

1) Static Total Investment
2) Power Generation
3) Tariff
4) Annual O&M Cost

Assuming the above four factors vary in the range of -10% to 10%, the project IRR ( without the income
from CERs sales) varies to different extents as shown in Table B-6 and Figure B-1 below.

Table B-6 Results of the sensitivity analysis
-10.00% -5.00% 0.00% 5.00% 10.00%
Static Total Investment 7.96% 7.20% 6.51% 5.87% 5.21%
Power Generation 4.93% 5.78% 6.51% 7.22% 7.92%
Tariff 4.93% 5.78% 6.51% 7.22% 7.92%
Annual O&M Cost 6.79% 6.65% 6.51% 6.36% 6.22%

Figure B-1 Results of the sensitivity analysis

9%

8%

7%
IRR

6%

5%

4%
-1 0% -5% 0% 5% 1 0%

St at i c Tot al I nvest ment Power Gener at i on
Tar i ff Annual O&M Cost

The total investment is an important factor affecting the financial attractiveness of the proposed project.
In the case that the total investment decreases by more than 10%, IRR of the proposed project begins to
exceed the benchmark. However, most of the total investment is related to purchasing raw materials and
equipments and the trend of price for raw materials and equipments is rising. Therefore, the total
investment is not likely to decrease by more than 10%.

Another important factor affecting the financial attractiveness is power generation. The output of power
generation is subject to two factors, namely, the total installed capacity and the annual operational hours.
As the total installed capacity has already been fixed, the output of power generation lies only in



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operational hours. According to the feasibility report, the average wind velocity for the recent 30 years,
20 years and 10 years are 2.7m/s, 2.6m/s and 2.5m/s respectively. Lower PLF (plant load factor) due to
lower wind velocity will result in reduced power generation. For this reason, the chances of power
generation exceeding 10% are extremely small due to the fact that the average wind speed at the proposed
project site has been decreasing over the past 30 years.

Tariff is also an important factor affecting the financial attractiveness. In the case that tariff increases by
more than 10%, IRR of the proposed project begins to exceed the benchmark. In Letter of Acceptance for
Bidding8, RMB 0.78/kWh (including VAT) is chosen as the on-grid tariff which will be fixed in the
future. Hence, it is impossible that the tariff increases to 10%.

Based on the Investment Analysis above, the proposed project is not financially attractive without CERs
sales revenues. Alternative 1 of the proposed project undertaken without being registered as a CDM
project activity is not feasible.

In conclusion, Alternative 4 - Equivalent electricity service provided by the Central China Grid is
the only feasible alternative.

Step 4 Common practice analysis

Sub-step 4a Analyze other activities similar to the proposed project activity:

According to China Wind Farm Installed Capacity Statistic in 2007 by Shi Pengfei9，there are no other
wind power projects that are operational in Jiangxi Province10. The proposed project is one of the first
wind power projects in Jiangxi Province. In conclusion, there are no other activities similar to the
proposed project activity.

Sub-step 4b Discuss any similar options that are occurring

Since there is serious investment barrier for the proposed project, the CDM has been considered in early
evaluation period. The proposed project is one of the first wind power projects in Jiangxi Province. Hence,
the proposed project is not a common practice.

In conclusion, the proposed project is additional, not (part of) the baseline scenario. Without CDM
support, the proposed project would unlikely occur. The proposed project can reduce the greenhouse gas
emissions. If the proposed project fails to be registered as a CDM project, this portion of emission
reduction can not be realized.

B.6. Emission reductions:

B.6.1. Explanation of methodological choices:
>>

8
Letter of Acceptance for Bidding was provided to DOE for verifying
9
http://www.cwea.org.cn/upload/20080324.pdf
10
http://www.jxdpc.gov.cn/zxxx/gzdt-hy/20071128/100048.htm



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ACM0002, Baseline Emission Factor of Chinese Power Grids in 200811 is applied as the following steps,
and the data are from China Electric Power Yearbook and China Energy Statistical Yearbook.

The key methodological steps are:

1. Calculating the Baseline Emission（BEy）;
2. Calculating the Project Emission（PEy）;
3. Calculating the Leakage Emission（ LEy）;
4. Calculating the Emission Reduction（ERy）

1. Calculating the Baseline Emission

According to ACM0002, the baseline emission (BEy) is the product of the baseline emission factor
(EFgrid,CM,y) times the electricity supplied by the project activity to the grid (EGy). First, the baseline
emission factor is calculated as the Combined Margin emission factor.

1.1 Calculation of the baseline emission factor (EFgrid,CM,y)

According to ACM0002, the baseline emission factor (EFgrid,CM,y) is calculated by “Tool to calculate the
emission factor for an electricity system”.

The baseline emission factor (EFgrid,CM,y) is the Combined Margin emission factor, which consists of the
weighted average of Operating Margin emission factor and Build Margin emission factor by utilizing the
latest data vintage (ex-ante) for the Central China Grid

Six steps are utilized to calculate the baseline emission:

Step 1 – Identify the relevant electric power system.
Step 2 – Select an operating margin (OM) method.
Step 3 – Calculate the operating margin emission factor (EF grid,OM,y)according to the selected method.
Step 4 – Identify the cohort of power units to be included in the build margin (BM).
Step 5 – Calculate the build margin emission factor (EF grid,BM,y).
Step 6 – Calculate the combined margin emissions factor (EF grid,CM,y).

Step 1 – Identify the relevant electric power system

According to ‘Tool to calculate the emission factor for an electricity system’ and ‘Baseline Emission
Factor of Chinese Power Grids in 2008’ published by Chinese DNA, the relevant electric power system
of the proposed project is Central China Grid, and the data of calculation are from China Electric Power
Yearbook and China Energy Statistical Yearbook.

Step 2 –Select an operating margin (OM) method

The calculation of (EF grid,OM,y) is based on one of the four following methods:

11
http://cdm.ccchina.gov.cn/web/NewsInfo.asp?NewsId=2875



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(a) Simple OM, or
(b) Simple Adjusted OM, or
(c) Dispatch Data Analysis OM, or
(d) Average OM.

As the detailed dispatch data of the Central China Grid is unavailable, method (c) and method (b) is not
applicable.

Method (a) can only be used where low-cost/must run resources12 constitute less than 50% of total grid
generation in: 1) average of the five most recent years, or 2) based on long-term normals for
hydroelectricity production.

According to the total electricity generation in 2002-2006 of the Central China Grid, the low-cost/must
run resources constitute less than 50% of total amount grid generating output (see Annex 3 for details).
Therefore, Method (a) simple OM is used to calculate the simple OM emission factor utilize the data of
2004-2006 in ex-ante option.

Step 3 –Calculate the operating margin emission factor (EFgrid, OM, y) according to the selected
method.

According to “Tool to calculate the emission factor for an electricity system”, the simple OM emission
factor in y year (EFgrid,OM,simple,y ) 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. It may be calculated:

Option A: Based on data on fuel consumption and net electricity generation of each power plant / unit, or
Option B: Based on data on net electricity generation, the average efficiency of each power unit and the
fuel type(s) used in each power unit, or
Option C: Based on data 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 A should be preferred and must be used if fuel consumption data is available for each power
plant/unit. In other cases, option B or option C can be used. For the purpose of calculating the simple
OM, Option C should only be used if the necessary data for option A and option B is not available and
can only be used if only nuclear and renewable power generation are considered as low-cost/must-run
power sources and if the quantity of electricity supplied to the grid by these sources is known.

Because the fuel consumption and net electricity generation data of each power plant / unit in the Central
China Grid is unavailable, but the total net electricity generation, the fuel types and total fuel
consumption of all power plants in the Central China Grid is available and the low-cost/must run power
resources in Central China Power Grid include only nuclear and renewable power generation,, so option
C is selected.

The formula of EF grid,OM,simple,y in option C is:

12
The low-cost/must run resources include hydro power, geothermal sources, wind power, solar sources etc



page 16

∑ FC i, y × NCVi , y × EFCO 2,i , y
EFgrid ,OMsimple, y = i

EG y
(1)

Where:

EFgrid,OMsimple,y = Simple operating margin CO2 emission factor in year y (tCO2/MWh);
FCi,y =Amount of fossil fuel type i consumed in the project electricity system in year y (mass
or volume unit);
NCVi,y = Net calorific value (energy content) of fossil fuel type i in year y (GJ / mass or volume
unit);
EFCO2,i,y = CO2 emission factor of fossil fuel type i in year y (tCO2/GJ);
EGy = Net electricity generated and delivered to the grid by all power sources serving the
system, not including low-cost / must-run power plants / units, in year y (MWh);
i = All fossil fuel types combusted in power sources in the project electricity system in
year y;
y = the three most recent years for which data is available at the time of submission of the
CDM-PDD to the DOE for validation.

The data in the calculation is from China Electric Power Yearbook 2005-2007.

Step 4 – Identify the cohort of power units to be included in the build margin

According to “Tool to calculate the emission factor for an electricity system”, the sample group m
consists of either 1) the five power plants that have been built most recently; or 2) the power plant
capacity additions in the electricity system that comprise 20% of the system generation and that built
most recently. The one with larger annual generation should be used.

However, the information on the five power plants built most recently in the Central China Grid is not
publicly available. Therefore, option 2 is selected.

EB guidance on the application of approved methodology AM0005 now consolidated into ACM0002 can
be applied for the purposed project for estimating the build margin emission factor for each fuel type. The
proposed deviations accepted and the alternative solutions in absence of data were as follows:

1) It is agreed to use the new capacity additions during the past 1-3 years to calculate the Build Margin
emission factor;

2) It is agreed that the use of the installed capacity to replace the annual electricity generation to calculate
the Build Margin emission factor;

Using the average fuel efficiency of existing power plants as the baseline will bring about higher baseline
emission and result in higher emission reductions, as the average fuel efficiency of old power plants is
lower than the new power plants, which is not a conservative method.

Step 5 - Calculation of the Build Margin Emission Factor (EFgrid,BM,y)



page 17

Due to the difficulty of separating the coal-fired, gas-fired or oil-fired installed capacity from the total
fuel-fired installed capacity, according to the suggestion on the alternative solutions in absence of data by
CDM EB, the Build Margin emission factor (EFBM,y ) will be calculated as :

1) Based on the most recent year’s energy balance of the Central China Grid, calculating the percentages
of CO2 emissions from the coal-fired, oil-fired and gas-fired power plants in total fuel-fired CO2
emissions;

2) Based on the most advanced commercialized technologies which applied by the coal-fired, oil-fired
and gas-fired power plants, calculating the fuel-fired emission factor of the Central China Grid;

3) Calculating the Build Margin emission factor (EFBM,y)through fuel-fired emission factor times the
weighted-average of fuel-fired installed capacity which is more close to 20% in the new capacity
additions. The detailed calculation as follows:

Sub-Step 5a. Calculating the percentages of CO2 emissions from the coal-fired, oil-fired and gas-fired
power plants in total fuel-fired CO2 emissions.

∑F
i∈Coal , j
i, j, y × COEFi , j , y
λCoal = (2)
∑F
i, j

∑F
i∈Oil , j
λOil = (3)
∑F
i, j

∑F
i∈Gas , j
λGas = (4)
∑F
i, j

Where:
Fi ,j, y is the amount of fuel i (in a mass or volume unit) consumed by relevant power sources j in year(s) y
COEFi,j,y is the CO2 emission coefficient of fuel i (tCO2e/ mass or volume unit of the fuel), taking into
account the carbon content of the fuels used by relevant power sources j and the percent oxidation of the
fuel in year(s) y
λCoal is the percentage of CO2 emissions from the coal-fired power plants in total fuel-fired CO2 emissions;
λOil is the percentage of CO2 emissions from the oil-fired power plants in total fuel-fired CO2 emissions;
λGas is the percentage of CO2 emissions from the gas-fired power plants in total fuel-fired CO2 emissions;

Sub-Step 5b. Calculating the fuel-fired emission factor

EFThermal = λCoal × EFCoal , Adv + λOil × EFOil , Adv + λGas × EFGas , Adv (5)

Where:



page 18

EFThermal is the fuel-fired emission factor;
EFCoal,Adv，EFOil,Adv and EFGas ，Adv are corresponding to the emission factors of coal, oil and gas fired
power plants which are applied by the most advanced commercialized technologies.

3.6 × EFCO2,i, y × 44 (6)
EFCoal, Adv = (i ∈ Coal)
FCRCoal, Adv ×1000×12
3.6 × EFCO2,i, y × 44
EFOil, Adv = (i ∈Oil) (7)
FCROil, Adv × 1000× 12
3.6 × EFCO2,i , y × 44
EFGas, Adv = (i ∈ Gas) (8)
FCRGas, Adv ×1000×12
FCRCoal , Adv : The fuel consumption rate of Coal-fired power plants which employed the most advanced
commercialized technologies
FCROil , Adv : The fuel consumption rate of Oil-fired power plants which employed the most advanced
FCRGas , Adv : The fuel consumption rate of Gas-fired power plants which employed the most advanced

Sub-Step 5c. Calculating the Build Margin Emission Factor.

CAPThermal
EFBM , y = × EFThermal (9)
CAPTotal
Where:
EFBM,y is the Build Margin emission factor with advanced commercialized technologies for year y;
CAPTotal is the new capacity additions;
CAPThermal is the new fuel-fired capacity additions.

Step 6 - Calculation of the Baseline Emission Factor (EFgid,CM,y)

EFgrid ,CM , y = EFgrid ,OM , y × wOM + EFgrid , BM , y × wBM (10)
Where:
According to the ‘Tool to calculate the emission factor for an electricity system’, the default weights of
wind farm project are ωOM =0.75 and ω BM = 0.25.

1.2. Calculation of the Baseline Emission (BEy)

BE y = (EG y − EG baseline )× EFgrid ,CM , y (11)

Where:
BEy is baseline emissions in year y (tCO2/yr).
EGy is electricity supplied by the project activity to the grid (MWh), EG y = EG PJ to grid, y − EG grid to PJ, y .
EGbaseline is baseline electricity supplied to the grid in the case of modified or retrofit facilities(MWh). For
new power plants this value is taken as zero.



page 19

EFgrid,CM,y is 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”.

2. Project Emission

According to the methodology, there are no expected project emissions for a wind farm project.

Therefore, PEy=0

3. Leakage Emission

According to the methodology, the leakage of the proposed project need not be considered. LEy=0.

4. Emission Reduction

Emission reductions will be estimated based on the baseline emission, the project emission and the
leakage emission. The emission reduction ERy due to the proposed project activity during a given year y is
calculated as follows:

ER y = BE y − PE y − LE y (12)

B.6.2. Data and parameters that are available at validation:

Data / Parameter: FCi,y
Data unit: 104t/108m3
Description: Amount of fossil fuel type i consumed in the project electricity system in year
y
Source of data used: China Energy Statistical Yearbook 2005-2007
Value applied: See Annex 3 for details
Justification of the Data that is collected from the official statistics.
choice of data or
description of
measurement methods
and procedures actually
applied :
Any comment:

Data / Parameter: EFCO2,i,y
Data unit: tC/TJ
Description: the CO2 emission factor per unit of energy of the fuel i in year y
Source of data used: Table 1.4 of Chapter 1 of Vol.2 of the 2006 IPCC Guidelines
Justification of the Data that is collected from the IPCC because the local data is not available.
choice of data or
description of
measurement methods



page 20

applied :
Any comment:

Data / Parameter: NCV i ,y
Data unit: TJ/ mass or volume unit of a fuel
Description: the net calorific value (energy content) per mass or volume unit of a fuel i in
year y
Source of data used: China Energy Statistical Yearbook 2007
Justification of the China Energy Statistics Yearbook is published by China Statistics Press, it is
choice of data or authorized.
description of
measurement methods
applied :
Any comment:

Data / Parameter: Installed Capacity
Data unit: MW
Description: Installed capacities of the Central China Grid 2002-2006
Source of data used: China Electric Power Yearbook 2003-2007
choice of data or
description of
measurement methods
applied :
Any comment:

Data / Parameter: Electricity Generation
Data unit: MWh
Description: The electricity generated by source j
choice of data or
description of
measurement methods
applied :
Any comment:

Data / Parameter: Auxiliary Power Ratio
Data unit: %
Description: The auxiliary power ratio of source j in Central China Grid



page 21

choice of data or
description of
measurement methods
applied :
Any comment:

Data / Parameter: FCRCoal，Adv
Data unit: %
Description: The fuel consumption rate of coal-fired power plants which employed the
most advanced commercialized technologies.
Source of data used: From Chinese DNA
Value applied: 37.28%
choice of data or
description of
measurement methods
applied :
Any comment:

Data / Parameter: FCROil，Adv
Data unit: %
Description: The fuel consumption rate of Oil-fired power plants which employed the most
advanced commercialized technologies.
choice of data or
description of
measurement methods
applied :
Any comment:

Data / Parameter: FCRGas,，Adv
Data unit: %
Description: The fuel consumption rate of Gas-fired power plants which employed the
most advanced commercialized technologies.
choice of data or
description of



page 22

measurement methods
applied :
Any comment:

B.6.3 Ex-ante calculation of emission reductions:
>>
1. Calculating the Baseline Emission

1.1 Calculation of the baseline emission factor (EFgrid,CM,y)

Therefore, the Operating Margin emission factor (EFOM,simple ) is the weighted emission factors of 2004-
2006 of Central China Grid:
EF OM , simple =1.2783 tCO2e/MWh

The Build Margin emission factor can be calculated by formulae (2)-(9):
EFBM,y=0.7156 tCO2e/MWh

The baseline emission factor EFy is calculated as formula (10). Thus,
EFy = 1.1376 tCO2e/MWh

1.2. Calculation of the Baseline Emission (BEy)

The baseline emission BEy is calculated as formulae (11):
( )
BEy = BE y = EG y − EGbaseline × EFgrid ,CM , y ＝（55,042－0）×1.1376 =62,616 tCO2e /year

See Annex 3 for details.

2. Project Emission

PEy = 0.

3. Leakage Emission

LEy=0.

4. Emission Reduction

The Emission Reductions (ERy) for the proposed project activity could be calculated as the formula (12):
ERy =62,616 -0-0 = 62,616 tCO2e /year

B.6.4 Summary of the ex-ante estimation of emission reductions:
>>
Table B-2 Estimation of emission reductions due to the proposed project
Estimation of Estimation of Estimation of Estimation of
Year
project activity baseline leakage overall emission



page 23

emissions emissions (tonnes of CO2e) reductions
(tonnes of CO2e) (tonnes of CO2e) (tonnes of CO2e)
2009 0 62,616 0 62,616
2010 0 62,616 0 62,616
2011 0 62,616 0 62,616
2012 0 62,616 0 62,616
2013 0 62,616 0 62,616
2014 0 62,616 0 62,616
2015 0 62,616 0 62,616
Total (tonnes of CO2e) 0 438,312 0 438,312
Note: The starting date of the first crediting period is expected to be Jan. 1, 2009, and the deadline is Dec. 31, 2015.

B.7 Application of the monitoring methodology and description of the monitoring plan:
>>

B.7.1 Data and parameters monitored:
Data / Parameter: EGPJ to grid,y
Data unit: MWh
Description: Electricity supplied to the grid by the proposed project
Source of data to be Measured by meters; 100% of data will be monitored and electronic archived.
used:
Value of data applied 55,042 MWh
for the purpose of
calculating expected
emission reductions in
section B.5
Description of Hourly measurement and monthly recording
measurement methods
and procedures to be
applied:
QA/QC procedures to The measurement will in compliance with the National Guidelines and
be applied: requirements of the grid company for accuracy and reliability. The calibration
will be carried out according to relevant national standards and regulations by
authorized organisation.
Any comment: Double check by receipt of sales

Data / Parameter: EGgrid to PJ，y
Data unit: MWh
Description: Electricity supplied to the proposed project by the grid
Source of data to be Measured by meters
used:
Value of data applied 0
for the purpose of
section B.5



page 24

Description of Hourly measurement and monthly recording
measurement methods
applied:
QA/QC procedures to The measurement will in compliance with the National Guidelines and
be applied: requirements of the grid company for accuracy and reliability. The calibration
will be carried out according to relevant national standards and regulations by
authorized organisation.
Any comment: Double check by receipt of sales

Data / Parameter: EGy
Data unit: MWh
Description: Net electricity delivered to the grid by the proposed project
Source of data to be Calculated from data EGPJ to grid,y and EGgrid to PJ，y
used:
Value of data applied 55,042MWh
for the purpose of
section B.5
Description of EGy = EGPJ to grid,y － EGgrid to PJ，y
measurement methods
applied:
QA/QC procedures to
be applied:
Any comment:

B.7.2 Description of the monitoring plan:
>>
1. Key data to be monitored

The data required to be monitored during the implementation of the proposed project include those listed
in B.7.1.

2. The Operational and Management Structure for Monitoring

The project owner will set up a CDM Monitoring Office and designate a qualified staff responsible for all
relevant matters, including data collection and archiving, QC/QA, and verification. The structure of the
CDM Monitoring Office is outlined in Figure B-2.

Figure B-2 Organization chart of CDM project management office



page 25

CDM Monitoring Office

Office Manager

Monitoring Section Audit Section

The responsibilities of the sections are briefly described as follows:
Office Manager: Manage the work of CDM Monitoring Office; Charge of all relevant matters with
the monitoring activity.
Monitoring Section: Monitor, collect and archive the data according to the Monitoring Plan.
Audit Section: Audit the work of Monitoring Section and execute the QC/QA procedures according
to the Monitoring Plan.

3. Metering Systems

The connecting method of the proposed project is one turbine along with one transformer. Each turbine
will have a 0.69kV/35kV transformer. The proposed project will be connected to 35kV/110kV
transformer station via two 35kV transmission lines (See Figure B-3). The 110kV transformer station is
linked to Central China Grid through Jiangxi provincial Grid.

Figure B-3 Simplified electrical connection diagram



page 26

Backup Meter Main Meter

M2 M1

35kV/110kV Transformer station
0.69kV/35kV transformer
0.69kV line
transformer
35kV line

110kV
li
Wind turbine

The bi-direction main meter (M1 in Figure B-3) is expected to be installed at outflow side of the on-site
35kV/110kV transformer to measure net electricity supplied by the proposed project, which is treated as
the main recording system. The sales receipts will be made according to the data on the main meter
agreed by both the project owner and Jiangxi Provincial Grid Company. Net electricity delivered to the
grid by the proposed project will be cross-checked against sales receipts. The expected accuracy degree of
the main meter is 0.2S.

The bi-direction backup meter (M2 in Figure B-3) is employed to measure the input and output electricity
which is treated as the backup recording system.

4. Calibration

The calibration of the electric meters will be at least annually carried out according to relevant standards
and regulations. The electric meters for the electricity delivered to the grid by the proposed project should
be tested by a qualified metrical organization co-authorized by the owner and Jiangxi Provincial Grid
Company. After the calibration, the electric meters should be jointly inspected and sealed by the parties
concerned and shall not be accessible by either party without the presence of the other party or its
accredited representatives.

When remove, replacement, disassembling, sealing, seal-breaking, incident treatment and etc. happens to
the main recording system, Jiangxi Provincial Grid Company is the responsible operator, and the
representative of the project owner should attend.



page 27

If the parties have dissidence on the operation condition of the main metering system, the main metering
system will be calibrated by the qualified metrical organization co-authorized by both parties. Both
parties will decide the amount of electricity depending on the results of the calibration and relevant
regulations. If the parties have dissidence on the calibration results, a metrical organization with higher
qualification will be authorized to re-calibrate the meters.

If the main metering system has failure, damage or missing, the amount of the electricity delivered to the
grid by the proposed project will be determined by the records of the backup metering system or other
relevant metering system agreed by both parties.

5. Data Collection and Management

Two methods will be used to measure and record the data: hand log and automatic log.

Under the monitoring system, a data management system will be set up for keeping data and information,
and tracking information from the primary source to data calculation, in paper format. It is the
responsibility of the project entity to provide additional necessary data, information and document for
validation and verification requirements of respective DOE.

Paper documentation such as maps, diagrams and environmental assessment will be collected in a central
place, together with this monitoring plan. In order to facilitate auditor’s reference, monitoring results
should be indexed. All paper-based information will be stored by the owner and kept at least one copy.

The data monitored and required for verification and issuance will be kept for two years after the end of
the crediting period or the last issuance of CERs for this proposed project activity, whichever occurs later.

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)
>>
Date of completion of the baseline study and monitoring methodology: 26/03/2008

Responsible persons of completion of the baseline study and monitoring methodology:
1) Ms. Fu Shujie, CDM Project Development Center of CPCEC,
E-mail: fushujie@cpcec.com , Tel: +86 10 85285120-809.

2) Mr. Jia Xu, CDM Project Development Center of CPCEC,
E-mail: jiaxu@cpcec.com , Tel: +86 10 85285120-826.

Persons and entities as listed above are not project participants involved.

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:
>>
26/11/2007



page 28

C.1.2. Expected operational lifetime of the project activity:
>>
20 years 0 month

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:
>>
01/01/2009 or date of registration, whichever is later.

C.2.1.2. Length of the first crediting period:
>>
7 years 0 month

C.2.2. Fixed crediting period:

C.2.2.1. Starting date:
>>
Not applicable

C.2.2.2. Length:
>>
Not applicable

SECTION D. Environmental impacts
>>

D.1. Documentation on the analysis of the environmental impacts, including transboundary
impacts:
>>
The proposed project EIA was carried out by Jiangxi Academy of Environmental Sciences and approved
by Jiangxi Environmental Protection Administration. The summary of this evaluation is as follows:

1. Water pollution impacts

The small amount of waste water during the construction period is mainly sewage. Water-processing
facility such as drain for sorting and disposing sewage will be built and waste water will be released after
being treated up to standard.

2. Air pollution impacts:



page 29

The dust and exhaust gas will be mainly generated in construction period. To reduce the pollution impact
on air, the following measures are applied:

(1) Control quantities of vehicles; limit speed of vehicles; avoid overload of vehicles
(2) Set up fences in construction area, apply watering regularly
(3) Soil left after backfill in construction period should be removed in time to recover vegetation

3. Solid waste pollution impacts

Solid waste in construction period includes mainly construction trash and living trash. Living trash should
be collected into dustbin and construction trash should be buried in appointed location.

4. Noise pollution impacts:

A. Construction period
It includes mainly machine noise, operation noise and vehicle noise. To reduce noise impacts, the
following measure are applied:

(1) Arrange operation timetable properly according to related regulation. Operation with high level noise
at night is prohibited.
(2) Set up cover around high level noise facility
(3) Control quantities and density of vehicles

Besides, the construction site is far away from residential area and construction work will be mainly
carried out during daytime. Therefore, the impact of noise is minor.

B. Operation period
It will meet the noise standard for the construction site during the operation period. In addition, there are
not any environmental protected sensitive objects surrounding this project. For this reason, the proposed
project will not have bad impact on this point.

5. Ecological environmental impacts:

There’s no precious plant in local area and recover and afforestation will be applied after construction
period.

There are no big size animals in this area and this proposed project is not located on the birds’ migratory
routes, so it seldom happens that the blades will knock on the birds.

Even the construction work of this project will occupies relatively limited area of their activity place,
animals can easily find other places on other part of grassland. Meanwhile, after finishing of construction,
these animals can move back.

In conclusion, through taking the above measures, the negative impacts on environments will be
minimized and meet requirements of laws and regulations during the construction and implementation.
Furthermore, as renewable power project, the proposed project can reduce the consumption of fossil fuel
sources and GHG emission. In addition, the operation of the proposed project will improve the
development of the local tourism.



page 30

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:
>>
According to EIA, no significant environmental impacts are discovered by the project participants or the
host party. Jiangxi Environmental Protection Administration has approved the EIA.

SECTION E. Stakeholders’ comments
>>
E.1. Brief description how comments by local stakeholders have been invited and compiled:
>>
The project owner has carried out investigation on the public’s comments by way of questionnaires and
the investigation lasted for one month.

52 questionnaires were distributed and 45 valid questionnaires have been returned.

The questions in the questionnaires include:
What do you think about the proposed project?
What do you think the positive influence on the conditions of the local ecosystem?
What do you think the negative influence on the local economy?
What do you think the positive influence on the local economy?
Do you support the construction of the proposed project?
Do you support the applying of CDM for the proposed project?

The investigated stakeholders include residents, technicians and related governmental officials. The
outcome of the consultation is described in section E.2.

E.2. Summary of the comments received:
>>
Comments from the questionnaires

Of all investigated persons, 100% supported the construction of the proposed project; 84.4% think
positive influences will be brought by the proposed project and 15.6% think the proposed project has no
influence on their daily life. On the question of potential negative influence on daily life, 33.3% chose no
influence and 44.4% chose noise influence which is the most percentage.

E.3. Report on how due account was taken of any comments received:
>>
According to the above information, local residence and government are very supportive to the proposed
project; there are no negative comments on it.

As for the noise impacts which are mostly worried by local residents, the following measures will be
taken:

(1) Arrange operation timetable properly according to related regulation. Operation with high level noise
at night is prohibited.



page 31

(2) Set up cover around high level noise facility
(3) Control quantities and density of vehicles

Based on the related comments, the project entity will take environmental protection measures in both
construction period and operation period to make sure that the negative impact on environment will be
reduced to the lowest level.



page 32

Annex 1

CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY

Organization: Jiangxi Zhongdiantou New Energies Co. Ltd.
Street/P.O.Box: No. 699 Lvyin Road
Building: /
City: Nanchang
State/Region: Jiangxi Province
Postfix/ZIP: 330038
Country: China
Telephone: +86-0791-3961875
FAX: /
E-Mail: yihongjing@cpijx.cn
URL: /
Represented by: Hongjing Yi
Title: /
Salutation: /
Last Name: Yi
Middle Name: /
First Name: Hongjing
Department: /
Mobile: /
Direct FAX: /
Direct tel: +86-0791-3961875
Personal E-Mail: yihongjing@cpijx.cn

Organization: KfW



page 33

Street/P.O.Box: Palmengartenstr. 5-9.
Building: /
City: Frankfurt
State/Region: /
Postfix/ZIP: 60325
Country: Germany
Telephone: +49 69 7431 4032
FAX: +49 69 7431 4775
E-Mail: /
URL: www.kfw.de/carbonfund
Represented by: Florian Sekinger
Title: Senior Project Manager
Salutation: Mr.
Last Name: Sekinger
Middle Name: /
First Name: Florian
Department: KfW Carbon Fund
Mobile: /
Direct FAX: +49 69 7431 4775
Direct tel: +49 69 7431 4032
Personal E-Mail: florian.sekinger@kfw.de



page 34

Annex 2

INFORMATION REGARDING PUBLIC FUNDING

No public funding from Annex I parties is involved in this project activity.


CDM – Executive Board page 35

Annex 3

BASELINE INFORMATION

Step 1 – Identify the relevant electric power system

According to ‘the Baseline Emission Factor of Chinese Power Grids in 2008’ published by Chinese DNA, the relevant electric power system of the project is
Central China Grid, and the data of calculation are from China Electric Power Yearbook and China Energy Statistical Yearbook.

Step 2 –Select an operating margin (OM) method

According to the electricity generation in 2002-2006 of the Central China Grid, the low-cost/must run resources constitute less than 50% of total amount grid
generating output. Method (a) simple OM is used to calculate the simple OM emission factor utilize the data of 2004-2006 in ex-ante option for the proposed
project.

Step 3 – Calculating an operating margin (OM)

The emission factor and average low caloric value used to calculate operating margin and build margin are listed below:

Table 1 Data of Emission Factor and Average Low Caloric Value for different types of fuel
Emission Factor
Fuel Average Low Caloric Value (MJ/t, km3)
(tc/TJ)
H J
Raw Coal 25.8 20908
Cleaned Coal 25.8 26344
Other Washed Coal 25.8 8363
Brown Coal Briquettes 26.6 20908
Coke 29.2 28435
Coke Oven Gas 12.1 16726
Other Gas 12.1 5227
Crude Oil 20 41816
Gasoline 18.9 43070
Coal Oil 19.6 43070
Diesel Oil 20.2 42652



Fuel Oil 21.1 41816
PLG 17.2 50179
Refinery Gas 15.7 46055
Natural Gas 15.3 38931
Other Petroleum Products 20 38369
Other Coking Products 25.8 28435
Other Energy 0 0
Source: 1 “Revised 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Volume 2 Energy”, Chapter One
2 China Energy Statistical Yearbook 2007

Table 2 Annual Electricity Generation of Central China Grid 2002-2006
Electricity Generation (MWh)
Split of
Year
Hydro Thermal Total Thermal

2002 112440000 200347000 312787000 64.05%
2003 126448000 240839000 367287000 65.57%
2004 169094000 270846000 439940000 61.56%
2005 187734000 303976000 491720000 61.82％
2006 192296000 355453000 547859000 64.88%
Source: China Electric Power Yearbook 2003-2007

Procedures of calculating simple OM for Central China Grid from 2004 to 2006 is as below:

Table 3 Calculation of the Operating Margin Emission Factor, 2004
Emission Average Low
Fuel Unit Jiangxi Henan Hubei Hunan Chongqing Sichuan Total Factor Caloric Value CO2 Emission（tCO2e）
（tc/TJ）（MJ/t,km3）

K=G*H*I*44/12/10000
G=A+B+C （质量单位）
A B C D E F H I
+D+E+F K=G*H*I*44/12/1000
（体积单位）



Raw Coal 104 t 1863.8 6948.5 2510.5 2197.9 875.5 2747.9 17144.1 25.8 20908 339092605
4
Cleaned Coal 10 t 0 2.34 0 0 0 0 2.34 25.8 26344 58316
Other Washed
104 t 48.93 104.22 0 0 89.72 0 242.87 25.8 8363 1921441
Coal
Coke 104 t 0 109.61 0 0 0 0 109.61 29.2 28435 3337011
8 3
Coke Oven Gas 10 m 0 0 1.68 0 0.34 0 2.02 12.1 16726 149900
8 3
Other Gas 10 m 0 0 0 0 2.61 0 2.61 12.1 5227 60527
4
Crude Oil 10 t 0 0.86 0.22 0 0 0 1.08 20 41816 33118
4
Gasoline 10 t 0 0.06 0 0 0.01 0 0.07 18.9 43070 2089
4
Diesel Oil 10 t 0.02 3.86 1.7 1.72 1.14 0 8.44 20.2 42652 266627
4
Fuel Oil 10 t 1.09 0.19 9.55 1.38 0.48 1.68 14.37 21.1 41816 464893
4
PLG 10 t 0 0 0 0 0 0 0 17.2 50179 0
4
Refinery Gas 10 t 3.52 2.27 0 0 0 0 5.79 15.7 46055 153506
8 3
Natural Gas 10 m 0 0 0 0 0 2.27 2.27 15.3 38931 495775
Other
Petroleum 104 t 0 0 0 0 0 0 0 20 38369 0
Products
Other Coking
104 t 0 0 0 0 0 0 0 25.8 28435 0
Products
Other Energy 104tce 0 16.92 0 15.2 20.95 0 53.07 0 0 0
Total 346035810
Sources: China Energy Statistical Yearbook 2005

Table 4 Calculation of thermal power supply to Central China Grid, 2004
Electricity Auxiliary Supplied
Province generation power ratio electricity
（MWh) （%）（MWh)
Jiangxi 30127000 7.04 28006059
Henan 109352000 8.19 100396071
Hubei 43034000 6.58 40202363



Hunan 37186000 7.47 34408206
Chongqin
16520000 11.06 14692888
g
Sichuan 34627000 9.41 31368599
Total 249074186
Source：China Electric Power Yearbook 2005

EFGrid,OM,simple,2004=1.38929

Table 5 Calculation of the Operating Margin Emission Factor, 2005


K=G*H*I*44/12/10000
A B C D E F H I
+D+E+F K=G*H*I*44/12/1000
（体积单位）
Raw Coal 104 t 1869.29 7638.87 2732.15 1712.27 875.4 2999.77 17827.75 25.8 20908 352614497
4
Cleaned Coal 10 t 0.02 0 0 0 0 0 0.02 25.8 26344 498
Other Washed
104 t
Coal 0 138.12 0 0 89.99 0 228.11 25.8 8363 1804669
4
Coke 10 t 0 25.95 0 105 0 0 130.95 29.2 28435 3986695
8 3
Coke Oven Gas 10 m 0 0 1.15 0 0.36 0 1.51 12.1 16726 112054
Other Gas 108m3 0 10.2 0 0 3.12 0 13.32 12.1 5227 308897
Crude Oil 104 t 0 0.82 0.36 0 0 0 1.18 20 41816 36185
Gasoline 104 t 0 0.02 0 0 0.02 0 0.04 18.9 43070 1194
Diesel Oil 104 t 1.3 3.03 2.39 1.39 1.38 0 9.49 20.2 42652 299798
Fuel Oil 104 t 0.64 0.29 3.15 1.68 0.89 2.22 8.87 21.1 41816 286959
PLG 104 t 0 0 0 0 0 0 0 17.2 50179 0



Refinery Gas 104 t 0.71 3.41 1.76 0.78 0 0 6.66 15.7 46055 176572
Natural Gas 108m3 0 0 0 0 0 3 3 15.3 38931 655209
Other Petroleum 4
10 t
Products 0 0 0 0 00 0 0 20 38369 0
Other Coking 4
10 t
Products 0 0 0 1.5 0 0 1.5 25.8 28435 40349
104tc
Other Energy
e 0 2.88 0 1.74 32.8 0 37.42 0 0 0
Total 360323575

generation power ratio electricity
Province

Jiangxi 30000000 6.48 28056000

Henan 131590000 7.32 121957612

Hubei 47700000 2.51 46502730

Hunan 39900000 5 37905000

Chongqin
17584000 8.05 16168488
g

Sichuan 37202000 4.27 35613475

Total 286203305

EFGrid,OM,simple,2005=1.25898
Table 7 Calculation of the Operating Margin Emission Factor in Central China Grid, 2006




K=G*H*I*44/12/10000
A B C D E F H I
+D+E+F K=G*H*I*44/12/1000
（体积单位）
Raw Coal 104 t 1926.02 8098.01 3179.79 2454.48 1184.3 3285.22 20127.82 25.8 20908 398107508
4
Cleaned Coal 10 t 0 0 0 0 5.79 0 5.79 25.8 26344 144295
Other Washed 4
10 t
Coal 4.51 104.12 0 8.59 79.21 0 196.43 25.8 8363 1554036
Brown Coal 4
10 t
Briquettes 0 0 0 0 0 0.01 0.01 26.6 20908 204
4
Coke 10 t 0 17.23 0 0.32 0 0 17.55 29.2 28435 534299
8 3
Coke Oven Gas 10 m 0 0.52 1.07 4.24 0.38 0.01 6.22 12.1 16726 461572
8 3
Other Gas 10 m 12.69 3.95 0 1.7 4.36 0.01 22.71 12.1 5227 526655
4
Crude Oil 10 t 0 0.49 0 0 0 0 0.49 20 41816 15026
4
Gasoline 10 t 0 0.01 0 0 0 0 0.01 18.9 43070 298
4
Diesel Oil 10 t 0.91 2.23 1.41 1.78 0.96 0 7.29 20.2 42652 230298
4
Fuel Oil 10 t 0.51 1.26 1.31 0.8 0.57 3.49 7.94 21.1 41816 256872
4
PLG 10 t 0 0 0 0 0 0 0 17.2 50179 0
Refinery Gas 104 t 0.86 8.1 1 0.97 0 0 10.93 15.7 46055 289780
Natural Gas 108m3 0 0 0.28 0 0.16 18.63 19.07 15.3 38931 4164943
Other Petroleum 4
10 t
Products 0 0 0 0 0 0 0 20 38369 0
Other Coking 4
10 t
Products 0 0 0 0 0 0.01 0.01 25.8 28435 269
104tc
Other Energy
e 17.45 37.36 31.55 18.29 29.35 0 134 0 0 0
Total 406286055




Auxiliary Supplied
Electricity generation
power ratio electricity
Province
（MWh)
（%）（MWh)

Jiangxi 34449000 6.17 32323497

Henan 151235000 7.06 140557809

Hubei 54841000 2.75 53332873

Hunan 46408000 4.95 44110804

Chongqing 23487000 8.45 21502349

Sichuan 44193000 4.51 42199896

Net Electricity imported from
3028950
Northwest China Grid

Total 337056176


Table 9 Calculation of the Operating Margin Emission Factor in Northwest China Grid, 2006

Fuel Unit Shanxi Gansu Qinghai Ningxia Xinjiang Total Factor Caloric Value CO2 Emission（tCO2e）

I=F*G*H*44/12/10000
F=A+B+C （质量单位）
A B C D E G H
+D+E I=F*G*H*44/12/1000
（体积单位）



Raw Coal 104 t 2834.44 1660.92 421.86 1833.72 1547.69 8298.63 25.8 20908 164138337
Cleaned Coal 104 t 0 0 0 0 0 0 25.8 26344 0
Other Washed 4
10 t
Coal 0 0 0 112.7 8.45 121.15 25.8 8363 958466
Coke 104 t 0 0 0 0.01 0 0.01 29.2 28435 304
Coke Oven Gas 108m3 0.2 0 0 0 0.08 0.28 12.1 16726 20778
8 3
Other Gas 10 m 0.1 0 0 0 0 0.1 12.1 5227 20778
4
Crude Oil 10 t 0 0 0 0 0.02 0.02 20 41816 613
4
Gasoline 10 t 0.01 0 0 0 0 0.01 18.9 43070 298
4
Diesel Oil 10 t 1.14 0.24 0.61 0 1.25 3.24 20.2 42652 102355
4
Fuel Oil 10 t 0 0.6 0 0 0.11 0.71 21.1 41816 22970
4
PLG 10 t 0 0 0 0 0 0 17.2 50179 0
4
Refinery Gas 10 t 0 0 0 0 0 0 15.7 46055 0
8 3
Natural Gas 10 m 1.59 0.56 1.06 0 7.49 10.7 15.3 38931 2336911
Other Petroleum
104 t
Products 0 0 0 0 0 0 20 38369 0
Other Coking
104 t
Products 1.86 0 0 0 0 1.86 25.8 28435 50033
104tc
Other Energy
e 33.57 8.81 0 0 2.2 44.58 0 0 0
Total 167633385
Sources: China Electric Power Yearbook 2007

Table 10 Calculation of total power supply to Northwest China Grid, 2006
generation power ratio electricity
Province

Shanxi 58200000 6.97 54143460

Gansu 52900000 4.29 50630590



Qinghai 28000000 2.57 27280400

Ningxia 39100000 39100000

Xinjiang 35600000 8.02 32744880

Total 203899330


Therefore, the average emission factor of Northwest China Grid in 2006 is 0.82214tCO2/MWh, the OM emission factor of Central China Grid in 2006 is

EFGrid,OM,simple,2006=(0.82214*3028950+406286055)/ 337056176=1.212784

Thus, the Operating Margin (OM) emission factor is the average emission factors of 2004-2006, as:
EFGrid,OM,simple=(346035810+360323575+0.82214*3028950+406286055)/( 249074186+286203305+337056176)= 1.2783 tCO2e/MWh

Step 4 – Identify the cohort of power units to be included in the build margin

The proposed project used the deviations agreed by EB guidance on the application of approved methodology AM0005 now consolidated into ACM0002 can
be applied for the purposed of estimating the build margin emission factor for each fuel type. The proposed deviations accepted and the alternative solutions
in absence of data were as follows: 1) It is agreed to use the new capacity additions during the past 1-3 years to calculate the Build Margin emission factor; 2)
It is agreed that the use of the installed capacity to replace the annual electricity generation to calculate the Build Margin emission factor; 3) As a similar
conservative estimation, to calculate the total fuel consumption of different fuel-fired power plants by utilization of the most advanced commercialized
technologies. Using the average fuel efficiency of existing power plants as the baseline will bring about higher baseline emission and result in higher emission
reductions, as the average fuel efficiency of old power plants is lower than the new power plants, which is not a conservative method.

Step 5. Calculation of the Build Margin Emission Factor (EFgrid,BM,y)

Sub-Step 5a. Calculating the percentages of CO2 emissions from the coal-fired, oil-fired and gas-fired power plants in total fuel-fired CO2 emissions.

Table 11 Percentage of CO2 emissions from the coal-fired, gas-fired and oil-fired power plants in total fuel-fired CO2 emissions
Fuel Unit
Jiangxi Henan Hubei Hunan Chongqing Sichuan Total Emission Oxidation Average Low CO2 Emission
Factor Caloric Value tCO2e



(tC/TJ) (kJ/kg,m3)
G=A+B+ K=G*H*I*J*44/12/
A B C D E F H I J
C+D+E 100
Raw Coal 104 t 1926.02 8098.01 3179.79 2454.48 1184.3 3285.22 20217.82 25.8 1 20908 398107508
Cleaned 4
10 t 0 0 0 0 5.79 0 5.79 25.8 1 26344 144295
Coal
Other
Washed 104 t 4.51 104.12 0 8.59 79.21 0 196.43 25.8 1 8363 1554036
Coal
Brown
Coal 104 t 0 0 0 0 0 0.01 0.01 26.6 1 20908 204
Briquettes
Coke 104 t 0 17.23 0 0.32 0 0 17.55 29.2 1 28435 534299
Add Up 400340342
Crude Oil 104 t 0 0.49 0 0 0 0 0.49 20 1 41816 15026
Gasoline 104 t 0 0.01 0 0 0 0 0.01 18.9 1 43070 298
Kerosene 104 t 0 0 0 0 0 0 0 19.60 1 43070 0
Diesel Oil 104 t 0.91 2.23 1.41 1.78 0.96 0 7.29 20.2 1 42652 230298
Fuel Oil 104 t 0.51 1.26 1.31 0.8 0.57 3.49 7.94 21.1 1 41816 256872
Other
Petroleum 104 t 0 0 0 0 0 0 0 20 1 38369.00 0
Products
Other
Coking 104 t 0 0 0 0 0 0.01 0.01 25.8 1 28435 269
Products
Add Up 502763
Natural 108m
3 0 0 2.8 0 1.6 186.3 190.7 15.3 1 38931 4164943
Gas
8
Coke Oven 10 m
3 0 5.2 10.7 42.4 3.8 0.1 62.2 12.1 100 16726 461572
Gas
8
10 m
Other Gas 3 126.9 39.5 0 17 43.6 0.1 227.1 12.1 100 5227 526655
4
LPG 10 t 0 0 0 0 0 0 0 17.2 100 50179 0
Refinery
104 t 0.86 8.1 1 0.97 0 0 10.93 15.7 100 46055 289780
Gas



Add Up 5442950
Total 406286055
Source: China Energy Statistical Yearbook 2006

Based on the data from the Table 11, and the formula (2), (3) and (4), calculating

λcoal = 98.54% λOil = 0.12% λGas = 1.34%

Sub-Step 5b. Calculating the fuel-fired emission factor

Table12 Emission factors of Coal, Oil and gas with the most advanced commercialized technologies applied by the fuel-fired power plants
Fuel
Fuel Emission
consumption Emission Factor (tCO2/MWh)
Factor (tC/TJ)
rate
A B D=3.6/A/1000*B*C*44/12
Coal-fired plant EFCoal,Adv 37.28% 25.8 0.9135
Oil-fired plant EFOil,Adv 48.81% 15.3 0.4138
Gas-fired plant EFGas,Adv 48.81% 21.1 0.5706
Source: The Baseline Emission Factors of Chinese Power Grids, NRDC

Then, calculating

EFThermal = λCoal × EFCoal , Adv + λOil × EFOil , Adv + λGas × EFGas , Adv = 0.9064tCO2 / MWh

Sub-Step 5c. Calculating the Build Margin Emission Factor

Table 13 Installed Capacities of the Central China Grid, 2006
Installed Capacity Unit Jiangxi Henan Hubei Hunan Chongqing Sichuan Total
Fuel-fired MW 6568 32603 11623 10715 5594 9555 76658
Hydro MW 3288 2553 8521 8648 1979 17730 42719



Nuclear MW 0 0 0 0 0 0 0
Wind & Others MW 0 106 0 0 0 0 106
Total MW 9856 35262 20144 19363 7573 27285 119483
Source: China Electric Power Yearbook 2007

Installed Capacity Unit Jiangxi Henan Hubei Hunan Chongqing Sichuan Total
Fuel-fired MW 5906 26267.8 9526.3 7211.6 3759.5 7496 60167.2
Hydro MW 3019 2539.9 8088.9 7905.1 1892.7 14959.6 38405.2
Nuclear MW 0 0 0 0 0 0 0
Wind & Others MW 0 0 0 0 24 0 24
Total MW 8925 28807.7 17615.2 15116.7 5676.2 22455.6 98596.4

Installed Capacity Unit Jiangxi Henan Hubei Hunan Chongqing Sichuan total
Fuel-fired MW 5496 21788.5 9590.3 6779.5 3271.1 6900.3 53825.7
Hydro MW 2549.9 2438 7415.1 7448.2 1407.9 13382.9 34642
Nuclear MW 0 0 0 0 0 0 0
Wind & Others MW 0 0 0 0 0 0 0
Total MW 8045.9 24226.5 17005.4 14227.7 4679 20283.2 88467.7

Table 14 Calculation of BM From 2002 – 2005



2004-2006 New Capacity Percentage of New Capacity
Year 2004 Year 2005 Year 2006
Additions Additions
A B C D=C-B
Fuel-fired (MW) 53825.7 60167.2 76658 16490.8 78.95%
Hydro (MW) 34642 38405.2 42719 4313.8 20.65%
Nuclear (MW) 0 0 0 0 0.00%
Wind (MW) 0 24 106 82 0.39%
Total 88467.7 98596.4 119483 20886.6 100.00%
Percentage of Year 2004 74.04% 82.52% 100%

CAPThermal
Thus, EFGrid , BM , y = × EFThermal = 78.95% × 0.9064 = 0.7156tCO2 e / MWh
CAPTotal

Step 6. Calculation of the Baseline Emission Factor (EFgid,CM,y)

EFgrid ,CM , y = EFgrid ,OM , y × wOM + EFgrid , BM , y × wBM =0.75×1.2783+0.25×0.7156=1.1376 tCO2/MWh



page 48

Annex 4

MONITORING INFORMATION

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