APPENDIX A - Springer978-94-010-0153-3/1.pdf · Dr., Head, Energy & Global Change Dept., ABB...
Transcript of APPENDIX A - Springer978-94-010-0153-3/1.pdf · Dr., Head, Energy & Global Change Dept., ABB...
APPENDIX A
STRUCTURE OF CETP
Steering Committee
Stakeholder Technical Advisory Advisory
Group Program Director Board
Program Manager
12 Tasks 12 Principal Investigators
75 Scientists
Markus Bayegan
Baldur Eliasson
Paul T.P. Chan
David H. Marks
Tomonori Matsuo
Shuichiro Asao
Bjorn Stigson
Ulrich W. Suter
Roger Baud
Yam Y. Lee
APPENDIXB
STEERING COMMITTEE
Chairman Prof. Dr., Chief Technology Officer, Group R&D, ABB Ltd., Switzerland
Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, Switzerland
Senior Vice President, Communication and Sustainability Affairs, ABB China, Beijing China
James Mason Crafts Professor, Civil and Environment Engineering, Director, MIT Laboratory for Energy and The Environment, Cambridge, USA
Professor, Center,
Director, Environment The University of
Science Tokyo
AGS Coordinator(Replaced Prof. Matsuo as SC member February 2001), The University of Tokyo
President, World Business Council for Sustainable Development, Geneva, Switzerland
Professor, Polymer Chemistry, Dept. of Materials Institute of Polymers, ETH, Zurich, Switzerland Current Title: Vice President for Research and Industrial Relations
Finances Financial Administration, Alliance for Global Sustainability, ETH, Zurich, Switzerland Secretary Dr., Consultant, Energy & Global Change Dept., ABB Corporate Research, BadenDiittwil, Switzerland
752 APPENDIX B: CETP ORGANIZATION
STAKEHOLDER ADVISORY GROUP
RishengGuo
ZhenouHu
WenranLi
Dinghuan Shi
Huijiong Wang
Xiubin Xi
ZhonghuiZhan
KunZhang
Qingbo Zhao
Dadi Zhou
Deputy Director-General, the Administrative Center for China's Agenda 21, China
Deputy Director, Office of External Financing Bureau of International Cooperation, Chinese Academy of Sciences, China
Senior Consultant, former Vice Director, Environmental Protection Bureau of Shandong, China
Secretary General, Ministry of Science and Technology China
Senior Economist, Senior Engineer, Vice President of Academic Committee, Development Research Center, State Council, China
Shandong Economy and Trade Commission, China
Vice Director General, Department of Science & Technology and Environmental Protection, State Power Corporation of China
Director General, China-Japan Center for Environmental Protection, State Environmental Protection Agency, China
Senior Engineer, President of Shandong Electric Power Research Institute, China
Director General, Energy Research Institute, State Development Planning Commission, China
APPENDIX B: CETP ORGANIZATION 753
TECHNICAL ADVISORY BOARD
Jefferson W. Tester
Baldur Eliasson
Wolfgang Kroger
Chairman H.P. Meissner Professor of Chemical Engineering, MIT Cambridge, USA
Dr., Head, Energy & Global Change Dept., ABB Corporate Research, Baden-Diittwil, Switzerland
Prof. Dr., Head, Nuclear Energy and Safety Research Department, Paul Scherrer Institute, Switzerland
APPENDIXC
LIST OF CETP P ARTICIP ANTS
(Authors are marked with an *)
ABB Energy & Global Change Dept., Baden-Diittwil, Switzerland Name Function in CETP Tasks Baldur Eliasson * Program Director
Overall Management and Coordination All
Yam Y. Lee* Program Manager All Christopher Russo* Principal Investigator Database
JiangMa* Development
Coordination and Support Data Collection
ABB China Ltd., Beijing, China Name Paul Chan Shiwen Zheng
ABB China Ltd., Jinan, China Name
Tianpeng Liu (presently Shanghai) Victoria Su
Function in CETP Advisory Coordination China
Function in CETP
Coordination China Support (Jinan) Coordination China Support (Jinan)
Paul Scherrer Institute, Villigen, Switzerland Name Function in CETP Stefan Hirschberg* Principal Investigator
Principal Investigator
Roberto Dones* Principal Investigator Principal Investigator
Technical Coordinator
Tasks Data Collection Data Collection Support (Beijing)
Tasks
Data Collection
Data Collection
Tasks Risk Assessment Assessment of Environmental Impacts & External Costs DVD Life Cycle Assessment DVD
756 APPENDIX C: LIST OF CETP P ARTICIP ANTS
Socrates Kypreos*
Robert A. Krakowski *
Alexander Roeder*
Peter Burgherr* Thomas Heck*
Principal Investigator
Scientist
Scientist
Scientist Scientist
Energy Economy Modeling Energy Economy Modeling Energy Economy Modeling Risk Assessment Environmental Impact Assessment
Swiss Federal Institute of Technology (EPFL), Laboratory of Energy Systems (LASEN), Lausanne, Switzerland
Name Function in CETP Gerard Sarlos Advisory Pierre-Andre Haldi* Scientist
Jacques Pictet* Scientist
Tasks MCDA Output Integration (MCDA) Output Integration (MCDA)
(Current affiliation: Bureau d' Aide a la Decision Pictet & Bolliger) Edgard Gnansounou* Scientist Demand Forecasting Jun Dong* Doctoral student Demand Forecasting
Swiss Federal Institute of Technology (ETH) Zurich, Switzerland Name Function in CETP Tasks Adrian V. Gheorghe* Scientist Electric Sector
Warren W. Schenler* (Current affiliation: PSI)
Scientist
Stuttgart University, Stuttgart, Germany Name Function in CETP Wolfram Krewitt* Scientist (current affiliation: German Aerospace Center) Alfred Trukenmiiller* Scientist (Current affiliation: Hamburg University)
International Atomic Energy Agency, Vienna, Austria Name Function in CETP Joseph V. Spadaro* Scientist
Cazzoli Consulting, Switzerland Name Function in CETP Erik Cazzoli* Scientist
Simulation Electric Sector Simulation
Tasks Environmental Impact Assessment Environmental Impact Assessment
Tasks Environmental Impact Assessment
Tasks Risk Assessment
APPENDIX C: LIST OF CETP PARTICIPANTS 757
Vitty Consulting, Vitty, Slovakia Name Function in CETP Jirina Vitazek* Scientist
Massachusetts Institute of Technology, Cambridge, USA Name Function in CETP Stephen R. Connors* Principal Investigator
Chia-Chin Cheng* Doctoral student
Tasks Risk Assessment
Tasks Electric Sector Simulation Electric Sector Simulation
Energy Research Institute, State Development Planning Commission, Beijing China
Name Function in CETP Tasks Dadi Zhou* Principal Investigator Demand Forecasting Zhonghu Wu Advisory Demand Forecasting Shixian Gao* Scientist Demand Forecasting Xing shan Zhu Scientist Demand Forecasting Xiaoli Liu Scientist Demand Forecasting XinminXue Scientist Demand Forecasting Zhengming Su Scientist Demand Forecasting
China-Japan Friendship Center for Environmental Protection, State Environmental Protection Agency (SEP A), Beijing, China
Name Function in CETP Kun Zhang Advisory
Tasks Life Cycle Assessment Environmental Impact Assessment Risk Assessment
Policy research Center for Environment & Economy, State Environmental Protection Administration, Beijing, China
Name Function in CETP Tasks Guang Xia Advisory Environmental
Impact Assessment Lulian Cheng* Scientist Risk Assessment Yihong Zhao* Scientist Environmental
Impact Assessment Dianlin Li Scientist Environmental
Impact Assessment XinZhou* Scientist Life Cycle
Assessment Chunxiu Tian* Scientist Life Cycle
Assessment Xiangyang Xu Scientist Environmental
758 APPENDIX C: LIST OF CETP PARTICIPANTS
Zhongping Zhou
Yongqi Lu* (Tsinghua University)
Scientist
Scientist
Shandong Electric Power Group Corp., Shandong, China Name Function in CETP Zhenlin Xu Advisory Jianmin Hu Advisory
Impact Assessment Environmental Impact Assessment Environmental Impact Assessment
Tasks Data Collection Data Collection
Shandong Electric Power Group Corp., Shandong Electric Power Research Institute, Jinan, Shandong, China
Name Function in CETP Qingbo Zhao* Advisory Y ong Xu * Scientist Baoguo Shan Scientist Jingwei Shen Scientist Huijun Zhang Scientist
Universityo/Tokyo, Tokyo, Japan Name Function in CETP Kenji Yamaji*
Takeo Imanaka* (CRIEPI)
Principal Investigator
Scientist
Tasks Data Collection Data Collection Data Collection Data Collection Data Collection
Tasks Energy Transportation Modeling Energy Transportation Modeling
Tsinghua University, Global Climate Change Institute, Beijing, China Name Function in CETP Tasks Zhihong Wei* Scientist Energy Economy
Modeling Wenying Chen* Scientist Energy Economy
Modeling
APPENDIX C: LIST OF CETP P ARTICIP ANTS 759
Participants who left their participating institutions during the course of this work:
Alain Bill Bingzhang Xue* Jean Gao Urs Gantner* Gerard Spiekerman* Jennifer Barker Christopher Hansen* Nuko A. Iiiadis
Institution/organization ABB, Switzerland ABB, Switzerland ABB China Ltd., Beijing, China PSI, Switzerland PSI, Switzerland MIT, USA MIT, USA MIT, USA
1. Project Management
APPENDIXD (CHAPTER 1)
TASK DESCRIPTION
A main element of CETP is the program management by industry. A steering committee guides the program. An overall program coordinator is responsible for overseeing the running of the program, maintaining links to the steering committee and promoting outreach. A program manager is responsible for daily operation and coordination of the program. ABB was responsible for this task
2. Data Collection The data collection task was responsible for coordinating and orgamzmg the collection of data for different tasks from various sources and partners in CETP. ABB was responsible for this task
3. Database Development In order to organize and disseminate the data collected efficiently to the project participants, a database has been developed. Along with a database, a website at http://www.cetp.ch was also developed. ABB was responsible for this task.
4. Demand Forecasting To determine the strategy for energy planning, it is necessary to be able to forecast energy and electricity demand. The Energy Research Institute (ERI) of the SDPC of China is responsible for this task. They used the MEDEE-S model, which is a longterm, bottom-up final energy demand simulation model for developing countries in this study. EPFL worked closely with ERI and is responsible for performing an electricity demand and load forecasting using a bottom-up approach and the DEMELEC-PRO software.
Energy and Electricity Modeling Tasks
Tasks 5, 6 and 7 are three modeling activities relating to energy and electricity modeling. The approach is to investigate the energy mix options based on different economic and environmental constraints using both optimization and simulation techniques
762 APPENDIX D: TASK DESCRIPTION
5. EnergylEconomy Modeling The Energy Economics group of the Paul Scherrer Institute (PSI) was responsible for this task and worked closely with the Global Climate Change Institute of Tsinghua University. The Market Allocation Model (MARKAL) which is a processoriented engineering model that describes all energy transformations from primary sources to energy services was used to study the Shandong Province. PSI has also developed a multi-regional optimization model called the China Regional Electricity Trade Model (CRETM). The CRETM was used to examine a set of energyeconomic-environmental driven scenarios in order to quantify related policy implications.
6. Electric Sector Simulation This task involved bottom-up, engineering-based modeling of the Chinese electricity sector in Shandong. The task was the responsibility of the AGREA research group at the MIT Energy Laboratory. The comparative analysis of alternative strategies, under various uncertainties, is a requirement in the search for robust, long-term technological strategies and related policies. MIT has engaged the stakeholders' interaction in this task and used a simulation dispatch model (EGEAS) to simulate both technological and operational alternatives. ETHZ works closely with MIT for integration of this task with other analytic initiatives in CETP.
7. Energy Transportation Modeling The Energy Transportation Model developed at the University of Tokyo was used to simulate the electricity sector for Shandong Province in China. It is an optimization model used to study the least-cost expansion planning of the power system in Shandong Province taking into account the fossil fuel transportation to the power plants and the electricity transmission networks. It has investigated the configuration of power plants and electricity generation mix, power plant sites, expansion of transmission lines, coal flows and S02 and CO2 emission control measures.
Environmental, health and safety related Tasks
PSI was responsible for three environmental/health/safety related tasks (Tasks 8, 9 and 10). In carrying out these tasks, PSI worked closely with the Policy Research Center for Environment and Economy of the State Environmental Protection Administration of China
8. Life Cycle Assessment The Life Cycle Assessment (LCA) methodology was used to develop suitably complete environmental inventories for major present and future energy systems for the generation of electricity in Shandong. LCA provides input for the decisionmaking on energy choices by performing the full scope evaluation of the amounts of pollutants emitted into the environment from the entire chains of energy systems, including fuel mining, processing, power generation, transmission lines and waste management.
APPENDIX D: TASK DESCRIPTION 763
9. Environmental Impact Assessment Two modeling approaches were used in this task. Firstly, the RAINS-Asia model developed by IIASA was used in this study to help decision-makers analyze future trends in emissions, estimate regional impacts of resulting deposition levels, and to evaluate costs and effectiveness of alternative mitigation options. Secondly, applying the 'impact pathway approach', the environmental external costs associated with the various energy chains were estimated. The basic tool used in this analysis was the model EcoSense developed by the University of Stuttgart. It was adapted to the Chinese conditions.
10. Risk Assessment The objective of this task was to provide a balanced perspective on the severe accident risks specific for China. The assessment addressed fossil energy sources such as coal, oil and gas, nuclear power and hydropower. In addition to the power production step ofthese energy chains, whenever applicable, exploration, extraction, transports, processing, storage and waste disposal were also considered. Apart from focusing on the historical data, existing Probabilistic Safety Assessment approach was also used, particularly for the nuclear chain.
11. Integration, Decision Support and DVD ABB was responsible for integrating the results from different tasks and developed a coherent product for this study. Integration was a continuous process and conducted at various levels.
One of the goals of CETP was to develop a user-friendly decision supportaiding tool. A set of scenarios of interests was chosen from the electric sector simulation for the multi-criteria Decision Aiding (MCDA) analysis. EPFL has chosen ELECTRE III , an MCDA tool, for use in CETP since the objective of CETP was not to choose a 'best' solution but to compare different options from a sustainability standpoint.
In order to allow the stakeholders and users to fully utilize the results obtained from this study, an integrated software tool, DVD, has also been developed. The wide spectrum of targeted users was reflected in the modular design of the software, which should satisfy the needs of users having different backgrounds and interests. This task was the responsibility of PSI and was based on the contributions from all Principal Investigators and their collaborators.
12. Outreach and Technical Exchange Stakeholder involvement in CETP is essential to ensure that the results are applicable and will be used. The outreach activities were conducted to solicit inputs from stakeholders as well as inform the scientific community and various stakeholders about the progress of the program.
As CETP is an international cooperative program, technical exchange between the program participants played an important role in its activities. Technical exchange of personnel and visits to each other's institutions were encouraged as it strengthened the cooperative spirit, communication and technology transfer.
APPENDIXE (CHAPTER 1)
ABBINCHINA
ABB is one of the world's largest technology companies. Since ABB was created from the 1988 merger of Sweden's Asea and Switzerland's Brown Boveri, it has become the world leader in electrical engineering. In the last two years, ABB has pulled out of the capital-intensive and low-margin transportation and large-scale power generation businesses.
Currently, ABB is made up of two customer divisions responsible for serving end-users (ABB Website [2002] www.abb.com): The Power Technologies division serves electric, gas and water utilities as well as industrial and commercial customers, with a broad range of products, systems and services for power transmission, distribution and automation. PT produces transformers, switchgear, breakers, capacitors, cables and other products and technologies for high- and medium-voltage applications. The Automation Technologies division serves customers in the automotive, chemicals, consumer, electronics, life sciences, manufacturing, marine, metals, minerals, paper, petroleum, turbo-charging and utility industries.
ABB's friendship with China dates back to the beginning oflast century, when it supplied the country with a steam boiler in 1907. Responding to China's open policy, ABB China established its headquarter in Beijing in 1994. In 1997, China selected ABB as the major supplier to the Three Gorges Project. In 2002, ABB China had 5500 employees working in 22 branches and sales offices in China. In addition, it had 26 joint ventures and wholly owned companies. The annual revenue of ABB China is about $650 million, which accounts for about one-third of ABB's revenue in Asia.
ABB Corporate Research has been actively supporting research work in the areas of coal combustion, pollution control, and greenhouse gas emission reduction in top universities in China since the mid-1990s. In the spirit of technology transfer, ABB has established Joint Research Laboratories with Tsinghua University in Beijing and Tianjin University in Tianjin. The Greenhouse Gas Laboratory of the Energy and Global Change Department of ABB Corporate Research in Switzerland, which has trained about ten visiting Chinese scientists over the last 5 years, was transferred to the Chemistry Department at Tsinghua University and to the Chemical Engineering Department at Tianjin University. This is a pioneering step for ABB in transferring technology and research knowledge to developing countries.
In addition, ABB has supported conferences, seminars, and training courses at a number of Chinese Universities including Fudan University in Shanghai, Tsinghua University in Beijing, Tianjin University in Tianjin, Jiaotong University in Xian and
766 APPENDIX E: ABB IN CHINA
Zhejiang University in Hangzhou. In 1995, ABB scholarships were established to support the nation's development of young talent at a number of top universities in China.
APPENDIXF (CHAPTER 4)
ADDITIONAL TABLES OF DATA
Table 1. Physical value balance sheet of several types of energy of Shandong province in 1995 and 1999
Items Coal (Mt) Oil (Mt) Gas (Mm3)
1995 1999 1995 1999 1995 1999 Total energy available for consumption 111.19 108.94 13.44 15.76 1285 352
Storage at beginnin~ of year ~.72 16.87 0.56
Output 88.27 89.95 30.06 26.65 1285 733
Import from other province 23.62 25.02 0.08 0.6
Import from outside 2.57
Export to other province (-) -3.36 -4.88 -13.36 -12.37 -381
Export to outside (-) -0.06 -2.7 -1.88
Storage at end of year -18.02 -0.64 -0.37
Processing and transformation input (-) output (+) -71.02 -63.27 -12.94 -14.96 -44 -18
Thermal power -34.87 -36.82 -0.37 -0.27 -39 -18
Heat supply -4.74 -3.89 -5
Coal washing and dressing -30.13 -21.9
Coking -1.03 -0.47
Petroleum refining -12.57 -14.69
Gas production -0.25 -0.19
Losses in transportation 0.96 1.02 0.02 0.069
Total consumption 39.16 44.61 0.52 0.73 1241 334
Prim~ sector 1.77 5.03
Secondary sector 29.45 33.92 0.51 0.72 641 88
- Industry 29.1 32.16 0.49 0.69 641 88
- Construction 0.35 1.76 0.02 0.03
Tertiary sector 4.57 2.63 0.01 0.01
768 APPENDIX F: TABLES OF DATA
- Transport, ~Iecommunication, etc. 1.14 0.98 0.005 0.0083
-Commerce 1.73 1.07 0.005 0.0017
- Others 1.7 0.58
Household sector 3.37 3.03 600 246
- Urban 1.99 2.27 600 246
- Rural 1.38 0.76
Balance 0.05 0.04 -0.04 0.001 0 0 Source: Shandong Statistics Bureau
Table 2. Electricity balance sheet
Unit:TWh
Item 1985 1990 1995 1996 1997
Total energy available for consumption 26.29 44.99 74.04 79.63 85.53
Output 26.15 44.67 73.62 79.22 85.34
Thermal power 26.15 44.67 73.24 78.77 84.88
Heat supply 0.38 0.45 0.46
Import 0.15 0.32 0.42 0.43 0.2
Export (-) 0.014 0.004 0.02 0.011
Total consumption 24.67 44.76 74.1 79.68 85.46
Primary sector 2.22 3.45 4.28 4.62 4.91
Secondary sector 20.29 35.5 57.74 61.46 64.08
Industry 19.89 35.33 57.13 60.8 63.41
Construction 0.4 0.18 0.61 0.66 0.67
Tertiary sector 0.19 2.06 4.13 4.66 6.44
Transport, telecom, etc. 0.083 0.51 0.76 0.85 2.44
Commerce 0.Ql8 0.53 1.19 1.31 1.5
Others 0.089 1.02 2.18 2.5 2.5
Household sector 1.97 3.75 7.95 8.94 10.03
Urban 1.1 2.1 3.62 4.15 4.62
Rural 0.87 1.65 4.33 4.79 5.41
Balance 1.62 0.23 -0.06 -0.05 0.07
APPENDIX F: TABLES OF DATA 769
Source: Shandong Statistics Bureau
Note: There are some differences in the electricity statistics derived from the data sources of the Shandong Statistics Bureau and SEPCO. In the statistics of the Shandong Statistics Bureau, losses of electricity in transmission and distribution are included in the figures for consumption.
Table 3. Electricity consumption, growth rate and structure
Total Primary Industry Constructi Service Trans, House-on etc hold
Electricity 74.076 4.281 57.096 0.612 3.376 0.757 7.954 consumption in 1995,TWh Growth rate 11.4 5.6 11.1 8.9 15.5 5 16.2 in 1985-1995, %p.a. Electricity 94.586 5.392 69.054 0.753 5.95 1.182 12.255 consumption in2000,TWh Growth rate 4.8 3.66 3.76 4.07 11.95 8.07 8.61 in 1995-2000, %p.a. Electricity 100 9.7 78 0.6 3.2 1.7 6.8 structure in 1985, % Electricity 100 5.78 77.08 0.82 4.56 1.02 10.74 structure in 1995, % Electricity 100 5.7 73 0.8 6.29 1.25 12.96 structure in 2000, %
770 APPENDIX F: TABLES OF DATA
Table 4. Comparative Statistics among China, Shanghai and Shandong
In year 1995 China Shanghai Shandong GDP (Billion Yuan) 5847.81 246.26 500.2 GDP per capita (Yuan/person by end of year) 4828 18928 5746 Economic structure (%):
Primary sector 20.51 2.5 20.2 Secondary sector 48.8 57.3 47.4 Tertiary sector 30.69 40.2 32.4
Population 1211.21 13.01 87.05 (Million by end of year)
Urban 351.74 (29%) 9.57 (73.6%) 21.7 (24.9%) Rural 859.47(71%) 3.44 (26.4%) 65.35 (75.1 %)
Electricity consumption (TWh) 1002.34 37.92 74.1 Electricity structure (%):
Primary sector 5.81 3.14 5.78 Secondary sector 78.01 76.48 77.92 Tertiary sector 6.15 12.39 5.58 Household 10.03 7.99 10.72
Electricity growth (% p.a.) in 1986-1990: Total 8.64 11.1
Primary sector 8 Secondary sector 10.7 Tertiary sector 11.3 Household 18.4
Electricity growth in 1991-1995 (% p.a.): Total 10.16 8.33 12.3
Primary sector 10.6 2.3 Secondary sector 5.9 12.5 Tertiary sector 21.4 16.1 Household 17.8 16
Electricity growth in 1996 comparing to 1995 (%): Total 7.3 6.88 7.5
Primary sector 5.1 7.56 7.8 Secondary sector 5.78 3.62 6.4 Tertiary sector 11.3 21.49 12.7 Household 12.7 14.85 12.4
Electricity growth in 1997 comparing to 1996 (%): Total 4.4 6.14 5.4
Primary sector 5.6 -29 6.4 Secondary sector 2.9 5.52 4.3 Tertiary sector 10.5 15.76 6 Household 10.6 8.9 12.1
Electricity per capita (kWh/person 827.6 2914 851.3 by end of year) Electricity intensity (k WhIY uan)
Primary sector 0.049 0.193 0.042
APPENDIX F: TABLES OF DAT A 771
Secondary sector 0.274 0.206 0.243 Tertiary sector 0.034 0.047 0.026
Table 5. Assumptions for households
1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995 Population growth 0.8 0.68 0.58 0.42 0.21 1.36 (%p.a.) Year 2000 2005 2010 2015 2020 1995 Urbanization rate (% 26 35 42 47 50 25 at end of period) Family size (personslhousehold at end of period) Urban 3.1 3.06 3.04 3.03 3.02 3.19 Rural 3.9 3.8 3.65 3.4 3.23 4.07
1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995 Growth of average electricity per household (% p.a.) Urban 7 5 3 2 2 3.79 Rural 6 5.5 5 4 4 16.41
772 APPENDIX F: TABLES OF DATA
Table 6. Assumptions for production sectors
1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 1985-1995
Economic growth 10 9 8 7.5 6.5 11.7 (Base1ine-E scenario), (% p.a.) Lower economic growth 9 8 7 6.5 5.5 (Lowgdp-E scenario), (% p.a.)
2000 2005 2010 2015 2020 1995
Economic structure (%) (Base1ine-E scenario)
Agriculture 16.5 14 12.4 11.5 11 20.2 Industry 43.8 44.2 43.6 42.8 41.6 42.2 Construction 3.7 2.8 2.2 1.7 1.4 5.2 Service 29.5 32 34 35.5 37 26.4 Transport, etc. 6.5 7 7.8 8.5 9 6
Changed economic structure (%) (Structure-E scenario)
Agriculture 16.5 14 12.4 11.5 11 Industry 42.8 43.2 42.6 41.8 40.6 Construction 3.7 2.8 2.2 1.7 1.4 Service 30.5 33 35 36.5 38 Transport, etc. 6.5 7 7.8 8.5 9
Quicker decrease of intensity year) (%p.a.) (Baseline-E scenario)
Agriculture 0.2 0.2 0.1 -1 -1 0.9 Construction -1 -1 -1 -1 -1 -1.6 Service 1 1 0.5 -1 -1 2.2 Transport, etc. -5 -4 -4 -3 -3 -4.8
Slower decrease of intensity (% p.a.) (Inefficient-E scenario)
Agriculture 0.7 0.7 0.6 -0.5 -0.5 Construction -0.5 -0.5 -0.5 -0.5 -0.5 Service 1.5 1.5 I -0.5 -0.5 Transport, etc. -4 -3 -3 -2 -2
APPENDIX F: TABLES OF DATA 773
Table 7. Assumptions for intensity change in industry subsectors
1 99S-2000 2000-200S 200S-201O 20IO-20IS 20IS-2020
Quicker decrease of intensity (% p.a.) (Baseline-E scenario)
Nonferrous -S -4.S -3 -2 -1 Textile -4.S -4 -3 -2 -1 Chemical -4.S -4 -3 -2 -1 Energy -3.S -2.S -2 -1 -1 Others -S -4.S -3 -2 -1
Slower decrease of intensity (% p.a.)(Inefficient-E scenario)
Nonferrous Textile -4 -3.S -2 -1 0 Chemical -3.S -3 -2 -1 0 Energy -3.S -3 -2 -I 0 Others -2.S -1.5 -I -O.S 0
-4 -3.S -2 -I 0
Table 8. Assumptions for intensity change for EIPs in industry sector
I 99S-2000 2000-200S 200S-201O 20IO-201S 20 I S-2020
Quicker decrease of intensity -S -4.S -3 -2 -1 (% p.a.) (Baseline-E scenario)
Slower decrease of intensity -4 -3.S -2 -I 0 (% p.a.)(Inefficient-E scenario)
774 APPENDIX F: TABLES OF DATA
Table 9. Energy demand forecast by sector and by fuel in the baseline scenario
Unit· ktoe Industry
1995 2000 2005 2010 2015 2020
Fossil Fuels 26050.89 25435.39 27660.44 30187.5 34449.38 37762.48
Coal 16636.96 16017.58 17380.73 18992.49 21245.4 23122.72
Charcoal 2443.05 2775.23 3065.91 3453.26 4295.58 4685.55
Fuel Oil 4593.55 3922.63 3724.05 3580.83 3676.17 3771.67
LPG 266.09 347.72 522.83 689.78 894.84 1050.78
Gas 2111.24 2372.24 2966.92 3471.15 4337.38 5131.76
Motor Fuels 705.69 902.8 1197.26 1466.93 1744.41 1944.11
Electricity 4909.33 6379.00 8823.99 11105.71 13939.31 16427.56
TOTAL 31665.91 32717.19 37681.69 42760.14 50133.10 56134.15
Subsector of 1995 2000 2005 2010 2015 2020 Industry
Fossil Fuels 18824.89 18039.06 19681.15 21575.21 24453.98 27145.15
Coal 12285.12 11760.44 12834.41 14091.42 15917.31 17640.47
Charcoal 330.92 556.52 832.97 1085.7 1378.09 1599.58
Fuel Oil 4082.88 3386.27 3125.94 2924.58 2906.8 2921.76
LPG 244.38 313.4 488.65 651.01 841.05 982.76
Gas 1881.59 2022.43 2399.19 2822.51 3410.72 4000.58
Motor Fuels 705.69 902.8 1197.26 1466.93 1744.41 1944.11
Electricity 4069.02 5443.01 7715.58 9726.97 12313.46 14489.43 TOTAL 23599.60 24384.87 28593.99 32769.11 38511.85 43578.69
TEXTILE 1995 2000 2005 2010 2015 2020
Motor Fuels 97.57 45.74 61.46 71.04 82.87 90.12
Electricity 367.03 321.77 423.87 496.56 588.65 726.54
Fossil Fuels 1586.56 687.01 691.08 781.46 902.88 1029.09
Coal 1499.66 507.45 502.31 563.40 657.71 675.74
Charcoal 1.67 2.28 2.72 3.39 4.08 4.25
Fuel Oil 8.57 39.20 42.05 50.83 56.04 165.36
LPG 76.66 138.08 144.00 163.84 185.05 183.74
TOTAL 2051.16 1054.52 1176.41 1349.05 1574.4 1845.76
CHEMICAL 1995 2000 2005 2010 2015 2020
Motor Fuels 55.85 67.24 72.88 81.14 87.94 89.12
Electricity 1084.94 1258.22 1569.06 1783.79 1970.84 2118.36
Fossil Fuels 10311.03 7892.22 6661.59 5791.11 5212.71 4695.46
Coal 5632.83 4545.80 3677.42 2984.44 2186.53 1538.17
APPENDIX F: TABLES OF DATA 775
Charcoal 153.87 107.95 108.64 115.73 122.59 128.52
Residual Fuel 3256.35 2436.50 2137.42 1828.12 1736.06 1725.61 Oil
LPG 34.05 0.00 0.00 0.00 0.00 0.00
Gas 1233.93 801.98 738.10 862.82 1167.54 1303.17
TOTAL 11451.81 9217.68 8303.53 7656.04 7271.5 6902.93
ENERGY 1995 2000 2005 2010 2015 2020
Motor Fuels 417.14 632.57 880.04 1110.37 1351.83 1531.24
Electricity 1701.37 2694.27 4213.63 5646.76 7535.36 9023.07 Fossil Fuels 2317.12 3572.45 5120.65 6888.9 9064.2 11273.82
Coal 1328.46 1863.96 3099.33 4561.58 6473.56 8328.98
Charcoal 4.04 6.44 8.26 9.70 10.85 10.99
Fuel Oil 426.70 575.49 621.00 690.45 720.93 660.87
LPG 15.26 21.56 31.06 41.45 54.10 66.06
Gas 542.66 1105.00 1361.01 1585.72 1804.77 2206.93
TOTAL 4435.63 6899.29 10214.32 13646.03 17951.39 21828.13
OTHERS 1995 2000 2005 2010 2015 2020
Motor Fuels 113.97 144.27 169.85 191.23 208.6 220.29
Electricity 685.41 972.7 1305.26 1588.84 1984.71 2364.08
Fossil Fuels 3952.3 5225.07 6558.27 7458.55 8628.18 9505.25
Coal 3366.06 4276.76 5001.09 5467.52 6102.96 6633.03
Charcoal 132.84 387.59 661.35 904.10 1196.66 1411.58
Residual Fuel 230.00 291.51 282.15 311.21 349.80 325.68 Oil
LPG 118.40 153.76 313.59 445.71 601.89 732.96
Gas 105.00 115.45 300.08 330.00 376.85 402.00
TOTAL 4751.68 6342.04 8033.37 9238.62 10821.48 12089.62
EIPs of Industry
1995 2000 2005 2010 2015 2020
Fossil Fuels 7226 7396.33 7979.28 8612.29 9995.4 10617.34
Coal 4351.84 4257.14 4546.32 4901.07 5328.09 5482.26
Charcoal 2112.14 2218.7 2232.94 2367.56 2917.49 3085.97
Fuel Oil 510.67 536.36 598.12 656.25 769.37 849.91
LPG 21.71 34.32 34.17 38.77 53.79 68.02
Gas 229.65 349.81 567.73 648.64 926.65 1131.19
Electricity 840.31 935.99 1108.41 1378.74 1625.85 1938.13
TOTAL 8066.31 8332.32 9087.69 9991.03 11621.25 12555.47
CEMENT 1995 2000 2005 2010 2015 2020
Electricity 144 175.5 193.79 224.61 249.71 282.31
Fossil Fuels 2645.85 2743.07 2865.77 2980.53 3096.46 3226.76
776 APPENDIX F: TABLES OF DATA
Coal 2352.5 2414.63 2498.32 2584.67 2645.25 2717.6
Fuel Oil 219.28 229.78 242.5 253.59 267.46 282.63
LPG 21.34 32.89 31.93 36.3 50.53 64.72
Gas 52.73 65.78 93.02 105.99 133.22 161.81
Total 2789.85 2918.58 3059.57 3205.14 3346.17 3509.07
GLASS 1995 2000 2005 2010 2015 2020
Electricity 229 256.9 294.2 325 357.9 388.7
Fossil Fuels 34.2 41.79 49.29 52.92 56.79 63.23
Coal 30.7 36.21 41.24 42.94 44.56 48.26
Fuel Oil 2.81 3.34 3.81 4.06 4.32 4.73
LPG 0.37 1.43 2.24 2.48 3.26 3.3
Gas 0.32 0.82 1.99 3.44 4.66 6.94
Total 263.2 298.69 343.49 377.92 414.7 451.93
PAPER 1995 2000 2005 2010 2015 2020
Electricity 164.15 193.5 276.02 441.35 587.75 750.54
Fossil Fuels 662.05 740.77 1020.96 1291.36 1685.4 2121.12
Coal 587.67 645.46 870.04 1092.5 1410.5 1756.81
Fuel Oil 74.38 82.15 113.1 144.08 183.36 235.1
Gas 0 13.17 37.82 54.77 91.54 129.22
Total 826.2 934.27 1296.98 1732.7 2273.15 2871.66
STEEL 1995 2000 2005 2010 2015 2020
Electricity 303.17 310.09 344.39 387.79 430.49 516.59
Fossil Fuels 3883.9 3870.69 4043.27 4287.48 5156.74 5206.23
Coal 1380.96 1160.85 1136.72 1180.95 1227.79 959.59
Charcoal 2112.14 2218.7 2232.94 2367.56 2917.49 3085.97
Fuel Oil 214.2 221.1 238.71 254.52 314.23 327.45
Gas 176.6 270.05 434.9 484.44 697.23 833.22
Total 4187.06 4180.78 4387.66 4675.27 5587.23 5722.81
Household Sector
1995 2000 2005 2010 2015 2020
Electricity 684.56 1051.13 1523.44 2099.51 2678.5 3097.16
Fossil Fuels 2518.37 2946.35 3447.52 3959.27 4445.73 4874.6
Coal 1688.22 2073.22 2482.78 2877.84 3193.51 3443.35
Kerosene 162.54 128.59 102.41 80.32 63.69 48.28
Gas 510.24 554.73 634.71 741.81 906.38 1080.83
LPG 157.37 189.81 227.61 259.3 282.15 302.14
TOTAL 3202.93 3997.48 4970.96 6058.78 7124.23 7971.76
CONSUMPTION BY USAGE
APPENDIX F: TABLES OF DATA 777
Cooking 2510.39 2952.74 3465.54 3985.46 4483.71 4926.23
Lighting 114.54 164.96 222.12 281.48 327.02 359.75
Elect. Appliances 571.12 855.76 1217.27 1662.84 2095.57 2364.46
Air Conditioning 6.88 24.02 66.03 129 217.93 321.3
TOTAL 3202.93 3997.48 4970.96 6058.78 7124.23 7971.76
Service Sector
1995 2000 2005 2010 2015 2020
Electricity 290.53 412.42 556.82 722.32 914.29 1131.97
Fossil Fuels 2798.48 3052.32 3363.5 3729.21 4144.2 4601.54
Coal 1902.37 1837.83 1787.11 1747.53 1708.53 1678.11
Diesel 887.14 1201.38 1561.09 1961.68 2410.87 2893.28
Fuel Oil 8.96 11.26 13.14 15.06 16.62 18.2
Gas 0 1.85 2.16 4.94 8.18 11.95
TOTAL 3089.01 3464.74 3920.32 4451.54 5058.49 5733.5
Transport Sector
1995 2000 2005 2010 2015 2020
Petrol 1986.16 2454.75 3347.14 3964.38 4716.83 5411.7
Diesel 1128.49 1261.22 1638.31 2048.54 2501.78 3115.38
Electricity 6.34 7.26 9.14 11.49 15.77 21.35
Coal 76.36 65.74 39.32 0 0 0
Jet Fuel 67.8 86.83 106.34 127.39 151.93 178.96
TOTAL 3265.15 3875.79 5140.25 6151.8 7386.32 8727.39
TRANSPORT SECTOR
1995 2000 2005 2010 2015 2020
PASSENGER TRANSPORT DOMESTIC AIR 67.8 86.83 106.34 127.39 151.93 178.96 TRANSPORT Jet Fuel PUBLIC 667.56 1019.51 1493.76 1871.23 2201.44 2473.55 TRANSPORT ROAD,BUSES 570.62 912.55 1368.73 1712.04 2051.11 2334.66
Petrol 515.24 819.73 1223.12 1513.9 1765.65 1943.76
Diesel 55.38 92.82 145.61 198.14 285.46 390.9
RAIL 89.58 96.35 110.57 143.27 133.04 120.4
Coal 15.24 14.38 8.88 0 0 0
Diesel 74.34 81.96 101.46 142.63 131.71 118.36
Electricity 0 0.01 0.23 0.64 1.33 2.05
WATER (Diesel) 7.36 10.61 14.47 15.92 17.29 18.49
PRIVATE CARS 82.94 226.58 413.27 591.94 801.16 1074.19 TRANSPORT Petrol 77.59 204.24 350.4 455.13 572.51 738.5
Diesel 5.35 22.34 62.86 136.82 228.65 335.69
778 APPENDIX F: TABLES OF DATA
TOTAL 818.3 1332.92 2013.37 2590.57 3154.53 3726.7
Freight Transport
1995 2000 2005 2010 2015 2020
ROAD 1818.82 1915.6 2437.31 2816.64 3452.02 4198.04
Petrol 1393.33 1430.78 1773.62 1995.35 2378.68 2729.45
Diesel 425.5 484.82 663.69 821.29 1073.35 1468.59
RAIL 359.29 344.06 378.91 406.93 423.44 427.1
Coal 61.12 51.36 30.44 0 0 0
Diesel 298.16 292.68 347.7 405.12 419.21 419.84
Electricity O.oI 0.03 0.78 1.82 4.23 7.26
WATERWAYS 262.4 275.99 302.53 328.62 346.11 363.51 I (Diesel) PIPELINE 6.33 7.23 8.13 9.03 10.22 12.04 i(Electricity) TOTAL 2446.84 2542.87 3126.88 3561.23 4231.79 5000.69
Agricultural Sector
1995 2000 2005 2010 2015 2020
MOTOR FUELS 919.53 1049.98 1190.72 1385.19 1540.56 1649.74
FOSSIL FUELS 887.19 1476.14 2238.96 2346.78 2415.18 2416.41
ELECTRICITY 369.22 489.94 734.78 1000.99 1239.1 1504.71
TOTAL 2175.94 3016.06 4164.46 4732.96 5194.84 5570.86
Construction Sector
1995 2000 2005 2010 2015 2020
MOTOR FUELS 101.45 136.13 182.06 240.34 290.38 364.05
ELECTRICITY 0.6 0.71 0.86 1.02 1.16 1.46 I(TWH) TOTAL 152.9 197.27 255.59 327.84 390.26 489.46
APPENDIX F: TABLES OF DATA 779
Table 10. Forecast of electricity demand in the different scenarios
Electricity (GWh) Scenarios 2000 2005 2010 2015 2020 Productive sectors Baseline-E Total 86677.53 110545.90 140102.00 178703.93 226101.39 Agriculture 5639.08 7435.73 9725.38 12314.05 15346.87 Industry 72850.71 89596.05 109488.38 137070.01 171462.53 Construction 680.34 753.34 827.08 872.56 936.26 Service 6494.40 11392.16 18234.09 25992.73 35297.94 Transport. etc. 1013.00 1368.62 1827.06 2454.59 3057.80
Lowgdp-E Total 83049.61 101062.05 122206.22 148719.32 179454.25 Awiculture 5387.38 6783.89 8469.58 10234.39 12167.33 Industry 69839.96 81948. 73 95545.61 114116.73 136135.39 Construction 649.97 687.30 720.29 725.20 742.29 Service 6204.52 10393.49 15879.60 21602.95 27984.96 Transport. etc. 967.78 1248.64 1591.14 2040.04 2424.29
Structure-E Total 85466.01 109104.18 138375.00 176515.50 223260.19 Agriculture 5639.08 7435.73 9725.38 12314.05 15346.87 Industry 71419.05 87798.33 107225.09 134149.38 167667.33 Construction 680.34 753.34 827.08 872.56 936.26 Service 6714.55 11748.17 18770.39 26724.92 36251.94 Transport, etc. 1013.00 1368.62 1827.06 2454.59 3057.80
Inefficient-E Total 90939.90 121464.79 160940.16 212989.50 281802.34 Agriculture 5781.19 7815.22 10479.57 13607.47 17391.44 Industry 76736.82 99369.57 127794.64 166688.30 219408.17 Construction 697.69 792.26 892.01 965.05 1061.93 Service 6656.75 11968.86 19638.46 28708.77 39980.80 Transport, etc. 1067.45 1518.87 2135.48 3019.90 3960.00
Household 2000 2005 2010 2015 2020 Total 11883.54 17784.41 23961.61 29897.11 35942.01 Urban 5673.89 10215.94 14724.88 18639.45 22197.15 Rural 6209.65 7568.47 9236.73 11257.65 13744.86
Total 2000 2005 20IO 2015 2020 Baseline-E 98561.07 128330.31 164063.60 208601.04 262043.40 Lowgdp-E 94933.15 118846.46 146167.83 178616.42 215396.26 Structure-E 97349.55 126888.59 162336.61 206412.61 259202.20 Inefficient-E 102823.44 139249.20 184901.77 242886.61 317744.35
APPENDIXG (CHAPTER 7)
MATHEMATICAL DESCRIPTION OF THE MODEL
As mentioned above, ETM is a linear-programming (LP) model minimizing the total system cost, which is sum of generation, power transmission and fuel transportation cost. In this section, variables in the LP are written in lower case.
Constraints
1. Total capacity of generating plants Total capacity of generating plants in the power system must cover the peak load in the system taking capacity reserve rate into account.
N BG N CG 1 N NG 1
(1 + CRR)PeakL1 ~ I I BGCn,bg,1 + I I I cigCn,cg,I' + I I I nigcn,ng,I' n=1 bg=1 n=1 cg=1 1'=1 n=1 ng=1 t'=1
(1)
where, n (=I, ... ,N) : indices of node, t (=1, ... ,1) : indices of period c (=I, ... ,C) : indices of coal production site bg (=I, ... ,BG) : indices of the coal-fired plant installed before the planning period
(existing coal plant) at each node. cg (=I, ... ,CG) : indices of coal-fired plant type installed in the planning periods
(new coal plant) ng (=I, ... ,NG): indices of plant type (other than coal-fired plant) installed in the
planning periods (non-coal plant) BGCn.bg,t : capacity of existing coal plant. cgicn.cg,t : capacity of new coal plant installed in period t ngicn,ng,t: capacity of the non-coal plant installed in period t PeakLt : peak load (including loss on T &D) CRR : capacity reserve rate
2. Existing plants constraints 2.1 Existing plants supplemented with FGD All the existing plants are assumed to be the plants without FGD, and can be the candidates for installing FGD. The closing of the existing plant have to be considered for the FGD installation capacity. It's not applied only for existing plant
782 APPENDIX G: MATHEMATICAL DESCRIPTION
but also for all the coal-fired plant, coal from any source can be used, changed, and mixed. And electrical energy output for instantaneous peak is set to be negligible in this model.
o ~ mbgcn,bg,1 ~ BGCn,bg,1 (2)
bgcmn,bg,1 ~ mbgcn,bg,1 for t = 1 (3)
bgcmn,bg,1 ~ mbgcn,bg,1 - mbgcn,bg,I_1 for t = 2, K,T C
Lmbgon,bg,C,I,h ~ mbgcn,bg,t (4) c=1
C H H
LL T' mbgon,bg,c,t,h ~ CFL T· mbgcn,bg,t (5) c=1 h=1 h=1
where, bgemn,bg,1 : exisiting plant capacity modified (supplemented with FGD) in period t. mgben,bg,t : modified existing plant capacity. h (=O, ... ,H) : indices of time zone (h=O: instantaneous peak, 1: peak, 2: middle, 3: off-peak) mbgon,bg,c,t,h : output of modified existing plant using coal e T : width of time zones CF : maximum capacity factor.
2.2 The other existing plants C
Lbgon,bg,c,t,h ~ BGCn,bg,1 -mbgcn,bg,t (6) c=1
C H H
L LT' bgOn,bg,c,t,h ~ CFL T' (BGCn,bg,1 - mbgcn,bg,l) (7) c=1 h=! h=!
where, bgOn,bg,c,t,h : output of existing plant (not modified) using coal e
3. New plants constraints 3.1 Pulverized Coal (PC) plants supplemented with FGD PC plants, which constructed with FGD are distinguished in the model description byeg. FGD installation to PC plants w/o FGD is allowed one period after the installation of the plant.
cgcmn I = 0 for t = 1 I-I I-I (8)
cgcmn,t ~ Lcgicn,cg=[Pc,w/o.FGDl,t' - Lcgcmn,t for t = 2, KT I' I'
C I
Lmcgon,c,l,h ~ Lcgcmn,I' (9)
c=1 1'=1
APPENDIX G: MATHEMATICAL DESCRIPTION 783
C H H /
LL1"mcgon,C,/,h ~ CFL 1"Lcgcmn,I' (10) c=1 h=1 h=1 1'=1
where, egemn,t: PC plant capacity modified (supplemented with FGD) in period t. megon,c,t,h : output of modified PC plant using coal e
3.2 The other PC plants
for eg = PC wlo FGD, C 1 1
Lcgon,cg,c,t,h ~ Lcgicn,cg,I' - Lcgcmn,t' (11) c=1 /'=1 /'=1
~ t. ~. ego.,,,",,., ,; eFt. ~ -( t egie .... ,,' - t egem •. ,. J (12)
where, cgon,cg,c,t,h output of PC plant using coal c
3.3 The other coal-fired plant for cg* PC wlo FGD
C 1
Lcgon,Cg,C,I,h ~ Lcgicn,cg,I' (13) c=1 /'=1 C H H /
LL 1"cgon,Cg,c,/,h ~ CFL 1" Lcgicn,cg,I' (14) c=1 h=1 h=1 /'=1
3.4 Longkou coal limitation As stated above, Longkou mine-mouth plant in Yantai can use the Longkou coal without rail or ship transportation, but the production amount from the Longkou mine is limited.
for c=Longkou, n=Yantai
BG H BG H
LL1'·bgon,bg,C,I,h + LL1"mbgon,bg,c,t,h bg=1 h=1 bg=1 h=1
(15) CG H H
+ LL 1"cgon,cg,c,t,h + L 1"mcgon,c,t,h ~ LongkouMaxGWh cg=1 h=1 h=!
784 APPENDIX G: MATHEMATICAL DESCRIPTION
3.5 The other plants
I <" . ngon.ng.l.h - L.... nglCn•ng .l, 1'=1
H H I
I ,,·ngon,ng,l,h ~ CFI ". Ingicn,I' h=1 h=1 1'=1
where, ngon,cg,c,t,h : output of non-coal plants
3.6 Plants' construction constraints
ngicn,ng,1 = 0 for t < Available periodng
. >LL' CglCn,cg,1 - CglCn,cg,1
(16)
(17)
(18)
(19)
Available periodng : the period generating technology ng become available. LLcgicn,cg.l: plants' installation lower bound (e,g. for the plants under construction)
4. Electric power transmission 4.1 Power flow equation This is an equation by DC method, assuming no loss on the modeled transmission network. The left side of the equation is the net output from the node, and the right side is the total power flow to other nodes. This equation also represents the supplydemand balance in the power system,
BG C BG C CG C C
IIbgon,bg,C,I,h + IImbgon,bg,C,I,h + IIcgon,Cg,C,I,h + Imcgon,c,l,h bg=1 c=1 bg=1 c=1 cg=1 c=! c=1
NG N 8 _8 + "ngo - L -" n,l,h m,l,h
L.... n,ng,l,h n,l,h - L.... X ng=! m=1 n,m
m:t:.n
Ln,l,h : electricity load at node, Un,t.h : phase angle at node,
(20)
APPENDIX G: MATHEMATICAL DESCRIPTION 785
Xn,m : reactance oftransmission line between node nand m (ifthere no transmission line (branch) between nand m, IIXn,m = 0)
4,2 Capacity constraints of transmission lines
o -0 n,l,h m,l,h (21 )
Xnm
b : indices of branch correspondence to a pair of nodes (e,g, nand m) r : maximum operation rate of transmission lines,
BBCb : capacity of transmission line installed before the planning period, ibch,t: transmission capacity installed in the planning periods,
5 Emission control
(1) Local SOx Emission Control
nsulfurn,t :::; nSELn (22 )
where, nsuljurn,t : SOx emission at nodes (Mt-S)
BG C H BG C H
= IIIr,bSEn,hg,C ,bgOn,bg,c,l,h + IIIr,mbSEn,bg,c ·mbgon,bg,c,t,h bg=1 c=1 h=1 bg=1 c=1 h=1 m C H C H
+ IIIr'eSEcg,c ·egon,cg,c,t,h + IIr.meSEc ·megon,c,t,h cg=1 c=1 h=1 c=1 h=1 NG H
+ I I r· nSEng . ngon,ng,t,h ng=1 h=l
(23)
bSEn,bg,n mbSEn,bg,c, cSEcg,c, mcSEn nSEng : SOx emission coefficient (S-t/kWh) nSELn : local (nodal) SOx emission control level
(2) provincial Total SOx Emission Control
786 APPENDIX G: MATHEMATICAL DESCRIPTION
N
L nsulfurn,t ~ SEL (24)
n=1
where, SEL : provincial SOx emission control level
(3) CO2 Emission Control
N BG C H N BG C H
LLLL'X"·bCEn,bg,e ·bgOn,bg,e,t,h + LLLL'X"'mbCEn,bg,e 'mbgon,bg,e,t,h n=1 bg=1 e=1 h=1 n=1 bg=1 e=1 h=1
N 00 C H N C H
+ LLLL'X"'cCEeg,e 'cgon,eg,e,t,h + LLL'X"·mcCEe 'mcgon,e,t,h n=1 eg=1 e=1 h=1 n=1 e=1 h=1 N NG H
+ LLL'X"·nCEng 'ngon,ng,t,h ~CEL n=1 ng=1 h=1
(25)
where, bCEn,bg,c, mbCEn,bg,e, eCEeg,e, meCEe, nCEng : CO2 emission coefficient (C-tlkWh) CEL : CO2 emission control level
(4) Sulfur dioxide Control Zone In Sulfur dioxide control zone, new plants burning coal of which sulfur content is over 1% must build FGD, and existing plant burning coal of which sulfur content is over 1 % must build FGD must be supplemented with FGD by 2010.
for n E S02 Control zone, cg=PC wlo FGD, e of sulfur contain;;::: 1 %
cgon,eg,e,t,h ~ 0
bgon,ng,e,t,h ~ 0 for t;;::: 2010
Objective function
J = Ic + tc + vc + cc + nc + tax ---t min
where, Ie : fuel cost, te : fuel( coal) transportation cost, ve: variable O&M cost ee : fixed cost of generating plants, ne : fixed cost of transmission cost
(26)
(27)
APPENDIX G: MATHEMATICAL DESCRIPTION 787
stax : SOx tax
Je = t,m-:( TVFt.~~t.~.bFC,.bg,' ·bgo.,g"" J
+ t,pvF,( TVFt.~~t.~.mbFC'bg, ·mbgo.,bg</.. J
+ t,PVF,(TVFt.~~t.~.eFC"" ·ego.,,,,,,,,b J (28)
+ t,PVF,( TVFt.~t.~.meFc,.mego."".) T ( N NG H J
+ ~PVF, TVF~~l~'Z"onFCng °ngon,ng,t,h
T ( NBGCH J tC= ~PVF, TVF~~~~'Z"obTCn'bg,C obgOn,bg,c,t,h
T ( NBGCH J + ~PVF, TVF~~~~'Z"ombTCn'bg,C ombgon,bg,c,t,h
( 29)
T ( NCGCH J + ~PVF, TVF~&;~~'Z"oCTCn,cg,c °cgon,cg,c,t,h
T ( N C H J + ~PVF, TVF~~~'Z"omcTCn,c °mcgon,c,t,h
788 APPENDIX G: MATHEMATICAL DESCRIPTION
ve = t PVf{ TVF t. ~ t. t. r b VOM bgo 'h'" J
+ tPVJ~( TVFt.~t.t.r.mVOM.mbgO'b"" J
+ tPVF,( TVFt.~t.t. r.cVOM •. " ·ego •. ,g.,.,.' J (30)
T ( N C H J + ~PV~ TVF~~~r.mVOMn ·mcgon,c,t,h
T ( N NG H J + ~PV~ TVF~,&;~r.nVOMng ·ngon,ng,t,h
T ( NBGt J cc= ~PV~ TVF~~~mbARCn ·bgcmn,bg,f'
T ( N BG J + ~PV~ TVF~~mbFOM ·mbgcn,bg,t
T ( N CG t J + ~PV~ TVF~~~CAFCn,cg 'cgicn,cg,t' (31)
T ( N t J + ~PV~ TVF~~mcAAFCn ·cgcmn,t'
T ( N NG t J + ~PV~ TVF~~~nAFCng ·cgicn,ng,t'
T ( B t J nc = ~PV~ TVF~~ATCb ·ibcn,b,t' (32 )
stax = fpV~(TVF' ISTAX. nsu!furn,t] t nESCzone
(33)
APPENDIX G: MATHEMATICAL DESCRIPTION 789
where,
PVE: = (_1_)1(1-1), TVF = t(_l_)Y-l l+R y=l l+R
bFCn.bg.e, mbFCn.bg.e, cFCeg.e, mcFCe, nFCng :fuel cost of generating plants ($/kWh) *coal transportation cost is not included. bTCn.bg,c. mbTCn.bg.e, cTCn.eg.e, mcTCn.e :coal transportation cost of generating plants ($/kWh) bVOM, mVOMn, cVOMn.eg, nVOMng :variable O&M cost of generating plants ($/kWh), mbARCn: annual recovery cost for FGD installation of existing plant ($/kW/yr.) mbFOM: fixed O&M cost of supplemented FGD in existing plant ($/kW/yr.) cAFCn.eg : annual fixed cost (annual recovery cost and fixed O&M cost) of new coal plant ($/kW/yr.) mcAAFCn : additional annual fixed cost for supplemented FGD in PC ($/kW/yr.) nAFCng : annual fixed cost of non-coal plant ($/kW/yr.) ATCb: annual fixed cost of transmission line ($/kW/yr.), ST AX: Emission Charge of SOx ($/t-S) I: period interval R : discount rate
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Business As Usual (simulation case)
Billion Cubic Meter (natural gas)
British Petroleum
Boiling Water Reactor
Commercial, Constant (see Scenario)
Clean Air and Clean Energy Technology Cooperation Canadian Deuterium (pressurized heavy water nuclear reactor)
Coal Bureau
Coalbed Methane
792
CC
CC
CCGT
CCII
CCIY
CCPP
CDF CENTREL
CETP
CFC
CHEM CI
CIESIN
CISDOC
CLAB
CLSC
CM
CM
CMD
CNEIC CO
CO2
COD
COE
CON
COSHY
COST CAP
COY
CPIY
CRETM
CRIEPI
CT
ACRONYMS AND ABBREVIATIONS
Combined Cycle
CO2 Control (simulation case)
Combined Cycle Gas Turbine
China Coal Information Institute
China Coal Industry Yearbook
Combined Cycle Power Plant
Core Damage Frequency Regional group of Czech, Hungarian, Polish, and Slovak power companies
China Energy Technology Program
Chlorofluorocarbon
Chemical sector Statistical Confidence Interval (usually, 68% or 95%)
Center for International Earth Science Information Network International Occupational Health and Safety Centre Bibliographic Database by the International Labor Organization (ILO) Central interim storage facility for spent nuclear fuel, Sweden (Centralt Lager fOr Anviint Briinsle)
CO2 and Local SOx Control (simulation case)
Construction Materials
Coal Mine
Coal Mine District
China Nuclear Energy Industry Corp. Carbon monoxide
Carbon dioxide
Chemical Oxygen Demand
Cost Of Electricity
Conversion technologies
China Occupational Safety and Health Yearbook
Cost of Capital investment
China Ocean Yearbook.
China Petroleum Industry Yearbook
China Regional Energy Trade Model Central Research Institute of the Electric Power Industry (Japan)
Combustion Turbine
DC
DELECt
DEMELEC-PRO
DF
DM
DOE
DOE/EIA
DOM
DRAG
DSM DSO
Dt
E3
EcoSense
EE
EEC
EEM
EGEAS ElA
EIN
EIP
EIPs
ElS
ELASGDP
ELASPRC
ELECTRE
ENC
ENSAD
ACRONYMS AND ABBREVIATIONS
Direct Current
Electricity demand at time t DEM and of ELECtricity, a general model for electricity market study
Demand Forecasting
Demand
Department of Energy (US) Department of Energy/Energy Information Administration
Domestic (coal-fired plants)
Data Reliability Advisory Group
Demand Side Management Dam Safety Office, Bureau of Reclamation, US Department of Interior
Demand at time t
Energy-Economy-Environment Integrated Impact Assessment and External Cost Model (full impact pathway approach)
Electrical Energy Generation
European Economic Community
Energy Economy Modeling
Electric Generation Expansion System Environmental Impact Assessment
European Internet Network
Energy Intensive Sector
Energy Intensive Products
Energy Intensive Product
Income (GDP) elasticity of demand
Price elasticity of demand Elimination and Choice Reflecting the Reality (Elimination Et Choix TRaduisant la REalite)
Total discounted energy cost Energy-related .s.evere Accidents .Qatabase; this comprehensive database on severe accidents with emphasis on those associated with the energy sector has been established by the Paul Scherrer
793
794
EPA
EPB
EPFL
EPFL-LASEN
EPR
EPRI ERF
ERI
ES&H
ESBWR
ESP ESS
ETH
ETHZ
ETL
ETM
EU
EUE
EXP Fer
fer
FBC
FE
FeM
FGD
FYP
G&A
GAMS
GCC
GDP
GEN
ACRONYMS AND ABBREVIATIONS
Institute, Switzerland.
Environmental Protection Agency (US)
Electric Power Bureau Federal Institute of Technology, Lausanne (Ecole Polytechnique Federale de Lausanne, Switzerland) Laboratory of Energy Systems of EPFL, Ecole Polytechnique Federale de Lausanne (Switzerland)
European Pressurized Water Reactor
Electric Power Research Institute (USA) Exposure Response Function
Energy Research Institute (Beijing)
Environment, Safety, and Health
European Simplified Boiling Water Reactor
Electrostatic Precipitator Electric Sector Simulation
Federal Institute of Technology (Eidgenossische Technische Hochschule) Federal Institute of Technology, Zurich (Eidgenossische Technische Hochschule ZUrich)
Endogenous Technological Learning
Energy Transportation Modeling
European Union
End-Use Efficiency
Export Exposure response function
Exposure response function slope
Fluidized Bed Combustion coal power plant
Final Energy demand
Ferrous Metals
Flue Gas Desulfurization
Five Year Plan
General and Administrative
General Arithmetic Modeling System
Gas Combined Cycle power plant
Gross Domestic Product
electrical GENeration
GGDP GIS
GNP
GHG,GHGs GPCC
GPCP
GPRICEt
GT
GT
GWP
H,HH, HC:
REU
HFC
HLW
HM
HSE
HSELINE
HTGR HTM
HYDRO I
ISUWM
IAEA
ICOLD
lEA IEPE
IGCC
IIASA
ILO
ILW
IMP
IND,I
ACRONYMS AND ABBREVIATIONS
GDP Growth Geographical Information System
Gross National Product
Greenhouse Gas, Greenhouse Gases Global Precipitation Climatology Centre
Global Precipitation Climatology Project
fuel price growth rate at time t
GeoThermal
Gas Turbine
Greenhouse Warming Potential
High, higher, etc. Human Capital
Highly Enriched Uranium
Hydrofluorocarbons
High Level radioactive Waste
Heavy Metal (nuclear spent fuel)
Health and Safety Executive (UK).
Library and Information Services ofHSE
High Temperature Gas Reactor Harwell Trajectory Model, long-range atmospheric dispersion model for primary and secondary species
HYDROelectric Health impact
Simple Uniform World Model impact estimate
International Atomic Energy Agency (UN)
International Commission on Large Dams
International Energy Agency (OECD, Paris) Institute of Energy Policy and Economics of the University of Grenoble, France Integrated Gasification Combined Cycle coal power plant
International Institute for Applied Systems Studies
International Labor Organization
Intermediate Level radioactive Waste
Import
INDustry
795
796
IPA
IPCC ISC
ISL
ISO k:
kuru KWUIEDF
L,LL,LLL LAMSADE
LASEN
LCA
LCI
LCIA
LERF
LHV
LLP
LLW
LNG
LP
LPG
LSC
LWR M:
MARKAL
max
MCDA
MCDA
MED
ACRONYMS AND ABBREVIATIONS
Impact Pathways Approach (or Analysis)
Intergovernmental Panel on Climate Change (United Nations) Industrial Source Complex Model
In-Situ Leaching (chemical mining technique)
International Organization for Standardization Pollutant depletion or atmospheric removal velocity (usually, in cm/s); with "p" subscript for primary pollutant and "s" subscript for secondary species Primary to secondary pollutant chemical transformation velocity Uniform World Model (uni subscript) depletion velocity
KraftwerkunionlElectricite de France
Low, Lower, etc. Laboratory for the Analysis and Modeling of Decision Aid Systems, Paris (Laboratoire d' Analyse et Modelisation des Systemes pour I' Aide a la DEcision) Laboratory of Energy Systems (Laboratoire des Systemes ENergetiques), Switzerland
Life Cycle Assessment
Life Cycle Inventory assessment
Life Cycle Impact Assessment
Large Early Release Frequency
Lower Heating Value Lloyd's Casualty Week; formerly Lloyd's of London Press
Low Level radioactive Waste
Liquefied Natural Gas
Linear Programming
Liquefied Petroleum Gas
Local SOx Control (simulation case)
Light Water Reactor Pollutant removal flux along the earth's surface
MARket Allocation model
maximum
Multi-Criteria Decision Aid(ing)
Multi-Criteria Decision Analysis
Medium (capacity)
MEDEE-S MHIDAS
MIN
min
MIT
MOX
MRC NCAR
NCEP
NEA NFeM
NGCC NH3
NIOSHTIC NOx
NPIC
NPP
NPV
NUCL,NE
O&M
OECD Q QUERI
PC
PDS
PE
PFBC
PHWR
PI
PLM PMIO,PMIO
ACRONYMS AND ABBREVIATIONS
Modele d'Evaluation de la Demande En Energie Major Hazards Incidence Data Service of the UK Health and Safety Executive (HSE)
MINing
minimum
Massachusetts Institute of Technology, Cambridge, US
Mixed Oxide Fuel Mixed-refrigerant cycle (natural gas liquefaction process) National Center for Atmospheric Research
National Centers for Environmental Prediction
Nuclear Energy Agency (OECD)
Non-ferrous Metals
Natural Gas Combined-Cycle Ammonia
National Institute of Occupational Safety and Health (USA) Nitrogen Oxides
Nuclear Power Institute of China
Nuclear Power Plant
Net Present Value
Nuclear Energy
Operation and Maintenance Organization for Economic Cooperation and Development Pollutant annual emissions rate
Simplified impact assessment model included in the AirPacts package
Pulverized Coal combustion power plant
Plant Damage State
Primary Energy demand
Pressurized Fluidized Bed Coal Combustion
Pressurized Heavy Water Reactor (CANDU)
Principal Investigator
Peak Load Management Particulate Matter of aerodynamic diameter of 10 microns (0.001 mm) or less
797
798
PM2.5, PM2,5
PNNL
POP
PP PPPGNP
PRC PRCEE
PRIS
PSA
PSI
PSP
Pt
PV
PWR
QU R
R&D
RA RAINS
RC
RD&D
RES
RNW
ROM RUWM
S
SAC
SAG
ACRONYMS AND ABBREVIATIONS
Particulate Matter of aerodynamic diameter of2.5 microns(O.OOl mm) or less
Pacific Northwest National Laboratory
POPulations
Power Plant Purchasing Power Parity Gross National Product
Processes Policy Research Center for Environment and Economy, SEPA, China
IAEA's Power Reactor Information System
Probabilistic Safety Assessment
Paul Scherrer Institute, Villigen, Switzerland
Pre-Specified Pathway Program
Price at time t
Photo Voltaic
Pressurized Water Reactor
Qinghua University. Beijing, China (see TV) Downwind distance from source or source-receptor position vector
Research and Development
Risk Assessment Regional Air Pollution Information and Simulation
Raw coal
Research, Development, and Design
Reference Energy System
Renewables
Run-of-mine coal Robust Uniform World Model
Sulfur
Shandong Aluminum Company
Chinese Stakeholders Advisory Group
SC Steering Committee Scenarios (Region)-(Policy)(Discount Rate)(Demand)(Fossil Fuel)(Technology)
B
C
Business as usual (no specific emission controls); Baseline technology availabilities, costs, etc.
China (Region), Constant (fossil fuel prices)
E
H
L
S
S
SCIA
SCZ
SD
SDPC SEMA
SEPA
SEPCO
SEPRI SESAMS
SIB SIGMA
SPC, SPCC
SRC
SSB
STK SUWM
SWU
SX
T
T&D
TCH
TCM
TGP Trans,etc.
ACRONYMS AND ABBREVIATIONS
Environmental (S + C) Policy
High demand, discount rate, Increasing fossil fuel prices
Endogenous Technological Learning (ETL)
Sulfur control, Shandong Province (Region)
Services
State Coal Industry Administration, China
SOx Control Zones (simulation case)
Shandong Province, China
State Development Planning Commission, China French company, Paris (Societe d'etude et de mathematiques appJiquees)
State Environmental Protection Administration, China
Shandong Electric Power Group Company, China
Shandong Electric Power Research Institute, China Strategic Electric Sector Assessment Methodology Under Sustainability conditions
Siberia Sigma is published approximately eight times a year by SwissRe's Economic Research & Consulting team based in Zurich, New York and Hong Kong. Sulfur Dioxide
Sulfur Oxides
State Power Corporation of China
Source
State Statistical Bureau of China
Stocks Simple Uniform World Model
Separative Work Unit (for uranium enrichment)
Shanxi Province Time or tons (1 million grams)
Transportation sector
Transmission and Distribution
Technology (process, conversion, etc.)
Trillion Cubic Meter (natural gas)
Three Gorges Project Transport, telecommunication and other sectors in the demand forecasting
799
800
TSC
TSP
TU u(U)
UCTE
DE
UI
UN
UNDP UNSCEAR
URBAN
US
USDOE
USEPA
UT VLYL
VSL
VVER
WBCSD
WCD
WEC
WNA WTM
WTO WTP
WWW
XJ
YEARPP YOLL
ACRONYMS AND ABBREVIATIONS
Total SOx Control (simulation case)
Total Suspended Particulates
Tsinghua University, Beijing, China (see QU) Wind speed
Union for the Coordination of Transmission of Electricity
Useful Energy demand
Uranium Institute (now World Nuclear Association)
United Nations
United Nations Development Program United Nations Scientific Committee on the Effects of Atomic Radiation Simplified impact assessment model included in the AirPacts package
United States
United States Department of Energy
United States Environmental Protection Agency
University of Tokyo, Tokyo, Japan Value of a Life Year Lost, economic cost of one year of life lost Value of Statistical Life, amount of money society is willing to spend to avoid a premature death Light water pressurized reactor of Russian design (V odoVodyanoy Energeticheskiy Reactor) World Business Council for Sustainable Development, Geneva, Switzerland
World Commission on Dams
World Energy Council, London
World Nuclear Association (former UI) Windrose Trajectory Model, long-range atmospheric dispersion model for primary and secondary species
World Trade Organization, Geneva Willingness To Pay to achieve an environmental benefit
World Wide Web
Xinjiang Province (Autonomous Region), China
YEARs Per Period Years Of Life Lost (reduction in life expectancy)
GDP attimet Geometric median of lognormal distribution
Puni
P
ACRONYMS AND ABBREVIATIONS
Uniform World Model (uni subscript) receptor density
Receptor density
Geometric standard deviation of lognormal distribution
801
a
BCM
Bq
BYuan
EJ
eq/ha/year:
g(COz-equiv.)
gce
GJ
GW
GWeyr
GWh
Gy
ha
J
kA
keq/ha/year
kgoe
km
kt
ktoe
kV
kW
UNITS
annum, year
billion cubic meter = 109 cubic meter
1 Becquerel = amount of material which will produce I nuclear decay per second. The Becquerel is the more recent SI unit for radioactive source activity. The curie (Ci) is the old standard unit for measuring the activity of a given radioactive sample. It is equivalent to the activity of 1 gram of radium. 1 curie = 3.7 x 1010 Becquerels. Billion Yuan
ExaJoules = 1018 Joule
Unit for critical loads, 1 eq/ha/year corresponds to 1.6 mg/m2/year gram COz equivalent, calculated using IPCC (200 I) GWP
gram coal equivalent (coal with LHV = 29.3 MJt!lkg)
GigaJoule = 109 Joule
GigaWatt = 109 W
GigaWatt-electric-year; I GWeyr = 8.76 X 109 kWh
Giga Watthour = 109 Wh
Gray; SI unit of absorbed radiation dose in terms of the energy actually deposited in the tissue. The Gray is defined as I joule of deposited energy per kilogram of tissue. The old SI unit is the rad. 1 Gy = 1 J/kg = 100 rad.
hectare
1 J = 1 N m= 1 mZ kg S·2. The Joule is the SI unit of work or energy. 1000 Ampere
1000 eq/ha/year
kilogram oil equivalent = 42.1 MJ
kilometer
kilotonne = 103 tonne, also kiloton
kiloton oil equivalent = 42.1 TJ
kilovolt
kiloWatt = 103 W
804
kWh
kWhth
m
mg
MJ
MJth
MSWU
Mt
Mtoe
MVA
MW
MWdth
MWh
MYuan
Ryr
s
SWU
t
tce
TCM
TJ
tkm
toe
TW
TWh
Twhe, Tweh
USD
W
UNITS
kiloWatthour; I kWh = 3.6 MJ
kilo W atthourthermal
meter
milligram = 10.3 gram
Megajoule = 106 Joule
Megajoule thermal = 106 Joule thermal
millimeter
Million cubic meter
Million Separative Work Unit = 106 SWU
Megatonne = 106 tonne, also megaton
Million ton oil equivalent = 42.1 PJ
MegaVolt-Ampere
MegaWatt = 106 W
MegaWattdaythermal
Mega Watthour = 106 Wh
Million Yuan
Nautical mile = 1852 m
Normal cubic meter
Reactor*year
second
Separative Work Unit (for uranium enrichment)
tonne, metric ton (1 t = 1000 kg), also ton
tonne coal equivalent = 29.3 GJ
Trillion Cubic Meter = 1012 cubic meter
1012 Joule
tonne-kilometer
tonnes of oil equivalent = 42.1 GJ
TeraWatt = 1012 W
TeraWatthour = 1012 Wh
Tera Watthour, electrical = 3.6 MJ
US Dollar
Watt 1 W = 1 J/s = 1 m2·kg·s-3
YOLL
yr
Ilg
UNITS
Years Of Life Lost (reduction in life expectancy)
Year
microgram (10-6 grams)
64'000 or 64,000 64000 (sixty four thousand)
64.000 64 (sixty four)
805
INDEX
A
ABB ................................... 3-5, 11-12, 16-20, 25-29, 33-39, 198, 274, 318,483,666-67, 751-55, 759-64, 790
ABB Corporate Research Center ... 33 ABB-China Library ............ 20,34,36 Academia ........................ 5-11, 17,27 accidents
severe .............................. 24, 493, 587, 588, 593-98, 604-08, 611-13, 621-22, 627-28, 643-46,651-58, 735-36, 763
severe, causes ......................... 601 severe, coal mining ................. 604 severe, dams ........................... 619 severe, hydropower chain ...... 618 severe, natural gas chain ....... 609 severe, oil chain .. .................... 606 smaller ............................... 597-98 worst ....................................... 593
Acidification ......... 447,535, 576, 734 Advanced light water reactors
(ALWR) ................................... 283 AFBC. .......... 130, 132, 138, 162,230,
246, 320, 348-50, 355, 358, 362-64, 396, 405, 411-12, 416-18, 428-29, 432, 573, 716, 732-34, 738-39, 790
Aggregation Method ............................ 664, 673-74,701
AGS ............................. 3-5, 11, 16-19, 26-28, 434, 661, 700, 751, 790
air pollutants and other emissions ...................... 447
airborne emissions. ............ 345, 380, 389, 405, 411, 423-25, 430-31, 747
airborne pollutants ...................... 321, 334, 337-38, 375, 392-93, 399,407,427,441, 731
AirPacts Program ........................ 522 Alliance for Global
Sustainability ........... 3-4,197-98, 201-02, 661, 751, 790
ALWRSee Advanced Light Water Reactor
analysis of emission control scenarios ...... ............... ...... ..... 543
annual sulfur depositions ..... 558, 559 approach
bottom-up ................ 21-22, 48-49, 110,115,120,204,275,452, 665, 701, 707-10, 715, 761-62
cradle-to-grave ..................... 2, 12 top-down .. ......................... 48, 451
Argentina .............................. 521, 528 ascending distillation ................... 679 Asia Development Bank ......... 545-46,
579 Asian financial crisis ...................... 99 ATMOS model ............................. 556 Atmospheric Fluidized-Bed (AFB)
................................................ 283 atmospheric modeling ......... 469,507,
510 attributes .......... l11, 176,208,215-18
B
Banqiao dam ................................ 619 BAU ............... See Business-As-Usual Beijing .................................... 7-9, 12,
18,27, 30, 98, 102, 191, 198,214, 322, 339, 365-67, 435, 438-39, 472, 477, 520, 526, 542, 550, 580-81,584-85,590-91,620,657, 751, 755-59, 764, 793, 79-99
Beishan area ................................. 384
808
biomass ............ See renewable energy Bohai Sea ................. 43,96,103,366 bottom-up ..................... See approach Brazil ............................ 521, 529, 614 Business-As-Usual (BAU) ........... 290,
294,299-01,305,313-15 BWR ........................ 385, 390, 621-22,
627-31,634-36,641-42, 790
C
CANDU ................ 323, 381, 790, 796 carbon emission limits ................. 144 carbon emissions .......................... 108 carbon tax .................................... 133 carbon-caps .................................. 144 CB ........................... See Coal Bureau CBM ................ See coal-bed methane CCGT .................................. 138, 284,
296-98,301,304-13,316-18, 791 Ce group ....................................... 623 Cement Industry ................ 71-72, 104 CETP
analytic framework ................. 729 comparison and integration of
tasks .................................. 703 conclusions and
recommendations .............. 729 energy and electricity demand
.......................................... 730 energy supply and use ............ 736 environmental damage, health
and accident risk ............... 731 overall remarks and foture
outlook .............................. 747 recommendations ................... 745 sustainability and stakeholder
perspectives ...................... 743 CETP program management
program communications ....... 726 stakeholder interaction ........... 727 technical exchange and
outreach ............................ 727 CETP Website ................................ 39 CFCs ........................................ 4,389 CH4 •.••...••••••••••••.•.• 320,373,412,426
INDEX
Chalmers University of Technology ................................. 3, 11 Changdao Island ............................ 68 Changqingjield ............................ 366 chemical industry ........................... 65 Chernobyl accident .............. 621,645 China and Shandong ..................... 34,
102,127, 138, 153-55, 191, 290, 474, 507, 535, 555-56, 573, 719
China National Offshore Oil Corporation .............................. 96
China National Petroleum Corp .. 367 China Oil and Natural Gas
Corporation .............................. 94 China Regional Electricity Trade
Model ........................ 22, 120, 762 China Regionalized (Electrical)
Energy Trade Model. See CRETM Chinese-Manufactured
Technology ............................. 192 chlorofluorocarbons ......................... 4 chronic mortality .................. 456,463 Clean Coal Technologies ............. 192 "clean" generator ........................ 209 "clean supply" strategy ............... 260 "clean" versus "dirty"
strategies .................... 505, 516-17 CO2 emissions ...................... 1-2, 114,
144,147, 155, 165, 171-73, 178, 182-83, 186-87, 190-91, 218, 234, 241-47, 251, 256, 260, 270, 277, 291-94, 302, 305, 308, 315-16, 366,371, 713
CO2 versus S02 plots ................... 189 coal bed methane ............... ........... 138 Coal Bureau (CB) ........................ 327 Coal Bureau Electricity
Generation Company ............. 327 coal chain .............................. 23, 323,
326-27,344-48, 351, 354, 376, 398, 403, 407, 417, 423, 427-28, 492, 500, 573, 588, 592-601, 644-48,651-57, 731-36
coal consumption in China .......... 538 coal mines (CM) ........................... 327 coal preparation ........................... 329
coal transportation ....... 288, 332, 339 coalbed methane ......................... 331,
345, 35~36~ 604, 654 coal-by-wire ................................. 234 coking coal ................... 329, 330, 333 Combined-Cycle Gas-Turbine .......... .
SeeCCGT commercial primary energy
use by energy carriers ............ 541 use by sectors ......................... 540
comparisons of CO2 results ............................. 712 conclusions ............................. 716 cost ................................... 711-712 cost components by task ......... 711 methodologies ......................... 704 task conclusions ...... ................ 714
competitive nuclear power ........... 192 concordance test .................. 675, 677 confidence interval (CI) ............... 461 construction sector ... 76, 77, 115,432 Conventional Coal Plus .. 260, 265-69 cost-reduction relationship .......... 127 cradle-to-grave ........... See approach CRETM. .............. ...... 22, 100-02, 109,
113-14,120-27,137-41,144,147, 151, 156, 159-71, 175-76, 183, 187-96, 707-09, 715, 762, 791
critical load mapping ................... 562 crop production data ............ 474,476 Cs group ....................................... 623
D
damage costs due to outdoor air pollution ............................ 480
damage dependence on plant location and technology ......... 482
Data Collection .. ..................... 17, 20, 29,31-36, 755, 758, 761
data management ........................... 30 Data Reliability Advisory Group
(DRAG) ............................. 32, 792 Database Development .................. 37
INDEX 809
decision-making ............................ 20, 23-25, 390, 446, 451, 572, 661-63,666-68, 714, 733, 762
demand for electrical energy ....... 219 Demand Forecasting ............... 18, 21,
43, 48-53, 56, 89, 223, 281, 710, 729-30
scope ......................................... 51 demand-side management ... See DSM demand-side options ........ 236, 253-55 demand-side strategies ................. 256 DEMELEC-PRO ........................... 21,
49-51, 54, 761, 792 descending distillation ................. 679 "dirty" generator ... ..................... 209 discount rate ......... 113, 153, 228, 797 distribution of damages ................ 481 diversified fuels and
technologies ............................ 192 dominant hazards ......... 592, 605, 609 DSM .......................... 236-41,256-57,
260, 269-74, 413, 417, 423, 444, 714, 744, 792
dust emissions ................... 10, 108-09, 330-32, 342-43, 443, 592-93, 601
DVD ........ 6, 26, 704, 717-20, 724-28 general features ...................... 718 general information ................ 719 guided exploration .................. 719 individual technical tasks ....... 720 movie ....................................... 719 Shandong Electricity
OptionsRanking (SEOR) ... 723 structure and content .............. 718 targeted users ......................... 718 tool .......................................... 717
E
E3 ................................................ See energy-economic-environmental
economic development ................... 57 economic structure ......... 58, 769, 771 economic structure change ............ 55 EcoSens emission scenario
manager .................................. 466
810
EcoSense ................................ 452-54, 457-76, 482, 505-20, 524-29, 532-34, 543-45, 576, 721, 763, 792
EcoSense China/Asia model . ....... 453 EEM ............................. 99-04, 109-11,
119, 127, 169-72, 187, 194-96, 325-26,434,578, 703-04, 707-10, 713-16, 720-21, 736-42, 792
efficiency improvement ................. 74, 82,105, 117-18, 130, 192-94
EGEAS .............. 22, 211-13,762,792 EGEAS simulation ....................... 211 EU ........................................ 2, 24-25,
169,216,241,259,320,325,342, 366, 370-73, 383, 399, 410, 425, 434-36, 461, 492, 505, 510, 703, 707, 710, 717, 721-22, 731, 734, 742,792
ELECTRE ............................. 25, 664, 673-74, 677-78, 682, 763, 792
ELECTRE 111... ...................... 25, 673, 677-78,682, 763
electric sector methodologies discussion ............................... 707
Electric Sector Simulation .. 17,22-23, 35, 53, 201-02, 209-10, 214-15, 221, 229, 270, 273, 446-48, 499-01,574, 651, 669, 704, 762, 793
electricity consumption 44, 73, 77, 81, 329-30, 335-36, 576, 768-69
electricity demand .................... 21-22, 48-51, 56, 62, 83, 86-92, 98, 125-25, 139, 152-54, 170, 187-88, 195, 201-02, 210-13, 216-23, 237-43, 246, 253, 256, 260-61, 268-75, 280-81, 324, 334, 410, 414, 417, 445-46, 499, 707, 711, 730, 761, 778
electricity generation mix ............. 23, 277, 324, 762
Electricity Sector Simulation ............ . ......................................... SeeESS
electricity transmission ................ 194 electrostatic precipitators ..... See ESP
INDEX
emission caps .............................. 135, 175, 178, 191,277
emission database and modeling areas ...................................... 464
emissions and atmospheric modeling ................................. 453
endogenous modeling ........... 126, 160 end-use efficiency ................ 237, 240,
258,793 Energy and Global Change ...... 11-12,
20, 34, 274, 764 energy conservation ....................... 69 energy consumption ................... 9-10,
44-49, 52, 59, 62-66, 69-81, 84-85, 88, 100, 107, 135, 294, 439, 536-39, 544, 551, 576, 581-84
energy consumption in China ........ 44 Energy Economic Modeling
....................................... SeeEEM energy efficiency ................. 21, 45-50,
54-56, 69, 73-79, 82, 94-98, 105, 117,126,193,396,537,544,591, 657,714
energy infrastructure .. .............. 94, 97 energy intensity ........... 21, 54, 64, 69,
72, 82, 99, 103-06, 117, 125-26, 328, 372, 388-89, 402, 405-06, 426-28, 540, 576
Energy Research Institute (ERJ) .. 12, 17, 21, 101-02, 115-121, 125-30, 151, 175-77, 196, 501, 542, 621, 627-29, 658, 668, 752, 757, 761, 793
energy resources .......................... 105 energy supply ........... .................. 7-14,
22, 27, 34, 45-48, 79, 94, 97, 129, 194, 275-77, 419, 435, 536-41, 544, 576-78, 587, 708
Energy Transportation Model ........................................ SeeETM
energy use .................................... 107 energy-economic-
environmenta .......... 100, 122, 762 Energy-Economy Modeling
....................................... SeeEEM enrichment .... 386, 389, 435, 439, 443
ENSAD ...... 588-89, 594-96, 606, 792 environmental burdens ...... 23,320-21,
327, 334,-48, 351-57, 366-68, 374, 385-88, 391-92, 396, 402-10, 426,431-34,460-61, 710, 730-31
Environmental Impact Assessment See ......................................... EIA
Environmental Impact assessment and external costs. 17,
23 of air pollution ... ..................... 445
EPFL ........................... 12, 17, 21, 25, 50,664, 723, 756, 761-63, 793
ERI .... See Energy Research Institute ESP .............................. 140, 162,230,
236, 337-38, 342-43, 343, 350, 362, 399, 404-06, 793
ESS ......... 109, 155, 169,201,208-10, 214, 218-19, 223, 228, 230-31, 234, 245, 272, 321, 325, 347, 368, 395, 404, 410-15, 425, 429, 432-34, 441, 444-50, 493, 499, 502-04, 515, 543, 574-78, 651, 703-04, 707-16, 720-23, 736-43, 793
ESS Scenarios .............................. 214 ETH ......... 3, 11, 22, 751, 756-57, 793 ETHZ .. 12, 17, 23, 436, 574,762,793 ETM ................................ 109-10, 169,
275-87, 290-92, 315-17, 325-26, 347, 434, 578, 703-04, 708-10, 716, 720, 736-42, 780, 793
EU-15 ............................. 89, 527, 529 Europe ................................. 2, 17,24,
64, 202, 321-24, 349, 359, 363, 368, 387-89, 428, 438-42, 448, 452-53, 457, 461, 465, 473, 479, 492, 496, 507, 509-10, 514, 521-22,527-29, 532-33, 562, 568, 573, 579-82, 585, 589, 614, 620, 659, 732
evolution of electricity consumption ............................. 81
excess acid deposition .................. 564 exogenous energy demand ........... 151 Exposure-Response (ER) ............. 461
INDEX 811
exposure-response functions for crops ........... ....................... 511
exposure-response functions for human health .................... 509
exposure-response models ... ........ 454 external benefits ................... 450,451 External Costs
Assessment ....... 24, 114, 120, 195, 216,313, 320, 387, 445, 450-52, 474, 479-81, 484-85, 492-96, 500-05, 535, 572-78, 583-586, 658, 706, 733-34, 737, 739, 743-46, 755, 763
future electricity supply scenarios for Shandong ..................... 499
externalities .......................... 102,111, 192, 195, 439, 450-53, 575, 578, 580-83, 706, 717, 730, 742, 746
F
Fatalities and land contamination ......................... 631
FGD ............... See gas desulJurization final energy demand ....................... 83 five-year plan ........... 45, 98, 549, 665 Fly ash emissions ......................... 109 forecasting electric loads ... ............ 89 forecasting peaks loads .................. 92 fossil-fuel prices ............. 131-34, 141
constant .... ............................... 134 Framatome ........................... 381,385 frequency of exceedance ....... 637-640 frequency-consequence curves
........................................... 645-50 fuel cost uncertainties .................. 241 fuel fabrication ....................... xii, 390 fueltTransportation ...................... 194 fuel type ................................ 340, 341 Fujian ........... 382,562, 564, 610, 620 FYp .............................. .45-47, 59, 63,
66-68,77,87- 89, 582, 793
G
Gansu ............ 366, 383-384, 442,619 "gas-by-wire" ............. 234,368,406
812
gas combined cycle power plant .................... 373, 793
gas desulJurization .............. 137, 230, 235, 241, 254, 259, 273-75, 283, 290, 294, 297, 299-02, 316, 320, 715-17
gas leaks ...................................... 370 gaseous diffusion enrichmen
plant ....................................... 383 gaseous gmissions .................. ..... 108 Gazprom .................. 370, 437-39, 442 GCC plants ................... 193, 374, 377 GDP ........ 5,12-13,34,43-45,54-64,
74, 77-79, 82-83, 99-05, 110-19, 122-27, 141, 144, 151-52, 155-59, 169-70, 175-77, 191, 477-78, 538-40, 572, 769, 792-94,799
and population .......................... 57 growth rate ............... 99,119, 156
GHG emission rates ......................... 356-58,408,415
GHG emissions ...... 103, 325, 356-58, 366,374,377,396,403,405,415, 417, 427-30, 448, 500, 575, 732
glass industry ............................ 72-73 global warming ............ 2,4,102,126,
192, 325, 389, 461, 492, 495, 496, 500,573-75,578, 710
GNP per capita ...... .480,513-16,575 greenhouse effect ..................... 2, 450 greenhouse gas emission
rates .......... 357-59, 375, 397, 416 greenhouse gas emissions ......... 1, 11,
272, 378, 427, 432-33, 437, 714, 747
Guangdong .............. 60, 64, 198,323, 368, 381, 562-64, 610, 620
Guangxi ........................ 384,564,610 Guangzhou ................... 365, 610, 620
H
health and environmental impact cost studies for China ............ 476
INDEX
health effects .......................... 24,217, 320, 351, 362, 399, 408, 425-26, 433, 441-48, 454, 479, 489, 573, 578, 580, 583, 584-86, 604, 621-25,706,744
health impacts ............... 425,486-88, 49~ 523, 572, 68~ 733, 743
Henan Province ............. 43, 339, 557, 562, 597, 601, 619
high voltage direct current (DC) transmission line ........... 368
high-effiCiency power generation technology ............ 549
HongKong ...... 513-15, 586, 610,798 household appliance ownership .... 80,
81 Households .............................. 59, 79,
85, 88, 551, 767, 769, 775, 778 HTGR ................................... 271,794 Hubei .................................... 562, 564 hydro ................ See renewable energy hydro power ........ 614, 619, 652, 655 hydroelectric ....................... 105, 140,
162, 195, 659 hydropower potential ........... 215,270
I
!AEA ................. 382-83, 387, 438-40, 443,518, 620, 659-60, 794, 797
IEPE ................................. 21, 50, 794 IGCC ................ 130-32,137, 160-62,
192-94, 230, 233, 246-47, 256, 260-61, 273, 283-84, 296-98, 301, 304-07, 310, 313, 320, 348-50, 355,358,362-96,401-04,411-12, 418, 428-29, 432, 499, 549, 573, 716, 732-39, 744, 794
IIASA .............................. 100-01, 125, 508, 579, 583-585, 763, 794
income elasticity .............. 117-18, 128 increased power demand ............. 191 independent provincial
power grid ................................ 68 Indonesia ............................. 323, 367,
372-73,377-80, 430
industrial boilers and kilns .. 550, 553 industrial sector ....................... 62, 71 industrial wastewater ................... 109 industry .......................... , 5-11, 17-18,
21, 27, 35, 45, 51-52, 60-77, 83-87, 92, 95-97, 112, 117, 201-04, 224, 241, 270, 326-28, 364-65, 370-72, 381, 432, 437, 451-53, 489, 540, 545, 548, 551-53, 569, 577, 590-94, 598, 605-07, 654, 657, 726-27, 761, 772
inefficient scenario .................. 54, 56, 83,86,88,95, 116, 771-72, 778
Institute of Energy Policy and Economics ........... 21, 50, 794
integration of LCA and EIA ......... 492 Intergovernmental Panel on
Climate Change ............. See IPCC International Institute for Applied
Systems Analysis .......... See IIASA IPCC .................................... 320,340,
396, 437, 442, 795, 802 iron and steel industry ................... 76
J
Japan .................................. 11-12, 43, 64, 74, 214, 290, 318, 330, 367, 368, 372, 437, 557, 612, 752, 757-58, 791, 799
Jiangsu .................................... 60, 64, 381, 437, 557, 562-64, 578, 620
Jinan ............................ 12, 18,26, 65, 103, 283, 286, 321, 341-43, 472, 482-83, 486, 489-93, 496-98, 520, 526, 550, 573, 755, 758
Jincheng ............. 327-28, 333, 336-39 Jining ................................... 283, 286,
331,339-43,468,488,520,526
K
Korean Peninsula ........................... 43 Kyoto Protocol .... ................. 194, 441
INDEX 813
L
La Hague ...................................... 409 Laboratory of Energy Systems ...... 21,
756, 793, 795 large dams .................................. 590,
614-18,655,660, 735 risks and failures .................... 616
large point sources (LPS) ............ 568 largest power plants in
Shandong ................................ 467 LASEN ......... 21, 50, 664, 756, 793-95 LCA ................. 17, 23-25,30,34,169,
194, 259, 319-27, 328, 344, 347-69, 374, 381-97, 403-21, 425-36, 446-50, 492, 494, 499, 502-05, 512,516,583, 703, 710, 762, 795
LC/ ................................ 320, 399, 795 LCIA ..................................... 320, 795 Liaocheng ............................ 283,286,
331, 339-43, 468, 573 Life Cycle Assessment .......... See LCA Life Cycle Inventory assessment ....... .
......................................... SeeLCI Light Water Reactor ............. See LWR line reactance ............................... 280 Linear Programming (LP) ... 120, 795 liquefaction to LNG ..................... 372 Liquefied Petroleum Gas ..... See LPG Liquefied Petroleum Gas
chain ............................. See LPG LNG .......................... 96-97, 111, 133,
138, 192, 320, 323, 365, 366-68, 372-80, 406, 430, 433, 436, 795
load curve .............. 49-51, 89-92, 281 Local SOx Control (CLSC) .......... 291,
308,316 Longkou ....................... 285, 287, 288,
289, 322, 335, 339, 341, 348-50, 355,441-42,468,488, 782
losses due to pollution in China ... 477 Lotus Notes Database ............... 37-39 low level waste depository .......... 391 LP ............. See Linear Programming
814
LPG ....................... .46, 53,64, 71-73, 77, 80, 84, 94, 588, 592, 609, 612-13,644-46,649, 773-75, 795
LPS ................ See large point sources LWR ............................. 320, 323, 385,
387, 390, 396, 407-08, 430, 795
M
MACCS calculations ......................... . ........................... 624-25, 631, 641
MAGES ........................................... 21 marginal costs ..................... 119, 139,
145-49, 166, 192, 311, 450-51, 568, 585
MARKAL .......................... 22, 101-03, 109,112-30,134,137-41,169-70, 175-76, 183-97, 707-09, 715, 762, 795
MARKAL-China ........................... 175 Market Allocation Model
................................ SeeMARKAL Massachusetts Institute of
Technology (MIT) ............ See MIT mathematical formulation of
ETM ........................................ 279 MCDA ..................... 18, 25,194,215,
259-63, 267-68, 319-21, 325-26, 347, 368, 401-04, 408-31, 434, 446,499-00,574,651-52,661-75, 679-83, 686-87, 700-03, 707, 710, 721-23, 727, 756, 763, 795
MEDEE2 ........................................ 50 MEDEE3 ........................................ 50 MEDEE-S ........................ 21, 49, 54,
115,118-19,196, 761 methane emissions ................. 331-33,
.................................. 369-71, 379 middlings ......... 329-30, 333, 337, 405 milling .................................. 389, 443 mining .................... 225,327-29,344,
38~39~ 43~ 44~ 443, 59~ 594
INDEX
MIT ................................. 3, 11-12, 17, 22, 23, 27, 197, 201-02, 212-13, 273, 574, 669, 700, 751-53, 757-59,762,796
mixed coal .................................... 333 Modeling areas ......................... .... 465 Modernization strategies ............. 261,
........................................ 266, 269 monetary valuation ...... 452, 460, 583 monetized impacts ........................ 572 morbidity ................ .457, 458, 513-14 morbidity effects ........... 447, 458, 484 mortality ........................... 24, 399-00,
410-11, 425, 447, 450, 454-63, 479-97, 500, 506, 509-14, 523, 534, 572-75, 579, 584-85, 625, 672, 722, 734-44
mortality due to outdoor air pollution ............ 400,456,480
Multi-Attribute Tradeoff Analysis ................................... 202
Multi-Criteria Decision Aiding ...... 25 Multi-Criteria Decision Analysis
.................................... SeeMCDA
N
N20 .............................. 320, 352, 358, 373,406, 411-12, 426
Nanding .......................... 331, 337-39, 340-43, 468, 487, 492, 573
natural gas chain ........................ 325, 365-68, 375-80, 396-97, 406-08, 430, 433, 609-11, 646, 649-52, 655-56, 735
natural gas cost uncertainty ........ 226 natural gas markets ...................... 192 network power flow .............. 277, 279 new generation options ........ 246, 737 NGCC ........................... 247,261, 796 Ningxia ................. 366, 383, 442, 477 non-discordance test ............ 675, 677 nonferrous metals ........................... 63 NOx emission rates ...................... 143,
146, 149-51, 361, 396-98, 405, 408,419-20,429, 732
NOx emissions ............................. 141, 144, 218, 246-47, 261, 294, 362, 377, 392, 404-05, 420, 429, 447-48, 467, 506, 732
NPP ................................ 381, 384-85, 407, 443, 625-28, 629, 632-36, 639, 659, 796
nuclear chain ................................ 320-23, 381-91, 395-98, 401-02, 407-10,
422, 430-433, 443, 492, 588, 620, 646-47, 652, 763
energy ............................ 138,195, 753, 791, 796
power ......................... 67, 94, 130, 138,161,172,230,233,275, 283, 305, 308, 311, 316, 323, 381-82,387,390,407,411-12,418,438,448,492-93, 540,544,574,583,587-88, 620-21, 627, 645, 650-52, 656-60, 763
reactors in China ... ................. 620
o O&M cost ..... 278, 284, 287, 785, 788 Ocean Oil Corporation .................. 94 OECD ......................... l, 198, 437-39, 589,609,612,618,644-59, 794, 796 offshore wind ................... 270-71, 746 oil chain ................................ 605, 654 oil spills ........................................ 609 optimization modeling .................. 153 optimization of demand .................. 94 overall damage estimates ............. 479
p
paper industry .......................... 73-75, 437-39, 583, 660
Paraguay .............................. 521, 529 particle emission rates ...................... .
................ See TSP emission rates
INDEX 815
particulates emissions ................. 108, 217-18, 272, 320-22, 340, 350, 362, 392, 421, 426, 431-32, 447-48, 455, 463, 474, 481, 507-08, 533-34, 573, 579, 731-33, 745
Paul Scherrer Institute .. ......... See PSI PE ...................... See primary energy Peak Load Management (PLM} .... 68,
236-37, 258, 796
per capita residential energy consumption .................. 80
performance matrix ...... 661, 669, 681 petrochemical industry ................... 66 PFBC ............ 162, 322, 428, 549, 796 Pingyin Aluminum Plant ................ 63 pipeline transport ......................... 370 PM2.5 ..................................... 217-18,
448, 456-57,507-11, 521 PMI0 .............................. 216-17, 241,
246-48, 251-53, 256, 260, 448, 455-58, 467, 486-88, 506-07, 511, 520-23, 526-30, 533-34, 581, 584, 796
Poland .......... 328, 441, 521, 528, 658 Policy Research Centre for
Environment & Economy ................................... See PRCEE
pollution pontrol... ........ 191, 547, 549 pollution control costs .................. 451 population ................................ 57, 61,
64, 104, 473-75, 510, 580, 627, 632-33, 730, 736, 769-70
power generation in Shandong .... 340 power generation technologies ... 280,
282, 317, 573 power plants ....................... 109, 332,
340,348,551 power transmission network ........ 280 PPPGNP ................. .461, 526-29, 797 PRCEE .................................. 12, 322,
327, 334, 339-40, 352, 797 precipitation ................... .470-71, 794 prepared coal ....................... 235, 258 Pre-Specified Pathway (PSP)
program ................................. 212
816
pressurized fluidized bed combustion power plant .................. See PFBC
pressurized water reactor .... See PWR price of coal .......................... 47, 138,
166,225,287,432 primary sector .. 56, 57, 58, 61, 62, 82 primary-energy .............. 99, 128, 129 Principal Investigators ..... 26, 32, 763 probabilistic safety assessment ... 437,
582, 622, 624, 645-46, 650-51, 655-58, 763, 797
PROMETHEE .............................. 664 PSA ............................ 622-23, 643-46,
652, 655, 658-59, 797 PSI ................................ 12, 17, 22-26,
110, 115, 120, 127, 197,436-37, 453, 499, 578, 582, 588-89, 658, 681, 717, 724, 753-756, 759, 762-63, 797
pulverized coal .................... 192,230, 233, 236, 241, 246, 273, 283, 294, 297-02, 315-17, 320-22, 734, 738-39
Purchase Power Parity (PPP) ..... 513 PWR. ................ 323, 381--85, 390-92,
443,620-22, 627-38, 641-42, 797
Q
Qingdao ........................... 27, 78, 270, 283, 286, 323, 339-43, 365, 368, 372, 430, 468, 486, 520, 526, 622, 626-27, 632-42, 646, 650-52
Qinghai ......................... 366,597,619
R
RA ................................... 17,23, 169, 582, 587, 703, 707, 731,755-57, 763, 797
radiation ............................... 448, 799 radioactive solid wastes ....... 394, 433 radionuclide group ....... 629, 634, 635 RAINS ............................. 450, 508-09,
535-38,541-45,556,568-69,576, 579-85, 763, 797
INDEX
Rains-Asia impact assessment approach ................................ 561
raw coal .............................. 64-66, 69, 235-36, 287, 328-30, 333-38, 345-46, 551, 554
RD&D Technology Development ........................... 193
reference coal power plant ......... 485, 489, 492
Reference Energy System ............ 103, 112,118,121, 797
regasification....... ..... ... ... ..... ... ..... 373 regional air pollution information and simulation ..... 508, 535, 576, 797 release sequences ......................... 632 renewable energy
biomass 4, 5, 80, 108, 138, 273, 434, 446, 588
hydro 4-5, 15, 34, 234, 324, 356, 445, 496, 540-41, 544, 576, 587-90, 614-18, 644-46,650-51,655-58, 715
solar energy ................................ 4 sources .................................... 195 wind energy .......... 4, 15, 397, 433 wind power ....................... 15, 395 windfarms ................................. 15
RES ...... See Reference Energy System reservoirs in China ....................... 615 restricted activity days ................. 459 retirement of small and low
efficiency units ....................... 548 retrofit ................................... 235, 670 risk
conclusions ............................. 654 energy chain comparisons ...... 644
RiskAssessment ...................... See RA risks for the Qingdao and Yantai sites
................................................ 636 Robust Uniform World Model
(RUWM) ................................. 522 run-of-mine (ROM) ...................... 327 Russian natural gas ................ 97, 370 RUWM ............................................... .
See Robust Uniform World Model
s SAG
.. See Stakeholders Advisor Group Scenario Construction ................... 54 scrubbers ....................... 99, 130, 131,
137-38, 161-63, 166-67, 178, 193-94,230, 250, 332, 351, 399, 414,418-19,425, 428-29,432,444, 501,707,714-15, 722, 737-46
Sellafield ....................................... 409 Sensitivity analysis ....................... 402 SEPA ............................... 12, 17, 384,
459, 511, 549, 551, 584-85, 757, 797-98
SEPCO ......................... 12-13, 35, 41, 44, 87-92, 98, 215, 219, 228-29, 272, 274, 280, 318, 321-23, 337-41, 344, 348-62, 396, 421-23, 427-29, 467-68, 479, 621, 727, 768, 798
SEPRl ................................ 12, 26, 33, 35-36, 41, 321, 331-33, 337-44, 348-53, 668, 728,752, 798
SESAMS .............................. 212, 274, 664, 679, 700, 798
Shaanxi ......................... 366, 383, 442 Shandong Aluminum Company (SAC)
.................................................. 63 Shandong Electric Powe Group
Corporation ............... See SEPCO Shandong Electric Power Research
Institute ........................ See SEPRI Shandong electricity demand ....... 499 Shandong grid .................... 229,241,
325, 344, 351-52, 356, 385, 403, 406, 427-29, 732
Shandong Options and Strategies 227 Shandongpower plants ...... 321,327, 344, 347, 403, 428, 482, 732
INDEX 817
Shandong province .................. 43, 48, 52, 56-68, 73-75, 89, 94, 98, 178, 182,275, 276, 281, 299, 365, 385, 395, 433, 449, 467, 490, 493, 499, 525, 534, 542, 545, 562, 569, 570, 577, 592, 603, 621-22, 625, 632-33, 642, 650-52, 655, 667, 704, 707-08, 729, 735, 741, 745, 766
Shandong uncertainties ................ 218 Shandong's energy profile .............. 44 Shanghai ......................... 60, 82, 102,
214, 365-67, 381, 458, 478, 520, 526, 550, 557, 564, 606, 619, 755, 764,769
Shanxi .......................... 215, 224, 228, 275-76, 285-89, 294, 301-02, 308, 322-39, 345-49, 358, 361-62, 383, 403, 414, 423, 426-28, 432, 439, 441-43, 493, 500, 512, 557, 564, 597, 601-04, 619, 652-54, 707, 732,798
Shengli Oil Field .......... 68, 69, 94, 96 Shenyang ...................... 456, 457, 509 Shimantan dam ............................. 619 Sichuan ........................... 366, 383-84,
557, 564, 591, 610 Simple Uniform World Model
(SUWM} .................................. 518 Simplified Life Cycle Impact
Assessment ..................... See LClA S02 Emissions ............................. 122 S02 emission rates .......... 163-64, 175,
178, 182, 359, 360, 397-98, 405, 408,417-19,428
S02 emissions ...................... 131, 132, 144, 149, 153-58, 165, 173-74, 178, 183-86, 189-93,217,244-47, 254, 260, 266, 269, 290-91, 297, 311, 332, 349, 359, 375, 418-19, 428,447,462,479,497,506,512, 535, 545-55, 570, 577, 716, 720, 721, 732-34, 737-42
818
Social and Economic Development ............................. 59
Socio-economic Structure ........... 103 solar energy ..... See renewable energy Solid waste production ........... 363-64,
376, 400, 422 SOx Control Zones (SCZ)290, 301,
315 SOx emissions .............. 275, 277, 283,
287, 291-93, 297-99, 302, 305, 308,311,315-16, 716
Spentfuel disposal ...................... 391 Spontaneous combustion of
coal ........................................ 333 Sr group ........................................ 623
Stakeholders ........... 5-9,17-22, 25-27, 30, 53, 100-02, 152, 169, 196, 201-05,208- 210,215,271-73, 406, 574, 578, 661-63, 666-69, 677-80, 684, 687, 700, 704-06, 710, 714, 717, 723, 726-29, 744-48, 752, 762-63
Advisory Group .......... 17, 27,202, 204,666-69,680,687,797
community ................................ 11 meetings ...................... 7, 8, 26, 30 symposium ................................ 18
Standard of Living .............. 57, 59, 94 State Environmental Protection
Administrationxx, 12, 20, 23, 584, 668, 757, 762, 798
steam coal ........................... 192, 224, 323, 327-30, 333, 345-47, 351, 405, 413, 441
steam coal cost uncertainties ....... 224 Steering Committee ... 8,16, 751, 797 Sulfur chemistry ........................... 473 Sulfur dioxide emissions .............. 109 Sulfur Taxes .................................. 131 Sulfur-Caps .................................. 147 Surmesure .............. 682, 685, 688-700
INDEX
sustainability ....................... 2-11, 25, 274, 447, 574, 661-62, 66-67, 700, 751, 763, 798
sustainable development ............................. 47 economic growth ............... 57, 58 energy ............................... 11, 15,
27,201, 270, 663, 728 power generation .................. 663
Swiss Federal Institute of Technology ............. 3, 12, 756-57
Swiss LCA study ................... 328, 359 system peak load .................. 281, 282
T
TAB ..................................... 8, 16, 753 Tarim Basin .................................. 366 TAX Case .............................. 290, 297 Technical Advisory Board .... See TAB technology
assessment ...................... 13 7, 164 costs ................................ 159, 232 diffusion .................................. 195
textile industry .. ........................ 64, 65 TGP .......... See Three Gorges Project Thailand ............................... 521, 527 thermal grid .................................... 95 Three Gorges Project ... 614, 764, 798 Tianjin .................... 60, 214, 366, 764 Tibetan plateau ............................. 562 top-down ....................... See approach tradeoff analysis ..................... 201-12,
215-18,246 traffic ...................................... 78, 610 transmission lines .................... 23, 68,
277-82, 332, 344, 351-52, 406, 708, 762, 784
transportation sector ...................... 77 "true" cost of electricity generation
............. 446, 493-95, 572-74, 734 Tsinghua University ................ 12, 22,
101-02, 547, 581, 585, 758, 762-64,799
TSP emission rates ................. 362-63, 399,410,413,421
UCTE .......................... 328, 348, 356, 360, 391, 396, 415, 418, 427-29, 441-44,799
University o/Stuttgart ..... 581-82, 763 University of Tokyo ............. 3, 11, 12,
23, 751, 758, 762, 799 uranium ....................... 123,271, 323,
382-90, 393, 402, 407-09, 430-43, 798,803
uranium enrichment ............. 407,438 Uranium Institute (UI) ................. 382 urbanization ....... 57-60, 77-79, 83, 97 USA ............................ 11-12, 17, 328,
370, 428, 438, 443, 458, 521, 528, 556, 580-85, 590-94, 597, 609, 612-14, 658, 751-53, 757-59, 793, 796
Value of Statistical Life (VSL) .... 460, 514
vitrification facility ... .................... 384 VSL ......... See Value of Statistical Life VVER ........................... 381,384,390,
621, 627-30, 799 waste recovery................................ 74 waste-to-energy technologies ...... 271 weighting process ...... 18, 661, 679-80 Westinghouse ....................... 385, 443 willingness-to-pay ................ See WTP wind energy ..... See renewable energy windfarms ........ See renewable energy wind power ...... See renewable energy wind power potential in
Shandong ............................... 395 Windrose Trajectory Model .. ............ .
See ...................................... WTM World Bank ........................ 45, 95, 98,
437-39, 459, 478-79, 511-15, 545-46, 580-85
World Business Councilfor Sustainable Development ........ 16,
INDEX 819
751, 799 World Trade Organization .. See WTO WTM ............................... 454, 464-66,
469-72,510,525-29,585, 799 WTO ................. 61, 96, 272, 666, 799 WTP ................................ 460, 478-79,
506, 513-17, 572, 575, 799 Xegroup ....................................... 623 Xinjiang ......................... 15, 138, 323,
345, 366-68, 370, 373-74, 377-82, 40~ 43~442, 732, 799
Xinwen ............... 286-89, 327, 332-37 Xishan .............................. 327, 336-38 Yangjiang ............................. 381, 620 Yangquan ... 327,331-33,336-38,441 Yankuang ................. 328, 331, 335-37 Yantai .................................. 270, 283,
285, 339-43, 468, 488, 521, 526, 610, 622, 626-27, 632, 633, 636, 639, 642, 646, 650, 782
Yanzhou .......................... 286-89, 299, 327-29, 332-33, 335
Years of Life Lost ............... See YOLL Yellow River .......................... 43, 103,
215,270,273-74 Yellow Sea .............................. 43, 103 Yibin ........................................ 383-85 YOLL ................................... 320, 325,
399, 410-11, 425, 455-64, 479, 492-93,496,502-06,509-10,514, 523, 534, 572-74, 683, 733-34, 799,804
Yun-nan ................................ 547, 562 Zhejiang ............................... 381, 557,
562-64, 597, 601, 620, 765 Zhejiang Qinshan ......................... 381 Zhou-xian power plant ................. 568 Zhumadian Prefecture .................. 619 Zibo ................................. 283-89, 294,
299, 327-28, 331, 335-37, 340