能源供给与能源消费的系统动力学模型
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
近年来中国能源供给和能源消费变化趋势受到普遍关注,研究方法也在不断改进。本文采用系统动力学的方法,根据原有能源供给Hubbert理论与能源消费分解法的原理,构建系统动力学模型,将原来Hubbert曲线与分解法的解析模型转变成动态模拟模型,其中能源消费分解法的系统动力学模型还增加了预测功能。通过对新构建系统动力学模型的模拟结果与原模型进行比较,给出系统动力学模型的预测能力检验和方法优势分析。
     另外,中国能源供给和能源消费的增长趋势是能源研究中有必要关注的重要问题。本文根据新构建的系统动力学模型,结合中国的具体情况,预测中国能源供给和消费的变化趋势,分别给出中国煤炭和石油的产量曲线、高峰预测和能源消费的近期预测及其影响因素的贡献率,并对中国主要能源的供求关系进行分析,给出相关的政策建议。
     论文的意义在于发挥系统动力学的方法优势,增强原有能源研究模型的动态模拟和预测能力,并用新构建的模型分析和预测现实中的能源供给和消费问题,对方法改进和现实问题的解释都有一定的积极作用。
     论文研究内容主要包括以下六个方面:
     (1)综述能源供给Hubbert理论与能源消费分解法的研究进展。对Hubbert理论的研究进展作了比较详尽的梳理,包括Hubbert理论内容、在能源产量预测中的应用,以及成为新热点的曲线形状问题等。对能源消费分解法的综述包括早期的研究成果、方法局限、方法的改进和主要研究成果的特征等,以及各国学者对中国能源消费的分解研究。
     (2)构建能源供给Hubbert曲线的系统动力学模型。通过分析Hubbert曲线方法中与储量、产量相关因素的因果关系,给出各因素间的反馈环路及分析。在反馈环路分析的基础上给出Hubbert曲线的系统动力学模型,用以描绘某地区石油等不可再生能源的产量曲线,其中包括产量高峰的预测,并以美国的相关石油数据检验模型的预测能力。
     (3)构建能源消费分解法的系统动力学模型。将解析算法支持的分解法模型转变为系统动力学的动态模拟模型,可以通过分解过去年份的能源消费增量得到影响因素的贡献率,还能模拟未来能源消费增量及影响因素的效应。文中结合辽宁省的有关数据,模拟辽宁省能源消费影响因素的效应值,并与完全分解法的计算结果进行比较,以证明系统动力学模型的模拟分解能力。
     (4)给出能源消费系统动力学模型的扩展模型。扩展模型包括煤炭、石油消费分解的系统动力学模型,用以模拟煤炭、石油未来消费的变动趋势,分析过去年份与未来一定期限内经济增长与能源强度等因素对消费增量的贡献程度。
     (5)预测中国煤炭和石油的产量变化趋势与高峰。本文采用能源供给Hubbert曲线的系统动力学模型模拟计算中国煤炭、石油的产量变化,绘制出中国煤炭和石油的产量曲线,并预测二者的产量高峰及高峰出现的年份。文中利用模型的参数试验功能对最终可采储量和成长系数进行情景分析,给出不同情景下煤炭和石油产量的浮动区间。
     (6)分析和预测中国能源消费的需求水平。文中采用能源消费分解的系统动力学模型,结合中国的能源消费分解状况,预测未来中国能源消费的变动及影响因素的贡献率。文中还应用扩展模型模拟和预测煤炭、石油消费的变化趋势以及因素贡献率,量化分析经济增长与能源强度对消费量变化的具体影响。
     论文的主旨是将解析算法的模型改进成具有动态模拟功能的系统动力学模型,增加模型的功能,降低计算成本。应用系统动力学模型对现实问题的讨论,一方面能促进中国主要能源供求的量化分析,为政策制定提供较科学的依据;另一方面是为今后系统动力学及其模型的应用和推广做一个铺垫。
In recent years, the issues of the energy supply and energy consumption in China have been the focus of both academic researchers and practitioners, with the progress of method modification. Based on the previous methods for energy supply and energy consumption, the System Dynamics is adapted to modify the Hubbert curve of energy supply and decomposition method of energy consumption in this dissertation. Therefore, the analytic models are transformed into the ones supported by the dynamic simulated arithmetic and forecasting function is added to decomposition model of energy consumption. By comparing the simulated results from System Dynamics models with that of original analytic models, tests of forecasting capability and method advantages for the new System Dynamics models are carried out.
     Moreover, it is the significant issues on China's energy supply and energy consumption in future. According to the situation in China, the System Dynamics models developed are utilized to simulate and analysis the changing trends for China's energy supply and consumption, including the Hubbert cuves for the main energy production, peak prediction, and tendency of main energy consumption with contributions by related factors. The related energy policies are given according to the equilibrium analysis on China's energy supply and consumption.
     The main objectives of this dissertation are as follows. The dynamic stimulation and forecasting ability are determined by the System Dynamics models and then energy supply and energy consumption are analyzed and forecasted by these new models, which have a positive effect on method modification and explanation for the reality.
     There are six main sections in this dissertation shown below.
     (1) Literatures on the Hubbert theory of energy supply and the decomposition method of energy consumption are reviewed. The former includes main theory body, applications as well as the shapes of Hubbert curve which is focused on recently. The latter includes the early achievements in researches, limitions and modifications of some methods, feature of main researches and the discussions on Chinese energy consumption.
     (2) Establishing a System Dynamics model for the Hubbert curve of energy supply. By analyzing the causality of reserves, production and other related factors of Hubbert curve, the feedback loops and their analysis are presented. Then the System Dynamics model of Hubbert curve is established to describe the production curve of nonrenewable energy in some regions and to forecast the production peak. In addition, the oil production data in U.S. is used to test the predicting capability of the new System Dynamics model.
     (3) Establishing a System Dynamics model for the decomposition method of energy consumption. The original model solved by analytic arithmetic can be transformed into the dynamically simulated model, sothat contributions of influential factors could be determined by decomposing the previous annual energy consumption change. Moreover, future energy consumption changes and factors'effects can be simulated by the related data of Liaoning Provinvce, with the decomposed results of the factors'effects compared with that of complete decomposed method, which shows that System Dynamics model performs better.
     (4) The extended System Dynamics models of energy consumption are presented, such as the decomposition models for the changes of coal and oil consumption. These two models are employed to simulate the tendency of coal and oil consumption, and to discuss the impacts of economic growth and energy intensity on the changes of coal and oil consumption.
     (5) Forecasting the changing tendency and production peak for Chinese coal and oil. The System Dynamics model of Hubbert curve developed in this dissertation is adapted to simulate China's coal and oil production to draw the production curves, to forecast peak productions and their corresponding years. The forecast and scenario analysis set by the growth rate "a" and ultimate reserves show the scopes of peak production.
     (6) Analyzing and Forecasting the future demand of China's energy, coal and oil consumption. This dissertation adapts the System Dynamics model of energy consumption to decompose China's energy consumption with related factors and simulate its future change in short term. Moreover, changing tendencies and factors' contribution for China's coal and oil consumption is forecasted by the extended models of energy consumption, in order to evaluate the effects of economic growth and energy intensity.
     The aims of this dissertation are setting System Dynamics models and make a discussion on China by models. The System Dynamics models presented in this dissertation have the advangtage of the more function and lower working cost than before. The discussion on China can provide the scientific base for energy policy-making according to the analyses on source demand and supply, as well as reinforce the application of System Dynamics.
引文
1. 中华人民共和国国家统计局.2007年国民经济和社会发展统计公报[R],[EB/OL].http://www.stats.gov.cn/tjgb/ndtjgb/qgndtjgb/t20080228_402464933.htm,2008,2,28.
    2. 国家统计局.中国能源统计年鉴[M],北京:中国统计出版社,2007.
    3. Brandt A R. Testing Hubbert [J], Energy Policy,2007,35(5):3074-3088.
    4. Zittel W. Analysis of the UK Oil Production [J], Ottobrunn,22nd February 2001.
    5. Szklo A, Machado G, Schaeffer R. Future oil production in Brazil—Estimates based on a Hubbert model [J], Energy Policy,2007,35 (4):2360-2367.
    6. Robinson B. Global Oil Vulnerability and the Australian Situation—A background paper for WA State Sustainability Strategy [A], June 2002 (Dept of the Premier and Cabinet, http://www.sustainability.dpc.wa.gov.au/docs/backgroundpapers.htm)
    7. Al-Husseini M. The debate over Hubbert's Peak:a review [J], GeoArabia,2006,11(2): 181-210.
    8. Hallock J L, Tharakan P J, Hall C A S, Jefferson M, Wu W. Forecasting the limits to the availability and diversity of global conventional oil supply[J], Energy,2004,29 (11): 1673-1696.
    9. Wood J H, Long G, Morehouse D F. Long term oil supply scenarios:the future is neither as rosy or as bleak as some assert [R], Energy Information Administration, 2000.
    10. Laherrere J H. Multi-Hubbert Modelling[R], [EB/OL].[2006-06-15].http://www. hubbertpeak.com/laherrere/multihub.htm.
    11. Azadeh A, Ghaderi S F, Sohrabkhani S. Annual electricity consumption forecasting by neural network in high energy consuming industrial sectors[J], Energy Conversion and Management,2008,49(8):2272-2278
    12. Lau H C W, Cheng E N M, Lee C K M, Ho G T S. A fuzzy logic approach to forecast energy consumption change in a manufacturing system[J], Expert Systems with Applications,2008,34(3):1813-1824.
    13. Pao H T. Comparing linear and nonlinear forecasts for Taiwan's electricity consumption[J], Energy,2006,31(12):2129-2141.
    14. Adams F G, Shachmurove Y, Modeling and forecasting energy consumption in China: Implications for Chinese energy demand and imports in 2020[J], Energy Economics, 2008,30(3):1263-1278.
    15. Howarth R B. Energy use in US manufacturing:the impacts of the energy shocks on sectoral output, industry structure and energy intensity [J], The Journal of Energy and Development,1991,14(2):175-91.
    16. Park S H. Decomposition of industrial energy consumption-an alternative method [J], Energy Economics,1992,14(4):265-70.
    17. Boyd G A, Hanson D A, Sterner T. Decomposition of changes in energy intensity-a comparison of the Divisia index and other methods [J], Energy Economics,1988,10(4): 309-312.
    18. Liu X Q, Ang B W, Ong H L. The application of the Divisia index to the decomposi-tion of changes in industrial energy consumption [J], The Energy Journal,1992,13(4): 161-177.
    19. Ang B W, Lee S Y. Decomposition of industrial energy consumption:some methodol-ogical and application issues [J], Energy Economics 1994,16(2):83-92.
    20. Sun J W, Quantitative analysis of energy consumption, efficiency and savings in the world,1973-1990[A], Turku School of Economics Press, series A-4:1996.
    21. Hubbert M K. Nuclear energy and the fossil fuels [A], In:Meeting of the Southern District, Division of Production, American Petroleum Institute. Shell Development Company, San Antonio, Texas.1956.
    22. Hubbert M K. Techniques of prediction with application to the petroleum industry[A], In:44th Annual Meeting of the American Association of Petroleum Geologists, Shell Development Company, Dallas, TX, p.43.1959.
    23. Wikipedia. Hubbert peak theory, the free encyclopedia[R], [EB/OL] http://en.wikipedia. org/wiki/Hubbert_ peak_theory.
    24. Campbell C J. Oil Crisis [M], Essex:Mult-science Publishing Company and Petrocon-sultants,2005.
    25. Hubbert M K. Energy Resources [A], In, P. Cloud (Ed.), Resources and Man. Freeman, San Francisco,1969,157-242.
    26. Campbell C J. The Coming Oil Crisis [M], Essex:Mult-science Publishing Company and Petroconsultants,1997.
    27. Deffeyes K S. Hubbert's Peak-The Impending World Oil Shortage [M], Princeton: Princeton University Press,2003.
    28. Duncan R C, Youngquist W. Encircling the peak of world oil production [J], Natural Resources Research,19998(3):219-232.
    29. Ivanhoe L F. Future world oil supplies:there is a finite limit [J], World Oil,1995 216(10):77-88.
    30. Simmons M R. ASPO Workshop [A],2nd International Workshop on Oil Depletion, May 26,2003.
    31. Duncan R, Youngquist W. The World Petroleum Life-Cycle [A], PTTC Workhop "OPEC Oil Pricing and Independent Oil Producers", California,1998
    32. Hirsch R L. The Inevitable Peaking of World Oil Production [J], The Atlantic Council Bulitin,2005, XVI (3).
    33. Zittel W, Schindler J. Future World Oil Supply[R], [EB/OL] http://www.peakoil.net/ publications/future-world-oil-supply,2002
    34. GEO 3005:Earth Resources[R], [EB/OL] http://www.geo.umn.edu/courses/3005/ resource. html
    35. Strahan D. Coal:Bleak outlook for the black stuff [J], New Scientist,2008,19(1): 38-41.
    36. Maugeri L. Oil:Never Cry Wolf—Why the Petroleum Age Is Far from over [J], Science,2004,304(20):1114-1115.
    37. Kavalov B, Peterves S D. The future of coal [R], [EB/OL] ie.jrc.ec.europa.eu/public-ations/scientific_publi-cations/2007/EUR22744EN.pdf
    38. Bentley RW. Global oil & gas depletion:an overview [J], Energy Policy,2002,30(3): 189-205.
    39. Hirsch R L. The shape of world oil peaking:learning from experience[R], Technical Report,2005.
    40. Bardi U. The mineral economy:a model for the shape of oil production curves [J], Energy Policy,2005,33 (1):53-61.
    41. Reynolds D B. The mineral economy:how prices and costs can falsely signal decree-sing scarcity [J], Ecological Economics,1999,31 (1):155-166.
    42. 翁文波.预测论基础[M],北京:石油工业出版社,1984.
    43. 陈元千.广义翁氏预测模型的推导与应用[J],天然气工业,1996,16(2):22-26.
    44. 陈元千,胡建国.对翁氏模型原建模的回顾及新的推导[J],中国海上油气(地质),1996,10(5):317-324.
    45. 陈元千,胡建国.预测油气田产量和可采储量的Weibull模型[J],新疆石油地质,1995,16(3):250-255.
    46. 胡建国,陈元千,张盛宗.预测油气田产量和可采储量的新模型[J],石油学报,1995,16(1):79-86.
    47. 胡建国,陈元千Hu-Chen(胡一陈)预测模型的建立与应用[J],天然气工业,1997,17(5):31-34.
    48. 陈元千,袁自学.对数正态分布(Log-Normal-Distribution)预测模型的建立和应用[J],石油学报,1997,18(2):84-88.
    49. 袁自学,陈元千.预测油气田产量和可采储量的瑞利(Rayleigh)模型[J],中国海上油气(地质),1996,10(2):101-105.
    50. 陈元千,李从瑞.广义预测模型的建立与应用[J],石油勘探与开发,1998,25(4):38-41.
    51. Redorbit. Feng L Y, Li J C, Pang X Q, etc. Peak Oil Models Forecast China's Oil Supply,Demand[EB/OL],http://www.redorbit.com/news/business/1254311/peak_oil_m odels_forecast_chinas_oil_supply_demand/
    52. Bossanyi E. UK primary energy consumption and the changing structure of final demand [J], Energy Policy,1979,7(6):253-8.
    53. Huntington H G, Myers J G. Sectoral shift and industrial energy demand:what have we learned [A], In:Farunqui A, Broehl J, Gellings CW, editors. The changing structure of American industry and energy use patterns. Colombus, OH:Battelle Press,1987: 353-88.
    54. Myers J, Nakamura L. Saving energy in manufacturing [M], Cambridge, MA:Ballinger, 1978.
    55. Reitler W, Rudolph M, Schaefer H. Analysis of the factors influencing energy consumption in industry-a revised method [J], Energy Economics,1987,9(3):145-8.
    56. Hankinson G A, Rhys J M W. Electricity consumption, electricity intensity and industrial structure [J], Energy Economics,1983,5(3):146-52.
    57. Li J W, Shrestha R M, Foell W K. Structural change and energy use:the case of the manufacturing sector in Taiwan [J], Energy Economics,1990,12(2):109-115.
    58. Torvanger A. Manufacturing sector carbon dioxide emissions in nine OECD countries: 1973-87[J], Energy Economics,1991,13(3):168-86.
    59. Ang B W. Decomposition methodology in industrial energy demand analysis [J], Energy,1995,20(11):1081-95.
    60. Ang B W, Zhang F Q. A survey of index decomposition analysis in energy and environmental studies[J], Energy,2000,25(12):1149-1176.
    61. Tornqvist L, Vartia P, Vartia Y. How should relative changes be measured? [J], The American Statistician,1985,39(1):43-6.
    62. Sato K. The ideal log-change index number [J], The Review of Economics and Statistics,1986,58(5):223-8.
    63. Wade S H. Measuring Change in Energy Efficiency for the Annual Energy Outlook 2002 [R], [EB/OL] Energy Information Administration, Washington, D.C. http://www. eia.doe.gov/oiaf/analysispaper/efficiency/pdf/efficiency.pdf
    64. Tedesco L, Thorpe S. Trends in Australian Energy Intensity 1973-74 to 2000-01 [R], ABARE Report 03.9 for the Ministerial Council on Energy, Canberra,2003
    65. Ang B W, Decomposition analysis for policymaking in energy:which is the preferred method? [J], Energy Policy,2004,32(9):1131-1139.
    66. Ang B W. The LMDI approach to decomposition analysis:a practical guide [J], Energy Policy,2005,33(7):867-871.
    67. Lermit J, Jollands N. Monitoring Energy Efficiency Performance in New Zealand:A Conceptual and Methodological Framework [M], Wellington:National Energy Efficiency and Conservation Authority,2001.
    68. Jenne C, Cattell R. Structural change and energy efficiency in industry [J], Energy Economics,1983,5(2):114-23.
    69. Howarth R B, Schipper L, Andersson B. The structure and intensity of energy use: trends in five OECD nations [J], The Energy Journal,1993,14(2):27-45.
    70. Ang B W, Zhang F Q. Inter-regional comparisons of energy-related CO2 emissions using the decomposition technique [J], Energy,1999,24(4):297-305.
    71. Shrestha R, Timilsina G R. Factors affecting CO2 intensities of power sectors in Asia:a Divisia decomposition analysis [J], Energy Economics,1996,18(4):283-293.
    72. Shrestha R, Timilsina G R. A Divisia decomposition analysis of NOx emission intensities for power sector in Thailand and South Korea [J], Energy,1998,23(6): 433-441.
    73. Greening L A, Davis W B, Schipper L. Decomposition of aggregate carbon intensity for the manufacturing sector:comparison of declining trends from 10 OECD countries for the period 1971-1991 [J], Energy Economics,1998,20(1):43-65.
    74. Proops J L R, Faber M, Wagenhals G. Reducing CO2 emissions:a comparative input-output study for Germany and the UK [M], Berlin:Springer,1993.
    75. Chung H S. Industrial structure and source of carbon dioxide emissions in East Asia: estimation and comparison [J], Energy & Environment,1998,9(5):509-33.
    76.高振宇,王益.我国生产用能源消费变动的分解分析[J],统计研究,2007,24(3):52-57.
    77.马晓微,刘兰翠.中国区域产业终端能源消费的影响因素分析[J],中国能源,2007,29(7):35-38.
    78. Shiu A, Lam P L. Electricity consumption and economic growth in China [J], Energy Policy,2004,32(1):47-54
    79. Zou G L, Chau K W. Short-and long-run effects between oil consumption and economic growth in China [J], Energy Policy,2006,34(18):3644-3655.
    80.韩志勇,魏一鸣,焦建玲等.中国能源消费与经济增长的协整性与因果关系分析[J],系统工程,2004,22(12):17-21.
    81. Garbaccio R F, Ho M S, Jorgenson D W. Why has the energy-output ratio fallen in China? [J], The Energy Journal,1999,20(3):63-91.
    82. Fisher-Vanden K, Jefferson G H, Liu H M, Tao Q. What is driving China's decline in energy intensity? [J], Resource and Energy Economics,2004,26(1):77-97.
    83. Hu J L, Wang S C. Total factor energy efficiency of regions in China[J], Energy Policy, 2006,34(17):3206-3217.
    84. Smil V. China's Energy [R], Report Prepared for the U.S. Congress Office of Technology Assessment, Washington, DC,1990.
    85. Kambara T. The energy situation in China [J], China Quart,1992 (131):608-636.
    86. Huang J P. Industrial energy use and structural change:a case study of the People's Republic of China [J], Energy Economics,1993,15(2):131-6.
    87. Sinton J, Levine M. Changing energy intensity in Chinese industry:the relative importance of structural shift and intensity change [J], Energy Policy,1994,22(3): 239-55.
    88. Lin X, Polenske K R. Input-output anatomy of China's energy use change in the 1980s [J], Economic Systems Research,1995,7(1):67-83.
    89. Zhang X Z. Why did the energy intensity fall in China's industrial sector in the 1990s? The relative importance of structural change and intensity change [J], Energy Econ, 2003,25(6):625-38.
    90. 王玉潜.能源消耗强度变动的因素分析方法及其应用[J],数量经济技术经济研究,2003,(8):151-154.
    91. 韩智勇,魏一鸣,范英.中国能源强度与经济结构变化特征研究[J],数理统计与管理,2004,23(1):1-7.
    92. 齐志新,陈文颖.结构调整还是技术进步?——改革开放后我国能源效率提高的因素分析[J],上海经济研究,2006,(6):8-16.
    93. 吴巧生,成金华.中国能源消耗强度变动及因素分解:1980-2004[J],经济理论与经济管理,2006,(10):34-40.
    94.彭源贤,张光明.中国能源消费效率提高因素分析1995~2003年产业结构和真实效率,谁更重要[J],生产力研究,2007,(10):98-99.
    95. 史丹,张金隆.产业结构变动对能源消费的影响[J],经济理论与经济管理,2003,(8):30-32.
    96. 周勇,李廉水.中国能源强度变化的结构与效率因素贡献——基于AWD的实证分析[J],产业经济研究,2006,(4):68-74.
    97. 张瑞,丁日佳,尹岚岚.中国产业结构变动对能源强度的影响[J],统计与决策,2007,(5):73-74.
    98. 刘红玖,陶全.大中型工业企业能源密度下降的动因探析[J],统计研究,2002,(9):30-34.
    99. 姚愉芳,陈杰,李花菊等.结构变化的节能潜力计算的方法论研究[J],数量经济技术经济研究,2007,(4):115-123.
    100. Forrester J W. Principles of Systems[M], Cambridge MA.:Productivity Press,1968.
    101. Forrester J W. Industrial Dynamics[M], Cambridge MA.:Productivity Press,1961.
    102.陶在朴.系统动态学:直击《第五项修炼》[M],北京:中国税务出版社,2005.
    103.王其藩.系统动力学(第二版)[M],北京:清华大学出版社,1994.
    104. Wiener N. Cybernetics-Control and Communication in the Animal and the Machine [M], Cambridge, MA:MIT Press,1948,1961.
    105.张丽峰.中国能源供求预测模型及发展对策研究[D],北京:首都经济贸易大学,2006.
    106. WEC (World Energy Council), Survey of Energy Resources[M], London,1995.
    107. International Energy Agency (IEA). IEA Coal Online database[DB], Available from: http://www.coalonline.org/site/coalonline/content/home
    108.国土资源局.固体矿产资源储量分类[S],北京:地质出版社,1999.
    109.陶在朴.生态包袱与生态足迹[M],北京:经济科学出版社,2003.
    110. Raggi A, Barbiroli G. Factors influencing changes in energy consumption; the case of Italy,1975-1985 [J], Energy Economics,1991,14(1):49-56.
    111. Bending R C, Cattell R K, Eden R J. Energy and structural change in the United Kingdom and Western Europe [J], Annual Review of Energy,1987,12:185-222.
    112. Hulten C R. Divisia index numbers [J], Econometrica,1973,41(6):1017-25.
    113. Diewert W E. Recent developments in the economic theory of index numbers:capital and the theory of productivity [J], American Economic Review,1980,70(2):260-7.
    114. Campbell C J. The Golden Century of Oil 1950-2050:the Depletion of a resource [M], Kluwer Academic Publishers,1991.
    115. Lynch M C. Petroleum resources pessimism debunked in hubbert model and hubbert modeler's assumptions [J], Oil and Gas Journal,2003,101(27):38-47.
    116. Laherrere J H. The Hubbert curve:its strengths and weaknesses [J], Oil & Gas Journal, 2004,98(16):63.
    117.辽宁省统计局.辽宁省统计年鉴[M],北京:中国统计出版社,2007.
    118.国家统计局.中国统计年鉴[M],北京:中国统计出版社,2007.
    119.孙梅,田立新,傅瑛.江苏-西部能源需求-供给模型及其动力学分析[J],系统科学与数学,2006,26(6):658-669.
    120. Feng L Y, Li J C, Pang X Q. China's oil reserve forecast and analysis based on peak oil models[J], [EB/OL],2008, www.elsevier.com/locate/enpol.
    121. Fan Y, Yang R G, Wei Y M. A system dynamics based model for coal investment[J], Energy,2007,32():898-905.
    122.俞珠峰,王立杰.浅析我国煤炭资源的有效供给能力[J],中国煤炭,2005,31(6): 24-26.
    123.吴吟.煤炭供求形势及保障有效供给的设想[J],中国能源,2004,24(4):4-6.
    124.蔡玺玉.影响我国电煤供给的主要量化因素分析[J],中国煤炭,2007,33(5):11-14.
    125. Platts. Safety, technology, dispersed production hamper coal growth [J], International Coal Report,2002, (587).
    126.陈武,唐辛,张希诚.我国煤炭资源及其开发利用研究[J],煤炭经济研究,2003,(7):6-11.
    127.杨瑞广,范英,魏一鸣.煤炭投资-供应的系统动力学分析模型[J],数理统计与管理,2005,25(5):6-12.
    128. Zhang B. Strengthen management, control total output, and adjust structure to meet the new century challenges [M], China Coal Industry Yearbook. Beijng:China Coal Industry Publishing House,2001.
    129. Guo B, Wang Y, Zhang A. China's Energy Future:Leap Tool Application in China [R], Asia Energy Security project. Vancoucer, Canada,2003.
    130.黄佐钘,邵汝军.中国煤炭产量预测[J],工业技术经济,2007,6(5):101-106.
    131.邵汝军,黄佐钘.关于我国煤炭需求的长期预测[J],煤炭经济论坛,2007,(3):8-14.
    132.中财网.中国石油发展战略研究[EB/OL]. http://wwwl.cfi.net.cn/newspage.aspx?id= 20070225000440&AspxAutoDetectCookieSupport=1
    133.浩君.石油效应一全球石油危机的背后[M],北京:企业管理出版社,2005.
    134.潘继平.中国油气资源勘探现状与前景展望[J],地质通报,2006,10(25):1055-1059.
    135.翟光明.我国油气资源和发展前景[J],勘探家,1996,1(2):1-5
    136. Laherrere J H. Forecasting production from discovery [A], ASPO Lisbon,2005, May 19-20, http://www.oilcrisis.com/laherrere/lisbon.pdfS
    137. Korpela S A. Oil Reserve Lifetimes [M], Department of Mechanical Engineering. OH, USA:The Ohio State University Columbus,2005.
    138. Pang X Q, Meng Q Y, Mariko N, Zhang J, Feng L Y. The challenge and countermeasures brought by the shortage of oil and gas in China [A], ASPO Lisbon, 2005, May 19-20.
    139.吴巧生,成金华.中国能源消耗强度变动及因素分解:1980-2004[J],经济理论与经济管理,2006(10):34-40.
    140.李凯,王秋菲,许波.美国、欧盟、中国绿色电力产业政策比较分析[J].中国软科学,2006,(2):54-60.
    141.许荣胜.中国国内生产总值与石油消费之间的关联度分析[J],国际石油经济,2006,(4):51-53.
    142.卢二坡.我国能源需求预测模型研究[J],统计与决策,2005,(10):29-31.
    143.李卓.石油战略储备与能源利用效率对石油消费的动态影响[J],数量经济技术经济研究,2005,(6):11-22.
    144.张明慧,李永峰.我国能源生产和消费增长的周期性波动探析[J],煤炭经济研究,2006,(7):29-33.
    145.国家发展和改革委员会能源研究所效率中心课题组.能源需求情景分析[R],北京:国家发展和改革委员会能源研究所,2004.
    146.戴彦德,朱跃中,刘志平.2020年中国能源需求情景分析[R],北京:国家发改委能源所,2003.
    147. Vuuren D V, Zhou F Q, Vries B D, Energy and emission scenarios for China in the 21st century-exploration of baseline development and mitigation options[J], Energy Policy, 2003,31(4):369-387.
    148.林伯强,魏巍贤,李丕东.中国长期煤炭需求:影响与政策选择[J],经济研究,2007,(2):48-58.
    149. Brendow K, WORLD COAL PERSPECTIVES TO 2030 [R], Working paper, World Energy Council,2004, http://www.worldenergy.org/documents/coal_summ.pdf
    150.何帆.对中国能源政策的几点建议[J],国际经济与评论,2007,(7-8):39-40.
    151.蔡秀云.我国能源产业调控政策探析[J],经济研究参考,2006,(91):28-34.
NGLC 2004-2010.National Geological Library of China All Rights Reserved.
Add:29 Xueyuan Rd,Haidian District,Beijing,PRC. Mail Add: 8324 mailbox 100083
For exchange or info please contact us via email.