北京市农村能源消费状况的统计分析
摘要
能源是人类社会发展必不可少的物质基础。农村能源建设是新农村建设的重要内容之一,是农村居民的基本需求。党中央在“十一五”规划中,提出大力发展农村能源建设。北京农村地区不合理的能源利用结构,严重影响了农村能源建设,影响生活环境,制约了农村社会、经济、环境的和谐发展。因此,使以可再生能源为主的农村能源建设和发展问题越来越受到人们的普遍关注,成为可持续发展战略的主要组成部分和北京农村经济新的增长点与动力。
本文运用统计学分析和建模方法,并将定性和定量分析相结合,对北京市农村能源消费状况进行统计分析。文章从能源消费总量和结构两方面对北京市农村地区的能源消费现状做了综合分析,在此基础上,分析了影响北京市农村能源消费状况的因素,并对影响因素做了重要性评价,得出人均纯收入是影响北京农村能源消费的最主要因素。鉴于能源系统的复杂性,在预测分析时,比较分析了趋势外推预测模型和灰色动态预测模型,根据预测模型的相对误差最小原则,最终采用GM(1,1)模型对北京市“十二五”期间农村能源消费总量做了预测分析。最后,提出了适合北京地区农村能源发展的政策建议:建立健全政策法规;科学制定规划;转变能源结构,建立合理的能源价格体系;加大宣传,合理开发可再生能源;加大农村能源投入力度,拓宽资金渠道;加大科研工作,构建完善服务体系。
The energy is essential material base on the human society development. Rural energy construction is the important content of building a new countryside and one of the basic needs of rural residents. In the "Eleventh Five-Year" plan, the government put forth great efforts to develop rural energy construction. The energy consumption structure in rural areas of Beijing is unreasonable, which has seriously affected the construction of rural energy, influenced the living environment and restricted the development of rural society, economy and environment in harmony. Therefore, the development of the rural renewable energy is becoming more and more important. It has been the main part of the sustainable development and the new growth point and momentum of rural economic.
In this paper, we use statistical analysis and modeling methods. Meanwhile, we combine qualitative and quantitative analysis method to analyze Beijing rural energy consumption. Based on a comprehensive analysis of rural energy consumption from energy total consumption and structure, we analyze the importance of factors affecting the energy consumption, and we evaluate the importance of the factors. We reach the conclusion that the rural per capita net income is the most important factor. In view of the complexity of energy systems, when we forecast, we through comparison and analysis of the trend extrapolation method and gray dynamic model, according to the relative error of prediction model minimum principle, GM(1,1) model is the eventual adoption to predict the total energy consumption in Beijing rural areas during "Twelfth Five-Year". Finally, we put forward some suitable policy recommendations for Beijing rural energy development : establish policies and regulations; make scientific plans; change the energy structure and establish a rational energy pricing system; increase the propaganda and do rational development of renewable energy; increase rural energy input and broaden the funding sources; increase research, build and consummate a service system.
本文运用统计学分析和建模方法,并将定性和定量分析相结合,对北京市农村能源消费状况进行统计分析。文章从能源消费总量和结构两方面对北京市农村地区的能源消费现状做了综合分析,在此基础上,分析了影响北京市农村能源消费状况的因素,并对影响因素做了重要性评价,得出人均纯收入是影响北京农村能源消费的最主要因素。鉴于能源系统的复杂性,在预测分析时,比较分析了趋势外推预测模型和灰色动态预测模型,根据预测模型的相对误差最小原则,最终采用GM(1,1)模型对北京市“十二五”期间农村能源消费总量做了预测分析。最后,提出了适合北京地区农村能源发展的政策建议:建立健全政策法规;科学制定规划;转变能源结构,建立合理的能源价格体系;加大宣传,合理开发可再生能源;加大农村能源投入力度,拓宽资金渠道;加大科研工作,构建完善服务体系。
The energy is essential material base on the human society development. Rural energy construction is the important content of building a new countryside and one of the basic needs of rural residents. In the "Eleventh Five-Year" plan, the government put forth great efforts to develop rural energy construction. The energy consumption structure in rural areas of Beijing is unreasonable, which has seriously affected the construction of rural energy, influenced the living environment and restricted the development of rural society, economy and environment in harmony. Therefore, the development of the rural renewable energy is becoming more and more important. It has been the main part of the sustainable development and the new growth point and momentum of rural economic.
In this paper, we use statistical analysis and modeling methods. Meanwhile, we combine qualitative and quantitative analysis method to analyze Beijing rural energy consumption. Based on a comprehensive analysis of rural energy consumption from energy total consumption and structure, we analyze the importance of factors affecting the energy consumption, and we evaluate the importance of the factors. We reach the conclusion that the rural per capita net income is the most important factor. In view of the complexity of energy systems, when we forecast, we through comparison and analysis of the trend extrapolation method and gray dynamic model, according to the relative error of prediction model minimum principle, GM(1,1) model is the eventual adoption to predict the total energy consumption in Beijing rural areas during "Twelfth Five-Year". Finally, we put forward some suitable policy recommendations for Beijing rural energy development : establish policies and regulations; make scientific plans; change the energy structure and establish a rational energy pricing system; increase the propaganda and do rational development of renewable energy; increase rural energy input and broaden the funding sources; increase research, build and consummate a service system.
引文
[1]陈永申.能源与中国经济现代化.http://www.cas.cn/html/Dir /2005/03/17/6109.htm.
[2] Eckholm. The other energy crisis: Firewood. Worldwatch Paper 1.Worldwatch Institute, Washington, DC.1975.
[3] PaskaJ, SlekaM, SurmaT. Current Status and Perspectives of Renewable Energy Sources in Poland[J] Renewable and Sustainable Energy Reviews[J],2007(6):12-15.
[4] Pablo delRio. Unruh G. Overcoming the Lock-out of Renewable Energy Technologies in Spain: The Cases of wind and Solar Electricity [J].Renewable and Sustainable Energy Reviews, 2007, 11.
[5] B K Bala. Computer Modeling of the Rural Energy System and of C02 Emissions for Bangladesh[J].Energy,1997,22(10): 999-1003.
[6] N.H.Ravindranath,H.I.Somashekar,M.S.Nagaraja. Assessment of sustainable non-Plantation biomass resources Potential for energy in India [J].Biomass and Bioenergy. 2005.29(3):178-190.
[7]高国录.白银区农村住宅能源消费结构分析[J],甘肃农业,2009(9).
[8]楼洪志,王仲淼.加快农村能源发展推进新农村建设对策研究[J],农业工程学报,2006,22(增1):32-36.
[9]陈彦玲等.北京市农村可再生能源发展状况研究[J].调研世界,2008(12).
[10]吴良,曾强能等.济南农村生活能源消费结构研究[J],山东农业科学,2007(2).
[11] Kraft J., Kraft A., On the Relationship between Energy and GNP, Journal of Energy and Development[J], 1978, 10 (3): 401-403.
[12]何永秀,李艳等.北京地区能源消费与经济增长的协整检验[J],统计与决策,2008(8):90-92.
[13]赵丽霞,魏巍贤.能源与经济增长模型研究[J],预测,1998,(6):32-49.
[14] Gundimeda H.,G.Kohlin .Fuel demand elasticities for energy and environmental Policies : Indian sample survey evidence[J].Energy Economies,2006:l-30.
[15]陆慧,卢黎.农民收入水平对农村家庭能源消费结构影响的实证分析[J].财贸研究,2006,3:28-34.
[16] Rao, M.N., B.S. Reddy .Variations in energy use by Indian households :An analysis of micro level data[J].Energy,2007,32:143-153.
[17] Gerald Leach.The energy transition[J].Energy Policy, February 1992, 116-123.
[18] Byrne J, Zhou A M, Shen B. Evaluating the potential of small-scale renewable energy options tomeet rural livelihoods needs: A GIS-and lifecycle cost-based assessment of Western China's options[J].Energy Policy,2007,35(8):4391-4401.
[19]徐长勇,尚杰.黑龙江省农村能源利用及生物质能发展实证研究[J],林业经济.2009(5).
[20]周丹丹,李蜀庆.重庆市能源消费影响因素分析[J],环境科学与工程,2009,3:192-194.
[21] Silberglitt Richard. Anders Hove. Peter Shulman. Analysis of US energy scenarios : Meta-scenarios, pathways, and policy implications[J]. Technological Forecasting &Social Change, 2003, 70(4):297-315.
[22] Tiwari Piyush. An analysis of sectoral energy intensity in India[J]. Energy Policy,2000, 28(11):771-778.
[23]周倩,黄树红,李爱军.湖北省能源需求预测及分析[J].统计与决策,2007,4:89-90.
[24]H. Mu,Y. Kondou,Y. Tonooka,Y. Sato,et al. Grey relative analysis and future prediction on rural household biofuels consumption in China[J]. Fuel Processing Technology,2004,85(8~10): 1231-1248.
[25]谢乃明,刘思峰.能源消费总量与结构预测分析[J],工业技术经济,2009.1:46-49
[26]王春清.吉林省家庭用能源消费预测模型的建立[J],吉林建筑工程学院学报,2005,22(2):39-41
[27]谭志豪.基于SD模型的中国能源需求预测[J],消费导刊,2008.6.
[28]王海建.经济结构变动与能源需求的投入产出分析[J].统计研究,1996,6:30-34
[29]王革华,艾德生.新能源概论[M],北京:化学工业出版社,2006.7
[30]国际能源署.世界能源展望2002[M].北京:中国石化出版社,2002.
[31]肖江平,肖乾刚.“可再生能源”的法律定义[J].法学评论,2004,124(2):101-206.
[32]湖南省人民代表大会常务委员会.湖南省农村可再生能源条例[R].2005.
[33]刘凯.农村能源建设与管理实用手册[M],北京北大方正电子出版社出版,2005.6.
[34]吴德春,董继斌.能源经济学[M]北京:中国工人出版社,1991.
[35]王革华等.能源与可持续发展[M],北京:化学工业出版社,2005.1.
[36]胡应得.可再生能源与农村可持续发展[D],浙江工业大学,2004.
[37]庄贵阳.中国经济低碳发展的途径与潜力分析[J],国际技术经济研究,2005.8(3):79-87.
[38]李光全,聂华林等.中国农村生活能源消费的区域差异及影响因素[J],山西财经大学学报,2010,32(2):68-73.
[39]徐晓刚.我国农村生活能源消费分析[D],中国农业科学院,2008.
[40]苏争鸣.西部可再生能源与农村能源建设[J].经济研究参考,2003,50:36-44.
[41] Lenzen M,Dey C,Foran B. Energy Requirements of Sydney Households [J]. Ecological Economics,2004, 49: 375-399.
[42]周玉敏,邓维斌.Spss16.0与统计数据分析[M].成都:.西南财经大学出版社,2009,8.
[43]蔡晓春,宋美喆.我国能源利用效率及其影响因素的灰色关联分析[J],统计与决策,2009(24):79-81.
[44]樊欢欢,张凌云编著.Eviews统计分析与应用[M],北京:机械工业出版社,2009.6.
[45]胡光宇.战略:预测与决策[M],北京:清华大学出版社,2005.1.169-177.
[46] International Energy Agency. World energy Outlook 2002:318-321.
[2] Eckholm. The other energy crisis: Firewood. Worldwatch Paper 1.Worldwatch Institute, Washington, DC.1975.
[3] PaskaJ, SlekaM, SurmaT. Current Status and Perspectives of Renewable Energy Sources in Poland[J] Renewable and Sustainable Energy Reviews[J],2007(6):12-15.
[4] Pablo delRio. Unruh G. Overcoming the Lock-out of Renewable Energy Technologies in Spain: The Cases of wind and Solar Electricity [J].Renewable and Sustainable Energy Reviews, 2007, 11.
[5] B K Bala. Computer Modeling of the Rural Energy System and of C02 Emissions for Bangladesh[J].Energy,1997,22(10): 999-1003.
[6] N.H.Ravindranath,H.I.Somashekar,M.S.Nagaraja. Assessment of sustainable non-Plantation biomass resources Potential for energy in India [J].Biomass and Bioenergy. 2005.29(3):178-190.
[7]高国录.白银区农村住宅能源消费结构分析[J],甘肃农业,2009(9).
[8]楼洪志,王仲淼.加快农村能源发展推进新农村建设对策研究[J],农业工程学报,2006,22(增1):32-36.
[9]陈彦玲等.北京市农村可再生能源发展状况研究[J].调研世界,2008(12).
[10]吴良,曾强能等.济南农村生活能源消费结构研究[J],山东农业科学,2007(2).
[11] Kraft J., Kraft A., On the Relationship between Energy and GNP, Journal of Energy and Development[J], 1978, 10 (3): 401-403.
[12]何永秀,李艳等.北京地区能源消费与经济增长的协整检验[J],统计与决策,2008(8):90-92.
[13]赵丽霞,魏巍贤.能源与经济增长模型研究[J],预测,1998,(6):32-49.
[14] Gundimeda H.,G.Kohlin .Fuel demand elasticities for energy and environmental Policies : Indian sample survey evidence[J].Energy Economies,2006:l-30.
[15]陆慧,卢黎.农民收入水平对农村家庭能源消费结构影响的实证分析[J].财贸研究,2006,3:28-34.
[16] Rao, M.N., B.S. Reddy .Variations in energy use by Indian households :An analysis of micro level data[J].Energy,2007,32:143-153.
[17] Gerald Leach.The energy transition[J].Energy Policy, February 1992, 116-123.
[18] Byrne J, Zhou A M, Shen B. Evaluating the potential of small-scale renewable energy options tomeet rural livelihoods needs: A GIS-and lifecycle cost-based assessment of Western China's options[J].Energy Policy,2007,35(8):4391-4401.
[19]徐长勇,尚杰.黑龙江省农村能源利用及生物质能发展实证研究[J],林业经济.2009(5).
[20]周丹丹,李蜀庆.重庆市能源消费影响因素分析[J],环境科学与工程,2009,3:192-194.
[21] Silberglitt Richard. Anders Hove. Peter Shulman. Analysis of US energy scenarios : Meta-scenarios, pathways, and policy implications[J]. Technological Forecasting &Social Change, 2003, 70(4):297-315.
[22] Tiwari Piyush. An analysis of sectoral energy intensity in India[J]. Energy Policy,2000, 28(11):771-778.
[23]周倩,黄树红,李爱军.湖北省能源需求预测及分析[J].统计与决策,2007,4:89-90.
[24]H. Mu,Y. Kondou,Y. Tonooka,Y. Sato,et al. Grey relative analysis and future prediction on rural household biofuels consumption in China[J]. Fuel Processing Technology,2004,85(8~10): 1231-1248.
[25]谢乃明,刘思峰.能源消费总量与结构预测分析[J],工业技术经济,2009.1:46-49
[26]王春清.吉林省家庭用能源消费预测模型的建立[J],吉林建筑工程学院学报,2005,22(2):39-41
[27]谭志豪.基于SD模型的中国能源需求预测[J],消费导刊,2008.6.
[28]王海建.经济结构变动与能源需求的投入产出分析[J].统计研究,1996,6:30-34
[29]王革华,艾德生.新能源概论[M],北京:化学工业出版社,2006.7
[30]国际能源署.世界能源展望2002[M].北京:中国石化出版社,2002.
[31]肖江平,肖乾刚.“可再生能源”的法律定义[J].法学评论,2004,124(2):101-206.
[32]湖南省人民代表大会常务委员会.湖南省农村可再生能源条例[R].2005.
[33]刘凯.农村能源建设与管理实用手册[M],北京北大方正电子出版社出版,2005.6.
[34]吴德春,董继斌.能源经济学[M]北京:中国工人出版社,1991.
[35]王革华等.能源与可持续发展[M],北京:化学工业出版社,2005.1.
[36]胡应得.可再生能源与农村可持续发展[D],浙江工业大学,2004.
[37]庄贵阳.中国经济低碳发展的途径与潜力分析[J],国际技术经济研究,2005.8(3):79-87.
[38]李光全,聂华林等.中国农村生活能源消费的区域差异及影响因素[J],山西财经大学学报,2010,32(2):68-73.
[39]徐晓刚.我国农村生活能源消费分析[D],中国农业科学院,2008.
[40]苏争鸣.西部可再生能源与农村能源建设[J].经济研究参考,2003,50:36-44.
[41] Lenzen M,Dey C,Foran B. Energy Requirements of Sydney Households [J]. Ecological Economics,2004, 49: 375-399.
[42]周玉敏,邓维斌.Spss16.0与统计数据分析[M].成都:.西南财经大学出版社,2009,8.
[43]蔡晓春,宋美喆.我国能源利用效率及其影响因素的灰色关联分析[J],统计与决策,2009(24):79-81.
[44]樊欢欢,张凌云编著.Eviews统计分析与应用[M],北京:机械工业出版社,2009.6.
[45]胡光宇.战略:预测与决策[M],北京:清华大学出版社,2005.1.169-177.
[46] International Energy Agency. World energy Outlook 2002:318-321.