基于节能调度与需求侧管理的电力优化运营研究
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摘要
电力工业作为能源产业的重要分支,是国民经济的基础产业,是经济发展和社会进步的重要保障。而节能型电力运营机制是实现电力工业可持续发展的必然选择。在当前电力体制下,由于电网公司作用于电力工业的发输配售各个环节,其在实现电力工业可持续发展当中发挥着重要作用,因此如何推动电网公司积极发挥主体作用,运用节能发电调度与电力需求侧管理等手段建设节能型电力运营机制成为目前我国迫切需要研究解决的前沿问题。进而研究探讨建立节能发电优化调度方法、制定需求侧管理措施以及构建节能型电力运营能力评估体系与评价模型等内容具有重要的理论价值和实际意义。
论文的主要创新点为:
1.建立了基于协整与支持向量机的中长期电量预测方法。通过协整技术建立了能源系统中变量间的长期均衡关系用于电量预测,而后通过支持向量机对协整预测误差进一步修正。计算结果表明此方法提高了预测的可靠性与预测精度。在运用此方法对我国进行中长期电量预测的基础上,对中国未来的节能潜力进行了分析预测。
2.构建了节能发电调度指标体系,建立了基于熵权与改进多粒子群算法的组合优化调度方法,实现了对发电侧资源的优化调度。从安全、节能、经济角度选取供电成本、供电煤耗、机组可靠性、厂用电率四个指标,而后运用熵权法计算上述指标的权重,进而构建最优调度目标函数,最后运用改进多粒子群算法实现优化调度。计算结果表明,此方法的计算结果优于遗传算法与模拟退火算法,达到了在降低总耗煤量的同时,其他指标不受过多损失的目的。
3.从电源供电能力、电网输配电能力、需求侧用电能力三个角度出发建立了节能型电力运营能力评价指标体系。体系的建立有助于评估电力运营的状态,并且有利于推动电网公司建设节能型电力运营机制,提升电力工业的可持续性。
4.建立了循序递进组合评价方法。首先,采用单一综合评价方法进行评价,对于不一致的评价结果,通过Spearman等级相关系数验证各单一评价方法间是否具有相关性;对存在相关性的单一评价方法采用组合评价法对其结果进行组合,若所得评价结果仍不一致,采用Spearman等级相关系数、关联度、最大偏差、平均偏差对组合评价方法的组合效果进行评价,最后运用熵权法对上述组合评价进一步组合得到最终评价结果。此方法克服了单一综合评价方法的片面性和不一致性,使所得评价结果更加客观公正。
Electric power industry as an important branch of the energy industry has become the foundation of the national economy industries,economic development and an important guarantee for social progress.The energy-saving operating mechanism for electricity power industry is the inevitable choice in order to achieve sustainable development.In the current power system mechanism,power grid companies are still responsible for the improvement of the electric power industry efficiency.How to promote the power grid companies to play the main role in actively using the energy-saving power generation dispatching,demand-side management and so on to build the energy-saving energy operating model has become a forefront problem,which needed to be solved urgently.Therefore,studying on the establishment of energy-saving optimization dispatching methods,the development of demand-side management measures,as well as construction of evaluation index system and evaluation model for energy-saving electric power system operating ability has important theoretical value and practical significance.
The primary innovations are as follows:
1.The middle-long power load forecasting method based on co-integration and support vector machine is set up.Firstly,the long-term equilibrium relationship of the variables in energy system is established by means of co-integration technology.The co-integration relationship and error correction model are used to forecast.Secondly,the support vector machine is used to predict the forecasting error of the co-integration and to make the further amendment.The forecasting results show that this model improves the reliability and accuracy.Based on the forecasting results the energy-saving potential of China's future projections is analyzed.
2.The index system of energy saving power generation dispatching is set up.The optimization method for power generation dispatching based on entropy and improved poly-particle swarm algorithm is set up to achieve the optimal scheduling of power generation side resources.The index system includes power supply cost,power supply coal consumption,and reliability of power plant and power consumption rate.The entropy is used to calculate the weights of upper four indexes.Then the objective function is set up.At last,the poly-particle swarm optimization algorithm is used to realize the optimal dispatching.The results show that this method is the best among genetic algorithm and simulated annealing algorithm.Meanwhile,the amount of the total coal consumption is reduced without the other indicators for the purpose have too many losses.
3.The evaluation index system for power system energy-saving operating ability is set up from power supply ability,power transmission and distribution ability,and power demand-side electricity usage ability.The index system helps to assess the status of power grid companies,and helps to promote the construction of energy-saving mechanism for electricity operators to enhance the sustainability.
4.A sequence and progressive combined evaluation method is set up.The thinking of this method as follows:Firstly,using single evaluation methods to evaluate.If the evaluation results aren't same,the Spearman rank correlation coefficient is used to calculate the correlation among the results of single evaluation methods.Based on the results,the traditional combined evaluation methods are used to combine the results of the single evaluation method.If the results of the upper combined methods are not same. Here the combined method evaluation indexes,such as Spearman rank correlation coefficient,correlation degree,the max deviation,average deviation,are used to evaluate the upper four combined evaluation methods.The entropy method is used to calculate the weights,and then get the final evaluation result.In this paper,using the indexes system and the data of them,the sequential progressive combined evaluation method is testified.This method overcomes the comprehensive evaluation method of a single one-sidedness and inconsistency,so that evaluation results from a more authentic.
论文的主要创新点为:
1.建立了基于协整与支持向量机的中长期电量预测方法。通过协整技术建立了能源系统中变量间的长期均衡关系用于电量预测,而后通过支持向量机对协整预测误差进一步修正。计算结果表明此方法提高了预测的可靠性与预测精度。在运用此方法对我国进行中长期电量预测的基础上,对中国未来的节能潜力进行了分析预测。
2.构建了节能发电调度指标体系,建立了基于熵权与改进多粒子群算法的组合优化调度方法,实现了对发电侧资源的优化调度。从安全、节能、经济角度选取供电成本、供电煤耗、机组可靠性、厂用电率四个指标,而后运用熵权法计算上述指标的权重,进而构建最优调度目标函数,最后运用改进多粒子群算法实现优化调度。计算结果表明,此方法的计算结果优于遗传算法与模拟退火算法,达到了在降低总耗煤量的同时,其他指标不受过多损失的目的。
3.从电源供电能力、电网输配电能力、需求侧用电能力三个角度出发建立了节能型电力运营能力评价指标体系。体系的建立有助于评估电力运营的状态,并且有利于推动电网公司建设节能型电力运营机制,提升电力工业的可持续性。
4.建立了循序递进组合评价方法。首先,采用单一综合评价方法进行评价,对于不一致的评价结果,通过Spearman等级相关系数验证各单一评价方法间是否具有相关性;对存在相关性的单一评价方法采用组合评价法对其结果进行组合,若所得评价结果仍不一致,采用Spearman等级相关系数、关联度、最大偏差、平均偏差对组合评价方法的组合效果进行评价,最后运用熵权法对上述组合评价进一步组合得到最终评价结果。此方法克服了单一综合评价方法的片面性和不一致性,使所得评价结果更加客观公正。
Electric power industry as an important branch of the energy industry has become the foundation of the national economy industries,economic development and an important guarantee for social progress.The energy-saving operating mechanism for electricity power industry is the inevitable choice in order to achieve sustainable development.In the current power system mechanism,power grid companies are still responsible for the improvement of the electric power industry efficiency.How to promote the power grid companies to play the main role in actively using the energy-saving power generation dispatching,demand-side management and so on to build the energy-saving energy operating model has become a forefront problem,which needed to be solved urgently.Therefore,studying on the establishment of energy-saving optimization dispatching methods,the development of demand-side management measures,as well as construction of evaluation index system and evaluation model for energy-saving electric power system operating ability has important theoretical value and practical significance.
The primary innovations are as follows:
1.The middle-long power load forecasting method based on co-integration and support vector machine is set up.Firstly,the long-term equilibrium relationship of the variables in energy system is established by means of co-integration technology.The co-integration relationship and error correction model are used to forecast.Secondly,the support vector machine is used to predict the forecasting error of the co-integration and to make the further amendment.The forecasting results show that this model improves the reliability and accuracy.Based on the forecasting results the energy-saving potential of China's future projections is analyzed.
2.The index system of energy saving power generation dispatching is set up.The optimization method for power generation dispatching based on entropy and improved poly-particle swarm algorithm is set up to achieve the optimal scheduling of power generation side resources.The index system includes power supply cost,power supply coal consumption,and reliability of power plant and power consumption rate.The entropy is used to calculate the weights of upper four indexes.Then the objective function is set up.At last,the poly-particle swarm optimization algorithm is used to realize the optimal dispatching.The results show that this method is the best among genetic algorithm and simulated annealing algorithm.Meanwhile,the amount of the total coal consumption is reduced without the other indicators for the purpose have too many losses.
3.The evaluation index system for power system energy-saving operating ability is set up from power supply ability,power transmission and distribution ability,and power demand-side electricity usage ability.The index system helps to assess the status of power grid companies,and helps to promote the construction of energy-saving mechanism for electricity operators to enhance the sustainability.
4.A sequence and progressive combined evaluation method is set up.The thinking of this method as follows:Firstly,using single evaluation methods to evaluate.If the evaluation results aren't same,the Spearman rank correlation coefficient is used to calculate the correlation among the results of single evaluation methods.Based on the results,the traditional combined evaluation methods are used to combine the results of the single evaluation method.If the results of the upper combined methods are not same. Here the combined method evaluation indexes,such as Spearman rank correlation coefficient,correlation degree,the max deviation,average deviation,are used to evaluate the upper four combined evaluation methods.The entropy method is used to calculate the weights,and then get the final evaluation result.In this paper,using the indexes system and the data of them,the sequential progressive combined evaluation method is testified.This method overcomes the comprehensive evaluation method of a single one-sidedness and inconsistency,so that evaluation results from a more authentic.
引文
[1]许洪胜.建设节能型、环保型发电企业促进广东电力可持续发展[J].广东科技,2006.6:25-26.
[2]张海林,张金升,解芳.内蒙古发电企业可持续发展分析[J].内蒙古电力技术,2008,26(3):12-14.
[3]吕强.发电企业核心竞争力评价指标体系的研究[J].中国电力,2007,40(8):82-86.
[4]张立辉,顾蓉,伍业锋.发电企业竞争力来源和评价模型[J].价值工程,2006,2:75-78.
[5]单宏胜,黄文杰.发电企业竞争力评价的弓箭理论模型[J].中国电力,2008,41(6):6-9.
[6]瞿斌,田惠英,翟亚军.发电企业综合竞争力评价指标体系构建与方法研究[J].工业技术经济,2006,25(9):85-87,95.
[7]李莉,雷宇,葛旭波,曹福成,谭忠富.电网企业可持续发展的指标体系及评价方法[J].电力学报,2007,22(1):1-4,14.
[8]朱清.供电企业可持续发展分析与评价.[硕士学位论文].武汉:武汉大学,2003.
[9]陶文斌.输电网运营经济性评价系统研发.[硕士学位论文].北京:华北电力大学,2003.
[10]刘敦楠,陈雪青,何光宇,周双喜.电力市场评价指标体系的原理和构建方法[J].电力系统自动化,2005,29(23):2-7,14.
[11]刘敏.电网公司“一强三优”技术经济评价指标体系研究.[硕士学位论文].长沙:长沙理工大学,2007.
[12]杨宇,陈沁,岳光辉.电网重组后企业运作综合实力评价体系的研究[J].电力科学与工程,2003,2:27-29.
[13]段福兴,于秀艳.基于DEA的信息产业效率分析与评价[J].华东经济管理,2002,16(5):33-35.
[14]彭晓峰,廖学中.基于DEA的供电企业技术效率分析[J].中国电力教育,2007,2:176-178.
[15]Feng-Yu Lo,Chen-Fu Chien,Lin,J.T..A DEA study to evaluate the relative efficiency and investigate the district reorganization of the Taiwan Power Company[J].Power Systems,2001,16(1):170 - 178.
[16]李刚.水火电系统短期节能发电调度研究与应用.[博士学位论文].大连:大连理工大学,2007.
[17]王超.四川电网节能减排发电实时调度优化模型的研究[J].四川电力技术,2008,31(1):67-69.
[18]朱成章,徐任武.需求侧管理[M].北京:中国电力出版社,1999:5-35.
[19]国家经贸委经济运行局.加拿大,美国电力需求侧管理可资借鉴[J].中国经贸导刊,1998,(11):45.
[20]发展改革委,环保总局,电监会,能源办.节能发电调度办法(试行).
[21]陈卫昀,严仰光.分布式电源[J].电力电子技术,1999,2:82-85.
[22]陈金富,卢炎生.分布式电源技术在我国的应用探讨[J].水电能源科学,2005,23(2):61-64.
[23]张国光.分布式电源技术简介[J].电气时代,2004,11:46.
[24]梁才浩,段献忠.分布式发电及其对电力系统的影响[J].电力系统自动化,2001,2:53-56.
[25]王敏,丁明.分布式发电及其效益[J].合肥工业大学学报(自然科学版),2004,27(4):344-348.
[26]吴靖,江吴.分布式发电系统的应用及前景[J].农村电气化,2003,7:19-20.
[27]莫颖涛,吴为麟.分布式发电的研究方向[J].热力发电,2006,5:71-72.
[28]杨培宏,刘文颖.分布式发电的种类及前景[J].农村电气化,2007,3:54-56.
[29]高虎,李俊峰,许洪华.太阳能光伏发电技术发展状况与趋势分析[J].中国科技产业,2006,72-75.
[30]王亦楠.对我国发展太阳能热发电的一点看法[J].中国能源,2006,28(8):5-10.
[31]包耳.风力发电技术的发展现状[J].可再生能源,2004,2:53-55.
[32]谢建民,曾建成,邱毓昌.风力发电成本主要影响因素分析与计算[J].华东电力,2003,1:6-9.
[33]周双喜,王海超,陈寿孙.风力发电运行价值分析[J].电网技术,2006,30(14):98-101.
[34]沈磊.我国水电发电效益的定量分析[J].水力发电,2000,4:7-9.
[35]余毅,叶念渝.火电厂动态成本分析系统的研究[J].华中科技大学学报(自然科学版),2004,32(5):73-75.
[36]陈立民,徐征,张贵山等.小型生物质直燃发电工程及其效益分析[J].水利电力机械,2006,28(12):1-4.
[37]樊京春,王永刚,秦世平.生物质能发电电价的敏感因素分析[J].可再生能源,2006,2:49-53.
[38]邓晟,陈波.秸秆发电利弊分析[J].水利电力机械,2006,28(12):42-44.
[39]朱成章.电力需求侧管理与电源建设同等重要[J].供用电,2005,22(3):1-3,24.
[40]陈晨.能效电厂开建云南节能减排又添新”武器”[N].云南电力报,2008-4-21.
[41]马驰,虞良荣.能效电厂实施的条件分析和对策探讨[J].上海节能,2007,1:13-16.
[42]河北省将建“虚拟调峰电厂”[J].电力需求侧管理,2002,4(4):13.
[43]Malik A S.Simulation of DSM Resources as Generating Units in Probabilistic Production Costing Framework[J].IEEE Trans.On Power Systems,1998,13(4):1528-1533.
[44]Billinton R,Lakhanpal D.Impacts of demand side management on reliability cost/reliability worth analysis[J].IEE Proc.-Gener.Transm.Distrib,1996,143(3):225-231.
[45]黄强.电力供需综合资源的全过程协调管理[J].华东电力,2004,32(5):42-44.
[46]曾鸣,张艳馥,王鹤,贾俊国.基于综合资源规划的供需资源优化组合模型[J].电力系统自动化,2007,31(3):24-28.
[47]刘纪平,陈煜辉,陈军.有效利用需求侧管理资源确保电网安全经济运行[J].电力需求侧管理,2005,5(3):5-6.
[48]Doonerman Gerard L,Wangensteen Ivar.Demand side provision of peaking capacity and reserves in deregulated power systems[C].International Conference on Electric Utility Deregulation and Research Restructuring and Power Technologies 2000.London(UK),2000:290-295.
[49]李锐.系统负荷率对电网降损节能的影响[J].电气时代,2006,9:80-81.
[50]李蒙,王静,胡兆光.用电负荷率同供电煤耗关系的定量分析[J].电力需求侧管理,2005,38(11):40-42.
[51]刘昌,姚建刚,余虎,葛亮,李继传.一种新型的电网输电阻塞管理模式[J].电网技术,2005,29(12):16-21.
[52]宋晓辉.考虑需求侧管理的高压配电网规划.[硕士学位论文].北京:中国电力科学研究院,2005.
[53]刘强,黄民翔,张圣楠.电力市场可中断负荷用户属性研究[J].华东电力,2007,35(11:88-91.
[54]WENDERS J T.Peak load pricing in the electric utility industry[J].The Bell Journal of Economics,1976,7(1):232-241.
[55]丁宁,吴军基,邹云.基于DSM的峰谷时段划分及分时电价研究[J].电力系统自动化,2001,25(23):9-12.
[56]SHEEN J N,CHEN C S,WANG T Y.Response of larger industrial customers to electricity pricing by voluntary time-of-use in Taiwan[J].IEE Proceedings:Generation,Transmission anDistribution,1995,142(2):157-166.
[57]李晖,康重庆,夏清.考虑用户满意度的需求侧管理价格决策模型[J].电网技术,2004,28(23):1-6.
[58]DAVID A K,LI Y Z.Effect of inter-temporal factors on the real time pricing of electricity [J].IEEE Trans on Power Systems,1993,8(3):44-52.
[59]KIRSCHEN D S,STRBAC G,CUMPERAYOT P,et al.Factoring the elasticity of demand in electricity prices[J].IEEE Trans on Power Systems,2000,15(2):612-617.
[60]秦祯芳,岳顺民,余贻鑫,等.零售端电力市场中的电量电价弹性矩阵[J].电力系统自动化,2004,28(5):16-19.
[61]CELEBI E,DAVID F J.A model for efficient consumer pricing schemes in electricity markets[J].IEEE Trans on Power Systems,2007,22(1):60-67.
[62]王锡凡.关于电价制定方法的初步探讨[J].中国电力,1999,32(6):1-3.
[63]SHEEN J N,CHEN C S,YANG J K.Time-of-use pricing for load management programs in Taiwan Power Company[J].IEEE Trans on Power Systems,1994,9(1):388-396.
[64]丁伟,袁家海,胡兆光.基于用户价格响应和满意度的峰谷分时电价决策模型[J].电力系统自动化,2005,29(20):10-14.
[65]束洪春,董俊,吴永军,等.销售侧分行业实行丰枯峰谷分时电价初探[J].电力系统自动化,2006,30(14):36-40.
[66]张钦,王锡凡,王建学,等.丰枯季节电价决策模型分析[J].电力系统自动化,2007,31(24):7-11.
[67]段登伟,刘俊勇,吴集光.计及风险的配电公司最优分时零售电价模型[J].电力系统自动化,2005,29(3):8-12.
[68]盛晓萍,李成仁.我国电力需求侧电价机制适应性分析[J].电力需求侧管理,2007,9(6):6-8.
[69]龚玲丽,韩铁.电价在我国电力需求侧管理中的应用综述[J].集团经济研究,2006,6:110-111.
[70]汤玉东,徐诚,邹云.基于DSM的峰谷分时电价[J].电力需求侧管理,2006,8(6):11-13.
[71]赵娟,谭忠富,李晓军.分时电价下供电公司盈亏风险分析模型[J].电力需求侧管理,2005,7(1):9-11.
[72]任玉珑,黄清辉.能源效率与电力需求侧管理[J].生态经济,2005,2:104-107.
[73]杜成刚,曹基华,林一,张华.电力节能降耗技术措施分析[J].电力需求侧管理,2007,40(9):46-48.
[74]石建林.加大技改力度 强化电力需求侧管理[J].中国氯碱,2006,7:33-34.
[75]涂正革,肖耿.中国工业增长模式的转变[J].管理世界,2006(10):57-67.
[76]林毅夫,张鹏飞.适宜技术、技术选择和发展中国家的经济增长[J].经济学(季刊),2006,5(4):985-1005.
[77]陈勇,唐朱昌.中国工业的技术选择与技术进步:1985-2003[J].经济研究,2006,9:50-61.
[78]金煜,陈钊,陆铭.中国的地区工业集聚:经济地理、新经济地理与经济政策[J].经济研究,2006,4:79-89.
[79]黄玖立,李坤望.对外贸易、地方保护和中国的产业布局[J].经济学(季刊),2006,5(3):733-760.
[80]李廉水,周勇.技术进步能提高能源效率吗?[J].管理世界,2006,10:82-89.
[81]曾鸣.电力需求侧管理[M].北京:中国电力出版社,2000:24-35.
[82]张永翔,王倩文,梁洪浩.大客户负荷管理模式的研究[J].电网技术,2004,28(12):39-42.
[83]赵晓丽,张素芳,电力需求侧管理的国内外对比研究[J].电力需求侧管理,2005,8:60-62.
[84]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.
[85]尹春华,顾培亮.我国产业结构的调整与能源消费的灰色关联分析[J].天津大学学报,2003,36(1):104-107.
[86]陈勇,唐朱昌.中国工业的技术选择与技术进步:1985-2003[J].经济研究,2006,9:50-61.
[87]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.
[88]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):1-6,52.
[89]李小平,朱钟棣.中国工业行业的全要素生产率测算[J].管理世界,2005,4:6-12.
[90]张安华.中国电力工业节能降耗影响因素分析[J].电力需求侧管理,2006,18(6):1-4.
[91]包正.“首钢”DSM经验的启示[J].电力需求侧管理,2002,4(2):16.
[92]田文烈.电力需求侧管理在首都钢铁公司的应用[J].电力需求侧管理,2002,4(1):47-49.
[93]孙彦伟.DSM在济钢电网中的应用分析[J].电力需求侧管理,2003,5(5):49-51.
[94]于颖,苏震.钢铁企业实施DSM应对电力紧张形势的策略[J].电力需求侧管理,2005,7(1):7-8.
[95]林海英,李建荣,宣菊琴,魏宏俊.钢铁行业负荷特性及需求侧管理潜力分析[J].华东电力,2005,33(11):53-57.
[96]周长敬.电力需求侧管理对胜利油田的激励作用[J].电力需求侧管理,2004,6(4):8-10.
[97]李志军.电力需求侧管理在石化企业的发展方向[J].电力需求侧管理,2003,5(2):13-15.
[98]祝小红.电力需求侧管理对终端设备的影响[J].电力需求侧管理,2003,5(3):11-12.
[99]杨希智.DSM在纺织企业的运用[J].电力需求侧管理,2003,5(3):13-14.
[100]发改委等部门要求发电调度体现节能环保优先.国家电力信息网,2006-7-11.
[101]国务院办公厅关于转发《节能发电调度办法(试行)》的通知.中国能源网,2007-8-10.
[102]Caves,D.W.,L.R.Christensen and W.E.Diewert,The economic theory of index numbers and the measurement of input,output,and productivity[J].Econometrica,1982,50(6):1393-1414.
[103]Balk,B.M.,Malmquist productivity indexes and Fisher ideal indexes:comment[J].Economic Journal 1993,103(418):680 - 682.
[104]Sun,J.W.Changes in energy consumption and energy intensity:A complete decomposition model[J].Energy Economics,1998,20:85 - 100.
[105]李小平,朱钟棣.中国工业行业的全要素生产率测算[J].管理世界,2005(4):56-64.
[106]林伯强.结构变化、效率改进与能源需求预测-以中国电力行业为例[J].经济研究,2003,5:7-10.
[107]倪铮,凌子未.中国石油需求量的协整计量分析[J].南开经济研究,2005,6:3-7.
[108]郑艳,刘磊,谢庄.城市增温与北京电力需求的计量分析[J].华北电力技术,2006,1:3-7.
[109]陈曦,丁明.采用协整检验的电力系统组合预测建模条件判定方法[J].电力自动化设备,2003,23(8):21-24.
[110]蔡杰进,马晓茜.支持向量机在电站汽轮机排汽焓在线预测中的应用[J].电力系统自动化,2006,30(18):77-82.
[111]许涛,贺仁睦,王鹏,徐东杰.基于输入空间压缩的短期负荷预测[J].电力系统自动化,2004,28(6):51-54,81.
[112]赵登福,王蒙,张讲社,王锡凡.基于支撑向量机方法的短期负荷预测[J].中国电机工程学报,2002,22(4):26-31.
[113]国家电力监管委员会,http://www.serc.gov.cn/
[114]李爱国.多粒子群协同优化算法[J].复旦学报(自然科学版),2004,43(5):1-5.
[115]J.Warfield.Societal Systems:Planning,Policy and Complexity,John Wiley & Sons,Inc.,New York,NY,1976:6-15.
[116]张鹏.电力需求侧管理改善电力系统可靠性的研究[硕士学位论文].河北:华北电力大学,2005.
[117]达庆利,何建敏.大系统理论和方法[M].南京:东南大学出版社,1989:34-46.
[118]Warfield J N.Participative methodology for public system planning[J].Computers & Electrical Engineering,1973,1(1):23-40.
[119]汪应洛.系统工程[M].北京:机械工业出版社,1986:24-56.
[120]汪应洛.系统工程理论、方法与应用[M].北京:高等教育出版社,1992:35-58.
[121]Huang,N.E.,Wu,Z.An adaptive data afialysis method for nonlinear and nonstationary time series:the empirical mode decomposition and hibert sepectual analysis.Proceedings of the 4th international conference on wavelet and its application,Macao,2005:569-578.
[122]张震龙.节能新机制在电力需求侧管理中的独特作用[J].电力需求侧管理,2003,5(5):24-26.
[123]樊正伟.电力需求侧管理与环境保护[J].电力需求侧管理,2005,7(3):27.
[124]林建新.以立体思维构筑保供电体系[J].中国经贸导刊,2005,21:16.
[125]陈湘桂.电力需求侧管理:调整电力供求结构的手段[J].市场论坛,2005,9(10):122-124.
[126]HERTER K.Residential implementation of critical-peak pricing of electricity[J].Energy Policy,2007,35(4):2121-2130.
[127]JORGE H,ANTUNES C H,MARTINS A G.A multiple objective decision support model for the selection of remote load control strategies[J].IEEE Trans on Power Systems,2000,15(2):865-872.
[128]GOMES A,ANTUNES C H,MARTINS A G.A multiple objective evolutionary approach for the design and selection of load control strategies[J].IEEE Trans on Power Systems,2004,19(2):1173-1180.
[129]GOMES A,ANTUNES C H,MARTINS A G.A multiple objective approach to direct load control using an interactive evolutionary algorithm[J].IEEE Trans on Power Systems,2007,22(3):1004-1011.
[130]HUANG K Y,HUANG Y C.Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services[J].IEEE Trans on Power Systems,2004,19(3):1626-1634.
[131]YAO L,CHANG W C,YEN R L.An iterative deepening genetic algorithm for scheduling of direct load control[J].IEEE Trans on Power Systems,2005,20(3):1414-1421.
[132]许之敏.电力需求侧管理现状、问题及对策[J].电力需求侧管理,2005,7(4):3-4.
[133]任玉珑,余良.需求侧管理技术对能源和环境的影响分析[J].重庆大学学报,2002,25(11):30-33.
[134]B.Satish,K.S.Swarup,S.Srinivas,A.Hanumantha Rao.Effect of temperature on short term load forecasting using an integrated ANN[J].Electric Power System Research,2004,72(2004):95-01.
[135]Chow T W S,Leung C T.Neural network based short-term load forecasting using weather compensation[J].IEEE Trans on Power System,1996,11(4):1736-1742.
[136]H.M.AL-Hamadi,S.A.Soliman.Long-term/mid-term electric load forecasting based on short-term correlation and annual growth[J].Electric Power Systems Research,2005,74(2005):353-361.
[137]Weigen,Andress S.Time serried analysisi and prediction using gated experts with application to energy demand forecasts[J].Applied Artificial Intelligence,1996,11-12:583-624.
[138]Soresen,bent.Non-linear modeling of integrated supply and demand systems[J].International Journal of Global Energy Issues,1999,1:131-137.
[139]S.Y.,Dong.Energy demand projections based on an uncertain dynamic system modeling approach[J].Energy Source,2000,7:443-451.
[140]Benjamin Warr,Robert Ayres.REXS:A forecasting model for assessing the impact of natural resource consumption and technological change on economic growth[J].Structural Change and Economic Dynamics,2005:45-54.
[141]Faruqui Ahmad,George Stephen.Quantifying customer response to dynamic pricing [J].The Electricity Journal,2005,18(4):53-63.
[142]Herter K,McAuliffe P,Rosenfeld A.An exploratory analysis of California residential customer response to critical peak pricing of electricity[J].Energy,2007,32(1):25-34.
[143]雷鸣.合同能源管理在电网企业开展节能服务中的实践应用[J].电力需求侧管理,2008,10(6):4-8.
[144]徐国泉,姜照华.技术进步、结构变化与美国能源效率的关系[J].科学学与科学技术管理,2007,3:104-107.
[145]刘文胜,叶永松,胡献忠,赖敏.华中电网电力节能潜力分析[J].华中电力,2004,17(5):47-49.
[146]朱守先,张雷.北京市产业结构的节能潜力分析[J].资源科学,2007,29(6):194-198.
[147]史丹.中国能源效率的地区差异与节能潜力分析[J].中国工业经济,2006,10:49-58.
[148]郭红岩,闫广林.山西铝厂电力消耗及节电潜力分析[J].有色冶金节能,2001,04:26-28.
[149]季强,李强,宋宏坤,菲利普·莫森索.江苏省能效资源潜力及能效电厂研究[J].电力需求侧管理,2005,4:19-22.
[150]房桂干.我国造纸工业节能减排现状和应采取的对策[J].江苏造纸,2007,4:8-10.
[151]张滨渭,祁君田,林心光.燃煤电厂电除尘器节电技术研究[J].电力设备,.2007,6:43-46.
[152]宋全.能源形势严峻建材企业节电迫在眉睫[J].中国建材,2007,8:54-55.
[153]魏桂华.建筑照明节能技术措施[J].广东建材,2007,9:182-184.
[154]王文森.产业结构相似系数在统计分析中的应用[J].中国统计,2007,10:47-48.
[155]刘祥文.负荷中心的确定方法[J].南昌航空工业学院学报,1998,1:63-68.
[156]龙文,王惠文.基于成分数据的市场集中度指标预测建模方法及应用[J].系统工程,2008,26(5):42-46.
[2]张海林,张金升,解芳.内蒙古发电企业可持续发展分析[J].内蒙古电力技术,2008,26(3):12-14.
[3]吕强.发电企业核心竞争力评价指标体系的研究[J].中国电力,2007,40(8):82-86.
[4]张立辉,顾蓉,伍业锋.发电企业竞争力来源和评价模型[J].价值工程,2006,2:75-78.
[5]单宏胜,黄文杰.发电企业竞争力评价的弓箭理论模型[J].中国电力,2008,41(6):6-9.
[6]瞿斌,田惠英,翟亚军.发电企业综合竞争力评价指标体系构建与方法研究[J].工业技术经济,2006,25(9):85-87,95.
[7]李莉,雷宇,葛旭波,曹福成,谭忠富.电网企业可持续发展的指标体系及评价方法[J].电力学报,2007,22(1):1-4,14.
[8]朱清.供电企业可持续发展分析与评价.[硕士学位论文].武汉:武汉大学,2003.
[9]陶文斌.输电网运营经济性评价系统研发.[硕士学位论文].北京:华北电力大学,2003.
[10]刘敦楠,陈雪青,何光宇,周双喜.电力市场评价指标体系的原理和构建方法[J].电力系统自动化,2005,29(23):2-7,14.
[11]刘敏.电网公司“一强三优”技术经济评价指标体系研究.[硕士学位论文].长沙:长沙理工大学,2007.
[12]杨宇,陈沁,岳光辉.电网重组后企业运作综合实力评价体系的研究[J].电力科学与工程,2003,2:27-29.
[13]段福兴,于秀艳.基于DEA的信息产业效率分析与评价[J].华东经济管理,2002,16(5):33-35.
[14]彭晓峰,廖学中.基于DEA的供电企业技术效率分析[J].中国电力教育,2007,2:176-178.
[15]Feng-Yu Lo,Chen-Fu Chien,Lin,J.T..A DEA study to evaluate the relative efficiency and investigate the district reorganization of the Taiwan Power Company[J].Power Systems,2001,16(1):170 - 178.
[16]李刚.水火电系统短期节能发电调度研究与应用.[博士学位论文].大连:大连理工大学,2007.
[17]王超.四川电网节能减排发电实时调度优化模型的研究[J].四川电力技术,2008,31(1):67-69.
[18]朱成章,徐任武.需求侧管理[M].北京:中国电力出版社,1999:5-35.
[19]国家经贸委经济运行局.加拿大,美国电力需求侧管理可资借鉴[J].中国经贸导刊,1998,(11):45.
[20]发展改革委,环保总局,电监会,能源办.节能发电调度办法(试行).
[21]陈卫昀,严仰光.分布式电源[J].电力电子技术,1999,2:82-85.
[22]陈金富,卢炎生.分布式电源技术在我国的应用探讨[J].水电能源科学,2005,23(2):61-64.
[23]张国光.分布式电源技术简介[J].电气时代,2004,11:46.
[24]梁才浩,段献忠.分布式发电及其对电力系统的影响[J].电力系统自动化,2001,2:53-56.
[25]王敏,丁明.分布式发电及其效益[J].合肥工业大学学报(自然科学版),2004,27(4):344-348.
[26]吴靖,江吴.分布式发电系统的应用及前景[J].农村电气化,2003,7:19-20.
[27]莫颖涛,吴为麟.分布式发电的研究方向[J].热力发电,2006,5:71-72.
[28]杨培宏,刘文颖.分布式发电的种类及前景[J].农村电气化,2007,3:54-56.
[29]高虎,李俊峰,许洪华.太阳能光伏发电技术发展状况与趋势分析[J].中国科技产业,2006,72-75.
[30]王亦楠.对我国发展太阳能热发电的一点看法[J].中国能源,2006,28(8):5-10.
[31]包耳.风力发电技术的发展现状[J].可再生能源,2004,2:53-55.
[32]谢建民,曾建成,邱毓昌.风力发电成本主要影响因素分析与计算[J].华东电力,2003,1:6-9.
[33]周双喜,王海超,陈寿孙.风力发电运行价值分析[J].电网技术,2006,30(14):98-101.
[34]沈磊.我国水电发电效益的定量分析[J].水力发电,2000,4:7-9.
[35]余毅,叶念渝.火电厂动态成本分析系统的研究[J].华中科技大学学报(自然科学版),2004,32(5):73-75.
[36]陈立民,徐征,张贵山等.小型生物质直燃发电工程及其效益分析[J].水利电力机械,2006,28(12):1-4.
[37]樊京春,王永刚,秦世平.生物质能发电电价的敏感因素分析[J].可再生能源,2006,2:49-53.
[38]邓晟,陈波.秸秆发电利弊分析[J].水利电力机械,2006,28(12):42-44.
[39]朱成章.电力需求侧管理与电源建设同等重要[J].供用电,2005,22(3):1-3,24.
[40]陈晨.能效电厂开建云南节能减排又添新”武器”[N].云南电力报,2008-4-21.
[41]马驰,虞良荣.能效电厂实施的条件分析和对策探讨[J].上海节能,2007,1:13-16.
[42]河北省将建“虚拟调峰电厂”[J].电力需求侧管理,2002,4(4):13.
[43]Malik A S.Simulation of DSM Resources as Generating Units in Probabilistic Production Costing Framework[J].IEEE Trans.On Power Systems,1998,13(4):1528-1533.
[44]Billinton R,Lakhanpal D.Impacts of demand side management on reliability cost/reliability worth analysis[J].IEE Proc.-Gener.Transm.Distrib,1996,143(3):225-231.
[45]黄强.电力供需综合资源的全过程协调管理[J].华东电力,2004,32(5):42-44.
[46]曾鸣,张艳馥,王鹤,贾俊国.基于综合资源规划的供需资源优化组合模型[J].电力系统自动化,2007,31(3):24-28.
[47]刘纪平,陈煜辉,陈军.有效利用需求侧管理资源确保电网安全经济运行[J].电力需求侧管理,2005,5(3):5-6.
[48]Doonerman Gerard L,Wangensteen Ivar.Demand side provision of peaking capacity and reserves in deregulated power systems[C].International Conference on Electric Utility Deregulation and Research Restructuring and Power Technologies 2000.London(UK),2000:290-295.
[49]李锐.系统负荷率对电网降损节能的影响[J].电气时代,2006,9:80-81.
[50]李蒙,王静,胡兆光.用电负荷率同供电煤耗关系的定量分析[J].电力需求侧管理,2005,38(11):40-42.
[51]刘昌,姚建刚,余虎,葛亮,李继传.一种新型的电网输电阻塞管理模式[J].电网技术,2005,29(12):16-21.
[52]宋晓辉.考虑需求侧管理的高压配电网规划.[硕士学位论文].北京:中国电力科学研究院,2005.
[53]刘强,黄民翔,张圣楠.电力市场可中断负荷用户属性研究[J].华东电力,2007,35(11:88-91.
[54]WENDERS J T.Peak load pricing in the electric utility industry[J].The Bell Journal of Economics,1976,7(1):232-241.
[55]丁宁,吴军基,邹云.基于DSM的峰谷时段划分及分时电价研究[J].电力系统自动化,2001,25(23):9-12.
[56]SHEEN J N,CHEN C S,WANG T Y.Response of larger industrial customers to electricity pricing by voluntary time-of-use in Taiwan[J].IEE Proceedings:Generation,Transmission anDistribution,1995,142(2):157-166.
[57]李晖,康重庆,夏清.考虑用户满意度的需求侧管理价格决策模型[J].电网技术,2004,28(23):1-6.
[58]DAVID A K,LI Y Z.Effect of inter-temporal factors on the real time pricing of electricity [J].IEEE Trans on Power Systems,1993,8(3):44-52.
[59]KIRSCHEN D S,STRBAC G,CUMPERAYOT P,et al.Factoring the elasticity of demand in electricity prices[J].IEEE Trans on Power Systems,2000,15(2):612-617.
[60]秦祯芳,岳顺民,余贻鑫,等.零售端电力市场中的电量电价弹性矩阵[J].电力系统自动化,2004,28(5):16-19.
[61]CELEBI E,DAVID F J.A model for efficient consumer pricing schemes in electricity markets[J].IEEE Trans on Power Systems,2007,22(1):60-67.
[62]王锡凡.关于电价制定方法的初步探讨[J].中国电力,1999,32(6):1-3.
[63]SHEEN J N,CHEN C S,YANG J K.Time-of-use pricing for load management programs in Taiwan Power Company[J].IEEE Trans on Power Systems,1994,9(1):388-396.
[64]丁伟,袁家海,胡兆光.基于用户价格响应和满意度的峰谷分时电价决策模型[J].电力系统自动化,2005,29(20):10-14.
[65]束洪春,董俊,吴永军,等.销售侧分行业实行丰枯峰谷分时电价初探[J].电力系统自动化,2006,30(14):36-40.
[66]张钦,王锡凡,王建学,等.丰枯季节电价决策模型分析[J].电力系统自动化,2007,31(24):7-11.
[67]段登伟,刘俊勇,吴集光.计及风险的配电公司最优分时零售电价模型[J].电力系统自动化,2005,29(3):8-12.
[68]盛晓萍,李成仁.我国电力需求侧电价机制适应性分析[J].电力需求侧管理,2007,9(6):6-8.
[69]龚玲丽,韩铁.电价在我国电力需求侧管理中的应用综述[J].集团经济研究,2006,6:110-111.
[70]汤玉东,徐诚,邹云.基于DSM的峰谷分时电价[J].电力需求侧管理,2006,8(6):11-13.
[71]赵娟,谭忠富,李晓军.分时电价下供电公司盈亏风险分析模型[J].电力需求侧管理,2005,7(1):9-11.
[72]任玉珑,黄清辉.能源效率与电力需求侧管理[J].生态经济,2005,2:104-107.
[73]杜成刚,曹基华,林一,张华.电力节能降耗技术措施分析[J].电力需求侧管理,2007,40(9):46-48.
[74]石建林.加大技改力度 强化电力需求侧管理[J].中国氯碱,2006,7:33-34.
[75]涂正革,肖耿.中国工业增长模式的转变[J].管理世界,2006(10):57-67.
[76]林毅夫,张鹏飞.适宜技术、技术选择和发展中国家的经济增长[J].经济学(季刊),2006,5(4):985-1005.
[77]陈勇,唐朱昌.中国工业的技术选择与技术进步:1985-2003[J].经济研究,2006,9:50-61.
[78]金煜,陈钊,陆铭.中国的地区工业集聚:经济地理、新经济地理与经济政策[J].经济研究,2006,4:79-89.
[79]黄玖立,李坤望.对外贸易、地方保护和中国的产业布局[J].经济学(季刊),2006,5(3):733-760.
[80]李廉水,周勇.技术进步能提高能源效率吗?[J].管理世界,2006,10:82-89.
[81]曾鸣.电力需求侧管理[M].北京:中国电力出版社,2000:24-35.
[82]张永翔,王倩文,梁洪浩.大客户负荷管理模式的研究[J].电网技术,2004,28(12):39-42.
[83]赵晓丽,张素芳,电力需求侧管理的国内外对比研究[J].电力需求侧管理,2005,8:60-62.
[84]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.
[85]尹春华,顾培亮.我国产业结构的调整与能源消费的灰色关联分析[J].天津大学学报,2003,36(1):104-107.
[86]陈勇,唐朱昌.中国工业的技术选择与技术进步:1985-2003[J].经济研究,2006,9:50-61.
[87]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.
[88]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):1-6,52.
[89]李小平,朱钟棣.中国工业行业的全要素生产率测算[J].管理世界,2005,4:6-12.
[90]张安华.中国电力工业节能降耗影响因素分析[J].电力需求侧管理,2006,18(6):1-4.
[91]包正.“首钢”DSM经验的启示[J].电力需求侧管理,2002,4(2):16.
[92]田文烈.电力需求侧管理在首都钢铁公司的应用[J].电力需求侧管理,2002,4(1):47-49.
[93]孙彦伟.DSM在济钢电网中的应用分析[J].电力需求侧管理,2003,5(5):49-51.
[94]于颖,苏震.钢铁企业实施DSM应对电力紧张形势的策略[J].电力需求侧管理,2005,7(1):7-8.
[95]林海英,李建荣,宣菊琴,魏宏俊.钢铁行业负荷特性及需求侧管理潜力分析[J].华东电力,2005,33(11):53-57.
[96]周长敬.电力需求侧管理对胜利油田的激励作用[J].电力需求侧管理,2004,6(4):8-10.
[97]李志军.电力需求侧管理在石化企业的发展方向[J].电力需求侧管理,2003,5(2):13-15.
[98]祝小红.电力需求侧管理对终端设备的影响[J].电力需求侧管理,2003,5(3):11-12.
[99]杨希智.DSM在纺织企业的运用[J].电力需求侧管理,2003,5(3):13-14.
[100]发改委等部门要求发电调度体现节能环保优先.国家电力信息网,2006-7-11.
[101]国务院办公厅关于转发《节能发电调度办法(试行)》的通知.中国能源网,2007-8-10.
[102]Caves,D.W.,L.R.Christensen and W.E.Diewert,The economic theory of index numbers and the measurement of input,output,and productivity[J].Econometrica,1982,50(6):1393-1414.
[103]Balk,B.M.,Malmquist productivity indexes and Fisher ideal indexes:comment[J].Economic Journal 1993,103(418):680 - 682.
[104]Sun,J.W.Changes in energy consumption and energy intensity:A complete decomposition model[J].Energy Economics,1998,20:85 - 100.
[105]李小平,朱钟棣.中国工业行业的全要素生产率测算[J].管理世界,2005(4):56-64.
[106]林伯强.结构变化、效率改进与能源需求预测-以中国电力行业为例[J].经济研究,2003,5:7-10.
[107]倪铮,凌子未.中国石油需求量的协整计量分析[J].南开经济研究,2005,6:3-7.
[108]郑艳,刘磊,谢庄.城市增温与北京电力需求的计量分析[J].华北电力技术,2006,1:3-7.
[109]陈曦,丁明.采用协整检验的电力系统组合预测建模条件判定方法[J].电力自动化设备,2003,23(8):21-24.
[110]蔡杰进,马晓茜.支持向量机在电站汽轮机排汽焓在线预测中的应用[J].电力系统自动化,2006,30(18):77-82.
[111]许涛,贺仁睦,王鹏,徐东杰.基于输入空间压缩的短期负荷预测[J].电力系统自动化,2004,28(6):51-54,81.
[112]赵登福,王蒙,张讲社,王锡凡.基于支撑向量机方法的短期负荷预测[J].中国电机工程学报,2002,22(4):26-31.
[113]国家电力监管委员会,http://www.serc.gov.cn/
[114]李爱国.多粒子群协同优化算法[J].复旦学报(自然科学版),2004,43(5):1-5.
[115]J.Warfield.Societal Systems:Planning,Policy and Complexity,John Wiley & Sons,Inc.,New York,NY,1976:6-15.
[116]张鹏.电力需求侧管理改善电力系统可靠性的研究[硕士学位论文].河北:华北电力大学,2005.
[117]达庆利,何建敏.大系统理论和方法[M].南京:东南大学出版社,1989:34-46.
[118]Warfield J N.Participative methodology for public system planning[J].Computers & Electrical Engineering,1973,1(1):23-40.
[119]汪应洛.系统工程[M].北京:机械工业出版社,1986:24-56.
[120]汪应洛.系统工程理论、方法与应用[M].北京:高等教育出版社,1992:35-58.
[121]Huang,N.E.,Wu,Z.An adaptive data afialysis method for nonlinear and nonstationary time series:the empirical mode decomposition and hibert sepectual analysis.Proceedings of the 4th international conference on wavelet and its application,Macao,2005:569-578.
[122]张震龙.节能新机制在电力需求侧管理中的独特作用[J].电力需求侧管理,2003,5(5):24-26.
[123]樊正伟.电力需求侧管理与环境保护[J].电力需求侧管理,2005,7(3):27.
[124]林建新.以立体思维构筑保供电体系[J].中国经贸导刊,2005,21:16.
[125]陈湘桂.电力需求侧管理:调整电力供求结构的手段[J].市场论坛,2005,9(10):122-124.
[126]HERTER K.Residential implementation of critical-peak pricing of electricity[J].Energy Policy,2007,35(4):2121-2130.
[127]JORGE H,ANTUNES C H,MARTINS A G.A multiple objective decision support model for the selection of remote load control strategies[J].IEEE Trans on Power Systems,2000,15(2):865-872.
[128]GOMES A,ANTUNES C H,MARTINS A G.A multiple objective evolutionary approach for the design and selection of load control strategies[J].IEEE Trans on Power Systems,2004,19(2):1173-1180.
[129]GOMES A,ANTUNES C H,MARTINS A G.A multiple objective approach to direct load control using an interactive evolutionary algorithm[J].IEEE Trans on Power Systems,2007,22(3):1004-1011.
[130]HUANG K Y,HUANG Y C.Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services[J].IEEE Trans on Power Systems,2004,19(3):1626-1634.
[131]YAO L,CHANG W C,YEN R L.An iterative deepening genetic algorithm for scheduling of direct load control[J].IEEE Trans on Power Systems,2005,20(3):1414-1421.
[132]许之敏.电力需求侧管理现状、问题及对策[J].电力需求侧管理,2005,7(4):3-4.
[133]任玉珑,余良.需求侧管理技术对能源和环境的影响分析[J].重庆大学学报,2002,25(11):30-33.
[134]B.Satish,K.S.Swarup,S.Srinivas,A.Hanumantha Rao.Effect of temperature on short term load forecasting using an integrated ANN[J].Electric Power System Research,2004,72(2004):95-01.
[135]Chow T W S,Leung C T.Neural network based short-term load forecasting using weather compensation[J].IEEE Trans on Power System,1996,11(4):1736-1742.
[136]H.M.AL-Hamadi,S.A.Soliman.Long-term/mid-term electric load forecasting based on short-term correlation and annual growth[J].Electric Power Systems Research,2005,74(2005):353-361.
[137]Weigen,Andress S.Time serried analysisi and prediction using gated experts with application to energy demand forecasts[J].Applied Artificial Intelligence,1996,11-12:583-624.
[138]Soresen,bent.Non-linear modeling of integrated supply and demand systems[J].International Journal of Global Energy Issues,1999,1:131-137.
[139]S.Y.,Dong.Energy demand projections based on an uncertain dynamic system modeling approach[J].Energy Source,2000,7:443-451.
[140]Benjamin Warr,Robert Ayres.REXS:A forecasting model for assessing the impact of natural resource consumption and technological change on economic growth[J].Structural Change and Economic Dynamics,2005:45-54.
[141]Faruqui Ahmad,George Stephen.Quantifying customer response to dynamic pricing [J].The Electricity Journal,2005,18(4):53-63.
[142]Herter K,McAuliffe P,Rosenfeld A.An exploratory analysis of California residential customer response to critical peak pricing of electricity[J].Energy,2007,32(1):25-34.
[143]雷鸣.合同能源管理在电网企业开展节能服务中的实践应用[J].电力需求侧管理,2008,10(6):4-8.
[144]徐国泉,姜照华.技术进步、结构变化与美国能源效率的关系[J].科学学与科学技术管理,2007,3:104-107.
[145]刘文胜,叶永松,胡献忠,赖敏.华中电网电力节能潜力分析[J].华中电力,2004,17(5):47-49.
[146]朱守先,张雷.北京市产业结构的节能潜力分析[J].资源科学,2007,29(6):194-198.
[147]史丹.中国能源效率的地区差异与节能潜力分析[J].中国工业经济,2006,10:49-58.
[148]郭红岩,闫广林.山西铝厂电力消耗及节电潜力分析[J].有色冶金节能,2001,04:26-28.
[149]季强,李强,宋宏坤,菲利普·莫森索.江苏省能效资源潜力及能效电厂研究[J].电力需求侧管理,2005,4:19-22.
[150]房桂干.我国造纸工业节能减排现状和应采取的对策[J].江苏造纸,2007,4:8-10.
[151]张滨渭,祁君田,林心光.燃煤电厂电除尘器节电技术研究[J].电力设备,.2007,6:43-46.
[152]宋全.能源形势严峻建材企业节电迫在眉睫[J].中国建材,2007,8:54-55.
[153]魏桂华.建筑照明节能技术措施[J].广东建材,2007,9:182-184.
[154]王文森.产业结构相似系数在统计分析中的应用[J].中国统计,2007,10:47-48.
[155]刘祥文.负荷中心的确定方法[J].南昌航空工业学院学报,1998,1:63-68.
[156]龙文,王惠文.基于成分数据的市场集中度指标预测建模方法及应用[J].系统工程,2008,26(5):42-46.
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