低碳发电调度模式及其电价机制研究
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摘要
发电调度模式是随着电力技术的进步、电力工业体制的变革乃至资源与环境约束的渐强而与时俱进的。近年来,受气候变暖趋势加速的影响,全球极端天气气候事件发生的频率及强度激增,控制温室气体排放已成为世界各国的普遍共识。作为化石能源消耗与CO2排放的重点行业,电力行业仅考虑节约化石能源及减排SO2和氮氧化物的调度运行模式显然已不能适应新形势,亟需构建以低碳为主要特征的新型发电调度模式。本文在剖析低碳发电调度提出背景及现实目标的基础上,系统、深入地研究了低碳发电调度的实现模式及上网电价机制。论文研究取得了以下主要研究成果：
以发电能耗最小与碳排放量最小为目标,建立了低碳发电调度的日前发电计划模型；而后,在建立与外部环境约束相适应的碳排放外部成本量化模型基础上,通过引入燃料价格、碳排放外部成本,从而将具有双重优化目标的低碳发电调度优化模型转化为以系统发电能耗与碳排放总成本最小化为目标的单目标优化模型。算例结果表明,相比于节能发电调度模式,低碳发电调度可显著降低电力系统的碳排放总量,促进包含环境效益在内的社会效益的增进。
在区域层面统一开展低碳发电调度有利于促进互联电网节能减碳效益的增进,但也面临着省间利益调整带来的现实阻力,因而,亟需研究一种可实现节能低碳的调度优化目标并兼顾省间利益均衡性的跨省区低碳发电调度实现模式。针对该问题,本文以进一步挖掘互联电力系统节能减碳潜力为目标,以兼顾省间利益均衡性为约束,提出了两种促进跨省区低碳发电调度的区域发电权交易模式,即考虑省间利益调整约束的区域统一优化模式和网省分层优化模式；而后,结合发电权交易中市场主体的报价特点,建立了考虑发电商报价风险的发电权交易市场均衡模型,结合具体算例,验证了模型的有效性,并应用该模型对两种可行模式的运行效果进行了仿真分析。仿真结果表明,考虑省间利益调整约束的区域统一优化模式可在兼顾省间利益均衡性的前提下,促进互联系统节能减碳效益的提升。
将风电与抽水蓄能联合运行是在当前风电大规模、集中式开发引发并网难题的现实背景下,解决风电发展瓶颈约束、促进系统节能减碳优化目标实现的一种低碳发电调度实现模式。本文在考虑抽水蓄能机组运行特性的基础上,建立了含抽水蓄能电力系统的低碳发电调度优化模型；并在该模型基础上,以社会效益最大化为目标,构建了风电—抽水蓄能匹配容量优化模型。算例分析表明,所提模型可促进风电与抽水蓄能的合理配置,实现社会效益的提高。
合理的上网电价机制设计,是解决调度模式变革形势下发电企业利益失衡问题的根本路径,同时也是低碳发电调度实施所依赖的重要外部系统条件。本文提出分时电价、两部制电价等两种可能的低碳发电调度上网电价机制,并分别建立了定价模型。算例分析表明,两部制上网电价可在合理解决发电企业利益失衡问题的基础上,实现电网购电成本最低目标以及低碳发电调度目标的统一,是符合激励相容理念的低碳发电调度上网电价机制；而后,重点研究了两部制上网电价中容量电价定价模式的优化设计问题,在仿真验证了基于可靠性定价模型的容量电价定价模式有效性的基础上,针对于该定价模式下需由政府委托电网企业进行容量需求预测,并应通过合理的机制设计激励电网企业提高容量需求预测准确性的问题,应用委托代理理论,提出了基于逆向选择模型的政府—电网企业委托代理机制设计方案,并通过算例验证了设计机制的有效性。
本文提出的低碳发电调度模式及其上网电价机制,为当前电力系统运行实现节能低碳目标提供有价值的参考方案,不仅具有学术价值,而且对改进发电调度方式、促进电力工业与经济社会和谐发展、实现低碳经济发展具有实践价值。
The development of generation dispatch mode is relevant to the power technology advancement, reforming for power industry, as well as increasing resources and environmental constrains. In recent years, with the acceleration of global warming, the frequency and intensity of extreme weather events increased, control greenhouse gas emissions has become the general consensus of the world. The power industry, as the key industries of fossil energy consumption and CO2emissions, its traditional run mode that only considering fossil energy conservation and emission reduction of SO2and NOX, can not adapt to the new situation, need to establish a new generation dispatch mode.
Based on the analyze the background and realistic goals of low-carbon generation dispatch, this paper intended to provide a comprehensive and in-depth analysis of the implementation mode and its support conditions of low-carbon generation dispatch. First, research on the implementation mode of low-carbon generation dispatch including the internal and across province were studied with the target of energy-saving and carbon-reducing. Second, research on the price mechanism of low-carbon generation dispatch and optimal capacity of wind power and pumped-storage power station in order to promote and safeguard the smooth implementation of low-carbon generation dispatch. The research work has made the following key results:
Comprehensively considering the unit commitment, economical load allocation, a low-carbon generation dispatching model was established. Then, in order to calculate external costs of carbon emissions, considering the emission reduction constraints, this paper established a quantitative model with the objective of minimization the cost of power generation, a specific examples was given to prove the validity of this model.
With the target of expanding the potential of energy conservation and emission reduction and promoting the optimal allocation of regional resources, two regional generation right trading mode was proposed, layered optimization mode between regional and provincial networks, and integrated optimization mode with interest constraints in regional networks. Considering the bidding strategies of the main players in the generation right trade, this paper established a market equilibrium model of generation right trade, and apply this model for the simulation analysis of the operating results of the two possible modes, example analysis shows that integrated optimization mode can maximize benefit of energy-saving and carbon-reducing and meet the interest constraints.
Optimize capacity of wind power and pumped-storage power station in power system can promote the development of wind power and provide the material basis for low-carbon generation dispatch. Considering the operating characteristics of pumped-storage power station, this paper established the low-carbon generation dispatching model in PS integrated systems. Based on this model, this paper established a capacity optimization model of wind power and pumped-storage power station using maximize the social benefits as objective function. example analysis shows that this model can promote the development of wind power and improve the social benfits of power systems.
Design reasonable price mechanism is the fundamental way to control the imbalance between power companies in low-carbon generation dispatch mode. Based on the price theory and practical experience, this paper proposed time-of-use price and two-part price as the possible price mechanism for low-carbon generation dispatch mode, and establish the corresponding pricing model. The simple case show that two-part price can slove the imbalance problem and achieve the unity of minimum the power purchase costs and minimum the cost of energy consumption and carbon emissions. Then, this paper focus on the optimal design of capacity pricing mode. The effectiveness of the capacity price mode based on reliability pricing model was verified by using the system dynamics model which is established in this paper. In this price mode, the government as a regulator need to entrust the grid company to forecast the capacity needed, to inspire the grid company to improve the accuracy of system capacity demand forecast, a mechanism of the capacity price regulation based on principal-agent theory is designed, and examples are given finally to verify its correctness.
以发电能耗最小与碳排放量最小为目标,建立了低碳发电调度的日前发电计划模型；而后,在建立与外部环境约束相适应的碳排放外部成本量化模型基础上,通过引入燃料价格、碳排放外部成本,从而将具有双重优化目标的低碳发电调度优化模型转化为以系统发电能耗与碳排放总成本最小化为目标的单目标优化模型。算例结果表明,相比于节能发电调度模式,低碳发电调度可显著降低电力系统的碳排放总量,促进包含环境效益在内的社会效益的增进。
在区域层面统一开展低碳发电调度有利于促进互联电网节能减碳效益的增进,但也面临着省间利益调整带来的现实阻力,因而,亟需研究一种可实现节能低碳的调度优化目标并兼顾省间利益均衡性的跨省区低碳发电调度实现模式。针对该问题,本文以进一步挖掘互联电力系统节能减碳潜力为目标,以兼顾省间利益均衡性为约束,提出了两种促进跨省区低碳发电调度的区域发电权交易模式,即考虑省间利益调整约束的区域统一优化模式和网省分层优化模式；而后,结合发电权交易中市场主体的报价特点,建立了考虑发电商报价风险的发电权交易市场均衡模型,结合具体算例,验证了模型的有效性,并应用该模型对两种可行模式的运行效果进行了仿真分析。仿真结果表明,考虑省间利益调整约束的区域统一优化模式可在兼顾省间利益均衡性的前提下,促进互联系统节能减碳效益的提升。
将风电与抽水蓄能联合运行是在当前风电大规模、集中式开发引发并网难题的现实背景下,解决风电发展瓶颈约束、促进系统节能减碳优化目标实现的一种低碳发电调度实现模式。本文在考虑抽水蓄能机组运行特性的基础上,建立了含抽水蓄能电力系统的低碳发电调度优化模型；并在该模型基础上,以社会效益最大化为目标,构建了风电—抽水蓄能匹配容量优化模型。算例分析表明,所提模型可促进风电与抽水蓄能的合理配置,实现社会效益的提高。
合理的上网电价机制设计,是解决调度模式变革形势下发电企业利益失衡问题的根本路径,同时也是低碳发电调度实施所依赖的重要外部系统条件。本文提出分时电价、两部制电价等两种可能的低碳发电调度上网电价机制,并分别建立了定价模型。算例分析表明,两部制上网电价可在合理解决发电企业利益失衡问题的基础上,实现电网购电成本最低目标以及低碳发电调度目标的统一,是符合激励相容理念的低碳发电调度上网电价机制；而后,重点研究了两部制上网电价中容量电价定价模式的优化设计问题,在仿真验证了基于可靠性定价模型的容量电价定价模式有效性的基础上,针对于该定价模式下需由政府委托电网企业进行容量需求预测,并应通过合理的机制设计激励电网企业提高容量需求预测准确性的问题,应用委托代理理论,提出了基于逆向选择模型的政府—电网企业委托代理机制设计方案,并通过算例验证了设计机制的有效性。
本文提出的低碳发电调度模式及其上网电价机制,为当前电力系统运行实现节能低碳目标提供有价值的参考方案,不仅具有学术价值,而且对改进发电调度方式、促进电力工业与经济社会和谐发展、实现低碳经济发展具有实践价值。
The development of generation dispatch mode is relevant to the power technology advancement, reforming for power industry, as well as increasing resources and environmental constrains. In recent years, with the acceleration of global warming, the frequency and intensity of extreme weather events increased, control greenhouse gas emissions has become the general consensus of the world. The power industry, as the key industries of fossil energy consumption and CO2emissions, its traditional run mode that only considering fossil energy conservation and emission reduction of SO2and NOX, can not adapt to the new situation, need to establish a new generation dispatch mode.
Based on the analyze the background and realistic goals of low-carbon generation dispatch, this paper intended to provide a comprehensive and in-depth analysis of the implementation mode and its support conditions of low-carbon generation dispatch. First, research on the implementation mode of low-carbon generation dispatch including the internal and across province were studied with the target of energy-saving and carbon-reducing. Second, research on the price mechanism of low-carbon generation dispatch and optimal capacity of wind power and pumped-storage power station in order to promote and safeguard the smooth implementation of low-carbon generation dispatch. The research work has made the following key results:
Comprehensively considering the unit commitment, economical load allocation, a low-carbon generation dispatching model was established. Then, in order to calculate external costs of carbon emissions, considering the emission reduction constraints, this paper established a quantitative model with the objective of minimization the cost of power generation, a specific examples was given to prove the validity of this model.
With the target of expanding the potential of energy conservation and emission reduction and promoting the optimal allocation of regional resources, two regional generation right trading mode was proposed, layered optimization mode between regional and provincial networks, and integrated optimization mode with interest constraints in regional networks. Considering the bidding strategies of the main players in the generation right trade, this paper established a market equilibrium model of generation right trade, and apply this model for the simulation analysis of the operating results of the two possible modes, example analysis shows that integrated optimization mode can maximize benefit of energy-saving and carbon-reducing and meet the interest constraints.
Optimize capacity of wind power and pumped-storage power station in power system can promote the development of wind power and provide the material basis for low-carbon generation dispatch. Considering the operating characteristics of pumped-storage power station, this paper established the low-carbon generation dispatching model in PS integrated systems. Based on this model, this paper established a capacity optimization model of wind power and pumped-storage power station using maximize the social benefits as objective function. example analysis shows that this model can promote the development of wind power and improve the social benfits of power systems.
Design reasonable price mechanism is the fundamental way to control the imbalance between power companies in low-carbon generation dispatch mode. Based on the price theory and practical experience, this paper proposed time-of-use price and two-part price as the possible price mechanism for low-carbon generation dispatch mode, and establish the corresponding pricing model. The simple case show that two-part price can slove the imbalance problem and achieve the unity of minimum the power purchase costs and minimum the cost of energy consumption and carbon emissions. Then, this paper focus on the optimal design of capacity pricing mode. The effectiveness of the capacity price mode based on reliability pricing model was verified by using the system dynamics model which is established in this paper. In this price mode, the government as a regulator need to entrust the grid company to forecast the capacity needed, to inspire the grid company to improve the accuracy of system capacity demand forecast, a mechanism of the capacity price regulation based on principal-agent theory is designed, and examples are given finally to verify its correctness.
引文
[1]张坤民.低碳经济论[M].北京：中国环境科学出版社,2008：48－56
[2]TSO. Energy White Paper:Our Energy Future—Create a Low Carbon Economy[Z], London, UK:TSO,2003
[3]中国工控网.2011年中国工业节能与自动化需求研究报告[M].北京：中国工控网,2011
[4]国务院.国务院批转国家经委等部门《关于鼓励集资办电和实行多种电价的暂行规定》的通知[S].北京：国务院,1985
[5]国务院.电网调度管理条例[Z].北京：国务院,1993
[6]国家电力监管委员会.关于促进电力调度公开、公平、公正的暂行办法[Z].北京：国家电力监管委员会,2004
[7]国家发展和改革委员会、国家环境保护总局、国家电力监管委员会、国家能源领导小组办公室.节能发电调度试点工作方案和实施细则(试行),发改能源[2007]3523号[S].北京：国家发展改革委,2007
[8]国务院办公厅.国务院关于转发发展改革委等部门节能发电调度办法(试行)的通知,国办发[2007]53号[S].北京：国务院办公厅,2007
[9]陈俊武.中国中长期碳减排战略目标研究[M].北京：中国石化出版社,2012：32-33
[10]于尔铿.现代电力系统经济调度[M].北京：水利电力出版社,1986：21－25
[11]谢国辉.绿色发电调度模式和模型研究[D].北京：华北电力大学,2010
[12]国家电力监管委员会.欧洲,澳洲电力市场改革[M].北京：中国电力出版社,2006：125-245
[13]王楠.发电调度优化模型与方法研究[D].北京：华北电力大学,2011
[14]李彩华,郭志忠,樊爱军.电力系统优化调度概述(Ⅰ)—经济调度与最优潮流[J].电力系统及其自动化学报,2002,14(2)：60-63
[15]卫志农,鞠平.电力系统经济调度综述[J].河海科技进展,1994,14(2)：29-31
[16]Steinberg M J, Smith Theodore H. The theory of incremental rates and their practical application to load division-part I. Transactions of the American Institute of Electrical Engineers[J].1934,53(3):432-445
[17]Steinberg M J, Smith Theodore H. The theory of incremental rates and their practical application to load division-part II. Transactions of the American Institute of Electrical Engineers [J].1934,53(4):571-584
[18]Kirchmayer L K, Stagg G W.Analysis of total and incremental losses in transmission systems[J]. AIEE Traps,1951,70(2):647-653
[19]Carpentier J. Contribution a'letude du Dispatching Economique[J]. Bulletin de laociete Francaise des Electriciens,1962,3(1)431-447
[20]Rabih A. Jabr. A Primal-Dual Interior-Point Method to Solve the Optimal Power Flow Dispatching Problem[J]. Optimization and Engineering,2003,4(4):1-6
[21]Cai H R, Chung C Y, Wong K P. Application of differential evolution algorithm for transient stability constrained optimal power flow[J]. IEEE Trans on Power Systems,2008,23(2):719-728
[22]Capitanescu F, Glavic M, Ernst D, etal. Contingency filtering techniques for preventive security-constrained optimal power flow[J]. IEEE Trans on Power Systems,2007,22(4):1690-1697
[23]Liu Keyan, Sheng Wanxing, Li Yunhua. Research on parallel algorithm of DC optimal power flow in large interconnection power grids[C]. Proceedings of the Eighth International Conference on Electrical Machines and Systems,2005,2: 1031-1036
[24]刘科研,盛万兴,李运华.互联电网的直流最优潮流分解算法研究[J].中国电机工程学报,2006,26(12)：21-25
[25]Somuah G B, Khunaizi N. Application of linear programming redispatch technique to dynamic generation allocation[J]. IEEE Trans on Power Systems,1990,5(1): 20-26
[26]韩学山.动态优化调度的积留量法[D].哈尔滨：哈尔滨工业大学,1994
[27]Barcelo W R, Rastgoufard P. Dynamic economic dispatch using the extend security constrained economic dispatch algorithm[J]. IEEE Trans on Power Systems,1997, 12(2):961-967
[28]Panigrahi C K, Chattopadhyay P K, Chakrabarti R N, et al. Simulated annealing technique for dynamic economic dispatch [J]. Electric Power Components and Systems,2006,34(5):577-586
[29]杨朋朋, 韩学山.一种考虑时间关联约束的安全约束经济调度解法[J].电力系统自动化,2008,32(17)：30-34
[30]杨明,韩学山,梁军.计及网络安全约束及用户停电损失的动态经济调度方法[J].电力系统自动化,2009,33(14)：27-31
[31]Rabih A. Jabr.'A Primal-Dual Interior-Point Method to Solve the Optimal Power Flow Dispatching Problem[J]. Optimization and Engineering,2003,4(4):1-6
[32]王锡凡,王秀丽,陈皓勇.电力市场基础[M].西安：西安交通大学出版社,2003：11－20
[33]尚金成.基于时间尺度的节能发电优化调度协调模型及算法[J].电力系统自动化,2008,32(15)：56-61
[34]胡建军,李嘉龙,陈慧坤.基于煤耗和排放的日发电曲线编制模型[J].电力系统自动化,2009,33(12)：43-45,96
[35]Gentm R, Lamont J W. Minimum Emission Dispatch[J]. IEEE Trans. On PAS, 1971,90:2650-2660
[36]张宁,陈慧坤,骆晓明,等.广东电网节能发电调度计划模型与算法[J].电网技术,2008,32(23)：7－12
[37]王超,张晓明,唐茂林,等.四川电网节能减排发电实时调度优化模型[J].电力系统自动化,2008,32(4)：89-92
[38]陈启鑫,康重庆,夏清.低碳电力调度方式及其决策模型[J].电力系统自动化,2010,34(12)：18－22
[39]朱建广,谢青松.基于适应性遗传算法的新型低碳发电调度[J].广东电力,2011,24(2)：32-36
[40]黎灿兵,刘玛,曹一家,等.低碳发电调度与节能发电调度的一致性评估[J].中国电机工程学报,2011,31(31)：94-101
[41]崔明勇,艾欣.基于混沌蚁群算法的微网多目标低碳调度[J].中国电业(技术版),2012,(7)：1－5
[42]高春成,王良缘,刘文彬,等.低碳调度下机组组合问题的混沌遗传混合优化方法[J].华东电力,2013,41(1)：160-164
[43]朱泽磊,周京阳,韩忠旭,等.基于多阶段不同政策机制的低碳电力调度模型[J].电网技术,2013,37(2)：287-294
[44]Tamura H, Kimura T. Evaluating the Effectiveness of Carbon Tax and Emissions Trading for Resolving Social Dilemma on Global Environment[C]. Systems, Man and Cybernetics,2007. ISIC. IEEE International Conference,1746-1751
[45]YU Z, PRECKEL P V, NDERITU G, et al. A locational gaming model with CO2 emission tax and limits[J]. International Journal of Electrical Power & Energy Systems,2001,23(6):451-457
[46]于超,谭忠富,胡庆辉,等.激励发电节能减排交易的Nash均衡两级优化模型[J].电力系统保护与控制,2011,39(7)：63－66,73
[47]于超,谭忠富.基于排放绩效的燃煤电厂碳税优化模型[J].华东电力,2011,39(6)： 845－849
[48]魏学好,李瑞庆,陈宇晨.具有节能减排内核的电力市场新模型[J].电力系统自动化,2009,33(15)：24-28,106
[49]Ellerman A D, Buchner B K. The European Union emissions trading scheme: origins, allocation and early results[J]. Review of Environmental Economics and Policy,2007,1(1):66-87
[50]史彪,刘晓东.欧盟碳排放交易制度对我国的启示[J].山西师范大学学报,2011,38(7)：23-25
[51]王毅刚.中国碳排放交易体系设计研究[D].北京：中国社会科学研究院.2010
[52]刘国中,文福拴,薛禹胜.温室气体排放权交易对发电公司最优报价策略的影响[J],电力系统自动化,2009,33(19)：15－20
[53]高慧,魏学好,文福拴.排污权交易实施后的寡头垄断电力市场的均衡分析[J],华北电力大学学报,2009,36,(6)：8-13
[54]王万山.庇古与科斯的规制理论比较[J].贵州财经学院学报,2007,(3)：23－28
[55]刘红,唐元虎.外部性的经济分析与对策[J].南开经济研究,2001,(1)：45－48
[56]杨帆.国际碳定价机制研究及其启示[J].商业时代,2012,(4)：7－8
[57]Day C J, Hobbs B F, Pang J S. Oligopolistic Competition In Power Networks: A Conjectured Supply Function Approach[J]. IEEE Trans on Power Systems, 2002,17(3):597-607
[58]Wang Xian, Li Yuzeng, Zhang Shaohua. Oligopolistic equilibrium analysis for electricity markets:a nonlinear complementarity approach[J]. IEEE Trans on Power Systems,2004,19(3):1348-1355
[59]Bower J, Bunn D. Experimental analysis of the efficiency of uniform price versus discriminatory auctions in the England and Wales electricity market [J]. Journal of Economic Dynamics and Control,2001,25(4):561-592
[60]Sun J, Tesfatsion L. Dynamic testing of wholesale power market designs:an open source agent based framework[J]. Computational Economics,2007,30(3):291-327
[61]Power Systems Engineering Research Center(PSERC). Power web user's manual version 2.7[M], Cornell University,2001
[62]Center for Energy, Environmental and Economic Systems Analysis (CEEESA) Decision and Information Sciences Division. Electricity market complex adaptive system(EMCAS)user's manual version 2.0, Argonne National Laboratory,2006
[63]Weber J D, Oberbye T J. A two level optimization problem for analysis of market bidding strategies[C]. Proceedings of IEEE Power Engineering Society Summer Meeting, July18-22,1999, Edmonton, Canada:682-687
[64]Wwber J D. An individual welfare maximization algorithm for electricity markets[J]. IEEE Trans on Power Systems,2002,17(3):590-596
[65]杨彦,陈皓勇,张尧.基于协同进化算法求解寡头电力市场均衡[J].电力系统自动化,2009,33(18)：42－46
[66]Son Y, Baldick R. Hybrid co-evolutionary programming for Nash equilibrium search in games with local optima[J]. IEEE Transactions on Evolutionary Computation,2004,8(4):305-315
[67]Cau T D H, Anderson E J. A co-evolutionary approach to modeling the behavior of participants in competitive electricity markets[C]. Proceedings of IEEE Power Engineering Society Summer Meeting, July 25,2002, Chicago, IL, USA:1534-154
[68]Chen H, Wong K P, Nguyen D H M, etal. Analyzing oligopolistic electricity market using co-evolutionary computation. IEEE Trans on Power Systems,2006, 21(1):143-152
[69]陈皓勇,杨彦,张尧.电力市场智能模拟中代理决策模块的实现[J].电力系统自动化,2008,32(20)：12－16
[70]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6)：13-18
[71]王雁凌,张粒子,杨以涵.基于水火电置换的发电权调节市场[J],中国电机工程学报,2006,26(5)：131-136
[72]尚金成.基于节能减排的发电权交易理论及应用：(一)发电权交易理论[J],电力系统自动化,2009,33(12)：46－52
[73]尚金成,何洋.基于节能减排的发电权交易理论及应用：(二)发电权交易分析及应用[J],电力系统自动化,2009,33(13)：37－42
[74]王雁凌,程倩.基于节能降耗的发电权交易模型[J],电力系统保护与控制,2010,38(18)：28-32
[75]伍玉林,文福拴,丁剑鹰,等.基于两部制电价的发电权交易模式[J],华北电力大学学报,2010,37(5)：16－22
[76]陈赞,严正.考虑节能减排与网络约束的发电权交易模型[J],电力系统保护与控制,2009,37(12)：52-57
[77]廖湘凯,鲍海.考虑阻塞的发电权交易改进模型[J].现代电力,2010,27(1)：81－85
[78]陈启鑫,康重庆,程旭东,等.考虑阻塞管理的发电权交易模型及其网络流算法[J].中国电机工程学报,2008,28(34)：106－111
[79]肖健,文福拴.发电权交易的阻塞调度[J].电力系统自动化,2008,32(18)： 24-29
[80]舒隽,张丽娟,张粒子,等.发电权竞价交易的两阶段方法[J].电网技术,2011,35(11)：200-205
[81]张午阳.发电权转让交易中的博弈行为的研究[J].华中电力,2005,18(6)：1－4
[82]廖屹.基于博弈理论的发电权交易研究[D].成都：西南交通大学,2008
[83]于琪.区域发电权交易优化模式研究[D].北京：华北电力大学,2012
[84]迟永宁,刘燕华,王伟胜,等.风电接入对电力系统的影响[J].电网技术,2007,31(3)：77-81
[85]戴慧珠,王伟胜,迟永宁.风电场接入电力系统研究的新进展[J].电网技术,2007,31(20)：16-23
[86]张红光,张粒子,陈树勇,等.大容量风电场对电力系统小干扰稳定和阻尼特性的影响[J].电网技术,2007,31(13)：75－80
[87]Barton J P, Infield D G. Energy storage and its use with intermittent renewable energy[J]. IEEE Trans, on Energy Conversion,2004,19(2):441-448
[88]Abbey C, Joos G. Supercapacitor energy storage for wind energy application [J]. IEEE Trans on Industry Applications,2007,43(3):769-776
[89]张步涵,曾杰,毛承雄,等.电池储能系统在改善并网风电场电能质量和稳定性中的应用[J].电网技术,2006,30(15)：54－58
[90]于芃,周玮,孙辉,等.用于风电功率平抑的混合储能系统及其控制系统设计[J].中国电机工程学报,2011,31(17)：127－133
[91]C. Buen, J. A. Carta. Technical-economic analysis of wind-powered pumped hydro storage systems, Part Ⅰ:model development[J].Solar Energy,2005,78(3): 396-405
[92]刘德有,谭志忠,王丰.风电-抽水蓄能联合运行系统的可行性研究[J].上海电力,2007,(1)：39－42
[93]李强,袁越,李振杰,等.考虑峰谷电价的风电-抽水蓄能联合系统能量转化效益研究[J].电网技术,2009,33(6)：13－18
[94]Edgardo D. Castronuovo, Lopes Joao A. Pecas. Optimal operation and hydro storage sizing of a wind-hydro power plant[J]. Electrical Power and Energy Systems.2004,26(10):771-778
[95]范永威.风——水电联合优化运行研究[D].河海大学,2007
[96]王艳.风—蓄联合运行系统可行性研究[D].华北电力大学(北京),2008
[97]潘文霞,范永威,朱莉,等.风电场中抽水蓄能系统容量的优化选择[J].电 工技术学报,2008,23(3)：120－124
[98]李志恒.风蓄联合系统规划问题研究[D].华中科技大学,2008
[99]张粒子.区域电力市场电价机制[M].北京：中国电力出版社,2004：84-85
[100]国家发展和改革委员会.发改价格[2005]514号,上网电价管理暂行办法[S].北京：国家发展和改革委员会,2005
[101]李帆,朱敏.英国电力市场及输电系统简介[J].电力系统自动化,1999,23(2)：33-40
[102]Johannes Pfeifenberger, Samuel Newel, IRobert Earle, etc. Review of PJM's Reliability Pricing Model(RPM)[R].2008, http://www.pjm.com
[103]Benjamin FHobbs, Ming-CheHu, JavierG Inon, etc. A Dynamic Analysis of a Demand Curve-Based Capacity Market Proposal:The PJM Reliability Pricing Model[J]. IEEE Trans. On Power System,2007,22(1):3-14
[104]PJM training materials Reliability Pricing Model[R]. Auction Clearing Example. http://www.pjm.com
[105]郝继陶,周丽丽.两部制上网电价的定价原则与模型[J].武汉汽车工业大学学报.2000,(22)4：98－101
[106]王黎,马光文.两部制上网电价定价方法初探[J].四川大学学报(工程科学版).2000,(32)1：62-66
[107]马光文,王黎.两部制上网电价的长期边际成本定价方法[J].水力发电学报.2000,4：66-71
[108]赵建国.容量电价随市场变化的两部制电价模式探讨rJ].华北电业,1998,9：4-6
[109]黄健柏,邵留国,张仕骡.两部制电价与发电容量投资的系统动力学分析[J].电力系统及其自动化学报,2007,19(2)：21－27
[110]黄健柏,邵留国,张仕骡,等.两部制电价下电力市场系统动力学仿真[J].系统管理学报,2007,16(4)：407-416,421
[111]张媛媛.基于需求曲线的容量市场定价模型研究[D].北京：华北电力大学,2009
[112]张可佳.基于委托代理理论的容量电价规制模型研究[D].北京：华北电力大学,2010
[113]张森林.节能发电调度配套上网电价定价机制研究[J].电网技术,2009,33(18)：105－110
[114]张粒子,谢国辉,朱泽,等.准市场化的节能发电调度模式[J].电力系统自动化,2009,33(8)：29-32,43
[115]高磊.上网侧两部制电价在南方区域的适用性探讨[J].云南电业,2011,(11)：39-40
[116]王绵斌,谭忠富,张蓉,等.发电侧峰谷分时电价设计及电量分配优化模型[J].电力自动化设备,2007,27(8)：16-21
[117]曾鸣,刘敏,赵庆波,等.上网侧与销售侧峰谷分时电价联动的理论及应用[J].中国电力,2003,36(9)：70-74
[118]曾鸣,孙听,赵庆波,等.上网侧与销售侧峰谷分时电价的联动与整体优化的方法及实证分析[J].电力需求侧管理,2003,5(4)：9-13
[119]陈建长,黄锟宁.基于需求侧响应的上网侧与售电侧峰谷分时电价联动机制[J].系统工程,2006,24(10)：88-91
[120]刘贵友,陈芳元,汪玉凤,等.基于DSM的发电侧与销售侧峰谷分时电价联动方案[J].沈阳航空工业学院学报,2006,23(3)：90-93
[121]谭忠富,陈广娟,乞建勋,等.基于电力资源优化配置的发电侧峰谷分时电价研究[J].电网技术,2008,32(7)：61-65
[122]谭忠富,陈广娟,赵建保,等.以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J],中国电机工程学报,2009,29(1)：55-62
[123]胡鞍钢.中国如何应对全球气候变暖的挑战[M].国情报告,2007,(29)
[124]庄贵阳.中国经济低碳发展面临的机遇与挑战[M].北京：社会科学文献出版社,2007：335-345
[125]杨俊杰,周建中,喻菁,等.一种求解大规模机组组合问题的混合智能遗传算法[J].电网技术,2004,28(19)：47-50
[126]王威,邵山,李磊,等.电力市场效率理论及其评价方法[J],电网技术,2009,33(14)：66-71
[127]王睿,张粒子,张丽娟,等.区域发电权交易模式研究[J].华北电力大学学报,2012,39(4)：52-58
[128]张培.火电电网中抽水蓄能电站容量优化研究[D].北京：华北电力大学,2009
[129]王茜.风电场与输电网协调规划的模型和方法研究[D].北京：华北电力大学,2011
[130]曹昉,张粒子.结合系统调峰容量比确定抽水蓄能机组装机容量的方法[J].电力自动化设备,2007,27(6)：47-50
[131]王卿然,谢国辉,张粒子.含风电系统的发用电一体化调度模型[J].电力系统自动化,2011,35(5)：15-18,30
[132]王睿,张粒子,张丽娟,等.对节能发电调度经济补偿问题的再探讨[J].华东电力,2011,39(6)：832-834
[133]Sterman J Business Dynamics. System thinking and modelling for a complex world[M]. New York:Irwin McGraw-Hill,2000
[134]于尔铿,周京阳,吴玉生.发电报价曲线研究[J].电力系统自动化,2001,25(2)： 23－26
[2]TSO. Energy White Paper:Our Energy Future—Create a Low Carbon Economy[Z], London, UK:TSO,2003
[3]中国工控网.2011年中国工业节能与自动化需求研究报告[M].北京：中国工控网,2011
[4]国务院.国务院批转国家经委等部门《关于鼓励集资办电和实行多种电价的暂行规定》的通知[S].北京：国务院,1985
[5]国务院.电网调度管理条例[Z].北京：国务院,1993
[6]国家电力监管委员会.关于促进电力调度公开、公平、公正的暂行办法[Z].北京：国家电力监管委员会,2004
[7]国家发展和改革委员会、国家环境保护总局、国家电力监管委员会、国家能源领导小组办公室.节能发电调度试点工作方案和实施细则(试行),发改能源[2007]3523号[S].北京：国家发展改革委,2007
[8]国务院办公厅.国务院关于转发发展改革委等部门节能发电调度办法(试行)的通知,国办发[2007]53号[S].北京：国务院办公厅,2007
[9]陈俊武.中国中长期碳减排战略目标研究[M].北京：中国石化出版社,2012：32-33
[10]于尔铿.现代电力系统经济调度[M].北京：水利电力出版社,1986：21－25
[11]谢国辉.绿色发电调度模式和模型研究[D].北京：华北电力大学,2010
[12]国家电力监管委员会.欧洲,澳洲电力市场改革[M].北京：中国电力出版社,2006：125-245
[13]王楠.发电调度优化模型与方法研究[D].北京：华北电力大学,2011
[14]李彩华,郭志忠,樊爱军.电力系统优化调度概述(Ⅰ)—经济调度与最优潮流[J].电力系统及其自动化学报,2002,14(2)：60-63
[15]卫志农,鞠平.电力系统经济调度综述[J].河海科技进展,1994,14(2)：29-31
[16]Steinberg M J, Smith Theodore H. The theory of incremental rates and their practical application to load division-part I. Transactions of the American Institute of Electrical Engineers[J].1934,53(3):432-445
[17]Steinberg M J, Smith Theodore H. The theory of incremental rates and their practical application to load division-part II. Transactions of the American Institute of Electrical Engineers [J].1934,53(4):571-584
[18]Kirchmayer L K, Stagg G W.Analysis of total and incremental losses in transmission systems[J]. AIEE Traps,1951,70(2):647-653
[19]Carpentier J. Contribution a'letude du Dispatching Economique[J]. Bulletin de laociete Francaise des Electriciens,1962,3(1)431-447
[20]Rabih A. Jabr. A Primal-Dual Interior-Point Method to Solve the Optimal Power Flow Dispatching Problem[J]. Optimization and Engineering,2003,4(4):1-6
[21]Cai H R, Chung C Y, Wong K P. Application of differential evolution algorithm for transient stability constrained optimal power flow[J]. IEEE Trans on Power Systems,2008,23(2):719-728
[22]Capitanescu F, Glavic M, Ernst D, etal. Contingency filtering techniques for preventive security-constrained optimal power flow[J]. IEEE Trans on Power Systems,2007,22(4):1690-1697
[23]Liu Keyan, Sheng Wanxing, Li Yunhua. Research on parallel algorithm of DC optimal power flow in large interconnection power grids[C]. Proceedings of the Eighth International Conference on Electrical Machines and Systems,2005,2: 1031-1036
[24]刘科研,盛万兴,李运华.互联电网的直流最优潮流分解算法研究[J].中国电机工程学报,2006,26(12)：21-25
[25]Somuah G B, Khunaizi N. Application of linear programming redispatch technique to dynamic generation allocation[J]. IEEE Trans on Power Systems,1990,5(1): 20-26
[26]韩学山.动态优化调度的积留量法[D].哈尔滨：哈尔滨工业大学,1994
[27]Barcelo W R, Rastgoufard P. Dynamic economic dispatch using the extend security constrained economic dispatch algorithm[J]. IEEE Trans on Power Systems,1997, 12(2):961-967
[28]Panigrahi C K, Chattopadhyay P K, Chakrabarti R N, et al. Simulated annealing technique for dynamic economic dispatch [J]. Electric Power Components and Systems,2006,34(5):577-586
[29]杨朋朋, 韩学山.一种考虑时间关联约束的安全约束经济调度解法[J].电力系统自动化,2008,32(17)：30-34
[30]杨明,韩学山,梁军.计及网络安全约束及用户停电损失的动态经济调度方法[J].电力系统自动化,2009,33(14)：27-31
[31]Rabih A. Jabr.'A Primal-Dual Interior-Point Method to Solve the Optimal Power Flow Dispatching Problem[J]. Optimization and Engineering,2003,4(4):1-6
[32]王锡凡,王秀丽,陈皓勇.电力市场基础[M].西安：西安交通大学出版社,2003：11－20
[33]尚金成.基于时间尺度的节能发电优化调度协调模型及算法[J].电力系统自动化,2008,32(15)：56-61
[34]胡建军,李嘉龙,陈慧坤.基于煤耗和排放的日发电曲线编制模型[J].电力系统自动化,2009,33(12)：43-45,96
[35]Gentm R, Lamont J W. Minimum Emission Dispatch[J]. IEEE Trans. On PAS, 1971,90:2650-2660
[36]张宁,陈慧坤,骆晓明,等.广东电网节能发电调度计划模型与算法[J].电网技术,2008,32(23)：7－12
[37]王超,张晓明,唐茂林,等.四川电网节能减排发电实时调度优化模型[J].电力系统自动化,2008,32(4)：89-92
[38]陈启鑫,康重庆,夏清.低碳电力调度方式及其决策模型[J].电力系统自动化,2010,34(12)：18－22
[39]朱建广,谢青松.基于适应性遗传算法的新型低碳发电调度[J].广东电力,2011,24(2)：32-36
[40]黎灿兵,刘玛,曹一家,等.低碳发电调度与节能发电调度的一致性评估[J].中国电机工程学报,2011,31(31)：94-101
[41]崔明勇,艾欣.基于混沌蚁群算法的微网多目标低碳调度[J].中国电业(技术版),2012,(7)：1－5
[42]高春成,王良缘,刘文彬,等.低碳调度下机组组合问题的混沌遗传混合优化方法[J].华东电力,2013,41(1)：160-164
[43]朱泽磊,周京阳,韩忠旭,等.基于多阶段不同政策机制的低碳电力调度模型[J].电网技术,2013,37(2)：287-294
[44]Tamura H, Kimura T. Evaluating the Effectiveness of Carbon Tax and Emissions Trading for Resolving Social Dilemma on Global Environment[C]. Systems, Man and Cybernetics,2007. ISIC. IEEE International Conference,1746-1751
[45]YU Z, PRECKEL P V, NDERITU G, et al. A locational gaming model with CO2 emission tax and limits[J]. International Journal of Electrical Power & Energy Systems,2001,23(6):451-457
[46]于超,谭忠富,胡庆辉,等.激励发电节能减排交易的Nash均衡两级优化模型[J].电力系统保护与控制,2011,39(7)：63－66,73
[47]于超,谭忠富.基于排放绩效的燃煤电厂碳税优化模型[J].华东电力,2011,39(6)： 845－849
[48]魏学好,李瑞庆,陈宇晨.具有节能减排内核的电力市场新模型[J].电力系统自动化,2009,33(15)：24-28,106
[49]Ellerman A D, Buchner B K. The European Union emissions trading scheme: origins, allocation and early results[J]. Review of Environmental Economics and Policy,2007,1(1):66-87
[50]史彪,刘晓东.欧盟碳排放交易制度对我国的启示[J].山西师范大学学报,2011,38(7)：23-25
[51]王毅刚.中国碳排放交易体系设计研究[D].北京：中国社会科学研究院.2010
[52]刘国中,文福拴,薛禹胜.温室气体排放权交易对发电公司最优报价策略的影响[J],电力系统自动化,2009,33(19)：15－20
[53]高慧,魏学好,文福拴.排污权交易实施后的寡头垄断电力市场的均衡分析[J],华北电力大学学报,2009,36,(6)：8-13
[54]王万山.庇古与科斯的规制理论比较[J].贵州财经学院学报,2007,(3)：23－28
[55]刘红,唐元虎.外部性的经济分析与对策[J].南开经济研究,2001,(1)：45－48
[56]杨帆.国际碳定价机制研究及其启示[J].商业时代,2012,(4)：7－8
[57]Day C J, Hobbs B F, Pang J S. Oligopolistic Competition In Power Networks: A Conjectured Supply Function Approach[J]. IEEE Trans on Power Systems, 2002,17(3):597-607
[58]Wang Xian, Li Yuzeng, Zhang Shaohua. Oligopolistic equilibrium analysis for electricity markets:a nonlinear complementarity approach[J]. IEEE Trans on Power Systems,2004,19(3):1348-1355
[59]Bower J, Bunn D. Experimental analysis of the efficiency of uniform price versus discriminatory auctions in the England and Wales electricity market [J]. Journal of Economic Dynamics and Control,2001,25(4):561-592
[60]Sun J, Tesfatsion L. Dynamic testing of wholesale power market designs:an open source agent based framework[J]. Computational Economics,2007,30(3):291-327
[61]Power Systems Engineering Research Center(PSERC). Power web user's manual version 2.7[M], Cornell University,2001
[62]Center for Energy, Environmental and Economic Systems Analysis (CEEESA) Decision and Information Sciences Division. Electricity market complex adaptive system(EMCAS)user's manual version 2.0, Argonne National Laboratory,2006
[63]Weber J D, Oberbye T J. A two level optimization problem for analysis of market bidding strategies[C]. Proceedings of IEEE Power Engineering Society Summer Meeting, July18-22,1999, Edmonton, Canada:682-687
[64]Wwber J D. An individual welfare maximization algorithm for electricity markets[J]. IEEE Trans on Power Systems,2002,17(3):590-596
[65]杨彦,陈皓勇,张尧.基于协同进化算法求解寡头电力市场均衡[J].电力系统自动化,2009,33(18)：42－46
[66]Son Y, Baldick R. Hybrid co-evolutionary programming for Nash equilibrium search in games with local optima[J]. IEEE Transactions on Evolutionary Computation,2004,8(4):305-315
[67]Cau T D H, Anderson E J. A co-evolutionary approach to modeling the behavior of participants in competitive electricity markets[C]. Proceedings of IEEE Power Engineering Society Summer Meeting, July 25,2002, Chicago, IL, USA:1534-154
[68]Chen H, Wong K P, Nguyen D H M, etal. Analyzing oligopolistic electricity market using co-evolutionary computation. IEEE Trans on Power Systems,2006, 21(1):143-152
[69]陈皓勇,杨彦,张尧.电力市场智能模拟中代理决策模块的实现[J].电力系统自动化,2008,32(20)：12－16
[70]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6)：13-18
[71]王雁凌,张粒子,杨以涵.基于水火电置换的发电权调节市场[J],中国电机工程学报,2006,26(5)：131-136
[72]尚金成.基于节能减排的发电权交易理论及应用：(一)发电权交易理论[J],电力系统自动化,2009,33(12)：46－52
[73]尚金成,何洋.基于节能减排的发电权交易理论及应用：(二)发电权交易分析及应用[J],电力系统自动化,2009,33(13)：37－42
[74]王雁凌,程倩.基于节能降耗的发电权交易模型[J],电力系统保护与控制,2010,38(18)：28-32
[75]伍玉林,文福拴,丁剑鹰,等.基于两部制电价的发电权交易模式[J],华北电力大学学报,2010,37(5)：16－22
[76]陈赞,严正.考虑节能减排与网络约束的发电权交易模型[J],电力系统保护与控制,2009,37(12)：52-57
[77]廖湘凯,鲍海.考虑阻塞的发电权交易改进模型[J].现代电力,2010,27(1)：81－85
[78]陈启鑫,康重庆,程旭东,等.考虑阻塞管理的发电权交易模型及其网络流算法[J].中国电机工程学报,2008,28(34)：106－111
[79]肖健,文福拴.发电权交易的阻塞调度[J].电力系统自动化,2008,32(18)： 24-29
[80]舒隽,张丽娟,张粒子,等.发电权竞价交易的两阶段方法[J].电网技术,2011,35(11)：200-205
[81]张午阳.发电权转让交易中的博弈行为的研究[J].华中电力,2005,18(6)：1－4
[82]廖屹.基于博弈理论的发电权交易研究[D].成都：西南交通大学,2008
[83]于琪.区域发电权交易优化模式研究[D].北京：华北电力大学,2012
[84]迟永宁,刘燕华,王伟胜,等.风电接入对电力系统的影响[J].电网技术,2007,31(3)：77-81
[85]戴慧珠,王伟胜,迟永宁.风电场接入电力系统研究的新进展[J].电网技术,2007,31(20)：16-23
[86]张红光,张粒子,陈树勇,等.大容量风电场对电力系统小干扰稳定和阻尼特性的影响[J].电网技术,2007,31(13)：75－80
[87]Barton J P, Infield D G. Energy storage and its use with intermittent renewable energy[J]. IEEE Trans, on Energy Conversion,2004,19(2):441-448
[88]Abbey C, Joos G. Supercapacitor energy storage for wind energy application [J]. IEEE Trans on Industry Applications,2007,43(3):769-776
[89]张步涵,曾杰,毛承雄,等.电池储能系统在改善并网风电场电能质量和稳定性中的应用[J].电网技术,2006,30(15)：54－58
[90]于芃,周玮,孙辉,等.用于风电功率平抑的混合储能系统及其控制系统设计[J].中国电机工程学报,2011,31(17)：127－133
[91]C. Buen, J. A. Carta. Technical-economic analysis of wind-powered pumped hydro storage systems, Part Ⅰ:model development[J].Solar Energy,2005,78(3): 396-405
[92]刘德有,谭志忠,王丰.风电-抽水蓄能联合运行系统的可行性研究[J].上海电力,2007,(1)：39－42
[93]李强,袁越,李振杰,等.考虑峰谷电价的风电-抽水蓄能联合系统能量转化效益研究[J].电网技术,2009,33(6)：13－18
[94]Edgardo D. Castronuovo, Lopes Joao A. Pecas. Optimal operation and hydro storage sizing of a wind-hydro power plant[J]. Electrical Power and Energy Systems.2004,26(10):771-778
[95]范永威.风——水电联合优化运行研究[D].河海大学,2007
[96]王艳.风—蓄联合运行系统可行性研究[D].华北电力大学(北京),2008
[97]潘文霞,范永威,朱莉,等.风电场中抽水蓄能系统容量的优化选择[J].电 工技术学报,2008,23(3)：120－124
[98]李志恒.风蓄联合系统规划问题研究[D].华中科技大学,2008
[99]张粒子.区域电力市场电价机制[M].北京：中国电力出版社,2004：84-85
[100]国家发展和改革委员会.发改价格[2005]514号,上网电价管理暂行办法[S].北京：国家发展和改革委员会,2005
[101]李帆,朱敏.英国电力市场及输电系统简介[J].电力系统自动化,1999,23(2)：33-40
[102]Johannes Pfeifenberger, Samuel Newel, IRobert Earle, etc. Review of PJM's Reliability Pricing Model(RPM)[R].2008, http://www.pjm.com
[103]Benjamin FHobbs, Ming-CheHu, JavierG Inon, etc. A Dynamic Analysis of a Demand Curve-Based Capacity Market Proposal:The PJM Reliability Pricing Model[J]. IEEE Trans. On Power System,2007,22(1):3-14
[104]PJM training materials Reliability Pricing Model[R]. Auction Clearing Example. http://www.pjm.com
[105]郝继陶,周丽丽.两部制上网电价的定价原则与模型[J].武汉汽车工业大学学报.2000,(22)4：98－101
[106]王黎,马光文.两部制上网电价定价方法初探[J].四川大学学报(工程科学版).2000,(32)1：62-66
[107]马光文,王黎.两部制上网电价的长期边际成本定价方法[J].水力发电学报.2000,4：66-71
[108]赵建国.容量电价随市场变化的两部制电价模式探讨rJ].华北电业,1998,9：4-6
[109]黄健柏,邵留国,张仕骡.两部制电价与发电容量投资的系统动力学分析[J].电力系统及其自动化学报,2007,19(2)：21－27
[110]黄健柏,邵留国,张仕骡,等.两部制电价下电力市场系统动力学仿真[J].系统管理学报,2007,16(4)：407-416,421
[111]张媛媛.基于需求曲线的容量市场定价模型研究[D].北京：华北电力大学,2009
[112]张可佳.基于委托代理理论的容量电价规制模型研究[D].北京：华北电力大学,2010
[113]张森林.节能发电调度配套上网电价定价机制研究[J].电网技术,2009,33(18)：105－110
[114]张粒子,谢国辉,朱泽,等.准市场化的节能发电调度模式[J].电力系统自动化,2009,33(8)：29-32,43
[115]高磊.上网侧两部制电价在南方区域的适用性探讨[J].云南电业,2011,(11)：39-40
[116]王绵斌,谭忠富,张蓉,等.发电侧峰谷分时电价设计及电量分配优化模型[J].电力自动化设备,2007,27(8)：16-21
[117]曾鸣,刘敏,赵庆波,等.上网侧与销售侧峰谷分时电价联动的理论及应用[J].中国电力,2003,36(9)：70-74
[118]曾鸣,孙听,赵庆波,等.上网侧与销售侧峰谷分时电价的联动与整体优化的方法及实证分析[J].电力需求侧管理,2003,5(4)：9-13
[119]陈建长,黄锟宁.基于需求侧响应的上网侧与售电侧峰谷分时电价联动机制[J].系统工程,2006,24(10)：88-91
[120]刘贵友,陈芳元,汪玉凤,等.基于DSM的发电侧与销售侧峰谷分时电价联动方案[J].沈阳航空工业学院学报,2006,23(3)：90-93
[121]谭忠富,陈广娟,乞建勋,等.基于电力资源优化配置的发电侧峰谷分时电价研究[J].电网技术,2008,32(7)：61-65
[122]谭忠富,陈广娟,赵建保,等.以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J],中国电机工程学报,2009,29(1)：55-62
[123]胡鞍钢.中国如何应对全球气候变暖的挑战[M].国情报告,2007,(29)
[124]庄贵阳.中国经济低碳发展面临的机遇与挑战[M].北京：社会科学文献出版社,2007：335-345
[125]杨俊杰,周建中,喻菁,等.一种求解大规模机组组合问题的混合智能遗传算法[J].电网技术,2004,28(19)：47-50
[126]王威,邵山,李磊,等.电力市场效率理论及其评价方法[J],电网技术,2009,33(14)：66-71
[127]王睿,张粒子,张丽娟,等.区域发电权交易模式研究[J].华北电力大学学报,2012,39(4)：52-58
[128]张培.火电电网中抽水蓄能电站容量优化研究[D].北京：华北电力大学,2009
[129]王茜.风电场与输电网协调规划的模型和方法研究[D].北京：华北电力大学,2011
[130]曹昉,张粒子.结合系统调峰容量比确定抽水蓄能机组装机容量的方法[J].电力自动化设备,2007,27(6)：47-50
[131]王卿然,谢国辉,张粒子.含风电系统的发用电一体化调度模型[J].电力系统自动化,2011,35(5)：15-18,30
[132]王睿,张粒子,张丽娟,等.对节能发电调度经济补偿问题的再探讨[J].华东电力,2011,39(6)：832-834
[133]Sterman J Business Dynamics. System thinking and modelling for a complex world[M]. New York:Irwin McGraw-Hill,2000
[134]于尔铿,周京阳,吴玉生.发电报价曲线研究[J].电力系统自动化,2001,25(2)： 23－26