用户报量不报价模式下电力现货市场需求响应机制与方法
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摘要
为了积极稳妥地推进中国电力现货市场建设,以用户报量不报价的方式开展需求侧响应是电力现货市场建设初期循序渐进的选择,由此产生了在日前市场模型中如何考虑需求弹性的问题。针对用户报量不报价方式下的市场运行特点,提出了相应的现货市场需求响应机制,研究了对用户日前申报负荷进行弹性化修正,并依据修正后的负荷开展安全校核,优化决策考虑需求弹性的日前发电计划模型和方法。首先分析用户日前负荷申报、对价格做出响应的行为机理,在此基础上研究基于模型和数据驱动的申报负荷弹性化修正方法,并建立了基于负荷需求弹性的日前发电计划优化与安全校核模型。通过在日前提前考虑用户在实时市场上的价格响应行为,实现了日前发电计划更优化、安全校核更精准。基于IEEE 30节点的算例分析验证了所提模式和方法的效益和有效性。
In order to promote the construction of Chinese electricity spot market actively and steadily, it is a gradual evolution path in the initial stage of electricity market construction to start with bidding without price on the demand side, which leads to the question of how to consider the demand elasticity in day-ahead market model. In view of the market operation characteristics in bidding mode without price, the response mechanism of corresponding spot market demand is proposed. The flexible modification of the users' day-ahead reporting load is studied and security check is carried out based on the modified load to optimize day-ahead generation scheduling model considering demand response. Mechanism of users' day-ahead bidding behavior and response behavior to price is analyzed firstly. Secondly, the model based method and data-driven method of elasticity revision for reporting load are discussed, respectively. Thirdly, the generation scheduling and security check model based on demand elasticity of load are formulated. Case study based on IEEE 30-bus system is employed to verify the benefits and effectiveness of the proposed mode and method.
In order to promote the construction of Chinese electricity spot market actively and steadily, it is a gradual evolution path in the initial stage of electricity market construction to start with bidding without price on the demand side, which leads to the question of how to consider the demand elasticity in day-ahead market model. In view of the market operation characteristics in bidding mode without price, the response mechanism of corresponding spot market demand is proposed. The flexible modification of the users' day-ahead reporting load is studied and security check is carried out based on the modified load to optimize day-ahead generation scheduling model considering demand response. Mechanism of users' day-ahead bidding behavior and response behavior to price is analyzed firstly. Secondly, the model based method and data-driven method of elasticity revision for reporting load are discussed, respectively. Thirdly, the generation scheduling and security check model based on demand elasticity of load are formulated. Case study based on IEEE 30-bus system is employed to verify the benefits and effectiveness of the proposed mode and method.
引文
[1] 国家发展和改革委员会,国家能源局.关于开展电力现货市场建设试点工作的通知[EB/OL].[2017-09-08].http://www.ndrc.gov.cn/gzdt/201709/t20170905_860117.html.National Development and Reform Commission of China,National Energy Administration of China.Notification on carrying out pilot project of electricity spot market[EB/OL].[2017-09-08].http://www.ndrc.gov.cn/gzdt/201709/t20170905_860117.html.
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[10] 吉兴全,王成山.考虑需求弹性的启发式输电网规划方法[J].电力系统及其自动化学报,2002,14(6):1-4.JI Xingquan,WANG Chengshan.Transmission expansion under spot pricing considering demand elasticity[J].Proceedings of the CSU-EPSA,2002,14(6):1-4.
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[14] 葛少云,贾鸥莎,刘洪.基于遗传灰色神经网络模型的实时电价条件下短期电力负荷预测[J].电网技术,2012,36(1):224-229.GE Shaoyun,JIA Ousha,LIU Hong.A gray neural network model improved by genetic algorithm for short-term load forecasting in price-sensitive environment[J].Power System Technology,2012,36(1):224-229.
[15] 何耀耀,刘瑞,撖奥洋.基于实时电价与支持向量分位数回归的短期电力负荷概率密度预测方法[J].中国电机工程学报,2017,37(3):768-776.HE Yaoyao,LIU Rui,HAN Aoyang.Short-term power load probability density forecasting method based on real time price and support vector quantile regression[J].Proceedings of the CSEE,2017,37(3):768-776.
[16] 罗纯坚,李姚旺,许汉平,等.需求响应不确定性对日前优化调度的影响分析[J].电力系统自动化,2017,41(5):22-29.DOI:10.7500/AEPS20160702006.LUO Chunjian,LI Yaowang,XU Hanping,et al.Influence of demand response uncertainty on day-ahead optimization dispatching[J].Automation of Electric Power Systems,2017,41(5):22-29.DOI:10.7500/AEPS20160702006.
[17] 周明,严宇,丁琪,等.国外典型电力市场交易结算机制及对中国的启示[J].电力系统自动化,2017,41(20):1-8.DOI:10.7500/AEPS20170223001.ZHOU Ming,YAN Yu,DING Qi,et al.Transaction and settlement mechanism for foreign representative power markets and its enlightenment for Chinese power market[J].Automation of Electric Power Systems,2017,41(20):1-8.DOI:10.7500/AEPS20170223001.
[18] 辛洁晴,程浩忠.电力需求短期分时价格弹性的特性及其应用[J].电力系统自动化,2007,31(10):32-35.XIN Jieqing,CHENG Haozhong.Properties of short-term TOU price elasticities of electricity demand and their application[J].Automation of Electric Power Systems,2007,31(10):32-35.
[19] 杰弗里·M·佩罗夫.中级微观经济学[M].北京:中国人民大学出版社,2014.PERLOFF J M.Microeconomics[M].Beijing:China Renmin University Press,2014.
[20] AEMO.Spot market operations timetable[EB/OL].[2017-12-19].http://www.aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Dispatch/Spot-Market-Operations-Timetable.pdf.
[21] LIJESEN M G.The real-time price elasticity of electricity[J].Energy Economics,2007,29(2):249-258.
[22] WEI Taoyuan.Impact of energy efficiency gains on output and energy use with Cobb-Douglas production function[J].Energy Policy,2007,35(4):2023-2030.
[23] 汪洋,夏清,康重庆.机组组合算法中起作用整数变量的辨识方法[J].中国电机工程学报,2010,30(13):46-52.WANG Yang,XIA Qing,KANG Chongqing.Identification of the active integer variables in security constrained unit commitment[J].Proceedings of the CSEE,2010,30(13):46-52.
[24] FERRERO R W,SHAHIDEHPOUR S M,RAMESH V C.Transaction analysis in deregulated power systems using game theory[J].IEEE Transactions on Power Systems,1997,12(3):1340-1347.
[2] 郭鸿业,陈启鑫,钟海旺,等.基于标准化金融交割曲线的现货市场建设路径设计[J].电力系统自动化,2017,41(17):1-8.DOI:10.7500/AEPS20170512009.GUO Hongye,CHEN Qixin,ZHONG Haiwang,et al.Spot market mechanism design and path planning based on standard curve for financial deliver[J].Automation of Electric Power Systems,2017,41(17):1-8.DOI:10.7500/AEPS 20170512009.
[3] DONNELLY W A,DIESENDORF M.Variable elasticity models for electricity demand[J].Energy Economics,1985,7(3):159-162.
[4] WHITTAKER J,BARR G I.The price elasticity of electricity demand in South Africa[J].Applied Economics,1989,21(9):1153-1157.
[5] DAVID A K,LI Y Z.Effect of inter-temporal factors on the real time pricing of electricity[J].IEEE Transactions on Power Systems,1993,8(1):44-52.
[6] KIRSCHEN D S,STRBAC G,CUMPERAYOT P,et al.Factoring the elasticity of demand in electricity prices[J].IEEE Transactions on Power Systems,2000,15(2):612-617.
[7] JIN Y,ZHANG S Q.Elasticity estimates of urban resident demand for electricity:a case study in Beijing[J].Energy & Environment,2013,24(7-8):1229-1248.
[8] D’ERRICO M C,BOLLINO C A.Bayesian analysis of demand elasticity in the Italian electricity market[J].Sustainability,2015(7):12127-12148.
[9] FAN Shu,HYNDMAN R J.The price elasticity of electricity demand in South Australia[J].Energy Policy,2011,39(6):3709-3719.
[10] 吉兴全,王成山.考虑需求弹性的启发式输电网规划方法[J].电力系统及其自动化学报,2002,14(6):1-4.JI Xingquan,WANG Chengshan.Transmission expansion under spot pricing considering demand elasticity[J].Proceedings of the CSU-EPSA,2002,14(6):1-4.
[11] 方陈,夏清,孙欣.考虑需求弹性的发电检修协调方法[J].电力系统保护与控制,2011,39(6):38-44.FANG Chen,XIA Qing,SUN Xin.Unit maintenance coordination method considering demand elasticity[J].Power System Protection and Control,2011,39(6):38-44.
[12] 康重庆,夏清,胡左浩,等.电力市场中预测问题的新内涵[J].电力系统自动化,2004,28(18):1-6.KANG Chongqing,XIA Qing,HU Zuohao,et al.New connotation of forecasting issues in electricity market[J].Automation of Electric Power Systems,2004,28(18):1-6.
[13] ZHANG Yun,ZHOU Quan,SUN Caixin,et al.RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment[J].IEEE Transactions on Power Systems,2008,23(3):853-858.
[14] 葛少云,贾鸥莎,刘洪.基于遗传灰色神经网络模型的实时电价条件下短期电力负荷预测[J].电网技术,2012,36(1):224-229.GE Shaoyun,JIA Ousha,LIU Hong.A gray neural network model improved by genetic algorithm for short-term load forecasting in price-sensitive environment[J].Power System Technology,2012,36(1):224-229.
[15] 何耀耀,刘瑞,撖奥洋.基于实时电价与支持向量分位数回归的短期电力负荷概率密度预测方法[J].中国电机工程学报,2017,37(3):768-776.HE Yaoyao,LIU Rui,HAN Aoyang.Short-term power load probability density forecasting method based on real time price and support vector quantile regression[J].Proceedings of the CSEE,2017,37(3):768-776.
[16] 罗纯坚,李姚旺,许汉平,等.需求响应不确定性对日前优化调度的影响分析[J].电力系统自动化,2017,41(5):22-29.DOI:10.7500/AEPS20160702006.LUO Chunjian,LI Yaowang,XU Hanping,et al.Influence of demand response uncertainty on day-ahead optimization dispatching[J].Automation of Electric Power Systems,2017,41(5):22-29.DOI:10.7500/AEPS20160702006.
[17] 周明,严宇,丁琪,等.国外典型电力市场交易结算机制及对中国的启示[J].电力系统自动化,2017,41(20):1-8.DOI:10.7500/AEPS20170223001.ZHOU Ming,YAN Yu,DING Qi,et al.Transaction and settlement mechanism for foreign representative power markets and its enlightenment for Chinese power market[J].Automation of Electric Power Systems,2017,41(20):1-8.DOI:10.7500/AEPS20170223001.
[18] 辛洁晴,程浩忠.电力需求短期分时价格弹性的特性及其应用[J].电力系统自动化,2007,31(10):32-35.XIN Jieqing,CHENG Haozhong.Properties of short-term TOU price elasticities of electricity demand and their application[J].Automation of Electric Power Systems,2007,31(10):32-35.
[19] 杰弗里·M·佩罗夫.中级微观经济学[M].北京:中国人民大学出版社,2014.PERLOFF J M.Microeconomics[M].Beijing:China Renmin University Press,2014.
[20] AEMO.Spot market operations timetable[EB/OL].[2017-12-19].http://www.aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Dispatch/Spot-Market-Operations-Timetable.pdf.
[21] LIJESEN M G.The real-time price elasticity of electricity[J].Energy Economics,2007,29(2):249-258.
[22] WEI Taoyuan.Impact of energy efficiency gains on output and energy use with Cobb-Douglas production function[J].Energy Policy,2007,35(4):2023-2030.
[23] 汪洋,夏清,康重庆.机组组合算法中起作用整数变量的辨识方法[J].中国电机工程学报,2010,30(13):46-52.WANG Yang,XIA Qing,KANG Chongqing.Identification of the active integer variables in security constrained unit commitment[J].Proceedings of the CSEE,2010,30(13):46-52.
[24] FERRERO R W,SHAHIDEHPOUR S M,RAMESH V C.Transaction analysis in deregulated power systems using game theory[J].IEEE Transactions on Power Systems,1997,12(3):1340-1347.