需求响应参与系统调峰研究综述
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摘要
由于我国电力供需矛盾和系统负荷峰谷差逐渐加大,需求响应措施在需求侧管理中得到广泛地应用。通过采用价格和激励措施,电力部门引导用户改善用电负荷,达到调峰的效果。以需求响应调峰可行性、优化模型以及评估方法为立足点,对需求响应参与系统调峰研究进行综述。首先,分析了用户的调峰特性。接着讨论了电价制定方法以及电价参与调峰的优化模型建立。然后概述了激励和电价联合参与调峰及需求侧资源参与系统长期调峰,并介绍了需求响应调峰效果的评估方法。最后,结合需求侧管理和智能电网的发展要求,对需求响应参与系统调峰的研究方向进行展望。
Due to the remarkable increase of unbalance be-tween power supply and demand as well as load variation, demandresponse has been widely applied in electricity management in Chi-na. Through the use of price and incentive measures, power utilitiescan guide users to improve their electricity consumption behavior,resulting in effective load management. This paper is intended tomake a survey on demand response applications in power systempeak shaving, including the feasibility of peak shaving, optimizationmodel and evaluation method. The characteristics of power user'speak shaving are analyzed first. Second, formulation method and theoptimization model of peak load management based on electricityprice are discussed. Then the paper summarizes the peak shaving re-searches based on the combination of incentive and price, and thelong-term peak shaving considering the participation of demand sideresources. The evaluation methods of peak shaving effect by demandresponse are also introduced. Finally, vistas of this research topicare projected into the future.
Due to the remarkable increase of unbalance be-tween power supply and demand as well as load variation, demandresponse has been widely applied in electricity management in Chi-na. Through the use of price and incentive measures, power utilitiescan guide users to improve their electricity consumption behavior,resulting in effective load management. This paper is intended tomake a survey on demand response applications in power systempeak shaving, including the feasibility of peak shaving, optimizationmodel and evaluation method. The characteristics of power user'speak shaving are analyzed first. Second, formulation method and theoptimization model of peak load management based on electricityprice are discussed. Then the paper summarizes the peak shaving re-searches based on the combination of incentive and price, and thelong-term peak shaving considering the participation of demand sideresources. The evaluation methods of peak shaving effect by demandresponse are also introduced. Finally, vistas of this research topicare projected into the future.
引文
[1]宁阳天.基于削峰填谷的储能系统调度模型[D].保定:华北电力大学,2015.
[2]Federal Energy Regulatory Commission.Assessment ofdemand response and advanced metering:2007 staff report[EB/OL].(2017-01-05)[2017-05-31].http://www.ferc.gov/legal/staff-reports/09-07-Demand-response.pdf.
[3]牛文娟.计及不确定性的需求响应机理模型及应用研究[D].南京:东南大学,2015.
[4]宁向南.基于遗传算法的DSM分时电价优化研究[D].天津:天津大学,2012.
[5]US Department of Energy.Benefits of demand response inelectricity markets and recommendations for achievingthem:a report to the United State Congress pursuant tosection 1252 of the Energy Policy Act of 2005[EB/OL].(2017-01-05)[2017-05-31].http://www.oe.energy.gov/Documentsand Media/congress_1252.pdf.
[6]Aimei Yan,Jinsong Wang,Liang Wu,et al.The Study ofEnterprise Working Time Optimization Simulation SystemConsidering the Peak-Valley Power Price[C]//Nanjing:International Conference on Computer Science andService System,2012:1 623-1 626.
[7]Asano H,Takahashi M,Y Namaguchi,et al.Demandparticipation in the power market by load curtailment ofbuilding energy use and distributed generation ofcommercial customers in Japan[C]//Italy:InternationalConference on Clean Electrical Power,2009:520-525.
[8]He Hao,Charles D,Kalsi K,et al.Transitive control of commercial buildings for demand response[J].IEEE Transactions on Power Systems,2016,32(1):774-783.
[9]Ju Ge,Shasha Luo,Chen Chen.Research on ancillary service management mechanism in the smart grid[C]//Wuhan:IEEE Power Engineering and Automation Conference,2011:429-432.
[10]张钦,王锡凡,王建学,等.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-106.
[11]Faruqui A,Gorge S S.The value of dynamic pricing in mass markets[J].The Electricity Journal,2002,15(6):45-55.
[12]Wolak F A.Residential customer response to real-time pricing:the Anaheim critical-peak pricing experiment[EB/OL].(2017-01-05)[2017-05-31].http://econ.la.psu.edu/CAPCP/Conferences/Anaheim_cpp_psu.pdf.
[13]Tang Yudong,Song Hongkun,Funian Hu,et al.Investigation on TOU pricing principles[C]//Dalian:IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,2005:1-9.
[14]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):9-12,16.
[15]胡福年.电力市场环境下峰谷分时电价理论建模与影响分析[D].南京:南京理工大学,2007.
[16]程瑜,翟娜娜.基于用户响应的分时电价时段划分[J].电力系统自动化,2012,36(9):42-46,53.
[17]林旻,朱艳卉,胡百林.基于供电成本的峰谷时段划分及分时电价研究[J].华东电力,2005,33(12):90-91.
[18]梁甜甜,王磊,高赐威.基于用户响应的尖峰电价模型研究[J].华东电力,2013,41(1):42-46.
[19]刘昌,姚建刚,姚文峰,等.基于DSM的分时电价的确定与分析[J].电力系统保护与控制,2005,33(15):57-61,85.
[20]崔强,王秀丽,曾平良,等.调峰约束下考虑风电消纳的多目标尖峰电价决策模型[J].中国电机工程学报,2015,35(11):2 662-2 669.
[21]张钦,王锡凡,王建学.尖峰电价决策模型分析[J].电力系统自动化,2008,32(9):11-15.
[22]Karen Herter.Residential implementation of criticalpeak pricing of electricity[J].Energy Policy,2007,35(4):2 121-2 130.
[23]A S Hu,T T Lie,H B Gooi.Load forecast for customers under real time pricing systems[C]//London:International Conference on Electric Utility Deregulation and Restructuring and Power Technologies,2000:538-543.
[24]傅利,周步祥,王小红,等.计及用户侧响应的含风电电力系统清洁经济调度[J].电力系统及其自动化学报,2014,26(12):74-79.
[25]陈晓露.交互式智能电网的负荷预测与定价机制[D].上海:上海交通大学,2013.
[26]曾勇.基于智能电网的实时电价研究[D].重庆:重庆大学,2011.
[27]谭忠富,王绵斌,张蓉,等.发电侧与供电侧峰谷分时电价联动的分级优化模型[J].电力系统自动化,2007,31(21):26-29,34.
[28]Huang K Y,Chin H C,Huang Y C.A model reference adaptive control strategy for interruptible load management[J].IEEE Transactions on Power Systems,2004,19(1):683-689.
[29]谭忠富,谢品杰,王绵斌,等.提高电能使用效率的可中断电价与峰谷分时电价的联合优化设计[J].电工技术学报,2009,24(5):161-168.
[30]刘小聪,王蓓蓓,李扬,等.智能电网下计及用户侧互动的发电日前调度计划模型[J].中国电机工程学报,2013,33(1):30-38.
[31]孙宇军,李扬,王蓓蓓,等.计及不确定性需求响应的日前调度计划模型[J].电网技术,2014,38(10):2 708-2 714.
[32]王晶晶.能效电厂项目的节电潜力分析[D].保定:华北电力大学,2014.
[33]刘彩霞,周晖,周伏秋.基于双种群入侵性杂草算法的服务型城市综合资源规划[J].电力系统保护与控制,2013,41(19):67-74.
[34]Zechun Hu,Shu Zhang,et al.SCUC with battery energy storage system for peak-load shaving and reserve support[C]//Canada:IEEE Power and Energy Society General Meeting,2013:1-5.
[35]张泽卉.需求响应效益的量化评估研究[D].济南:山东大学,2011.
[36]Alexandra Kapetanaki,Konstantinos Kopsidas.Reliability evaluation of demand response and TVTR considering the cost of interruptions[C]//Turkey:IEEE PES Innovative Smart Grid Technologies Conference Europe,2014:1-6.
[37]Yuko Omagari,Hideharu Sugihara,et al.An economic effect of demand response with thermal storage airconditioning systems in electricity markets[C]//Spain:1st IEEE-PES/IAS Conference on Sustainable Alternative Energy,2009:1-6.
[38]曹年林.与大规模新能源发电相适应的用户侧联合调峰技术研究[D].北京:北京交通大学,2015.
[39]程瑜,翟娜娜.面向智能电网的峰谷分时电价评估[J].电力系统保护与控制,2010,38(21):196-201,214.
[2]Federal Energy Regulatory Commission.Assessment ofdemand response and advanced metering:2007 staff report[EB/OL].(2017-01-05)[2017-05-31].http://www.ferc.gov/legal/staff-reports/09-07-Demand-response.pdf.
[3]牛文娟.计及不确定性的需求响应机理模型及应用研究[D].南京:东南大学,2015.
[4]宁向南.基于遗传算法的DSM分时电价优化研究[D].天津:天津大学,2012.
[5]US Department of Energy.Benefits of demand response inelectricity markets and recommendations for achievingthem:a report to the United State Congress pursuant tosection 1252 of the Energy Policy Act of 2005[EB/OL].(2017-01-05)[2017-05-31].http://www.oe.energy.gov/Documentsand Media/congress_1252.pdf.
[6]Aimei Yan,Jinsong Wang,Liang Wu,et al.The Study ofEnterprise Working Time Optimization Simulation SystemConsidering the Peak-Valley Power Price[C]//Nanjing:International Conference on Computer Science andService System,2012:1 623-1 626.
[7]Asano H,Takahashi M,Y Namaguchi,et al.Demandparticipation in the power market by load curtailment ofbuilding energy use and distributed generation ofcommercial customers in Japan[C]//Italy:InternationalConference on Clean Electrical Power,2009:520-525.
[8]He Hao,Charles D,Kalsi K,et al.Transitive control of commercial buildings for demand response[J].IEEE Transactions on Power Systems,2016,32(1):774-783.
[9]Ju Ge,Shasha Luo,Chen Chen.Research on ancillary service management mechanism in the smart grid[C]//Wuhan:IEEE Power Engineering and Automation Conference,2011:429-432.
[10]张钦,王锡凡,王建学,等.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-106.
[11]Faruqui A,Gorge S S.The value of dynamic pricing in mass markets[J].The Electricity Journal,2002,15(6):45-55.
[12]Wolak F A.Residential customer response to real-time pricing:the Anaheim critical-peak pricing experiment[EB/OL].(2017-01-05)[2017-05-31].http://econ.la.psu.edu/CAPCP/Conferences/Anaheim_cpp_psu.pdf.
[13]Tang Yudong,Song Hongkun,Funian Hu,et al.Investigation on TOU pricing principles[C]//Dalian:IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,2005:1-9.
[14]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):9-12,16.
[15]胡福年.电力市场环境下峰谷分时电价理论建模与影响分析[D].南京:南京理工大学,2007.
[16]程瑜,翟娜娜.基于用户响应的分时电价时段划分[J].电力系统自动化,2012,36(9):42-46,53.
[17]林旻,朱艳卉,胡百林.基于供电成本的峰谷时段划分及分时电价研究[J].华东电力,2005,33(12):90-91.
[18]梁甜甜,王磊,高赐威.基于用户响应的尖峰电价模型研究[J].华东电力,2013,41(1):42-46.
[19]刘昌,姚建刚,姚文峰,等.基于DSM的分时电价的确定与分析[J].电力系统保护与控制,2005,33(15):57-61,85.
[20]崔强,王秀丽,曾平良,等.调峰约束下考虑风电消纳的多目标尖峰电价决策模型[J].中国电机工程学报,2015,35(11):2 662-2 669.
[21]张钦,王锡凡,王建学.尖峰电价决策模型分析[J].电力系统自动化,2008,32(9):11-15.
[22]Karen Herter.Residential implementation of criticalpeak pricing of electricity[J].Energy Policy,2007,35(4):2 121-2 130.
[23]A S Hu,T T Lie,H B Gooi.Load forecast for customers under real time pricing systems[C]//London:International Conference on Electric Utility Deregulation and Restructuring and Power Technologies,2000:538-543.
[24]傅利,周步祥,王小红,等.计及用户侧响应的含风电电力系统清洁经济调度[J].电力系统及其自动化学报,2014,26(12):74-79.
[25]陈晓露.交互式智能电网的负荷预测与定价机制[D].上海:上海交通大学,2013.
[26]曾勇.基于智能电网的实时电价研究[D].重庆:重庆大学,2011.
[27]谭忠富,王绵斌,张蓉,等.发电侧与供电侧峰谷分时电价联动的分级优化模型[J].电力系统自动化,2007,31(21):26-29,34.
[28]Huang K Y,Chin H C,Huang Y C.A model reference adaptive control strategy for interruptible load management[J].IEEE Transactions on Power Systems,2004,19(1):683-689.
[29]谭忠富,谢品杰,王绵斌,等.提高电能使用效率的可中断电价与峰谷分时电价的联合优化设计[J].电工技术学报,2009,24(5):161-168.
[30]刘小聪,王蓓蓓,李扬,等.智能电网下计及用户侧互动的发电日前调度计划模型[J].中国电机工程学报,2013,33(1):30-38.
[31]孙宇军,李扬,王蓓蓓,等.计及不确定性需求响应的日前调度计划模型[J].电网技术,2014,38(10):2 708-2 714.
[32]王晶晶.能效电厂项目的节电潜力分析[D].保定:华北电力大学,2014.
[33]刘彩霞,周晖,周伏秋.基于双种群入侵性杂草算法的服务型城市综合资源规划[J].电力系统保护与控制,2013,41(19):67-74.
[34]Zechun Hu,Shu Zhang,et al.SCUC with battery energy storage system for peak-load shaving and reserve support[C]//Canada:IEEE Power and Energy Society General Meeting,2013:1-5.
[35]张泽卉.需求响应效益的量化评估研究[D].济南:山东大学,2011.
[36]Alexandra Kapetanaki,Konstantinos Kopsidas.Reliability evaluation of demand response and TVTR considering the cost of interruptions[C]//Turkey:IEEE PES Innovative Smart Grid Technologies Conference Europe,2014:1-6.
[37]Yuko Omagari,Hideharu Sugihara,et al.An economic effect of demand response with thermal storage airconditioning systems in electricity markets[C]//Spain:1st IEEE-PES/IAS Conference on Sustainable Alternative Energy,2009:1-6.
[38]曹年林.与大规模新能源发电相适应的用户侧联合调峰技术研究[D].北京:北京交通大学,2015.
[39]程瑜,翟娜娜.面向智能电网的峰谷分时电价评估[J].电力系统保护与控制,2010,38(21):196-201,214.