考虑电动汽车不确定性因素的配电网分布式电源优化布置
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摘要
分布式电源和电动汽车的规模化接入对配电网经济运行和电能质量产生了较大影响。分布式电源和电动汽车的功率具有不确定性。为实现分布式电源的合理配置,提出了一种考虑电动汽车不确定性因素的分布式电源优化布置方法。首先,以网络损耗最小、电压偏移最小和系统稳定性高为优化目标,利用机会约束规划方法建立分布式电源优化配置模型。然后,采用支持向量机算法和多目标粒子群算法对上述模型进行求解,得到其Pareto解集。以IEEE 37节点配电网为例对所提模型进行验证,结果表明该模型可以有效得到合理的配置方案。
The large-scale access of distributed generation and electric vehicles has a great impact on the economic operation and power quality of distribution network. Distributed power and electric vehicle power have uncertainties. In order to realize the rational distribution of distributed power, this paper presents a distributed power optimization layout method considering the uncertainties of electric vehicles. First of all, the optimal model of distributed generation is established by using the opportunistic constrained programming method with the least network loss, the minimum voltage offset and the high stability of the system. The SVM algorithm and the multi-objective particle swarm optimization algorithm are used to solve the above model, Pareto solution set is obtained. Finally, the model proposed in this paper is validated by IEEE37 node distribution network. The results show that the model can effectively get a reasonable configuration scheme.
The large-scale access of distributed generation and electric vehicles has a great impact on the economic operation and power quality of distribution network. Distributed power and electric vehicle power have uncertainties. In order to realize the rational distribution of distributed power, this paper presents a distributed power optimization layout method considering the uncertainties of electric vehicles. First of all, the optimal model of distributed generation is established by using the opportunistic constrained programming method with the least network loss, the minimum voltage offset and the high stability of the system. The SVM algorithm and the multi-objective particle swarm optimization algorithm are used to solve the above model, Pareto solution set is obtained. Finally, the model proposed in this paper is validated by IEEE37 node distribution network. The results show that the model can effectively get a reasonable configuration scheme.
引文
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[15]夏澍,周明,李庚银.分布式电源选址定容的多目标优化算法[J].电网技术,2011,35(9):115-121.XIA Shu,ZHOU Ming,LI Gengyin.Multi-objective optimization algorithm for distributed generation locating and sizing[J].Power System Technology,2011,35(9):115-121.
[16]管志成,丁晓群,张木银,等.考虑时序特性含电动汽车配电网分布式电源优化配置[J].电力系统保护与控制,2017,45(18):24-31.GUAN Zhicheng,DING Xiaoqun,ZHANG Muyin,et al.Optimal allocation of distributed generation of distributed network containing electric vehicle considering timing characteristics[J].Power System Protection and Control,2017,45(18):24-31.
[17]RANJAN R,DAS D.Voltage stability analysis of radial distribution networks[J].Electric Power Components&Systems,2001,23(2):129-135.
[18]QI X,LI K,WANG J,et al.Transformer top-oil temperature combination modeling based on thermal circuit and support vector machine[C]//2016 IEEE PESAsia-Pacific Power and Energy Engineering Conference(APPEEC),October 25-28,2016,Xi'an,China:1933-1937.
[19]RAQUEL C R,NAVAL JR P C.An effective use of crowding distance in multiobjective particle swarm optimization[C]//Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation,ACM,2005:257-264.
[20]IEEE Distribution System Analysis Subcommittee.IEEEradial test feeders[EB/OL].[2013-08-05].http://www.ewh.ieee.org/soc/pes/dsacom/testfeeders/index.html.
[2]MA Z,CALLAWAY D S,HISKENS I A.Decentralized charging control of large populations of plug-in electric vehicles[J].IEEE Transactions on Control Systems Technology,2013,21(1):67-78.
[3]EVANGELOPOULOS V A,GEORGILAKIS P S.Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm[J].IET Generation,Transmission&Distribution,2013,8(3):389-400.
[4]SUN Siyang,YANG Qiang,YAN Wenjun.Optimal temporal-spatial PEV charging scheduling in active power distribution networks[J].Protection and Control of Modern Power Systems,2017,2(2):379-388.DOI:10.1186/s41601-017-0065-x.
[5]EL-ELA A A A,ALLAM S M,SHATLA M M.Maximal optimal benefits of distributed generation using genetic algorithms[J].Electric Power Systems Research,2010,80(7):869-877.
[6]卢扬,吴俊勇,郝亮亮.基于改进MOBPSO算法的含分布式电源的多目标配电网重构[J].电力系统保护与控制,2016,44(7):62-68.LU Yang,WU Junyong,HAO Liangliang.Multiobjective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm[J].Power System Protection and Control,2016,44(7):62-68.
[7]胡文平,何立夫,陈杰军,等.考虑大规模电动汽车接入电网的双层优化调度策略[J].电力系统保护与控制,2016,44(21):22-28.HU Wenping,HE Lifu,CHEN Jiejun,et al.A bi-layer optimization based schedule considering large-scale electric vehicles[J].Power System Protection and Control,2016,44(21):22-28.
[8]刘志鹏,文福拴,薛禹胜,等.计及可入网电动汽车的分布式电源最优选址和定容[J].电力系统自动化,2011,35(18):11-16.LIU Zhipeng,WEN Fushuan,XUE Yusheng,et al.Optimal siting and sizing of distributed generators considering plug-in electric vehicles[J].Automation of Electric Power Systems,2011,35(18):11-16.
[9]彭显刚,林利祥,刘艺,等.计及电动汽车和可再生能源不确定因素的多目标分布式电源优化配置[J].电网技术,2015,39(8):2188-2194.PENG Xiangang,LIN Lixiang,LIU Yi,et al.Multiobjective optimal allocation of distributed generation considering uncertainties of plug-in electric vehicles and renewable energy sources[J].Power System Technology,2015,39(8):2188-2194.
[10]MUTOH N,MATUO T,OKADA K,et al.Predictiondata-based maximum-power-point-tracking method for photovoltaic power generation systems[C]//2002 IEEEPower Electronics Specialists Conference,June 23-27,2002,Cairns,Qld,Australia:1489-1494.
[11]ATWA Y M,EL-SAADANY E F,SEETHAPATHY R,et al.Effect of wind-based DG seasonality and uncertainty on distribution system losses[C]//2008 40th North American Power Symposium,September 28-30,2008,Calgary,AB,Canada:1-6.
[12]葛少云,王龙,刘洪,等.计及电动汽车入网的峰谷电价时段优化模型研究[J].电网技术,2013,37(8):2316-2321.GE Shaoyun,WANG Long,LIU Hong,et al.An optimization model of peak-valley price time-interval considering vehicle-to-grid[J].Power System Technology,2013,37(8):2316-2321.
[13]刘辉,魏岩岩,汪旎,等.电动汽车入网调频控制策略研究[J].电力系统保护与控制,2015,43(23):90-95.LIU Hui,WEI Yanyan,WANG Ni,et al.V2G control for EVs participating in primary frequency regulation[J].Power System Protection and Control,2015,43(23):90-95.
[14]李亮,唐巍,白牧可,等.考虑时序特性的多目标分布式电源选址定容规划[J].电力系统自动化,2013,37(3):58-63.LI Liang,TANG Wei,BAI Muke,et al.Multi-objective locating and sizing of distribution generators based on time-sequence characteristics[J].Automation of Electric Power Systems,2013,37(3):58-63.
[15]夏澍,周明,李庚银.分布式电源选址定容的多目标优化算法[J].电网技术,2011,35(9):115-121.XIA Shu,ZHOU Ming,LI Gengyin.Multi-objective optimization algorithm for distributed generation locating and sizing[J].Power System Technology,2011,35(9):115-121.
[16]管志成,丁晓群,张木银,等.考虑时序特性含电动汽车配电网分布式电源优化配置[J].电力系统保护与控制,2017,45(18):24-31.GUAN Zhicheng,DING Xiaoqun,ZHANG Muyin,et al.Optimal allocation of distributed generation of distributed network containing electric vehicle considering timing characteristics[J].Power System Protection and Control,2017,45(18):24-31.
[17]RANJAN R,DAS D.Voltage stability analysis of radial distribution networks[J].Electric Power Components&Systems,2001,23(2):129-135.
[18]QI X,LI K,WANG J,et al.Transformer top-oil temperature combination modeling based on thermal circuit and support vector machine[C]//2016 IEEE PESAsia-Pacific Power and Energy Engineering Conference(APPEEC),October 25-28,2016,Xi'an,China:1933-1937.
[19]RAQUEL C R,NAVAL JR P C.An effective use of crowding distance in multiobjective particle swarm optimization[C]//Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation,ACM,2005:257-264.
[20]IEEE Distribution System Analysis Subcommittee.IEEEradial test feeders[EB/OL].[2013-08-05].http://www.ewh.ieee.org/soc/pes/dsacom/testfeeders/index.html.