基于博弈论的多目标配电网重构
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摘要
提出了一种基于博弈论的多目标配电网重构模型,该模型充分考虑了风电和光伏发电的出力不确定性,以降低配电网有功损耗、均衡负荷过载和减少开关操作次数为综合优化目标。将3个目标函数视为不同的博弈者,并考虑各目标之间存在的相互制约关系,加入"后评价"选择机制,构建了合作博弈联盟模型探讨目标间可能存在的联系,并采用改进萤火虫算法对模型进行求解,利用适应度值的大小确定最终重构方案。IEEE 33节点配电网的测试结果表明,所用算法能够快速找到多目标重构博弈模型的均衡解,验证了在加入分布式电源的情况下,网络重构能明显改善配电网的各项指标。
A multi-objective reconfiguration model of distribution network based on game theory is proposed. The model takes full account of the uncertainties of wind power and photovoltaic power generation,and the objective of optimization is to reduce active loss of distribution network,balance overload and reduce the number of switching operation comprehensively. The cooperative game alliance model is established to discuss the possible relationships among the targets based on the "post-evaluation"selection mechanism,by treating the three objective functions as different players and considering their mutual restraint relationships. The improved firefly algorithm is applied to solve the model,and the final reconfiguration scheme is determined based on the fitness value. The test results of IEEE 33-bus distribution network show that the algorithm can quickly find the equilibrium solution of the multiobjective reconfiguration game model,and verify that the network reconfiguration can obviously improve the indexes of distribution network with distributed generation integrated.
A multi-objective reconfiguration model of distribution network based on game theory is proposed. The model takes full account of the uncertainties of wind power and photovoltaic power generation,and the objective of optimization is to reduce active loss of distribution network,balance overload and reduce the number of switching operation comprehensively. The cooperative game alliance model is established to discuss the possible relationships among the targets based on the "post-evaluation"selection mechanism,by treating the three objective functions as different players and considering their mutual restraint relationships. The improved firefly algorithm is applied to solve the model,and the final reconfiguration scheme is determined based on the fitness value. The test results of IEEE 33-bus distribution network show that the algorithm can quickly find the equilibrium solution of the multiobjective reconfiguration game model,and verify that the network reconfiguration can obviously improve the indexes of distribution network with distributed generation integrated.
引文
[1]王薪苹,卫志农,孙国强,等.计及分布式电源和负荷不确定性的多目标配网重构[J].电力自动化设备,2016,36(6):116-121.WANG Xinping,WEI Zhinong,SUN Guoqiang,et al. Multi-objective distribution network reconfiguration considering uncertainties of distributed generation and load[J]. Electric Power Automation Equipment,2016,36(6):116-121.
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[3]刘佳,程浩忠,肖峻,等.计及N-1安全准则的智能配电网多目标重构策略[J].电力系统自动化,2016,40(7):9-15.LIU Jia,CHENG Haozhong,XIAO Jun,et al. A multi-objective reconfiguration strategy for smart distribution network considering N-1security criterion[J]. Automation of Electric Power Systems,2016,40(7):9-15.
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[5] TULADHAR S R,SINGH J G,ONGSAKUL W. A multi-objective network reconfiguration of distribution network with solar and wind distributed generation using NSPSO[C]∥2014 International Conference on Green Energy for Sustainable Development. Cape Town,South Africa:IEEE,2014:1-7.
[6]孙惠娟,彭春华,袁义生.综合开关次数分析的配电网多目标动态重构[J].电力自动化设备,2014,34(9):41-46.SUN Huijuan,PENG Chunhua,YUAN Yisheng. Multi-objective dynamic distribution network reconfiguration considering switching frequency[J]. Electric Power Automation Equipment,2014,34(9):41-46.
[7]何禹清,刘定国,曾超,等.计及可靠性的配电网重构模型及其分阶段算法[J].电力系统自动化,2011,35(17):56-60.HE Yuqing,LIU Dingguo,ZENG Chao,et al. Novel model and multistage algorithm for distribution network reconfiguration considering system reliability[J]. Automation of Electric Power Systems,2011,35(17):56-60.
[8]李鹏,李涛,张双乐,等.基于混沌二进制粒子群算法的独立微网系统的微电源组合优化[J].电力自动化设备,2013,33(12):33-38.LI Peng,LI Tao,ZHANG Shuangle,et al. Combinatorial optimization of micro-sources in standalone microgrid based on chaotic binary particle swarm optimization algorithm[J]. Electric Power Automation Equipment,2013,33(12):33-38.
[9]MOJICA-NAVA E,MACANA C A,QUIJANO N. Dynamic population games for optimal dispatch on hierarchical microgrid control[J].IEEE Transactions on Systems Man and Cybernetics Systems,2014,44(3):306-317.
[10]王晶,王宗礼,陈骏宇,等.基于萤火虫优化算法的微网源-荷博弈模型及分析[J].电力系统自动化,2014,38(21):7-12.WANG Jing,WANG Zongli,CHEN Junyu,et al. A game model for DGs-loads in microgrid based on firefly algorithm and its analysis[J]. Automation of Electric Power Systems,2014,38(21):7-12.
[11]卢强,陈来军,梅生伟.博弈论在电力系统中典型应用及若干展望[J].中国电机工程学报,2014,34(29):5009-5017.LU Qiang,CHEN Laijun,MEI Shengwei. Typical applications and prospects of game theory in power system[J]. Proceedings of the CSEE,2014,34(29):5009-5017.
[12]张沈习,程浩忠,邢海军,等.配电网中考虑不确定性的分布式电源规划研究综述[J].电力自动化设备,2016,36(8):1-9.ZHANG Shenxi,CHENG Haozhong,XING Haijun,et al. Review of DG planning considering uncertainties for distribution network[J].Electric Power Automation Equipment,2016,36(8):1-9.
[13]陈春,汪沨,刘蓓,等.一种避免不可行解的配电网快速重构方法[J].电工技术学报,2015,30(7):34-43.CHEN Chun,WANG Feng,LIU Bei,et al. A fast network reconfiguration method avoiding infeasible solutions for distribution system[J]. Transactions of China Electrotechnical Society,2015,30(7):34-43.
[14]WANG Hui,WANG Wenjun,ZHOU Xinyu. Firefly algorithm with neighborhood attraction[J]. Information Sciences,2016,12:382-383.
[15]YANG Xinshe,DEB S. Eagle strategy using lévy walk and firely algorithms for stochastic optimization[J]. Study in Computational Intelligence,2010,284:101-111.
[16]ALWESHAH M,ABDULLAH S. Hybridizing firefly algorithms with a probabilistic neural network for solving classification problems[J]. Applied Soft Computing,2015,35(12):513-524.
[17]BARAN M E,WU F F. Network reconfiguration in distribution systems for loss reduction and load balancing[J]. IEEE Transactions on Power Delivery,1989,4(2):1401-1407.
[18]陈春,汪沨,刘蓓,等.基于基本环矩阵与改进和声搜索算法的配电网重构[J].电力系统自动化,2014,38(6):55-60.CHEN Chun,WANG Feng,LIU Bei,et al. Network reconfiguration based on basic ring matrix and improved harmony search algorithm[J]. Automation of Electric Power Systems,2014,38(6):55-60.
[2]陈春,汪沨,黎灿兵,等.含分布式风电的配电网预防性重构[J].电工技术学报,2013,28(9):172-177.CHEN Chun,WANG Feng,LI Canbing,et al. Preventive reconfiguration of distribution networks with distributed wind power[J].Transactions of China Electrotechnical Society,2013,28(9):172-177.
[3]刘佳,程浩忠,肖峻,等.计及N-1安全准则的智能配电网多目标重构策略[J].电力系统自动化,2016,40(7):9-15.LIU Jia,CHENG Haozhong,XIAO Jun,et al. A multi-objective reconfiguration strategy for smart distribution network considering N-1security criterion[J]. Automation of Electric Power Systems,2016,40(7):9-15.
[4]MALEKPOUR A R,NIKNAM T,PAHWA A,et al. Multi-objective stochastic distribution feeder reconfiguration in systems with wind power generators and fuel cells using the point estimate method[J].IEEE Transactions on Power Systems,2013,28(2):1483-1492.
[5] TULADHAR S R,SINGH J G,ONGSAKUL W. A multi-objective network reconfiguration of distribution network with solar and wind distributed generation using NSPSO[C]∥2014 International Conference on Green Energy for Sustainable Development. Cape Town,South Africa:IEEE,2014:1-7.
[6]孙惠娟,彭春华,袁义生.综合开关次数分析的配电网多目标动态重构[J].电力自动化设备,2014,34(9):41-46.SUN Huijuan,PENG Chunhua,YUAN Yisheng. Multi-objective dynamic distribution network reconfiguration considering switching frequency[J]. Electric Power Automation Equipment,2014,34(9):41-46.
[7]何禹清,刘定国,曾超,等.计及可靠性的配电网重构模型及其分阶段算法[J].电力系统自动化,2011,35(17):56-60.HE Yuqing,LIU Dingguo,ZENG Chao,et al. Novel model and multistage algorithm for distribution network reconfiguration considering system reliability[J]. Automation of Electric Power Systems,2011,35(17):56-60.
[8]李鹏,李涛,张双乐,等.基于混沌二进制粒子群算法的独立微网系统的微电源组合优化[J].电力自动化设备,2013,33(12):33-38.LI Peng,LI Tao,ZHANG Shuangle,et al. Combinatorial optimization of micro-sources in standalone microgrid based on chaotic binary particle swarm optimization algorithm[J]. Electric Power Automation Equipment,2013,33(12):33-38.
[9]MOJICA-NAVA E,MACANA C A,QUIJANO N. Dynamic population games for optimal dispatch on hierarchical microgrid control[J].IEEE Transactions on Systems Man and Cybernetics Systems,2014,44(3):306-317.
[10]王晶,王宗礼,陈骏宇,等.基于萤火虫优化算法的微网源-荷博弈模型及分析[J].电力系统自动化,2014,38(21):7-12.WANG Jing,WANG Zongli,CHEN Junyu,et al. A game model for DGs-loads in microgrid based on firefly algorithm and its analysis[J]. Automation of Electric Power Systems,2014,38(21):7-12.
[11]卢强,陈来军,梅生伟.博弈论在电力系统中典型应用及若干展望[J].中国电机工程学报,2014,34(29):5009-5017.LU Qiang,CHEN Laijun,MEI Shengwei. Typical applications and prospects of game theory in power system[J]. Proceedings of the CSEE,2014,34(29):5009-5017.
[12]张沈习,程浩忠,邢海军,等.配电网中考虑不确定性的分布式电源规划研究综述[J].电力自动化设备,2016,36(8):1-9.ZHANG Shenxi,CHENG Haozhong,XING Haijun,et al. Review of DG planning considering uncertainties for distribution network[J].Electric Power Automation Equipment,2016,36(8):1-9.
[13]陈春,汪沨,刘蓓,等.一种避免不可行解的配电网快速重构方法[J].电工技术学报,2015,30(7):34-43.CHEN Chun,WANG Feng,LIU Bei,et al. A fast network reconfiguration method avoiding infeasible solutions for distribution system[J]. Transactions of China Electrotechnical Society,2015,30(7):34-43.
[14]WANG Hui,WANG Wenjun,ZHOU Xinyu. Firefly algorithm with neighborhood attraction[J]. Information Sciences,2016,12:382-383.
[15]YANG Xinshe,DEB S. Eagle strategy using lévy walk and firely algorithms for stochastic optimization[J]. Study in Computational Intelligence,2010,284:101-111.
[16]ALWESHAH M,ABDULLAH S. Hybridizing firefly algorithms with a probabilistic neural network for solving classification problems[J]. Applied Soft Computing,2015,35(12):513-524.
[17]BARAN M E,WU F F. Network reconfiguration in distribution systems for loss reduction and load balancing[J]. IEEE Transactions on Power Delivery,1989,4(2):1401-1407.
[18]陈春,汪沨,刘蓓,等.基于基本环矩阵与改进和声搜索算法的配电网重构[J].电力系统自动化,2014,38(6):55-60.CHEN Chun,WANG Feng,LIU Bei,et al. Network reconfiguration based on basic ring matrix and improved harmony search algorithm[J]. Automation of Electric Power Systems,2014,38(6):55-60.