基于DAPSO算法的含分布式电源的配电网重构
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摘要
为了改善智能算法性能、提高寻优效率、满足网络辐射状和连通性约束,提出一种基于动态自适应粒子群优化(DAPSO)算法的含分布式电源的配电网络重构策略,用于求解重构的离散变量优化问题。动态自适应调整惯性权重和对速度进行变异,避免算法陷入局部最优,保持全局开拓和局部探索的动态平衡,加强算法的寻优性能。采用"解环"法,确保重构后网络为辐射型并保证网络的连通性。基于IEEE33和PG&E69节点系统的仿真结果显示,DAPSO算法收敛速度快、全局寻优能力强、稳定性好,其寻优重构方案可有效降低网损,改善电压水平,优于其他方法的结果,具有很好的实用价值。
In order to improve the performance of intelligent algorithms and the optimization efficiency;the dynamicadaptive particle swarm optimization(DAPSO)is presented in this paper to search the best scheme of network recon-figuration with distributed generation thus to meet the network radiation and connectivity constraints;and the recon-figuration of distribution is a discrete variable optimization problem. The DAPSO can adaptive change inertia weightand the speed of the particles. It maintains the global development and local exploration of dynamic balance thus canenhance the optimization performance of the algorithm. The"loop disconnect"method is used to solve the problem ofreconstruction. The network is kept in radiated and it can ensure network connectivity at the same time after configu-ration. The simulation results based on IEEE33 nodes system and PG & E69 nodes system show that DAPSO algo-rithm has the advantages of fast convergence speed;strong global optimization ability and great stability. Its optimalreconstruction scheme can effectively reduce the network loss and improve the voltage level. It's better than othermethods and has great practical value.
In order to improve the performance of intelligent algorithms and the optimization efficiency;the dynamicadaptive particle swarm optimization(DAPSO)is presented in this paper to search the best scheme of network recon-figuration with distributed generation thus to meet the network radiation and connectivity constraints;and the recon-figuration of distribution is a discrete variable optimization problem. The DAPSO can adaptive change inertia weightand the speed of the particles. It maintains the global development and local exploration of dynamic balance thus canenhance the optimization performance of the algorithm. The"loop disconnect"method is used to solve the problem ofreconstruction. The network is kept in radiated and it can ensure network connectivity at the same time after configu-ration. The simulation results based on IEEE33 nodes system and PG & E69 nodes system show that DAPSO algo-rithm has the advantages of fast convergence speed;strong global optimization ability and great stability. Its optimalreconstruction scheme can effectively reduce the network loss and improve the voltage level. It's better than othermethods and has great practical value.
引文
[1]徐玉琴,李雪冬,张继刚,等.考虑分布式发电的配电网规划问题的研究[J].电力系统保护与控制,2011,39(1):87-91.XU Yuqing,LI Xuedong,ZHANG Jigang,et al. Research on distribution network planning considering DGs[J]. Power System Protection and Control,2011,39(1):87-91.
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[5]栾伟杰,程浩忠,杨国健,等.考虑网络重构的配电网多目标运行方式优化[J].电力系统及其自动化学报,2016,28(10):1-7.LUAN Weijie,CHENG Haozhong,YANG Guojian,et al.Multi-objective operation mode optimization for distribution network using network reconfiguration[J]. Proceedings of the CSU-EPSA,2016,28(10):1-7.
[6]黄平.粒子群算法改进及其在电力系统的应用[D].广州:华南理工大学,2012.HUANG Ping. Dissertation submitted for the degree of doctor of philosophy[D]. Guangzhou:South China University of Technology,2012.
[7]冯春时.群智能优化算法及其应用[D].合肥:中国科学技术大学,2009.FENG Chunshi. Swarm intelligence optimization algorithms and their applications[D]. Hefei:University of Science and Technology of China,2009.
[8]贾树晋,杜斌,岳恒.基于局部搜索与混合多样性策略的多目标粒子群算法[J].控制与决策,2012,27(6):813-818.JIA Shujin,DU Bin,YUE Heng. Local search and hybrid diversity strategy based multi-objective particle swarm optimization algorithm[J]. Control and Decision,2012,27(6):813-818.
[9]于永哲,黄家栋.基于混合智能算法的配电网络重构[J].南方电网技术,2010,4(1):76-79.YU Yongzhe,HUANG Jiadong. Reconfiguration of distribution network based on hybrid intelligent algorithm[J].Southern Power System Technology,2010,4(1):76-79.
[10]刘健,张小庆,张志华,等.配电网两相接地短路故障定位与供电恢复[J].电力系统自动化,2013,37(5):105-110.LIU Jian,ZHANG Xiaoqing,ZAHNG Zhihua,et al.Loction and restoration of two-phase grounded short-circuit in distribution systems[J]. Automation of Electric Power Systems,2013,37(5):105-110.
[11]雷金勇,李战鹰,卢泽汉,等.分布式发电技术及其对电力系统影响研究综述[J].南方电网技术,2011,5(4):46-50.LEI Jinyong,LI Zhanying,LU Zehan,et al. Review on the Research of distributed generation technology and its impacts on electric power systems[J]. Southern Power System Technology,2011,5(4):46-50.
[12]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. Multi-objective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm[J]. Power System Protection and Control,2016,44(7):62-68.
[13]程虹,高元海,王淳.基于无重访NSGA-Ⅱ算法的配电网多目标重构[J].电力系统保护与控制,2016,7(23):10-16.CHENG Hong,GAO Yuanhai,WANG Chun. Multi-objective distribution network reconfiguration base on non-revisiting NSGA-II algorithm[J]. Power System Protection and Control,2016,7(23):10-16.
[14]刘衍民,隋常玲,赵庆祯.基于K—均值聚类的动态多种群粒子群算法及其应用[J].控制与决策,2011,26(7):1019-1025.LIU Yanming,SUI Changling,ZHAO Qingzhen. Dynamic multi-swarm particle swarm optimizer based on k-means clustering and its application[J]. Control and Decision,2011,26(7):1017-1025.
[15] SIERRA M R,COELLO C A. Multi-objective particle swarm optimizers:a survey of the state-of-the-art[J]. International Journal of Computational Intelligence Research,2006,2(3):287-308.
[16]付文锋,李嘉华,王蓝婧,等.基于动态自适应粒子群算法的二次再热燃煤—捕碳机组热力系统优化设计[J].中国电机工程学报,2017,37(9):2652-2659.FU Wenfeng,LI Jiahua,WANG Lanjing,et al. Optimal design for thermodynamics system of double reheat coal-fired power plants withpost-combustion carbon capture based on dynamic adaptive particle swarm optimization[J]. Proceedings of the CSEE,2017,37(9):2652-2659.
[17] RATNAWEERA A,HALGAMUGE S K,WATSON H C.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J]. IEEE Transactions onEvolutionaryComputation,2004,8(3):240-255.
[18] CHENG S,HU G,QIN T Y. Application of quorum sensing to pso and mopso for convergence promotion[C]//Chinese Control&Decision Conference.[S.l.]:[s.n.],2014:1106-1110.
[19]李娟,杨琳,刘金龙,等.基于自适应混沌粒子群优化算法的多目标无功优化[J].电力系统保护与控制,2011,39(9):26-31.LI Juan,YANG Lin,LIU Jinlong,et al. Multi-objective reactive power optimization based on adaptive chaos particle swarm optimization algorithm[J]. Power System Protection and Control,2011,39(9):26-31.
[20]吴辰斌,李海明,刘栋,等.一种改进型粒子群优化算法在电力系统经济负荷分配中的应用[J].电力系统保护与控制,2016,44(10):44-48.WU Chenbin,LI Haiming,LIU Dong,et al. Application of improved particle swarm optimization algorithm to power system economic load dispatch[J]. Power System Protection and Control,2016,44(10):44-48.
[21]黄炜果,刘俊勇,魏震波,等.考虑冗余电量和时序性的分布式电源的选址定容[J].高压电器,2016,52(3):93-99.HUANG Weiguo,LIU Junyong,WEI Zhenbo,et al. Sizing and siting of multi-types of distribution generator considering redundant electricity and timing characteristics[J].High Voltage Apparatus,2016,52(3):93-99.
[22]杨广杰.含分布式电源的配电网重构[D].北京:华北电力大学电气与电子工程学院,2012.YANG Guangjie. Research on network reconfiguration of distributionsystem with distributed generation[D]. Beijing:North China Electric Power University,2012.
[23]张万月,陈星莺,余昆,等.基于增广节点支路关联矩阵的前推回代潮流算法[J].电网与清洁能源,2015,31(12):62-67.ZHANG Wanyue,CHEN Xingying,YU Kun,et al. Augmented node branch incidence matrix based back/forward sweep flow calculation[J]. Power System and Clean Energy,2015,31(12):62-67.
[24]汤姗姗.基于改进自适应遗传算法的含分布式电源的配电网重构[D].济南:山东大学,2013.TANG Shanshan. Research on reconfiguration of distribution network with distributed generation based on refined adaptive genetic algorithm[D]. Jinan:Shandong University,2013.
[2]董开松,谢永涛,贾嵘,等.面向主动式配网的微电网技术探究[J].高压电器,2015,51(6):97-100.DONG Kaisong,XIE Yongtao,JIA Rong,et al. Research on microgrid technology for active distribution network[J].High Voltage Apparatus,2015,51(6):97-100.
[3] CHENG S,CHEN M Y,WAI R J,et al. Optimal placement of distributed generation units in distribution systems via an enhanced multi-objective particle swarm optimization algorithm[J]. Frontiers of Information Technology&Electronic Engineering,2014,15(4):300-311.
[4]程杉.含分布式电源的配电网多目标优化问题研究[D].重庆:重庆大学,2013.CHENG Shan. Study on multi-objective optimization of distribution network with distributed generation[D]. Chongqing:Chongqing University,2013.
[5]栾伟杰,程浩忠,杨国健,等.考虑网络重构的配电网多目标运行方式优化[J].电力系统及其自动化学报,2016,28(10):1-7.LUAN Weijie,CHENG Haozhong,YANG Guojian,et al.Multi-objective operation mode optimization for distribution network using network reconfiguration[J]. Proceedings of the CSU-EPSA,2016,28(10):1-7.
[6]黄平.粒子群算法改进及其在电力系统的应用[D].广州:华南理工大学,2012.HUANG Ping. Dissertation submitted for the degree of doctor of philosophy[D]. Guangzhou:South China University of Technology,2012.
[7]冯春时.群智能优化算法及其应用[D].合肥:中国科学技术大学,2009.FENG Chunshi. Swarm intelligence optimization algorithms and their applications[D]. Hefei:University of Science and Technology of China,2009.
[8]贾树晋,杜斌,岳恒.基于局部搜索与混合多样性策略的多目标粒子群算法[J].控制与决策,2012,27(6):813-818.JIA Shujin,DU Bin,YUE Heng. Local search and hybrid diversity strategy based multi-objective particle swarm optimization algorithm[J]. Control and Decision,2012,27(6):813-818.
[9]于永哲,黄家栋.基于混合智能算法的配电网络重构[J].南方电网技术,2010,4(1):76-79.YU Yongzhe,HUANG Jiadong. Reconfiguration of distribution network based on hybrid intelligent algorithm[J].Southern Power System Technology,2010,4(1):76-79.
[10]刘健,张小庆,张志华,等.配电网两相接地短路故障定位与供电恢复[J].电力系统自动化,2013,37(5):105-110.LIU Jian,ZHANG Xiaoqing,ZAHNG Zhihua,et al.Loction and restoration of two-phase grounded short-circuit in distribution systems[J]. Automation of Electric Power Systems,2013,37(5):105-110.
[11]雷金勇,李战鹰,卢泽汉,等.分布式发电技术及其对电力系统影响研究综述[J].南方电网技术,2011,5(4):46-50.LEI Jinyong,LI Zhanying,LU Zehan,et al. Review on the Research of distributed generation technology and its impacts on electric power systems[J]. Southern Power System Technology,2011,5(4):46-50.
[12]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. Multi-objective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm[J]. Power System Protection and Control,2016,44(7):62-68.
[13]程虹,高元海,王淳.基于无重访NSGA-Ⅱ算法的配电网多目标重构[J].电力系统保护与控制,2016,7(23):10-16.CHENG Hong,GAO Yuanhai,WANG Chun. Multi-objective distribution network reconfiguration base on non-revisiting NSGA-II algorithm[J]. Power System Protection and Control,2016,7(23):10-16.
[14]刘衍民,隋常玲,赵庆祯.基于K—均值聚类的动态多种群粒子群算法及其应用[J].控制与决策,2011,26(7):1019-1025.LIU Yanming,SUI Changling,ZHAO Qingzhen. Dynamic multi-swarm particle swarm optimizer based on k-means clustering and its application[J]. Control and Decision,2011,26(7):1017-1025.
[15] SIERRA M R,COELLO C A. Multi-objective particle swarm optimizers:a survey of the state-of-the-art[J]. International Journal of Computational Intelligence Research,2006,2(3):287-308.
[16]付文锋,李嘉华,王蓝婧,等.基于动态自适应粒子群算法的二次再热燃煤—捕碳机组热力系统优化设计[J].中国电机工程学报,2017,37(9):2652-2659.FU Wenfeng,LI Jiahua,WANG Lanjing,et al. Optimal design for thermodynamics system of double reheat coal-fired power plants withpost-combustion carbon capture based on dynamic adaptive particle swarm optimization[J]. Proceedings of the CSEE,2017,37(9):2652-2659.
[17] RATNAWEERA A,HALGAMUGE S K,WATSON H C.Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J]. IEEE Transactions onEvolutionaryComputation,2004,8(3):240-255.
[18] CHENG S,HU G,QIN T Y. Application of quorum sensing to pso and mopso for convergence promotion[C]//Chinese Control&Decision Conference.[S.l.]:[s.n.],2014:1106-1110.
[19]李娟,杨琳,刘金龙,等.基于自适应混沌粒子群优化算法的多目标无功优化[J].电力系统保护与控制,2011,39(9):26-31.LI Juan,YANG Lin,LIU Jinlong,et al. Multi-objective reactive power optimization based on adaptive chaos particle swarm optimization algorithm[J]. Power System Protection and Control,2011,39(9):26-31.
[20]吴辰斌,李海明,刘栋,等.一种改进型粒子群优化算法在电力系统经济负荷分配中的应用[J].电力系统保护与控制,2016,44(10):44-48.WU Chenbin,LI Haiming,LIU Dong,et al. Application of improved particle swarm optimization algorithm to power system economic load dispatch[J]. Power System Protection and Control,2016,44(10):44-48.
[21]黄炜果,刘俊勇,魏震波,等.考虑冗余电量和时序性的分布式电源的选址定容[J].高压电器,2016,52(3):93-99.HUANG Weiguo,LIU Junyong,WEI Zhenbo,et al. Sizing and siting of multi-types of distribution generator considering redundant electricity and timing characteristics[J].High Voltage Apparatus,2016,52(3):93-99.
[22]杨广杰.含分布式电源的配电网重构[D].北京:华北电力大学电气与电子工程学院,2012.YANG Guangjie. Research on network reconfiguration of distributionsystem with distributed generation[D]. Beijing:North China Electric Power University,2012.
[23]张万月,陈星莺,余昆,等.基于增广节点支路关联矩阵的前推回代潮流算法[J].电网与清洁能源,2015,31(12):62-67.ZHANG Wanyue,CHEN Xingying,YU Kun,et al. Augmented node branch incidence matrix based back/forward sweep flow calculation[J]. Power System and Clean Energy,2015,31(12):62-67.
[24]汤姗姗.基于改进自适应遗传算法的含分布式电源的配电网重构[D].济南:山东大学,2013.TANG Shanshan. Research on reconfiguration of distribution network with distributed generation based on refined adaptive genetic algorithm[D]. Jinan:Shandong University,2013.