基于粒子群克隆遗传算法的配电网络重构研究
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摘要
配电网络重构作为配电系统优化运行的重要手段,对提高系统的安全性、经济性和可靠性具有十分重大的意义。
本文针对克隆遗传算法(CGA)突变概率难选择和后期收敛缓慢等问题,结合粒子群算法(PSO),提出了粒子群克隆遗传算法(PCGA),构建了PSO变异算子,弥补了粒子群“早熟收敛”及克隆遗传算法的盲目性与无向性,能够根据历史个体记录和群体记录确定进化方向与幅度,同时保证全局收敛;针对配电网重构的特点,对PCGA中的初始种群、编码策略、收敛条件等方面进行优化,并分析了不可行解产生的原因,重点针对双环网和三环网提出了排除不可行解的方法。
另外,本文还采用适应于配电网络的列表法数据结构,实现了基于排序法的按层遍历的拓扑识别和基于前推回代法的配电网络潮流计算,并运用MATLAB的GUI工具箱设计配电网重构的操作界面。
利用IEEE标准算例,分别以降低网络损耗和以提高供电可靠性为目标,对正常运行和故障运行的配电网络进行重构。仿真结果表明,PCGA应用于配电网络重构能够有效地克服CGA运行速度慢、PSO早熟收敛的缺陷,排除不可行解,有效地改善收敛性能,与其他方法相比具有较高的搜索效率和较快的运行速度。
Distribution network reconfiguration is an important method of optimizing the distribution system, which is significant to enhance the security, the efficiency and the reliability of the system.
To resolve mutation probability and slow later-period convergence in the clonal genetic algorithm (CGA), this paper combines the particle swarm algorithm (PSO) with it, and proposes the particle clonal genetic algorithm (PCGA). It builds PSO mutation operator, and makes up premature convergence of PSO and blindness of CGA. It ensures evolution direction and range based on historical records and swarm records. Global optimal solution is found with fewer generations and shorter time. According to distribution network characteristic, initial swarm, code strategy and conditions of convergence of PCGA are optimized. The cause of infeasible solutions of distribution network reconfiguration is analyzed, and the method to eliminate infeasible solutions of the both loop and trip loop is given.
Besides, this paper adopts list data structure of adapting distribution network, accomplishes topology identification based on layer of traversal sort and backward/forward flow algorithm. Distribution network reconfiguration operation interface is design using GUI of MATLAB. Using IEEE standard examples, this paper separately takes the minimum network loss and the maximum power reliability as the objective functions, and reconfigures the normal and interrupted distribution network. The simulation results indicate that PCGA with application to distribution network reconfiguration can not only avoid slow running rate of CGA and precocity of PSO, eliminate infeasible solutions during search process, and improve convergence capability, but also have higher search efficiency and calculation rate than other methods.
本文针对克隆遗传算法(CGA)突变概率难选择和后期收敛缓慢等问题,结合粒子群算法(PSO),提出了粒子群克隆遗传算法(PCGA),构建了PSO变异算子,弥补了粒子群“早熟收敛”及克隆遗传算法的盲目性与无向性,能够根据历史个体记录和群体记录确定进化方向与幅度,同时保证全局收敛;针对配电网重构的特点,对PCGA中的初始种群、编码策略、收敛条件等方面进行优化,并分析了不可行解产生的原因,重点针对双环网和三环网提出了排除不可行解的方法。
另外,本文还采用适应于配电网络的列表法数据结构,实现了基于排序法的按层遍历的拓扑识别和基于前推回代法的配电网络潮流计算,并运用MATLAB的GUI工具箱设计配电网重构的操作界面。
利用IEEE标准算例,分别以降低网络损耗和以提高供电可靠性为目标,对正常运行和故障运行的配电网络进行重构。仿真结果表明,PCGA应用于配电网络重构能够有效地克服CGA运行速度慢、PSO早熟收敛的缺陷,排除不可行解,有效地改善收敛性能,与其他方法相比具有较高的搜索效率和较快的运行速度。
Distribution network reconfiguration is an important method of optimizing the distribution system, which is significant to enhance the security, the efficiency and the reliability of the system.
To resolve mutation probability and slow later-period convergence in the clonal genetic algorithm (CGA), this paper combines the particle swarm algorithm (PSO) with it, and proposes the particle clonal genetic algorithm (PCGA). It builds PSO mutation operator, and makes up premature convergence of PSO and blindness of CGA. It ensures evolution direction and range based on historical records and swarm records. Global optimal solution is found with fewer generations and shorter time. According to distribution network characteristic, initial swarm, code strategy and conditions of convergence of PCGA are optimized. The cause of infeasible solutions of distribution network reconfiguration is analyzed, and the method to eliminate infeasible solutions of the both loop and trip loop is given.
Besides, this paper adopts list data structure of adapting distribution network, accomplishes topology identification based on layer of traversal sort and backward/forward flow algorithm. Distribution network reconfiguration operation interface is design using GUI of MATLAB. Using IEEE standard examples, this paper separately takes the minimum network loss and the maximum power reliability as the objective functions, and reconfigures the normal and interrupted distribution network. The simulation results indicate that PCGA with application to distribution network reconfiguration can not only avoid slow running rate of CGA and precocity of PSO, eliminate infeasible solutions during search process, and improve convergence capability, but also have higher search efficiency and calculation rate than other methods.
引文
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[2]刘健,倪建,邓永辉.配电自动化系统.北京:中国水利水电出版社,2003.1-13
[3]http://www.pudong.gov.cn/website/pudongNews/InfoContent.jsp?ct_id=120009
[4]A.Merlin,H.Back.Search for a Minimal-loss Operating Spanning Tree Configuration for an Urban Power Distribution System.Proc.of 5th Power Systems Comp.Con(PSCC),Cambridge,U,K,1975,6
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[6]Ji-Yuan Fan,Lan Zhang,John D.McDonald.Distribution Network Reconfiguration:Single Loop Optimization IEEE Trans.On Power System,1996,11(3):1643-1647
[7]Civanlar S,Grainger J J,Yin H,et al.Distribution Feeder Reconfiguration for Loss Reduction.IEEE Trans on Power Delivery,1988,3(3):1217-1223
[8]孙健,江道灼.一种多目标配电网络重构新算法.电力系统自动化,2003,27(20):57-61
[9]王征.基于负荷变化的配电网络重构:[硕士学位论文].西安:西安理工大学,2007
[10]Shirmohammadi D,Wayne Hong H.Recontiguration of Electric Distribution Networks for Resistive Line Losses Reduction.IEEE Trans on Power Delivery,1989,4(2):1492-1498
[11]韩学军,陈鹏,国新凤等.基于潮流计算的配电网重构方法.电网技术,2007,31(17):60-63
[12]M.A.Kashem,V.Ganapathy,G.B.Jasmon.On-line network reconfiguration for enhancement of voltage stability in distribution systems using artificial neural networks.Electric Power Components and Systems,2001,29(4):361-373
[13]M.A.Kashem,V.Ganapathy,M.Negnevitsky.Enhancement of load balancing in electrical distribution networks using Artificial Neural Networks.IPEC 20036th International Power Engineering Conference,2003.907-912
[14]金丽成,邱家驹.基于CMAC神经网络的配电网重构模型.浙江大学学报(工学版),2004,38(6):784-788
[15]JEON Y J,KIM J C.Network reconfiguration in radial distribution system using simulated annealing and tabu search.Power Engineering Society Winter Meeting,2000,IEEE.Singapore:IEEE,2000,4:2329-2333
[16]Victor.Parada,Jacques A.Ferland,Miguel.Arias,et al.Optimization of electrical distribution feeders using simulated annealing.IEEE Transactions on Power Delivery,2004,19(3):1135-1141
[17]张步涵,沙立华,曾次玲.基于随机生成树的配电网重构模拟退火算法.华中科技大学学报(自然科学版),2005,33(6):76-79
[18]陈根军,李线洗,唐国庆.基于Tabu搜索的配电网络重构算法.中国电机工程学报,2002,22(10):28-33
[19]葛少云,刘自发,余贻鑫.基于改进禁忌搜索的配电网重构.电网技术,2004,28(23):22-26
[20]Yuji.Mishima,Koichi.Nara,Taiji.Satoh,et al.Method for minimum-loss reconfiguration of distribution system by tabu search.Electrical Engineering in Japan(English translation ofDenki Gakkai Ronbunshi),2005,152(2):18-25
[21]Liu Chen-Ching,Jae Lee S,Venkata S.S.An Expert System Operational Aid for Restoration and Loss Reduction of Distribution Systems.IEEE Trans on Power Systems,1998,3(2):619-626
[22]Kun-Yuan Huang,Hong-Chan Chin.Distribution Feeder Energy Conservation by Using Heuristics Fuzzy Approach.International Journal of Electrical Power and Energy System,2002,24(6):439-445
[23]康明才.模糊遗传算法在网络重构中的应用.继电器,2002,30(3):37-38,42
[24]Nara K,Shiose A,Kitagawa M.Implementation of genetic Algorithm for Distribution System Loss Minimum Reconfiguration.IEEE Trans on Power Systems,1992,7(3):1044-1051
[25]余贻鑫,邱炜,刘若沁.基于启发式算法与遗传算法的配电网重构.电网技术,2001,25(11):19-22
[26]汪超,马红卫,胡志坚等.基于蚁群系统(ACS)的配电网重构.继电器,2006,34(23):35-38
[27]韩富春,王晋,杨翠茹等.遗传算法与蚂蚁算法相融合的电力系统最优潮流计算.电力学报,2005,20(4):340-342
[28]R.C.Eberhart and J.Kennedy.A New Optimizer Using Particles Swarm Theory,Proc.Sixth International Symposium on Micro Machine and Human Science,Nagoya,Japan,1995
[29]白丹丹,刘观起,郭丽.基于改进粒子群算法的配电网重构的研究.华北电力 大学学报,2006,33(6):20-23
[30]许立雄,吕林,刘俊勇.基于PSO的配网重构与电容器投切综合优化算法.继电器,2006,34(17):25-28,33
[31]靳现林,王建生,韩蕾.一种改进粒子群优化算法的配电网重构.东北电力技术,2007,10:11-15
[32]C.H.Lin,C.S.Chen,C.J.Wu,et al.Application of immune algorithm to optimal switching operation for distribution-loss minimization and loading balance.IEE Proceedings:Communications,2003,150(2):183-189
[33]蒙文川,邱家驹.基于免疫算法的配电网重构.中国电机工程学报,2006,26(17):25-29
[34]王淳,程浩忠.基于模拟植物生长算法的配电网重构.中国电机工程学报,2007,27(19):50-55
[35]卜月华,吴健专,顾国华等.图论及其应用.南京:东南大学出版社,2002.3-9
[36]毕鹏翔,刘健,张文元.以提高供电电压质量为目标的配网重构.电网技术,2002,26(2):41-43
[37]余健明,蔡利敏,杨文字.基于提高系统可靠性降低网损的配电网络重构.电工技术学报,2004,19(10):70-73
[38]李海锋,张尧,钱国基,黄健.配电网故障恢复重构算法研究.电力系统自动化,2001,(08):34-37
[39]余加喜,郭志忠.一种面向对象的辐射状配电网潮流计算.哈尔滨理工大学学报,2004,9(6):17-20
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