基于改进量子遗传算法的配电网无功优化研究及应用
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摘要
提出一种基于改进量子遗传算法的配电网无功优化方法。采用量子比特概率幅对控制变量进行编码,提出交换个体局部最优目标值的量子交叉方式和互换量子个体α和β值的量子变异方式,丰富了种群多样性,缩短了运算周期,提高了算法计算效率与全局寻优能力。规范、简洁地给出配电网无功优化数学模型,详细阐明基于IQGA的无功优化方法。分别采用遗传算法、量子进化算法和文中方法对某城区局部中压配电网中选定节点系统进行仿真计算,验证了该方法的有效性和优越性。
In this paper, a reactive power optimization method of distribution network based on improved quantum-inspired genetic algorithm(IQGA) is proposed, in which the probability amplitude is used in the coding of the control variable, and the quantum crossover method based on exchanging local optimal between subjects and the quantum mutation method based on exchanging subject's α-value and β-value are proposed. These methods proposed enrich the diversity of population, shorten operation cycles, increase computational efficiency and improve the global searching capability. This paper provides a canonical and concise math model of reactive power optimization for distribution network, describes the reactive power optimization method in detail based on IQGA, and finally uses genetic algorithm, quantum-inspired evolutionary algorithm and IQGA to simulate the bus system of a certain partial medium voltage distribution network to prove the validity and practicability of IQGA.
In this paper, a reactive power optimization method of distribution network based on improved quantum-inspired genetic algorithm(IQGA) is proposed, in which the probability amplitude is used in the coding of the control variable, and the quantum crossover method based on exchanging local optimal between subjects and the quantum mutation method based on exchanging subject's α-value and β-value are proposed. These methods proposed enrich the diversity of population, shorten operation cycles, increase computational efficiency and improve the global searching capability. This paper provides a canonical and concise math model of reactive power optimization for distribution network, describes the reactive power optimization method in detail based on IQGA, and finally uses genetic algorithm, quantum-inspired evolutionary algorithm and IQGA to simulate the bus system of a certain partial medium voltage distribution network to prove the validity and practicability of IQGA.
引文
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[6]吴丽珍,蒋力波,郝晓弘.基于最优场景生成算法的主动配电网无功优化[J].电力系统保护与控制,2017,45(15):152-159.WU Lizhen,JIANG Libo,HAO Xiaohong.Reactive power optimization of active distribution network based on optimal scenario generation algorithm[J].Power System Protection and Control,2017,45(15):152-159(in Chinese).
[7]马晋弢,LAI L L,杨以涵.遗传算法在电力系统无功优化中的应用[J].中国电机工程学报,1995,15(5):347-353.MA Jintao,LAI L L,YANG Yihan.Application of genetic algorithm in reactive power optimization[J].Proceedings of the CSEE,1995,15(5):347-353(in Chinese).
[8]马立新,栾健.三目标遗传粒子算法的电力系统无功优化[J].华北电力大学学报(自然科学版),2015,42(3):31-35.MA Lixin,LUAN Jian.Three-objective hybrid algorithm of genetic and particle swarm optimization for reactive power optimization[J].Journal of North China Electric Power University(Nature Science Edition),2015,42(3):31-35(in Chinese).
[9]李渊博,蒋铁铮.采用改进遗传算法的无功优化规划[J].电力科学与工程,2014,30(9):39-45.LI Yuanbo,JIANG Tiezheng.Optimization of reactive power planning using improved genetic algorithm[J].Electric Power Science and Engineering,2014,30(9):39-45(in Chinese).
[10]陈光宇,何健,施蔚锦,等.基于量子混合蛙跳算法的含分布式电源配电网无功优化[J].电网与清洁能源,2015,31(5):36-41,46.CHEN Guangyu,HE Jian,SHI Weijin,et al.Reactive power optimization in distribution network with distributed generators based on quantum shuffled frog leaping algorithm[J].Power System and Clean Energy,2015,31(5):36-41,46(in Chinese).
[11]王韶,周鑫.应用层次聚类法和蚁群算法的配电网无功优化[J].电网技术,2011,35(8):161-167.WANG Shao,ZHOU Xin.Optimization of reactive power in distribution network with hierarchical clustering and ant colony algorithm[J].Power System Technology,2011,35(8):161-167(in Chinese).
[12]LIU Yutian,MA Ii,ZHANG Jianjun,GA/SA/TS hybrid algorithms for reactive power optimization[C]//IEEE PES Summer Meeting,2000(1):245-249.
[13]娄素华,吴耀武,熊信银.电力系统无功优化的变尺度混沌优化算法[J].电网技术,2005,29(11):20-24.LOU Suhua,WU Yaowu,XIONG Xinyin.Mutative scale chaos optimization algorithm for reactive power optimization of power system[J].Power System Technology,2005,29(11):20-24(in Chinese).
[14]刘红文,张葛祥.基于改进量子遗传算法的电力系统无功优化[J].电网技术,2008,32(12):35-38.LIU Hongwen,ZHANG Gexiang.A reactive power optimization method based on improved quantum-inspired genetic algorithm[J].Power System Technology,2008,32(12):35-38(in Chinese).
[15]单瑞卿,吕群芳,王建勋,等.基于自适应遗传算法的配电网无功优化[J].电力电容器与无功补偿,2010,31(3):18-21,57.SHAN Ruiqing,L譈Qunfang,WANG Jianxun.et al.Reactive power optimization of distribution network based on adaptive genetic algorithm[J].Power Capacitor&Reactive Power Compensation,2010,31(3):18-21,57(in Chinese).
[16]HAN K H,KIM H J.Quantum-inspire devolutionary algorithm for a class of combinatorial optimization[J].IEEE Trans on Evolutionary Computation,2002,6(6):580-593.
[17]HEY T.Quantum computation:an introduction[J].Computing&Engineering Jounal,1996,10(3).105-112.
[18]赵登福,杨靖,刘昱.基于改进遗传算法的配电网无功优化[J].西安交通大学学报,2001,35(12):1219-1222.ZHAO Dengfu,YANG Jing,LIU Yu.Reactive power optimization of the radial distribution system based on the improved genetic algorithm[J].Journal of Southwest Jiaotong University,2001,35(12):1219-1222.
[19]娄素华,李研,吴耀武,等.多目标电网无功优化的量子遗传算法[J].高电压技术,2005,31(9):69-71.LOU Suhua,LI Yan,WU Yaowu.Multi-objective reactive power optimization using quantum genetic algorithm[J].High Voltage Engineering,2005,31(9):69-71(in Chinese).
[2]谢海波,武小梅,林翔,等.含分布式电源的配电网无功优化研究综述[J].广东电力,2017,30(2):102-109.XIE Haibo,WU Xiaonei,LIN Xiang,et al.Review on reactive power optimization for power distribution network with distributed generation[J].Guangdong Power Journal 2017,30(2):102-109(in Chinese).
[3]周文俊,吴熙,施伟成.电力系统无功优化算法性能比较及分析[J].江苏电机工程,2013,32(4):24-27.ZHOU Wenjun,WU Xi,SHI Weicheng.Comparison and analysis of algorithms for power system reactive power optimization[J].Jiangsu Electrical Engineering,2013,32(4):24-27(in Chinese).
[4]袁辉,徐贵光,周京阳.基于模糊线性规划的无功电压优化[J].电网技术,2003,27(12):42-45.YUAN Hui,XU Guiguang,ZHOU Jingyang.A reactive power/voltage optimization based on fuzzy linear programming[J].Power System Technology,2003,27(12):42-45(in Chinese).
[5]胡晓阳,王卫平,王主丁,等.一种实用的配电网无功运行两层优化方法研究[J/OL].电力系统保护与控制,2015,43(3):14-21.HU Xiaoyang,WANG Weiping,WANG Zhuding,et al.A practical two-phase optimization method of dynamic var optimization in a distribution system[J].Power System Protection and Control,2015,43(3):14-21(in Chinese).
[6]吴丽珍,蒋力波,郝晓弘.基于最优场景生成算法的主动配电网无功优化[J].电力系统保护与控制,2017,45(15):152-159.WU Lizhen,JIANG Libo,HAO Xiaohong.Reactive power optimization of active distribution network based on optimal scenario generation algorithm[J].Power System Protection and Control,2017,45(15):152-159(in Chinese).
[7]马晋弢,LAI L L,杨以涵.遗传算法在电力系统无功优化中的应用[J].中国电机工程学报,1995,15(5):347-353.MA Jintao,LAI L L,YANG Yihan.Application of genetic algorithm in reactive power optimization[J].Proceedings of the CSEE,1995,15(5):347-353(in Chinese).
[8]马立新,栾健.三目标遗传粒子算法的电力系统无功优化[J].华北电力大学学报(自然科学版),2015,42(3):31-35.MA Lixin,LUAN Jian.Three-objective hybrid algorithm of genetic and particle swarm optimization for reactive power optimization[J].Journal of North China Electric Power University(Nature Science Edition),2015,42(3):31-35(in Chinese).
[9]李渊博,蒋铁铮.采用改进遗传算法的无功优化规划[J].电力科学与工程,2014,30(9):39-45.LI Yuanbo,JIANG Tiezheng.Optimization of reactive power planning using improved genetic algorithm[J].Electric Power Science and Engineering,2014,30(9):39-45(in Chinese).
[10]陈光宇,何健,施蔚锦,等.基于量子混合蛙跳算法的含分布式电源配电网无功优化[J].电网与清洁能源,2015,31(5):36-41,46.CHEN Guangyu,HE Jian,SHI Weijin,et al.Reactive power optimization in distribution network with distributed generators based on quantum shuffled frog leaping algorithm[J].Power System and Clean Energy,2015,31(5):36-41,46(in Chinese).
[11]王韶,周鑫.应用层次聚类法和蚁群算法的配电网无功优化[J].电网技术,2011,35(8):161-167.WANG Shao,ZHOU Xin.Optimization of reactive power in distribution network with hierarchical clustering and ant colony algorithm[J].Power System Technology,2011,35(8):161-167(in Chinese).
[12]LIU Yutian,MA Ii,ZHANG Jianjun,GA/SA/TS hybrid algorithms for reactive power optimization[C]//IEEE PES Summer Meeting,2000(1):245-249.
[13]娄素华,吴耀武,熊信银.电力系统无功优化的变尺度混沌优化算法[J].电网技术,2005,29(11):20-24.LOU Suhua,WU Yaowu,XIONG Xinyin.Mutative scale chaos optimization algorithm for reactive power optimization of power system[J].Power System Technology,2005,29(11):20-24(in Chinese).
[14]刘红文,张葛祥.基于改进量子遗传算法的电力系统无功优化[J].电网技术,2008,32(12):35-38.LIU Hongwen,ZHANG Gexiang.A reactive power optimization method based on improved quantum-inspired genetic algorithm[J].Power System Technology,2008,32(12):35-38(in Chinese).
[15]单瑞卿,吕群芳,王建勋,等.基于自适应遗传算法的配电网无功优化[J].电力电容器与无功补偿,2010,31(3):18-21,57.SHAN Ruiqing,L譈Qunfang,WANG Jianxun.et al.Reactive power optimization of distribution network based on adaptive genetic algorithm[J].Power Capacitor&Reactive Power Compensation,2010,31(3):18-21,57(in Chinese).
[16]HAN K H,KIM H J.Quantum-inspire devolutionary algorithm for a class of combinatorial optimization[J].IEEE Trans on Evolutionary Computation,2002,6(6):580-593.
[17]HEY T.Quantum computation:an introduction[J].Computing&Engineering Jounal,1996,10(3).105-112.
[18]赵登福,杨靖,刘昱.基于改进遗传算法的配电网无功优化[J].西安交通大学学报,2001,35(12):1219-1222.ZHAO Dengfu,YANG Jing,LIU Yu.Reactive power optimization of the radial distribution system based on the improved genetic algorithm[J].Journal of Southwest Jiaotong University,2001,35(12):1219-1222.
[19]娄素华,李研,吴耀武,等.多目标电网无功优化的量子遗传算法[J].高电压技术,2005,31(9):69-71.LOU Suhua,LI Yan,WU Yaowu.Multi-objective reactive power optimization using quantum genetic algorithm[J].High Voltage Engineering,2005,31(9):69-71(in Chinese).