基于智能优化算法的FACTS设备多目标优化配置Intelligent Optimization Algorithm Based Multi-Objective Optimal Configuration for FACTS Equipments
上官海洋;向铁元;张巍;殷杰;崔若涵;
摘要(Abstract):
综合考虑可用输电能力和柔性交流输电设备投资费用,建立了用于FACTS设备选址和定容的多目标优化模型。提出了一种基于变焦佳点集和种群熵的改进多目标引力搜索优化算法(improved multi-objective gravitational search algorithm,IMOGSA)。利用该算法对FACTS设备的位置及容量组合进行优化,得到包含对应组合的可用输电能力和投资费用信息的Pareto解集,并采用模糊满意度方法对所得Pareto解集进行分析,选出兼容性最好的解。在IEEE-14节点系统中对所提出的方法进行了验证,并和多目标引力搜索算法、多目标粒子群算法进行对比,结果表明改进多目标引力搜索优化算法优于后2种算法,是FACTS设备选址定容的首选。
关键词(KeyWords): 柔性交流输电系统;选址定容;改进的多目标引力搜索算法;变焦佳点集;种群熵;Pareto解集
基金项目(Foundation): 国家科技支撑计划项目(2013BAA02B00)~~
作者(Author): 上官海洋;向铁元;张巍;殷杰;崔若涵;
Email:
DOI: 10.13335/j.1000-3673.pst.2014.08.027
参考文献(References):
- [1]黄柳强,郭剑波,徐式蕴,等.适用于多工况的多FACTS广域协调控制研究[J].电力系统保护与控制,2013,41(18):1-8.Huang Liuqiang,Guo Jianbo,Xu Shiyun,et al.Wide-area multi-FACTS coordinated control strategy for multiple load cases[J].Power System Protection and Control,2013,41(18):1-8(in Chinese).
- [2]左玉玺,王雅婷,邢琳,等.西北750 kV电网大容量新型FACTS设备应用研究[J].电网技术,2013,37(8):2349-2354.Zuo Yuxi,Wang Yating,Xing Lin,et al.Applied research on new types of high capacity FACTS devices in northwest 750 kV power grid[J].Power System Technology,2013,37(8):2349-2354(in Chinese).
- [3]Wibowo R S,Yorino N,Eghbal M,et al.FACTS devices allocation with control coordination considering congestion relief and voltage stability[J].IEEE Transactions on Power Systems,2011,26(4):2302-2310.
- [4]Xinghao F,Chow J H,Xia J,et al.Sensitivity methods in the dispatch and siting of FACTS controllers[J].IEEE Transactions on Power Systems,2009,24(2):713-720.
- [5]张健,冀瑞芳,李国庆.TCSC优化配置提高可用输电能力的研究[J].电力系统保护与控制,2012,40(1):23-28.Zhang Jian,Ji Ruifang,Li Guoqing.Study of enhancement of available transfer capability using TCSC optimal allocation[J].Power System Protection and Control,2012,40(1):23-28(in Chinese).
- [6]Ya-Chin C.Multi-objective optimal SVC installation for power system loading margin improvement[J].IEEE Transactions on Power Systems,2012,27(2):984-992.
- [7]Gitizadeh M,Khalilnezhad H,Hedayatzadeh R.TCSC allocation in power systems considering switching loss using MOABC algorithm[J].Electrical Engineering(Archiv fur Elektrotechnik),2013,95(2):73-85.
- [8]赵渊,董力,谢开贵.FACTS元件的可靠性成本/效益分析及其优化配置模型研究[J].电力系统保护与控制,2012,40(1):107-114.Zhao Yuan,Dong Li,Xie Kaigui.Research on optimal placement of FACTS devices based on reliability cost/benefits analysis[J].Power System Protection and Control,2012,40(1):107-114(in Chinese).
- [9]张晓辉,董新华.含风电场多目标低碳电力系统动态经济调度研究[J].电网技术,2013,37(1):24-31.Zhang Xiaohui,Dong Xinhua.Research on multi-objective scheduling for low-carbon power system with wind farms[J].Power System Technology,2013,37(1):24-31(in Chinese).
- [10]刘刚,彭春华,相龙阳.采用改进型多目标粒子群算法的电力系统环境经济调度[J].电网技术,2011,35(7):139-144.Liu Gang,Peng Chunhua,Xiang Longyang.Economic environmental dispatch using improved multi-objective particle swarm optimization[J].Power System Technology,2011,35(7):139-144(in Chinese).
- [11]罗毅,刘明亮.计及风险备用约束的孤网系统环保经济调度[J].电网技术,2013,37(10):2705-2711.Luo Yi,Liu Mingliang.Research on environmental and economic dispatch for isolated microgrid system taken risk reserve constraints into account[J].Power System Technology,2013,37(10):2705-2711(in Chinese).
- [12]李智欢,段献忠.多目标进化算法求解无功优化问题的对比分析[J].中国电机工程学报,2010,30(10):57-65.Li Zhihuan,Duan Xianzhong.Comparison and analysis of multiobjective evolutionary algorithm for reactive power optimization[J].Proceedings of the CSEE,2010,30(10):57-65(in Chinese).
- [13]Taher S A,Amooshahi M K.New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems[J].International Journal of Electrical Power&Energy Systems,2012,43(1):899-909.
- [14]李茜,刘天琪,李兴源.大规模风电接入的电力系统优化调度新方法[J].电网技术,2013,37(3):733-739.Li Qian,Liu Tianqi,Li Xingyuan.A new optimized dispatch method for power grid connected with large-scale wind farms[J].Power System Technology,2013,37(3):733-739(in Chinese).
- [15]黄柳强,郭剑波,孙华东,等.基于智能计算的多FACTS协调配置[J].电网技术,2013,37(4):942-946.Huang Liuqiang,Guo Jianbo,Sun Huadong,et al.Intelligent computation based coordinated configuration of multi-FACTS devices[J].Power System Technology,2013,37(4):942-946(in Chinese).
- [16]王锡凡,方万良,杜正春.现代电力系统分析[M].北京:科学出版社,2012:209-210.
- [17]杨晓嵩.含柔性交流输电设备的电网可靠性评估及优化配置模型研究[D].重庆:重庆大学.2012.
- [18]Cai L J,Erlich I,Stamtsis G.Optimal choice and allocation of FACTS devices in deregulated electricity market using genetic algorithms[C]//Power Systems Conference and Exposition.2004:201-207.
- [19]Ali A,Mehdi A.A multi-objective gravitational search algorithm based approach of power system stability enhancement with UPFC[J].Journal of Central South University,2013,20(6):1536-1544.
- [20]Rashedi E,Nezamabadi-Pour H,Saryazdi S.GSA:a gravitational search algorithm[J].Information Sciences,2009,179(13):2232-2248.
- [21]陈义雄,梁昔明,黄亚飞.一种改进的混沌量子粒子群优化算法[J].计算机工程,2013,39(8):253-256.Chen Yixiong,Liang Ximing,Huang Yafei.An improved chaos quantum particle swarm optimization algorithm[J].Computer Engineering,2013,39(8):253-256(in Chinese).
- [22]汤可宗,肖绚,贾建华,等.基于离散式多样性评价策略的自适应粒子群优化算法[J].南京理工大学学报,2013,37(3):344-349.Tang Kezong,Xiao Xuan,Jia Jianhua,et al.Adaptive particle swarm optimization algorithm based on discrete estimate strategy of diversity[J].Journal of Nanjing University of Science and Technology,2013,37(3):344-349(in Chinese).
- [23]谢昶.电网检修计划优化编制方法研究及应用[D].北京:华北电力大学,2013.
- [24]Iyambo P K,Tzoneva R.Transient stability analysis of the IEEE14-bus electric power system[C]//AFRICON.2007:1-9.
- [25]颜楠楠,傅正财.基于多目标粒子群优化算法的UPFC协调控制[J].电力系统保护与控制,2010,38(8):43-48.Yan Nannan,Fu Zhengcai.Coordinated design of UPFC based on multi-objective particle swarm optimization[J].Power System Protection and Control,2010,38(8):43-48(in Chinese).
- [26]李倩,宫俊,唐加福.多目标粒子群算法在交叉培训规划中的应用[J].控制理论与应用,2013,30(1):17-22.Li Qian,Gong Jun,Tang Jiafu.Multi-objective particle swarm optimization algorithm for cross-training programming[J].Control Theory&Applications,2013,30(1):17-22(in Chinese).
- [27]刘文颖,谢昶,文晶,等.基于小生境多目标粒子群算法的输电网检修计划优化[J].中国电机工程学报,2013,33(4):141-148.Liu Wenying,Xie Chang,Wen Jing,et al.Optimization of transmission network maintenance scheduling based on niche multi-objective particle swarm algorithm[J].Proceedings of the CSEE,2013,33(4):141-148(in Chinese).