基于二进制粒子群算法的交直流混合配电网故障恢复方法
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摘要
针对交直流混合配电网特殊的网架结构和电气特性,构建交直流混合配电网故障恢复模型。所提出的模型以故障恢复综合满意度指标为目标函数,并计及潮流约束、节点电压约束、支路传输约束和网络辐射状约束等约束。对所建立的模型设计两阶段优化求解流程,第一阶段采用二进制粒子群算法进行求解,第二阶段采用粒子群算法进行求解。最后通过一个算例表明,交直流混合配电网故障位置对故障恢复策略以及故障恢复综合满意度指标有着较大影响,同时所提出的模型适用于交直流混合配电网故障恢复问题。
According to the special grid structure and electrical characteristics of AC/DC hybrid distribution network, a fault recovery model of AC/DC hybrid distribution network is constructed. The proposed model takes the fault recovery comprehensive satisfaction index as the objective function, while considering the power flow constraint, the node voltage constraints, the branch transmission constraints, the network radiation constraint, and so on. A two-stage optimization process is designed to solve the established model. In the first stage, the binary particle swarm optimization is used to solve the problem, then the second stage optimization is solved by particle swarm optimization. Finally, an example shows that the fault location of AC/DC hybrid distribution network has a great influence on the fault recovery strategy and the fault recovery comprehensive satisfaction index, and it is applicable to the fault recovery of AC/DC hybrid distribution network.
According to the special grid structure and electrical characteristics of AC/DC hybrid distribution network, a fault recovery model of AC/DC hybrid distribution network is constructed. The proposed model takes the fault recovery comprehensive satisfaction index as the objective function, while considering the power flow constraint, the node voltage constraints, the branch transmission constraints, the network radiation constraint, and so on. A two-stage optimization process is designed to solve the established model. In the first stage, the binary particle swarm optimization is used to solve the problem, then the second stage optimization is solved by particle swarm optimization. Finally, an example shows that the fault location of AC/DC hybrid distribution network has a great influence on the fault recovery strategy and the fault recovery comprehensive satisfaction index, and it is applicable to the fault recovery of AC/DC hybrid distribution network.
引文
[1]吴志程,江智军,杨晓辉.一种基于功率闭环控制的改进全局MPPT方法[J].电力系统保护与控制,2018,46(1):57-62.WU Zhicheng,JIANG Zhijun,YANG Xiaohui.An improved global MPPT method based on power closed loop control[J].Power System Protection and Control,2018,46(1):57-62.
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[15]李兴,杨智斌,颜远,等.考虑换流站损耗特性的交直流系统多目标无功优化控制[J].电力系统保护与控制,2017,45(9):119-125.LI Xing,YANG Zhibin,YAN Yuan,et al.Multi-objective reactive power optimal control of AC-DC systems including power loss characteristics of converter stations[J].Power System Protection and Control,2017,45(9):119-125.
[16]郑伟,陈仕彬,梁福波,等.基于PSO-PSA的光伏系统最大功率点跟踪技术[J].热力发电,2018,47(2):76-84.ZHENG Wei,CHEN Shibin,LIANG Fubo,et al.Maximum power point tracking technology for photovoltaic systems based on PSO-PSA[J].Thermal Power Generation,2018,47(2):76-84.
[17]敖鑫,王淳,蔡恒,等.计及接地支路的直流潮流算法[J].电力系统保护与控制,2017,45(16):8-15.AO Xin,WANG Chun,CAI Heng,et al.DC power flow algorithm considering grounding branches[J].Power System Protection and Control,2017,45(16):8-15.
[18]司徒友,吴杰康,郭清元,等.基于免疫PSO的新能源配电网无功多目标模糊优化[J].中国电力,2018,51(2):90-98.SITU You,WU Jiekang,GUO Qingyuan,et al.Multiobjective fuzzy optimization for reactive power of distribution network based on immune particle swarm optimization algorithm[J].Electric Power,2018,51(2):90-98.
[19]赵越,蒙毅,李仁义.基于粒子群优化算法分析约束条件对配煤最优价格的影响[J].热力发电,2017,46(12):99-104.ZHAO Yue,MENG Yi,LI Renyi.Influence of constraints on optimal price of blending coal:by particle swarm optimization algorithm[J].Thermal Power Generation,2017,46(12):99-104.
[20]康健,靳斌,段秀娟,等.基于贝叶斯-粒子群算法的微电网优化运行[J].电力系统保护与控制,2018,46(12):32-41.KANG Jian,JIN Bin,DUAN Xiujuan,et al.Optimal operation of microgrid based on Bayesian-PSO algorithm[J].Power System Protection and Control,2018,46(12):32-41.
[21]王守相,陈思佳,谢颂果.考虑安全约束的交直流配电网储能与换流站协调经济调度[J].电力系统自动化,2017,41(11):85-91.WANG Shouxiang,CHEN Sijia,XIE Songguo.Securityconstrained coordinated economic dispatch of energy storage systems and converter stations for AC/DCdistribution networks[J].Automation of Electric Power Systems,2017,41(11):85-91.
[2]王艳松,孙明鸿.含微网配电网的综合优化规划研究[J].中国电力,2018,51(2):118-124.WANG Yansong,SUN Minghong.Research on comprehensive optimization for distribution network with micro-grid[J].Electric Power,2018,51(2):118-124.
[3]庞清乐,高厚磊,李天友.基于负荷均衡的智能配电网故障恢复[J].电网技术,2013,37(2):342-348.PANG Qingle,GAO Houlei,LI Tianyou.Load balancing based fault service restoration for smart distribution grid[J].Power System Technology,2013,37(2):342-348.
[4]任洪波,邱留良,吴琼,等.分布式能源系统优化与设计综述[J].中国电力,2017,50(7):49-55.REN Hongbo,QIU Liuliang,WU Qiong,et al.A review of optimization planning and designing of distributed energy systems[J].Electric Power,2017,50(7):49-55.
[5]王增平,姚玉海,郭昆亚,等.基于等级偏好优序法和切负荷的配电网故障恢复[J].电工技术学报,2015,30(20):185-192.WANG Zengping,YAO Yuhai,GUO Kunya,et al.Distribution network service restoration based on rank preference optimal and load shedding[J].Transactions of China Electrotechnical Society,2015,30(20):185-192.
[6]陈昕玥,唐巍,陈禹,等.基于机会约束规划含光伏发电的配电网故障恢复[J].电网技术,2014,38(1):99-106.CHEN Xinyue,TANG Wei,CHEN Yu,et al.Chance constrained programming based fault recovery of distribution network containing photovoltaic generations[J].Power System Technology,2014,38(1):99-106.
[7]臧天磊,钟佳辰,何正友,等.基于启发式规则与熵权理论的配电网故障恢复[J].电网技术,2012,36(5):251-257.ZANG Tianlei,ZHONG Jiachen,HE Zhengyou,et al.Service restoration of distribution network based on heuristic rules and entropy weight[J].Power System Technology,2012,36(5):251-257.
[8]吴文传,张伯明.基于待恢复树切割的配电网故障恢复实时算法[J].电力系统自动化,2003,27(12):50-54.WU Wenchuan,ZHANG Boming.A candidate restoring tree cutting based algorithm for real-time distribution system restoration[J].Automation of Electric Power Systems,2003,27(12):50-54.
[9]王守相,李晓静,肖朝霞,等.含分布式电源的配电网供电恢复的多代理方法[J].电力系统自动化,2007,31(10):61-65,81.WANG Shouxiang,LI Xiaojing,XIAO Chaoxia,et al.Multi-agent approach for service restoration of distribution system containing distributed generations[J].Automation of Electric Power Systems,2007,31(10):61-65,81.
[10]IRVING M R,LUAN W P,DANIEL J S.Supply restoration in distribution networks using a genetic algorithm[J].International Journal of Electrical Power and Energy Systems,2002,24(6):447-457.
[11]巩伟峥,房鑫炎.基于混合编码方式的配电网故障恢复算法研究[J].电力系统保护与控制,2012,40(6):105-108.GONG Weizheng,FANG Xinyan.Research of distribution system service restoration algorithm based on hybrid encoding[J].Power System Protection and Control,2012,40(6):105-108.
[12]SHIN D J,KIM J O,KIM T K.Optimal service restoration and reconfiguration of network using genetic-Tabu algorithm[J].Electric Power Systems Research,2004,71(2):145-152.
[13]张钊,封亚琴.一种新型的配电网供电恢复重构寻优算法[J].电网技术,2008,32(7):51-55,65.ZHANG Zhao,FENG Yaqin.A novel optimization reconfiguration algorithm for power supply restoration of distribution network[J].Power System Technology,2008,32(7):51-55,65.
[14]杨丽君,刘建超,曹良晶,等.基于黑板模型的配电网故障恢复多代理协作机制设计[J].电力系统自动化,2012,36(6):85-89.YANG Lijun,LIU Jianchao,CAO Liangjing,et al.Multi-agent coordinated mechanism design of distribution network fault restoration based on blackboard model[J].Automation of Electric Power Systems,2012,36(6):85-89.
[15]李兴,杨智斌,颜远,等.考虑换流站损耗特性的交直流系统多目标无功优化控制[J].电力系统保护与控制,2017,45(9):119-125.LI Xing,YANG Zhibin,YAN Yuan,et al.Multi-objective reactive power optimal control of AC-DC systems including power loss characteristics of converter stations[J].Power System Protection and Control,2017,45(9):119-125.
[16]郑伟,陈仕彬,梁福波,等.基于PSO-PSA的光伏系统最大功率点跟踪技术[J].热力发电,2018,47(2):76-84.ZHENG Wei,CHEN Shibin,LIANG Fubo,et al.Maximum power point tracking technology for photovoltaic systems based on PSO-PSA[J].Thermal Power Generation,2018,47(2):76-84.
[17]敖鑫,王淳,蔡恒,等.计及接地支路的直流潮流算法[J].电力系统保护与控制,2017,45(16):8-15.AO Xin,WANG Chun,CAI Heng,et al.DC power flow algorithm considering grounding branches[J].Power System Protection and Control,2017,45(16):8-15.
[18]司徒友,吴杰康,郭清元,等.基于免疫PSO的新能源配电网无功多目标模糊优化[J].中国电力,2018,51(2):90-98.SITU You,WU Jiekang,GUO Qingyuan,et al.Multiobjective fuzzy optimization for reactive power of distribution network based on immune particle swarm optimization algorithm[J].Electric Power,2018,51(2):90-98.
[19]赵越,蒙毅,李仁义.基于粒子群优化算法分析约束条件对配煤最优价格的影响[J].热力发电,2017,46(12):99-104.ZHAO Yue,MENG Yi,LI Renyi.Influence of constraints on optimal price of blending coal:by particle swarm optimization algorithm[J].Thermal Power Generation,2017,46(12):99-104.
[20]康健,靳斌,段秀娟,等.基于贝叶斯-粒子群算法的微电网优化运行[J].电力系统保护与控制,2018,46(12):32-41.KANG Jian,JIN Bin,DUAN Xiujuan,et al.Optimal operation of microgrid based on Bayesian-PSO algorithm[J].Power System Protection and Control,2018,46(12):32-41.
[21]王守相,陈思佳,谢颂果.考虑安全约束的交直流配电网储能与换流站协调经济调度[J].电力系统自动化,2017,41(11):85-91.WANG Shouxiang,CHEN Sijia,XIE Songguo.Securityconstrained coordinated economic dispatch of energy storage systems and converter stations for AC/DCdistribution networks[J].Automation of Electric Power Systems,2017,41(11):85-91.