考虑负荷和分布式电源时变性的配电网多目标动态重构和DG调度
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摘要
实际配电网中用户负荷需求和分布式电源的出力上限在不断变换,故针对单一时间断面的静态重构和分布式电源(DG)调度无法满足配电网实际运行要求这一问题。建立以网损重构成本、电压指标和弃电率为优化目标,考虑负荷和DG时变性的配电网多目标协同优化模型,对配电网动态重构和DG调控联立优化求解。并为重构问题和出力调控问题分别设计基于协同进化的NSGA-II和MOCLPSO算法进行求解。基于美国PE&G 69节点配网系统设计多个仿真算例进行分析,结果表明在主动配电网(ADN)中结合动态重构和DG调控措施能实现两者的优势互补,有效提升配电网的运行水平,并验证了所提方法的有效性。
In view of the dynamic demand for power load and the constantly changing upper output limit for distributed generation in distribution network, the static network reconfiguration and DG output control in a single time section can not meet the requirements of actual operation of distribution network. Consequently, we proposed a multi-objective and co-evolution model considering the time-varying characteristic of load and distributed generation output, with the index of active power loss and reconfiguration cost, voltage index and discard rate, to synchronously deal with the problems of dynamic reconstruction and regulation for distributed generation in distribution network. The CE-NSGA-II algorithm and CE-MOCLPSO algorithm were respectively designed for the problem of dynamic reconstruction and distributed generation output in distribution network. Based on the example of PG&E 69 nodes distribution network in the United States,several simulation experiments were designed for analysis. Simulation results indicate that it can effectively improve the operation level of distribution network combined with ADN dynamic reconstruction and control measures of distribution generation output, and verify the effectiveness of the proposed method.
In view of the dynamic demand for power load and the constantly changing upper output limit for distributed generation in distribution network, the static network reconfiguration and DG output control in a single time section can not meet the requirements of actual operation of distribution network. Consequently, we proposed a multi-objective and co-evolution model considering the time-varying characteristic of load and distributed generation output, with the index of active power loss and reconfiguration cost, voltage index and discard rate, to synchronously deal with the problems of dynamic reconstruction and regulation for distributed generation in distribution network. The CE-NSGA-II algorithm and CE-MOCLPSO algorithm were respectively designed for the problem of dynamic reconstruction and distributed generation output in distribution network. Based on the example of PG&E 69 nodes distribution network in the United States,several simulation experiments were designed for analysis. Simulation results indicate that it can effectively improve the operation level of distribution network combined with ADN dynamic reconstruction and control measures of distribution generation output, and verify the effectiveness of the proposed method.
引文
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[15]李磊,王俊熙,贺易,等.基于K-means聚类粒子群算法的多点PV-DG日前分配计划[J].高电压技术,2017,43(4):1263-1270.LI Lei,WANG Junxi,HE Yi,et al.Particle swarm optimization based on k-means cluster for day-ahead allocation plan of multiple photovoltaic distributed generation[J].High Voltage Engineering,2017,43(4):1263-1270.
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[18]LIPKUS A H.A proof of the triangle inequality for the Tanimoto distance[J].Journal of Mathematical Chemistry,1999,26(1):263-265.
[19]冯雪平,宋晓辉,梁英,等.基于最小生成树及改进遗传算法的含分布式电源配电网孤岛划分方法[J].高电压技术,2015,41(10):3470-3478.FENG Xueping,SONG Xiaohui,LIANG Ying,et al.Islanding method based on minimum spanning tree and improved genetic algorithm for distribution system with DGs[J].High Voltage Engineering,2015,41(10):3470-3478.
[20]文娟,谭阳红,雷可君.基于量子粒子群算法多目标优化的配电网动态重构[J].电力系统保护与控制,2015,43(16):73-78.WEN Juan,TAN Yanghong,LEI Kejun.Multi-objective optimization of distribution network dynamic reconfiguration based on integer coded quantum particle swarm optimization algorithm[J].Power System Protection and Control,2015,43(16):73-78.
[2]易海川,张彼德,王海颖,等.提高DG接纳能力的配电网动态重构方法[J].电网技术,2016,40(5):1431-1436.YI Haichuan,ZHANG Bide,WANG Haiying,et al.Distribution network dynamic reconfiguration method for improving distribution network’s ability of accepting DG[J].Power System Technology,2016,40(5):1431-1436.
[3]丛鹏伟,唐巍,张璐,等.基于机会约束规划考虑DG与负荷多状态的配电网重构[J].电网技术,2013,37(9):2573-2579.CONG Pengwei,TANG Wei,ZHANG Lu,et al.Chance constrained programming based distribution network reconfiguration considering multi-states of distributed generation and load[J].Power System Technology,2013,37(9):2573-2579.
[4]周慧芝,唐飞,刘涤尘,等.考虑负荷时变性的主动配电网动态重构和DG动态调控策略[J].电网技术,2016,40(8):2423-2429.ZHOU Huizhi,TANG Fei,LIU Dichen,et al.Active distribution network dynamic reconfiguration and DG dynamic control strategy considering time-variant load[J].Power System Technology,2016,40(8):2423-2429.
[5]董如良,杨强,颜文俊.多智能体协同寻优的主动配网动态拓扑重构[J].浙江大学学报工学版,2015,49(19):1982-1989.DONG Ruliang,YANG Qiang,YAN Wenjun.MAS-based cooperative optimization of reconfiguration in active power distribution networks[J].Journal of Zhejiang University(Engineering Science),2015,49(19):1982-1989.
[6]赵静翔,牛焕娜,王钰竹.基于信息熵时段划分的主动配电网动态重构[J].电网技术,2016,41(2):402-408.ZHAO Jingxiang,NIU Huanna,WANG Yuzhu.Dynamic reconfiguration of active distribution network based on information entropy of time intervals[J].Power System Technology,2016,41(2):402-408.
[7]王淳,高元海.采用最优模糊C均值聚类和改进化学反应算法的配电网络动态重构[J].中国电机工程学报,2014,34(10):1682-1691.WANG Chun,GAO Yuanhai.Dynamic reconfiguration of distribution network based on optimal fuzzy c-means clustering and improved chemical reaction optimization[J].Proceedings of the CSEE,2014,34(10):1682-1691.
[8]王薪苹,卫志农,孙国强,等.计及分布式电源和负荷不确定性的多目标配网重构[J].电力自动化设备,2016,36(6):116-121.WANG Xinping,WEI Zhinong,SUN Guoqiang,et al.Multi-objective distribution network reconfiguration considering uncertainties of distributed generation and load[J].Electric Power Automation Equipment,2016,36(6):116-121.
[9]彭春华,于蓉,孙惠娟.基于K-均值聚类多场景时序特性分析的分布式电源多目标规划[J].电力自动化设备,2015,35(10):58-65.PENG Chunhua,YU Rong,SUN Huijuan.Multi-objective DG planning based on K-means clustering and multi-scenario timing characteristics analysis[J].Electric Power Automation Equipment,2015,35(10):58-65.
[10]李亮,唐巍,白牧可,等.考虑时序特性的多目标分布式电源选址定容规划[J].电力系统自动化,2013,37(3):58-63.LI Liang,TANG Wei,BAI Muke,et al.Multi-objective locating and sizing of distributed generators based on time-sequence characteristics[J].Automation of Electric Power Systems,2013,37(3):58-63.
[11]栗然,马慧卓,祝晋尧,等.分布式电源接入配电网多目标优化规划[J].电力自动化设备,2014,34(1):6-13.LI Ran,MA Huizhuo,ZHU Jinyao,et al.Multi-objective optimization for DG integration into distribution system[J].Electric Power Automation Equipment,2014,34(1):6-13.
[12]王建勋,吕群芳,刘会金,等.含分布式电源的配电网潮流快速直接算法[J].电力自动化设备,2011,31(2):17-21.WANG Jianxun,LüQunfang,LIU Huijin,et al.Fast and direct power flow algorithm for distribution network with distributed generation[J].Electric Power Automation Equipment,2011,31(2):17-21.
[13]POTTER M A,JONG K A D.A cooperative coevolutionary approach to function optimization[C]∥International Conference on Parallel Problem Solving from Nature.Springer,Berlin,Germany:Heidelberg,1994:249-257.
[14]黄新波,王玉鑫,朱永灿,等.基于遗传算法与模糊逻辑融合的线路覆冰预测[J].高电压技术,2016,42(4):1228-1235.HUANG Xinbo,WANG Yuxin,ZHU Yongcan,et al.Icing forecast of transmission line based on genetic algorithm and fuzzy logic[J].High Voltage Engineering,2016,42(4):1228-1235.
[15]李磊,王俊熙,贺易,等.基于K-means聚类粒子群算法的多点PV-DG日前分配计划[J].高电压技术,2017,43(4):1263-1270.LI Lei,WANG Junxi,HE Yi,et al.Particle swarm optimization based on k-means cluster for day-ahead allocation plan of multiple photovoltaic distributed generation[J].High Voltage Engineering,2017,43(4):1263-1270.
[16]HUANG V L,SUGANTHAN P N,LIANG J J.Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems[J].International Journal of Intelligent Systems,2006,21(2):209-226.
[17]赵劲帅,邱晓燕,马菁曼,等.基于模糊聚类分析与模型识别的微电网多目标优化方法[J].电网技术,2016,40(8):2316-2323.ZHAO Jinshuai,QIU Xiaoyan,MA Jingman,et al.Multi-objective optimization method of microgrid based on fuzzy clustering analysis and model recognition[J].Power System Technology,2016,40(8):2316-2323.
[18]LIPKUS A H.A proof of the triangle inequality for the Tanimoto distance[J].Journal of Mathematical Chemistry,1999,26(1):263-265.
[19]冯雪平,宋晓辉,梁英,等.基于最小生成树及改进遗传算法的含分布式电源配电网孤岛划分方法[J].高电压技术,2015,41(10):3470-3478.FENG Xueping,SONG Xiaohui,LIANG Ying,et al.Islanding method based on minimum spanning tree and improved genetic algorithm for distribution system with DGs[J].High Voltage Engineering,2015,41(10):3470-3478.
[20]文娟,谭阳红,雷可君.基于量子粒子群算法多目标优化的配电网动态重构[J].电力系统保护与控制,2015,43(16):73-78.WEN Juan,TAN Yanghong,LEI Kejun.Multi-objective optimization of distribution network dynamic reconfiguration based on integer coded quantum particle swarm optimization algorithm[J].Power System Protection and Control,2015,43(16):73-78.