基于集群划分的高渗透率分布式系统无功优化
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摘要
可再生能源在电力系统的渗透率不断增长,大规模分布式电源的接入对电力系统的优化调度带来新的挑战。在考虑分布式电源大规模接入的基础上,对电力系统进行集群划分和无功优化研究。首先引入改进的电气距离的概念,以此作为聚类算法的距离量度,应用谱聚类方法,将含高渗透率分布式可再生能源系统划分为若干亚群落,并确定各集群内关键节点。再以网损和电压波动最小为优化目标,调节关键节点处光伏逆变器的无功功率,达到减小网损和稳定电压输出的目的。为求解所建立的双目标无功优化问题,提出基于改进粒子群优化算法的智能调压策略,对多个亚群落进行无功优化。将集群划分方法和无功优化策略应用于IEEE 33节点标准系统,提高了节点电压稳定性,降低了网损。针对大规模分布式能源系统,进一步提出快速智能调压策略,应用于安徽省金寨县某台区实际系统,得到良好控制效果,且在调节时间、运行成本、投入成本方面均有大幅削减。
With the increase of distributed generator(DG)penetration in the power system,new challenges have been taken to the optimal operation of distributed system in large scale.The reactive power optimization is analyzed on the basis of cluster division with the consideration of DG integration.The modified electrical distance is introduced as the distance measurement in clustering algorithm.The spectral clustering method is applied to divide the high-denetration distributed renewable energy system into several sub-communities and determine the key nodes in each cluster.With the minimum network loss and voltage fluctuation as the optimization goal,the reactive power of the photovoltaic inverter at the key node is adjusted to reduce the network loss and stabilize the voltage output.In order to solve the problem of dual-objective reactive power optimization,an intelligent voltage regulation strategy based on improved particle swarm optimization algorithm is proposed to optimize reactive power for multiple sub-communities.The cluster division method and the reactive power optimization strategy are applied to the IEEE 33-bus standard system,which improves the node voltage stability and reduces the network loss.Aiming at the largescale distributed energy system,a fast intelligent voltage regulation strategy is further proposed,which is applied to the actual system of a certain district in Jinzhai County,Anhui Province,and has good control effect,and has been greatly reduced in terms of adjustment time,operation cost and input cost.
With the increase of distributed generator(DG)penetration in the power system,new challenges have been taken to the optimal operation of distributed system in large scale.The reactive power optimization is analyzed on the basis of cluster division with the consideration of DG integration.The modified electrical distance is introduced as the distance measurement in clustering algorithm.The spectral clustering method is applied to divide the high-denetration distributed renewable energy system into several sub-communities and determine the key nodes in each cluster.With the minimum network loss and voltage fluctuation as the optimization goal,the reactive power of the photovoltaic inverter at the key node is adjusted to reduce the network loss and stabilize the voltage output.In order to solve the problem of dual-objective reactive power optimization,an intelligent voltage regulation strategy based on improved particle swarm optimization algorithm is proposed to optimize reactive power for multiple sub-communities.The cluster division method and the reactive power optimization strategy are applied to the IEEE 33-bus standard system,which improves the node voltage stability and reduces the network loss.Aiming at the largescale distributed energy system,a fast intelligent voltage regulation strategy is further proposed,which is applied to the actual system of a certain district in Jinzhai County,Anhui Province,and has good control effect,and has been greatly reduced in terms of adjustment time,operation cost and input cost.
引文
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[7]刘双,张建周,王汉林,等.考虑多无功源的光伏电站两阶段无功电压协调控制策略[J].电力系统自动化,2017,41(11):120-125.DOI:10.7500/AEPS20160708004.LIU Shuang,ZHANG Jianzhou,WANG Hanlin,et al.Two stage reactive power and voltage coordinated control strategy for photovoltaic power station considering multiple reactive power sources[J].Automation of Electric Power Systems,2017,41(11):120-125.DOI:10.7500/AEPS20160708004.
[8]CARERI F,GENESI C,MARANNINO P,et al.Definition of a zonal reactive power market based on the adoption of a hierarchical voltage control[C]//7th International Conference on the European Energy Market,June 23-25,2010,Madrid,Spain:1-7.
[9]KANKANALA P,SRIVASTAVA S C,SRIVASTAVA A K,et al.Optimal control of voltage and power in a multi-zonal MVDC shipboard power system[J].IEEE Transactions on Power Systems,2009,27(2):642-650.
[10]李鹏,于航,夏曼,等.分布式光伏集群分层多模式无功控制策略[J].电网技术,2016,40(10):3038-3044.LI Peng,YU Hang,XIA Man,et al.A hierarchical multimode var control strategy for grid-connected PV clutters[J].Power System Technology,2016,40(10):3038-3044.
[11]朱俊澎,顾伟,张韩旦,等.考虑网络动态重构的分布式电源选址定容优化方法[J].电力系统自动化,2018,42(5):1-9.DOI:10.7500/AEPS20170605016.ZHU Junpeng,GU Wei,ZHANG Handan,et al.Optimal allocation of distributed generators considering dynamic network reconfiguration[J].Automation of Electric Power Systems,2018,42(5):111-119.DOI:10.7500/AEPS20170605016.
[12]田园,汪可友,李国杰,等.计及风电相关性的二阶锥动态随机最优潮流[J].电力系统自动化,2018,42(5):41-47.DOI:10.7500/AEPS20170605003.TIAN Yuan,WANG Keyou,LI Guojie,et al.Dynamic stochastic optimal power flow based on second-order cone programming considering wind power correlation[J].Automation of Electric Power Systems,2018,42(5):41-47.DOI:10.7500/AEPS20170605003.
[13]YANG S,WANG W,LIU C,et al.Optimal reactive power dispatch of wind power plant cluster considering static voltage stability for low-carbon power system[J].Journal of Modern Power Systems and Clean Energy,2015,3(1):114-122.
[14]SAMIMI A,NIKZAD M.Complete active-reactive power resource scheduling of smart distribution system with high penetration of distributed energy resources[J].Journal of Modern Power Systems and Clean Energy,2017,5(6):863-875.
[15]谭玉东,李欣然,蔡晔,等.基于电气距离的复杂电网关键节点识别[J].中国电机工程学报,2014,34(1):146-152.TAN Yudong,LI Xinran,CAI Ye,et al.Critical node identification for complex power grid based on electrical distance[J].Proceedings of the CSEE,2014,34(1):146-152.
[16]陈厚合,运奕竹,邢文洋,等.基于聚类分析方法的电力系统负荷节点分区策略[J].电力系统保护与控制,2013,41(12):47-53.CHEN Houhe,YUN Yizhu,XING Wenyang,et al.A novel strategy of network partitioning for load node in power systems using spectral clustering[J].Power System Protection and Control,2013,41(12):47-53.
[17]颜伟,王芳,唐文左,等.基于电源分区与短路阻抗距离的电压无功分区方法[J].电力系统保护与控制,2013,41(7):109-115.YAN Wei,WANG Fang,TANG Wenzuo,et al.Network partition for reactive power/voltage control based on power sources clustering and short-circuit impedance distance[J].Power System Protection and Control,2013,41(7):109-115.
[18]COTILLA-SANCHEZ E,HINES P D H,BARROWS C,et al.Multi-attribute partitioning of power networks based on electrical distance[J].IEEE Transactions on Power Systems,2013,28(4):4979-4987.
[19]肖传亮,赵波,周金辉,等.配电网中基于网络分区的高比例分布式光伏集群电压控制[J].电力系统自动化,2017,41(21):147-155.DOI:10.7500/AEPS20170101002.XIAO Chuanliang,ZHAO Bo,ZHOU Jinhui,et al.Network partition based cluster voltage control of high proportion distributed photovoltaic systems in distribution networks[J].Automation of Electric Power Systems,2017,41(21):147-155.DOI:10.7500/AEPS20170101002.
[20]孟庭如,邹贵彬,许春华,等.一种分区协调控制的有源配电网调压方法[J].中国电机工程学报,2017,37(10):2852-2860.MENG Tingru,ZOU Guibin,XU Chunhua,et al.A voltage regulation method based on district-dividing coordinated control for active distribution network[J].Proceedings of the CSEE,2017,37(10):2852-2860.
[21]BAHRAMIPANAH M,CHERKAOUI R,PAOLONE M.Decentralized voltage control of clustered active distribution network by means of energy storage systems[J].Electric Power Systems Research,2016,136:370-382.
[22]JIA Y,XU Z.A direct solution to bi-objective partitioning problem in electric power networks[J].IEEE Transactions on Power Systems,2017,32(3):2481-2483.
[23]ELRAZAZ Z S.Optimization allocation of reactors for lightload operation[J].IEE Proceeding:Generation,Transmission and Distribution,2001,148(4):350-354
[24]刘科研,盛万兴,李运华.基于改进遗传模拟退火算法的无功优化[J].电网技术,2007,31(3):13-18.LIU keyan,SHENG Wanxing,LI Yunhua.Research on reactive power optimization based on improved genetic simulated annealing algorithm[J].Power System Technology,2007,31(3):13-18.
[25]ZHANG M,CHEN J.Islanding and scheduling of power distribution systems with distributed generation[J].IEEETransactions on Power Systems,2015,30(6):3120-3129.
[26]林俐,潘险险.基于分裂层次半监督谱聚类算法的风电场机群划分方法[J].电力自动化设备,2015,35(2):8-14.LIN Li,PAN Xianxian.Wind turbine grouping based on semisupervised split-hierarchical spectral clustering algorithm for wind farm[J].Electric Power Automation Equipment,2015,35(2):8-14.
[27]周林,平西建,徐森,等.基于谱聚类的聚类集成算法[J].自动化学报,2012,38(8):1335-1342.ZHOU Lin,PING Xijian,XU Sen,et al.Cluster ensemble based on spectral clustering[J].Acta Automatica Sinica,2012,38(8):1335-1342.
[28]JAIN R,KORONIOS A.Innovation in the cluster validating techniques[J].Fuzzy Optimization&Decision Making,2008,7(3):233-241.
[29]庄楚天,吴戈.基于站点爬虫数据的公共自行车系统时空特征分析[J].交通信息与安全,2017,35(3):51-58.ZHUANG Chutian,WU Ge.Spatial-temporal charateristics of a shared bicycle system based on web crawler data[J].Journal of Transport Information and Safety,2017,35(3):51-58.
[30]YANG X S.Nature-inspired metaheuristic algorithms[M].2nd ed.UK:Luniver Press,2010:105-108.
[2]康重庆,姚良忠.高比例可再生能源电力系统的关键科学问题与理论研究框架[J].电力系统自动化,2017,41(9):2-11.DOI:10.7500/AEPS20170120004.KANG Chongqing,YAO Liangzhong.Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J].Automation of Electric Power Systems,2017,41(9):2-11.DOI:10.7500/AEPS20170120004.
[3]VALLEE F,BRUNIEAU G,PIRLOT M,et al.Optimal wind clustering methodology for adequacy evaluation in system generation studies using non-sequential Monte Carlo simulation[J].IEEE Transactions on Power Systems,2011,26(4):2173-2184.
[4]ZHAO Bo,XU Zhicheng,XU Chen,et al.Network partitionbased zonal voltage control for distribution networks with distributed PV systems[J].IEEE Transactions on Smart Grid,2018,9(5):4087-4098.
[5]丁明,王伟胜,王秀丽,等.大规模光伏发电对电力系统影响综述[J].中国电机工程学报,2014,34(1):2-14.DING Ming,WANG Weisheng,WANG Xiuli,et al.A review on the effect of large-scale PV generation on power system[J].Proceedings of the CSEE,2014,34(1):2-14.
[6]刘公博,颜文涛,张文斌,等.含分布式电源的配电网动态无功优化调度方法[J].电力系统自动化,2015,39(15):49-54.DOI:10.7500/AEPS20141013016.LIU Gongbo,YAN Wentao,ZHANG Wenbin,et al.Optimization and dispatching method of dynamic reactive power in distribution network with distributed generators[J].Automation of Electric Power Systems,2015,39(15):49-54.DOI:10.7500/AEPS20141013016.
[7]刘双,张建周,王汉林,等.考虑多无功源的光伏电站两阶段无功电压协调控制策略[J].电力系统自动化,2017,41(11):120-125.DOI:10.7500/AEPS20160708004.LIU Shuang,ZHANG Jianzhou,WANG Hanlin,et al.Two stage reactive power and voltage coordinated control strategy for photovoltaic power station considering multiple reactive power sources[J].Automation of Electric Power Systems,2017,41(11):120-125.DOI:10.7500/AEPS20160708004.
[8]CARERI F,GENESI C,MARANNINO P,et al.Definition of a zonal reactive power market based on the adoption of a hierarchical voltage control[C]//7th International Conference on the European Energy Market,June 23-25,2010,Madrid,Spain:1-7.
[9]KANKANALA P,SRIVASTAVA S C,SRIVASTAVA A K,et al.Optimal control of voltage and power in a multi-zonal MVDC shipboard power system[J].IEEE Transactions on Power Systems,2009,27(2):642-650.
[10]李鹏,于航,夏曼,等.分布式光伏集群分层多模式无功控制策略[J].电网技术,2016,40(10):3038-3044.LI Peng,YU Hang,XIA Man,et al.A hierarchical multimode var control strategy for grid-connected PV clutters[J].Power System Technology,2016,40(10):3038-3044.
[11]朱俊澎,顾伟,张韩旦,等.考虑网络动态重构的分布式电源选址定容优化方法[J].电力系统自动化,2018,42(5):1-9.DOI:10.7500/AEPS20170605016.ZHU Junpeng,GU Wei,ZHANG Handan,et al.Optimal allocation of distributed generators considering dynamic network reconfiguration[J].Automation of Electric Power Systems,2018,42(5):111-119.DOI:10.7500/AEPS20170605016.
[12]田园,汪可友,李国杰,等.计及风电相关性的二阶锥动态随机最优潮流[J].电力系统自动化,2018,42(5):41-47.DOI:10.7500/AEPS20170605003.TIAN Yuan,WANG Keyou,LI Guojie,et al.Dynamic stochastic optimal power flow based on second-order cone programming considering wind power correlation[J].Automation of Electric Power Systems,2018,42(5):41-47.DOI:10.7500/AEPS20170605003.
[13]YANG S,WANG W,LIU C,et al.Optimal reactive power dispatch of wind power plant cluster considering static voltage stability for low-carbon power system[J].Journal of Modern Power Systems and Clean Energy,2015,3(1):114-122.
[14]SAMIMI A,NIKZAD M.Complete active-reactive power resource scheduling of smart distribution system with high penetration of distributed energy resources[J].Journal of Modern Power Systems and Clean Energy,2017,5(6):863-875.
[15]谭玉东,李欣然,蔡晔,等.基于电气距离的复杂电网关键节点识别[J].中国电机工程学报,2014,34(1):146-152.TAN Yudong,LI Xinran,CAI Ye,et al.Critical node identification for complex power grid based on electrical distance[J].Proceedings of the CSEE,2014,34(1):146-152.
[16]陈厚合,运奕竹,邢文洋,等.基于聚类分析方法的电力系统负荷节点分区策略[J].电力系统保护与控制,2013,41(12):47-53.CHEN Houhe,YUN Yizhu,XING Wenyang,et al.A novel strategy of network partitioning for load node in power systems using spectral clustering[J].Power System Protection and Control,2013,41(12):47-53.
[17]颜伟,王芳,唐文左,等.基于电源分区与短路阻抗距离的电压无功分区方法[J].电力系统保护与控制,2013,41(7):109-115.YAN Wei,WANG Fang,TANG Wenzuo,et al.Network partition for reactive power/voltage control based on power sources clustering and short-circuit impedance distance[J].Power System Protection and Control,2013,41(7):109-115.
[18]COTILLA-SANCHEZ E,HINES P D H,BARROWS C,et al.Multi-attribute partitioning of power networks based on electrical distance[J].IEEE Transactions on Power Systems,2013,28(4):4979-4987.
[19]肖传亮,赵波,周金辉,等.配电网中基于网络分区的高比例分布式光伏集群电压控制[J].电力系统自动化,2017,41(21):147-155.DOI:10.7500/AEPS20170101002.XIAO Chuanliang,ZHAO Bo,ZHOU Jinhui,et al.Network partition based cluster voltage control of high proportion distributed photovoltaic systems in distribution networks[J].Automation of Electric Power Systems,2017,41(21):147-155.DOI:10.7500/AEPS20170101002.
[20]孟庭如,邹贵彬,许春华,等.一种分区协调控制的有源配电网调压方法[J].中国电机工程学报,2017,37(10):2852-2860.MENG Tingru,ZOU Guibin,XU Chunhua,et al.A voltage regulation method based on district-dividing coordinated control for active distribution network[J].Proceedings of the CSEE,2017,37(10):2852-2860.
[21]BAHRAMIPANAH M,CHERKAOUI R,PAOLONE M.Decentralized voltage control of clustered active distribution network by means of energy storage systems[J].Electric Power Systems Research,2016,136:370-382.
[22]JIA Y,XU Z.A direct solution to bi-objective partitioning problem in electric power networks[J].IEEE Transactions on Power Systems,2017,32(3):2481-2483.
[23]ELRAZAZ Z S.Optimization allocation of reactors for lightload operation[J].IEE Proceeding:Generation,Transmission and Distribution,2001,148(4):350-354
[24]刘科研,盛万兴,李运华.基于改进遗传模拟退火算法的无功优化[J].电网技术,2007,31(3):13-18.LIU keyan,SHENG Wanxing,LI Yunhua.Research on reactive power optimization based on improved genetic simulated annealing algorithm[J].Power System Technology,2007,31(3):13-18.
[25]ZHANG M,CHEN J.Islanding and scheduling of power distribution systems with distributed generation[J].IEEETransactions on Power Systems,2015,30(6):3120-3129.
[26]林俐,潘险险.基于分裂层次半监督谱聚类算法的风电场机群划分方法[J].电力自动化设备,2015,35(2):8-14.LIN Li,PAN Xianxian.Wind turbine grouping based on semisupervised split-hierarchical spectral clustering algorithm for wind farm[J].Electric Power Automation Equipment,2015,35(2):8-14.
[27]周林,平西建,徐森,等.基于谱聚类的聚类集成算法[J].自动化学报,2012,38(8):1335-1342.ZHOU Lin,PING Xijian,XU Sen,et al.Cluster ensemble based on spectral clustering[J].Acta Automatica Sinica,2012,38(8):1335-1342.
[28]JAIN R,KORONIOS A.Innovation in the cluster validating techniques[J].Fuzzy Optimization&Decision Making,2008,7(3):233-241.
[29]庄楚天,吴戈.基于站点爬虫数据的公共自行车系统时空特征分析[J].交通信息与安全,2017,35(3):51-58.ZHUANG Chutian,WU Ge.Spatial-temporal charateristics of a shared bicycle system based on web crawler data[J].Journal of Transport Information and Safety,2017,35(3):51-58.
[30]YANG X S.Nature-inspired metaheuristic algorithms[M].2nd ed.UK:Luniver Press,2010:105-108.