兼顾系统强度和直流支撑的500 kV电网分区方法
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摘要
兼顾考虑系统强度和直流支撑,以功率转移支撑强度、多直流馈入均衡度、电网平均强度综合最优为目标,建立500kV电网分区的多目标优化模型,并利用带精英策略的非支配解排序遗传算法(elitenon-dominatedsortinggenetic algorithm,NSGA-II)求解,得出Pareto最优的500kV电网分区方案集。开断交流通道是电网分区的实现手段,优化过程中需对500 kV电网的每个通道进行开断分析,计算量大,运行效率低,而且随机搜索空间太大,求得的Pareto解集可能局限于局部网架调整,达不到全局优化、全网分区的效果。提出以特高压变电站为枢纽点的分区模式为约束条件,引入基于复杂社团结构理论的电网分区方法,实现从每个通道到关键通道的降维,缩小了遗传算法的搜索范围,避免了局部Pareto解。以山东规划电网为例进行算例分析,验证模型和算法的有效性。
1 Taking comprehensive optimum of power transfer supporting strength, multi-infeed HVDC balance and grid average strength as objective, a multi-objective optimization model for partitioning 500 kV power network was established considering AC system strength and supporting ability to HVDC. Elite non-dominated sorting genetic algorithm(NSGA-II) was adopted to achieve optimal Pareto solution, partitioning scheme set for 500 kV power network. Given that breaking AC channel was the realization method of partitioning, the optimization process is needed to analyze whether each AC channel was broken or not, possibly resulting in heavy calculation burden, low efficiency, large search space and local Pareto optima. To solve these problems, new partitioning mode was taken as constraint, chosen as key point by UHV substation. The power network partition method based on community structure theory was introduced to realize dimension reduction from each channel to key channel, reducing search space of multi-objective optimization algorithm and avoiding local Pareto solution. Taking Shandong grid planning as an example, effectiveness of the models and algorithms were verified.
1 Taking comprehensive optimum of power transfer supporting strength, multi-infeed HVDC balance and grid average strength as objective, a multi-objective optimization model for partitioning 500 kV power network was established considering AC system strength and supporting ability to HVDC. Elite non-dominated sorting genetic algorithm(NSGA-II) was adopted to achieve optimal Pareto solution, partitioning scheme set for 500 kV power network. Given that breaking AC channel was the realization method of partitioning, the optimization process is needed to analyze whether each AC channel was broken or not, possibly resulting in heavy calculation burden, low efficiency, large search space and local Pareto optima. To solve these problems, new partitioning mode was taken as constraint, chosen as key point by UHV substation. The power network partition method based on community structure theory was introduced to realize dimension reduction from each channel to key channel, reducing search space of multi-objective optimization algorithm and avoiding local Pareto solution. Taking Shandong grid planning as an example, effectiveness of the models and algorithms were verified.
引文
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[2]潘高峰,王星华,彭显刚,等.复杂网络的社团发现方法在电网分区识别中的应用研究[J].电力系统保护与控制,2013,41(13):116-121.Pan Gaofeng,Wang Xinghua,Peng Xiangang,et al.Study of power gridpartitionidentificationmethodbasedoncommunitystructure detection[J].Power System Protection and Control,2013,41(13):116-121(in Chinese).
[3]刘玉田,谭冰雪.大电网恢复适应性分区方法[J].电力系统保护与控制,2013,41(2):49-54.Liu Yutian,Tan Bingxue.Adaptive partition method for large power system restoration[J].Power System Protection and Control,2013,41(2):49-54(in Chinese).
[4]倪向萍,阮前途,梅生伟,等..基于复杂网络理论的无功分区算法及其在上海电网中的应用[J].电网技术,2007,31(9):6-12.Ni Xiangping,Ruan Qiantu,Mei Shengwei,et al.A new network partitioningalgorithmbasedoncomplexnetworktheoryandits application in Shanghai power grid[J].Power System Technology,2007,31(9):6-12(in Chinese).
[5]刘文通,舒勤,钟俊,等.基于局部电压稳定指标及复杂网络理论的无功电压分区方法[J].电网技术,2018,42(1):269-278.LiuWentong,ShuQin,ZhongJun,etal.Anewalgorithmfor partitionedregulationbasedonlocalvoltagestabilityindexand complex network theory[J].Power System Technology,2018,42(1):269-278(in Chinese).
[6]许刚,王紫雷.基于Normal矩阵谱平分法的快速电压控制分区[J].电网技术,2014,38(1):199-204.XuGang,WangZilei.Fastvoltagecontrolpartitioningbasedon Normalmatrixspectralbisectionmethod[J]. PowerSystem Technology,2014,38(1):199-204(in Chinese).
[7]梁海平,顾雪平.基于谱聚类的黑启动子系统划分[J].电网技术,2013,37(2):372-377.Liang Haiping,Gu Xueping.Black-start network partitioning based on spectral clustering[J].Power System Technology,2013,37(2):372-377(in Chinese).
[8]杨冬.特高压输电网架结构优化与未来电网结构形态研究[D].济南:山东大学,2013:22.
[9]周勤勇,杨冬,刘玉田,等.多直流馈入电网限制短路电流方案多目标优化[J].电力系统自动化,2015,39(3):140-145.ZhouQinyong,YangDong,LiuYutian,etal.Multi-objective optimizationforshort-circuitcurrentlimitationschemesinmultiple DC infeed power systems[J].Automation of Electric Power Systems,2015,39(3):140-145(in Chinese).
[10]国家电网公司“十三五”电网发展规划[R].北京:国家电网公司,2015.
[11]覃琴,郭强,周勤勇,等.国网“十三五”规划电网面临的安全稳定问题及对策[J].中国电力,2015,48(1):25-32.Qin Qin,Guo Qiang,Zhou Qinyong,et al.The security and stability ofpowergridsin13thFive-Yearplanningandcountermeasures[J].Electric Power,2015,48(1):25-32(in Chinese).
[12]李明节.大规模特高压交直流混联电网特性分析与运行控制[J].电网技术,2016,40(4):985-991.LiMingjie. Characteristicanalysisandoperationalcontrolof large-scalehybridUHVAC/DCpowergrids[J]. PowerSystem Technology,2016,40(4):985-991(in Chinese).
[13]CIGREWorkingGroupB4-41.SystemswithmultipleDCinfeed[S].2008.
[14]Denis L H A,Andersson G.Voltage stability analysis of multi-infeed HVDCsystems[J].IEEETransactionsonPowerDelivery,1997,12(3):1318-1308.
[15]NewmanMEJ. Detectingcommunitystructureinnetworks[C]//Springer New York LLC,2004.
[16]Clauset A.Finding local community structure in networks[J].Physical ReviewE-Statistical,Nonlinear,andSoftMatterPhysics,2005,72(2).
[17]魏震波,苟竞.复杂网络理论在电网分析中的应用与探讨[J].电网技术,2015,39(1):279-287.WeiZhenbo,GouJing.Anoverviewonapplicationofcomplex networktheoryinpowersystemanalysis[J]. PowerSystem Technology,2015,39(1):279-287(in Chinese).
[18]蔡泽祥,王星华,任晓娜.复杂网络理论及其在电力系统中的应用研究综述[J].电网技术,2012,36(11):114-121.CaiZexiang,WangXinghua,RenXiaona.Areviewofcomplex network theory and its application in power systems[J].Power System Technology,2012,36(11):114-121(in Chinese).
[19]Floyd R W.Algorithm 97:shortest path[J].Communications of the ACM,1962,5(6):345.
[20]Warshall S.A theorem on boolean matrices[J].Journal of the ACM,1962,9(1):11-12.
[21]GirvanM,NewmanMEJ.Communitystructureinsocailand biologicalnetworks[J].ProceedingsoftheNationalAcademyof Sciences of the United States of America,2002,99(12):7821-7826.
[22]KalyanmoyD,AmritP,SameerA,etal.Afastandelitistmulti objectivegeneticalgorithm:NSGA-II[J]. IEEETransactionson Evolutionary Computation,2002,6(2):182-197.
[23]王秀丽,李淑慧,陈皓勇,等.基于非支配遗传算法及协同进化算法的多目标多区域电网规划[J].中国电机工程学报,2006,26(12):11-15.Wang Xiuli,Li Shuhui,Chen Haoyong,et al.Multi-objective and multi-districttransmissionplanningbasedonNSGA-IIand cooperative co-evolutionary algorithm[J].Proceedings of the CSEE,2006,26(12):11-15(in Chinese).