基于模糊搜索算法的考虑灵敏度约束相量量测单元最优配置
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摘要
相量量测单元(PMU)在电力网络节点中的配置关系到状态估计的质量。PMU应当以最小的成本布置在最优的节点,同时增加冗余性和可观性。本文提出了一种考虑非线性节点灵敏度约束的、基于模式搜索算法求解的PMU最优选址模型。通过计算考虑负荷变动的潮流得到电压均值,形成电压可靠性指标,以此判断灵敏节点。非线性约束中考虑零注入节点,减少PMU配置的数量同时满足状态估计的要求。节点的冗余性利用节点可观性指标得到,说明PMU布置在敏感节点的必要性。利用模式搜索算法求解该优化模型,并给出了以IEEE14节点为例的PMU最优配置具体模型。最后利用IEEE14和30节点进行了仿真算例分析,说明该模型和算法的有效性。
Allocation of Phasor Measurement Units(PMU) in a network isa work related to the quality of state estimation. So in order to increase redundancy and obtain complete observability, PMUs must be allocated at optimal places in the network with minimum cost. In this paper, a Pattern Search Algorithm(PSA) based PMU allocation model considering nonlinear sensitive constraints of buses considering is proposed. Sensitive buses are determined by formulating Voltage Stability Index(VSI) considering mean of voltages obtained from load flows with increasing loads. Modeling of nonlinear constraints integrated with Zero Injection(ZI) buses is taken into consideration to further minimize the number of PMUs. The redundancy at each bus is measured with Bus Observability Index(BOI) to show the importance of PMUs allocation at sensitive buses. Then a specific PMU allocation model considering the above mentioned constraints is formulated on IEEE14 bus feeders. The proposed method is programmed in MATLAB and applied on IEEE 14 and 30 bus feeders. The results obtained are analyzed and compared with other methods available in literature to show effectiveness of proposed method.
Allocation of Phasor Measurement Units(PMU) in a network isa work related to the quality of state estimation. So in order to increase redundancy and obtain complete observability, PMUs must be allocated at optimal places in the network with minimum cost. In this paper, a Pattern Search Algorithm(PSA) based PMU allocation model considering nonlinear sensitive constraints of buses considering is proposed. Sensitive buses are determined by formulating Voltage Stability Index(VSI) considering mean of voltages obtained from load flows with increasing loads. Modeling of nonlinear constraints integrated with Zero Injection(ZI) buses is taken into consideration to further minimize the number of PMUs. The redundancy at each bus is measured with Bus Observability Index(BOI) to show the importance of PMUs allocation at sensitive buses. Then a specific PMU allocation model considering the above mentioned constraints is formulated on IEEE14 bus feeders. The proposed method is programmed in MATLAB and applied on IEEE 14 and 30 bus feeders. The results obtained are analyzed and compared with other methods available in literature to show effectiveness of proposed method.
引文
[1] KORRES G N,Manousakis N M,XYGKIS T C,et al.Optimal phasor measurement unit placement for numerical observability in the presence of conventional measurements using semi-definite programming[J].Generation Transmission&Distribution Iet,2015,9(15):2427-2436.
[2]李英,于磊,赵洪山.考虑灵敏度约束条件的电力系统完全可观性的PMU最优配置方法[C]//中国高等学校电力系统及其自动化专业学术年会.2005.
[3]樊海锋,徐凯,江全元,等.考虑最大可观测通道数和关键故障线路约束的PMU优化配置研究[J].机电工程,2013,30(10):1240-1245.
[4]王小匆,刘亚东,盛戈皞,等.基于改进BPSO算法的PMU优化配置新方法[J].广东电力,2018(1):62-67.
[5]赵辉,赵少华,王红君,等.基于0-1规划迭代法优化PMU配置以提高混合状态估计准确度[J].电气应用,2017(5):80-84.
[6] XU J,WEN M H F,LI V O K,et al.Optimal PMU placement for wide-area monitoring using chemical reaction optimization[C]//Innovative Smart Grid Technologies(ISGT),2013 IEEE PES.IEEE,2013:1-6.
[7]郭佩英,郝红艳,邓颖,等.考虑测量冗余度最大的电力系统PMU最优配置[J].东北电力大学学报,2010,30(2):34-38.
[8]陈晓刚,于浩,王波,等.满足多种约束条件的最优PMU配置方法[J].浙江大学学报(工学版),2010,44(3):539-543.
[9] MAZHARI S M,MONSEF H,LESANI H,et al.A MultiObjective PMU Placement Method Considering Measurement Redundancy and Observability Value Under Contingencies[J].IEEE Transactions on Power Systems,2013,28(3):2136-2146.
[10]陈晓刚,陶佳,江全元,等.考虑高风险连锁故障的PMU配置方法[J].电力系统自动化,2008,32(4):11-14.
[11]黄姝雅,刘天琪,陈绩.动态状态估计中PMU配置的离散粒子群优化算法[J].电网技术,2006,30(24):68-72.
[12]毛义,吕飞鹏.基于博弈演化算法的PMU最优配置方法[J].电力自动化设备,2017,37(10):184-188.
[13]徐衍会,宫晓珊,伍双喜.用于负荷侧强迫振荡监测的PMU优化配置[J].广东电力,2017,30(7):24-29.
[14]郑明忠,张道农,张小易,等.基于节点集合的PMU优化配置方法[J].电力系统保护与控制,2017,45(13):138-142.
[15]卢毅.广域测量系统中计及安全性因素的PMU配置[D].浙江大学,2016.
[16]张开达.考虑静态电压稳定分析需求的电网PMU优化配置研究[D].湖南大学,2016.
[17]万蓉,薛蕙.考虑PMU的配电网潮流计算[J].电力自动化设备,2017,37(3):33-37.
[18]周波.配电网PMU优化配置及故障定位算法研究[D].长春工业大学,2017.
[19] GOU B.Generalized Integer Linear Programming Formulation for Optimal PMU Placement[J].IEEE Transactions on Power Systems,2008,23(3):1099-1104.
[20] MANOUSAKIS N M,KORRES G N.A Weighted Least Squares Algorithm for Optimal PMU Placement[J].IEEE Transactions on Power Systems,2013,28(3):3499-3500.
[2]李英,于磊,赵洪山.考虑灵敏度约束条件的电力系统完全可观性的PMU最优配置方法[C]//中国高等学校电力系统及其自动化专业学术年会.2005.
[3]樊海锋,徐凯,江全元,等.考虑最大可观测通道数和关键故障线路约束的PMU优化配置研究[J].机电工程,2013,30(10):1240-1245.
[4]王小匆,刘亚东,盛戈皞,等.基于改进BPSO算法的PMU优化配置新方法[J].广东电力,2018(1):62-67.
[5]赵辉,赵少华,王红君,等.基于0-1规划迭代法优化PMU配置以提高混合状态估计准确度[J].电气应用,2017(5):80-84.
[6] XU J,WEN M H F,LI V O K,et al.Optimal PMU placement for wide-area monitoring using chemical reaction optimization[C]//Innovative Smart Grid Technologies(ISGT),2013 IEEE PES.IEEE,2013:1-6.
[7]郭佩英,郝红艳,邓颖,等.考虑测量冗余度最大的电力系统PMU最优配置[J].东北电力大学学报,2010,30(2):34-38.
[8]陈晓刚,于浩,王波,等.满足多种约束条件的最优PMU配置方法[J].浙江大学学报(工学版),2010,44(3):539-543.
[9] MAZHARI S M,MONSEF H,LESANI H,et al.A MultiObjective PMU Placement Method Considering Measurement Redundancy and Observability Value Under Contingencies[J].IEEE Transactions on Power Systems,2013,28(3):2136-2146.
[10]陈晓刚,陶佳,江全元,等.考虑高风险连锁故障的PMU配置方法[J].电力系统自动化,2008,32(4):11-14.
[11]黄姝雅,刘天琪,陈绩.动态状态估计中PMU配置的离散粒子群优化算法[J].电网技术,2006,30(24):68-72.
[12]毛义,吕飞鹏.基于博弈演化算法的PMU最优配置方法[J].电力自动化设备,2017,37(10):184-188.
[13]徐衍会,宫晓珊,伍双喜.用于负荷侧强迫振荡监测的PMU优化配置[J].广东电力,2017,30(7):24-29.
[14]郑明忠,张道农,张小易,等.基于节点集合的PMU优化配置方法[J].电力系统保护与控制,2017,45(13):138-142.
[15]卢毅.广域测量系统中计及安全性因素的PMU配置[D].浙江大学,2016.
[16]张开达.考虑静态电压稳定分析需求的电网PMU优化配置研究[D].湖南大学,2016.
[17]万蓉,薛蕙.考虑PMU的配电网潮流计算[J].电力自动化设备,2017,37(3):33-37.
[18]周波.配电网PMU优化配置及故障定位算法研究[D].长春工业大学,2017.
[19] GOU B.Generalized Integer Linear Programming Formulation for Optimal PMU Placement[J].IEEE Transactions on Power Systems,2008,23(3):1099-1104.
[20] MANOUSAKIS N M,KORRES G N.A Weighted Least Squares Algorithm for Optimal PMU Placement[J].IEEE Transactions on Power Systems,2013,28(3):3499-3500.