主动配电网多目标PMU最优配置

随着大规模的分布式电源(distributed generation,DG)接入及电网与用户互动增加,主动配电网状态估计结果与量测配置需要考虑更多不确定性因素。为加强对配电网的实时监测与控制,提高配电网运行态势感知能力,需要发展同步相量测量装置(phasor measurement unit,PMU)。在计及DG与负荷不确定性的基础上,建立了考虑经济性、配电网状态估计精度以及节点电压越限概率的多目标PMU最优配置模型。以拟蒙特卡洛方法模拟DG与负荷的不确定性;基于两步式加权最小二乘方法,构建混合量测配电网状态估计模型,并利用改进的自适应多目标二进制差分进化算法进行求解,从而得到特定状态估计误差精度下的PMU最优配置Pareto非劣解集。通过IEEE 33节点配电网系统进行仿真计算分析,验证了所提模型与算法的可行性与有效性。

Multi-objective Optimal Placement of PMU in Active Distribution Network

Due to integration of distributed generations(DGs) and interaction between grids and consumers, more uncertain factors are needed to be considered in state estimation and meter deployment of active distribution network(ADN). To improve controllability and situation awareness ability, phasor measurement units(PMUs) should be developed in ADN. In this paper, a multi-objective model of PMUs placement is constructed considering cost, accuracy of state estimation and the probability voltage magnitude exceeds limit. Quasi-Monte-Carlo is used to simulate uncertainty of DGs and loads, and two-step weighted least squared method is used to solve the state estimation. Extended adaptive multi-objective binary differential evolution is adopted to obtain Pareto set of PMUs deployment. The proposed model and method is tested on IEEE 33-bus distribution network, and the results indicate their feasibility and effectiveness.