摘要
主动配电网的状态估计是配电管理系统必不可少的组成要素,其估计结果的准确性受量测位置的影响较大。为了提高系统状态估计的精度,优化实时数据库,结合一种基于并行置信传播算法的状态估计方法,建立了以主动配电网状态估计误差最小为目标的PMU量测位置优化模型,同时提出了利用优化粒子初始位置的改进免疫离散粒子群算法进行模型求解。最后通过算例仿真,得到了量测装置的优化配置方案,且在该方案下,状态估计的精度明显提高。
The state estimation of active distribution network is an essential component in the distribution management system.However,the accuracy of the estimation results is affected by the measurement position significantly.In order to improve the accuracy of state estimation and optimize the real-time database,this paper established an optimal PMU measurement location model which combined with a state estimation algorithm based on parallel belief propagation to minimize the state estimation error of an active distribution network.Furthermore,an improved immune particle swarm optimization algorithm which optimizes the initial position of the particles is proposed to solve the model.Finally,an optimal configuration scheme of the measuring device is obtained by example simulation.Under the scheme,the precision of the state estimation is improved obviously.
作者
李伟光
卢锦玲
Li Weiguang;Lu Jinling(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,Hebei,China)
出处
《电测与仪表》
北大核心
2018年第21期14-18,30,共6页
Electrical Measurement & Instrumentation
关键词
主动配电网
状态估计
量测位置
粒子群算法
active distribution network
state estimation
measurement position optimization
particle swarm optimization algorithm
