电力系统保护与控制Issue(22)：98-102,5.
基于粒子群算法的电力系统非线性谐波状态估计
Research on non-linear harmonic state estimation in power system based on particle swarm optimization algorithm
摘要
Abstract
To increase the redundancy of measurement data and improve the observability of linear harmonic state estimation, mixed measurements acquired from PMU and SCADA are used to build the mathematical model of non-linear harmonic state estimation. Then, it is rewritten as a sensitivity model, transformed into an optimization problem, and solved by particle swarm optimization algorithm. Example analysis shows the sensitivity model of non-linear harmonic state estimation is efficient. PSO algorithm can be used to solve this optimization problem. Mixed measurements are helpful to improve the accuracy of harmonic state estimation.关键词
谐波状态估计/相量量测/混合量测/量测配置/粒子群算法Key words
harmonic state estimation/phasor measurement/mixed measurement/measurement configuration/particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
韩美玉,王艳松,张丽霞..基于粒子群算法的电力系统非线性谐波状态估计[J].电力系统保护与控制,2013,(22):98-102,5.基金项目
国家自然科学基金项目(51207170)；中央高校基本科研业务费专项资金资助(12CX04066A) （51207170）
