广东电力Issue(7)：78-82,5.DOI:10.3969/j.issn.1007-290X.2014.07.016
基于遗传算法的电力系统自适应卡尔曼滤波动态状态估计
Self-adaptive Kalman Filter Dynamic State Estimation on Power System Based on Genetic Algorithm
钟志坚 1洪彬倬2
作者信息
- 1. 广东电网公司河源供电局，广东 河源 517000
- 2. 广东电网公司阳江供电局，广东 阳江 529500
- 折叠
摘要
Abstract
Aiming at problem of Kalman filter dynamic state estimation of which both Holts′parameters are constants and may produce bigger forecast error when power system running state changing,this paper proposes to use exponential smoot-hing method to carry on dynamic adjustment for parameters.By applying genetic algorithm in forecast steps,this method was able to dynamically confirm parameter size and realize self-adaptive optimization of forecast parameters.At last,simulation calculation on IEEE 1 4 node system was conducted.Compared with traditional method,the result indicated that this method was provided with obvious advantages.关键词
电力系统/卡尔曼滤波/动态状态估计/自适应/遗传算法Key words
power system/Kalman filter/dynamic state estimation/self-adaptive/genetic algorithm分类
信息技术与安全科学引用本文复制引用
钟志坚,洪彬倬..基于遗传算法的电力系统自适应卡尔曼滤波动态状态估计[J].广东电力,2014,(7):78-82,5.
