摘要
针对遗传算法容易出现早熟、局部寻优能力较差和收敛速度缓慢的问题,该文用模拟退火思想对适应度函数进行改善,用自适应算法对遗传算法的交叉、变异策略进行改进,采用精英保留策略,变异操作作用尾部占优原则,并把基于广义Tellegen定理的电压稳定裕度指标最小作为无功优化的目标函数之一,以改善电力系统的静态电压稳定性。用IEEE14I、EEE30和IEEE57节点系统进行验算,将优化结果与其他算法进行比较,表明本文算法优化结果更优,相对于简单遗传算法有更好地收敛性,加速了算法的收敛速度,在降低网损的同时能够有效提高负荷节点的电压稳定裕度。
The genetic algorithm has three disadvantages：early maturity,poor ability of local optimization,and slow convergence rate.In order to overcome these problems,some modified methods of reactive power optimization to improve the static voltage stability of power system were proposed.In this paper,fitness function was modified by using simulated annealing theory.Genetic algorithm crossover and mutation strategy were improved by using adaptive algorithm.The tactics of elites to keep and mutation operation used tail-prevailing principle were adopted.The minimization of voltage stability margin index based on the generalized Tellegen＇s theorem was taken as one of objective functions.Compared with the other methods on IEEE 14-bus,IEEE 30-bus and IEEE 57-bus system,the optimization results show that the proposed algorithm optimization has better convergence property than simple genetic algorithm,which accelerated the algorithm convergence speed,and effectively improve the voltage stability margin of load buses while reducing the power loss.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2011年第1期138-144,共7页
Proceedings of the CSU-EPSA
关键词
电力系统
无功优化
静态电压稳定
裕度指标
改进遗传算法
power system
reactive power optimization
static voltage stability
margin index
modified genetic algorithm
