基于改进遗传模拟退火算法的电网无功优化  

Grid Reactive Power Optimization Strategy Based on Genetic Simulated Annealing Algorithm

作　　者：王旭斌[1] 李鹏[1] 窦鹏冲[1] 

机构地区：[1]华北电力大学新能源电力系统国家重点实验室,河北保定071003

出　　处：《陕西电力》2013年第7期40-44,共5页Shanxi Electric Power

基　　金：国家自然科学基金(50977029)

摘　　要：电网无功优化问题是一个多变量、多约束的混合非线性规划问题,其操作变量既有连续变量又有离散变量,优化过程复杂繁琐。遗传算法是模拟生物在自然环境中的遗传和进化过程而形成的一种自适应的全局优化搜索算法,可用于解决含有离散变量的复杂优化问题。针对传统遗传算法的收敛速度慢,易陷入局部最优解等缺陷,提出一种基于遗传模拟退火思想求解电力系统无功优化的新算法,并引入灵敏度分析,对基本遗传算法的编码、初始种群、适应度函数和交叉、变异策略等进行改进。使用本文算法对IEEE14节点进行优化计算,仿真结果证明了本文模型和算法的实用性、可靠性和优越性。Grid voltage and reactive power optimal control is a mixed nonlinear programming problem with muhipal variables and constraints.Its operating variables includes both continuous variables and discrete variables and the optimization process is complicated.The genetic algorithm is an adaptive optimization search algorithm that is formed in the biological genetic and evolutionary process in the natural environment. And this algorithm can be used to solve complex optimization problems with discrete variables. For traditional genetic algorithm＇s defects , such as slow convergence speed and easy to fall into local optimal solution, this paper presents a new algorithm based on genetic simulated annealing to solve reactive power optimized problem and introduces the sensitivity analysis to improve the coding of the basic genetic algorithm, the initial population, fitness function and cross-mutation strategy. Using the proposed algorithm to optimize the IEEE14 node computing.Simulation results prove the practicality, reliability and superiority of the proposed model and algorithm.

关 键 词：电力系统 电压无功优化 遗传模拟退火算法 

分 类 号：TM714.3[电气工程—电力系统及自动化]