基于改进蜜蜂进化型遗传算法的电力系统无功优化  

Power system reactive power optimization based on improved bee evolutionary genetic algorithm

作　　者：林虹江 周步祥[1] 杨昶宇 冉伊[1] 詹长杰[1] 

机构地区：[1]四川大学电气信息学院,四川成都610065

出　　处：《可再生能源》2014年第10期1468-1473,共6页Renewable Energy Resources

摘　　要：文章采用改进蜜蜂进化型遗传算法求解电力系统无功优化问题,该算法引入了自适应调整选择算子的策略,使算法能及时开辟新的解空间,提高其搜索效率;引入了驱逐算子,增加了蜂群的生物多样性,提高了杂交效率,避免了算法过早收敛的问题。通过以IEEE-6节点和IEEE-30节点测试系统为例进行无功优化计算,并与其他优化算法进行了比较,结果表明了文章算法在求解电力系统无功优化问题的有效性,同时证明了该算法在收敛速度和优化效果上具有比其他优化算法更佳的性能。An improved bee evolutionary genetic algorithm （IBEGA） is used to solve reactive power optimization problem of power system. The algorithm introduces a strategy of adaptive selection operator to timely open up a new algorithm solution space to improve its search efficiency; introduces expulsion operator to increase biodiversity of bees to improve hybridization efficiency, then premature conver- gence problem of the algorithm is avoided. Taking IEEE6 node and IEEE-30 node test system as exam- ples, reactive power optimizations are carried out and compared with other optimization algorithms, the results show that the algorithm is effective in solving IBEGA reactive power optimization problem, and prove that the algorithm convergence speed and optimization algorithm have better performance than other optimization results.

关 键 词：改进蜜蜂进化型遗传算法 电力系统 无功优化 驱逐算子 收敛速度 

分 类 号：TM614[电气工程—电力系统及自动化]