摘要
电力系统无功优化是提高系统经济运行水平的有效手段。无功优化需要处理大量数据,而遗传算法能够有效地处理这些复杂问题。将育种算子应用于遗传算法,使算法不仅具有快速搜索、强鲁棒性等优点,而且收敛迅速、精度高。模拟仿真表明该算法具有收敛性好,适应性强等特点,具有较好的实用价值。
Reactive power optimization is an effective measure to increase the efficiency of electric power system economic operation. There is plenty of data to deal with in reactive optimization. The IGA can solve the problems effectively. The paper presents to apply Breeding Operator to Genetic Algorithm, and this algorithm combines characteristics of fast seek, strong robustness and easy convergence. This algorithm is applied to the problem of reactive power optimization, and the analysis of calculation results indicate that, the algorithm has been good in the astringency, the adaptability is strong, and it is of very good practical value to the reactive power optimization problem.
出处
《电力需求侧管理》
北大核心
2007年第4期31-33,共3页
Power Demand Side Management
关键词
电网无功优化
育种算子
改进遗传算法
reactive power optimization
breeding operator
improved genetic algorithm（IGA）
