基于遗传算法的配电网无功补偿优化研究

摘要

针对现有遗传算法在配电网无功补偿中的缺陷问题,提出了一种基于遗传算法的配电网无功优化方法.根据现有配电网的特性计算出全年的电压品质、网络损耗以及补偿设备投资,通过计算结果进行无功优化数学模型的建立,最后利用自适应遗传算法对数学模型进行改进优化.实验结果表明,所提方法可使配电网无功补偿优化能力在传统遗传算法的基础上进一步提升,并在提高计算效率的基础上,全局寻优能力也有明显的增强.%In view of the defects of traditional genetic algorithm (GA) applied to reactive power optimization of power system, and based on the characteristics of power distribution network, a mathematical model for reactive power optimization is established , which has comprehensively considered the yearly network loss, the voltage quality and the investment in compensation equipment. Meanwhile, adptive GA is used to improve the genetic operator and the termination criterion of traditional GA, and then an improved GA for reactive power optimization of distribution network is put forward to enhance the calculation efficiency and the ability of global optimization. Calculation examples shows that the optimization effect of the improved algorithm is better than that of the traditional GA.