基于遗传算法的电力系统综合负荷模型的建模与仿真

遗传算法是一种具有全局寻优能力的随机搜索算法,但其本身存在收敛速度慢和易早熟的缺陷。为此,引入一种改进的遗传算法用于电力负荷综合建模。该算法具有克服早熟、避免近亲繁殖和自适应的优良特性。应用建模实例表明,遗传算法辨识所得负荷模型的描述精度很高,其模型参数呈现很好的稳健性,从而有效地克服了传统优化方法的模型参数分散性。

Power system load modeling and simulation based on improved genetic algorithm

GA is a random optimization algorithm with global optimum capability,but it has the disadvantages of slow convergence and precocity.To solve above disadvantages,an improved GA was proposed in Load modeling.This adaptive improved GA could avoid precocity and inbreeding.Load modeling instances proved that the calculation precision based on genetic algorithm was better,the model parameters were more stable,thus effectively overcoming the diffusiveness of the model parameters of traditional optimization methods.