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为最大限度地保证电网系统最优运行,减少不必要的损耗,提出基于改进粒子群算法(particle swarm optimization algorithm,PSO)的电网无功优化方法。该算法对传统的惯性权重进行改进,使其可以按自身需求相应的变化,并动态地变化学习因子,最后引入了变异算子来更新种群。在IEEE 30节点系统测试中,基于改进的PSO算法避免陷入局部最优,其比改进前的PSO算法更具优势,改进后的PSO算法和其他优化算法相比,收敛速度更快,优化程度更高。
In order to ensure optimal operation of power system and reduce unnecessary loss, a reactive power optimization method based on improved particle swarm optimization algorithm (PSO) is proposed. The algorithm improves the traditional inertia weight so that it can change correspondingly according to its own needs, dynamically changes the learning factor, and finally introduces the mutation operator to update the population. In the IEEE 30-bus system test, the PSO algorithm based on the improved PSO avoids falling into the local optimum, which is more advantageous than the pre-modification PSO algorithm. Compared with other optimization algorithms, the improved PSO algorithm has faster convergence rate and more optimization high.