摘要
随着社会经济的不断发展,粒子群算法越来越多地应用到电力系统之中。由于粒子群算法在被人们使用的过程中越来越显现出精度较低的特点以及局限性的问题。所以根据电力系统的实际情况,应该将粒子群算法与遗传算法等算法相互结合,从而提高粒子群算法的适用性。本文主要对电力系统经济负荷分配数学模型在目标函数和约束条件方面进行了分析,然后对改进粒子群算法进行了说明,最后结合实例对这一情况进行了分析,希望对粒子群算法的改进有所帮助。
With the continuous development of social economy, particle swarm optimization algorithm is applied to power system. Because the particle swarm algorithm is used in the process of the people more and more show the characteristics of low accuracy and limitations of the problem. Therefore, according to the actual situation of power system, the particle swarm algorithm and genetic algorithm are combined to improve the applicability of the particle swarm optimization algorithm. In this paper, the economic load distribution of power system is analyzed in terms of objective function and constraints, and then the improved particle swarm optimization algorithm is described, and the case is analyzed.
出处
《电子测试》
2015年第10期47-48,共2页
Electronic Test
关键词
粒子群算法
电力系统
经济负荷分配
particle swarm optimization
power system
economic load distribution
