基于改进人工鱼群算法的含风电场电力系统最优潮流计算

将风电场看作PQ节点并考虑风电场输出功率随机性和负荷随机性,提出含风电场的电力系统最优潮流计算方法。分析基本人工鱼群算法原理及其缺陷,提出改进人工鱼群算法(IAFSA);提出人工鱼群的视野和步长的取值方法,对初始种群的生成、行动方式和终止判据进行改进;并基于动态调整罚函数将带约束的有功最优潮流问题转化为无约束优化问题,实现含风电场的电力系统最优潮流计算.实例分析结果表明:基于改进人工鱼群算法比基于基本人工鱼群算法和遗传算法进行含风电场电力系统最优潮流计算具有更优全局收敛性和更快计算速度.

IAFSA based optimal power flow calculation of power systems with wind farms

Improved artificial fish swarm algorithm （IAFSA） based optimal power flow calculation of power systems with wind farms is proposed with wind farms regarded as PQ nodes and the randomness of wind farms output power and load considered in this paper. The basic principle of artificial fish swarm algorithm and its defects are analyzed, and the IAFSA is proposed. The method of choosing artificial fish＇s vision and step values of calculation are proposed. The generation of initial population, the action means and termination criterion are improved. Based on the dynamic penalty function, the constrained active optimal power flow problem is transformed into the unconstrained optimization problem for computing the optimal power flow. Examples simulation results show that the proposed optimal power flow calculation with IAFSA has better global convergence and faster computing speed than that with the genetic algorithm.