混沌粒子群优化算法在水库防洪优化调度中的应用

为改善粒子群优化算法的寻优性能,提出了一种新的算法——混沌粒子群算法。该算法将混沌搜索机制引入到粒子群算法中来增加粒子的多样性,采用自适应惯性权重因子模型来设置惯性权重因子,改善了算法的全局寻优能力,并将其用于水库防洪优化调度中。实例计算表明该算法能较好地克服了粒子群算法易早熟和陷入局部最优的缺点,为解决水库防洪优化调度问题提供一种新的有效途径。

Optimal scheduling of hydroelectric station based on chaotic particle swarm optimization

Aiming to improve the performance of particle swarm optimization,this paper introduced a new algorithm,chaotic particle swarm algorithm.By integrating chaotic optimization into particle swarm optimization to increase the diversity of the particle and using adaptive inertia weights model to setting the inertia weights factor,it greatly enhances the global searching performance.The new method is applied in long-term reservoir operation optimization.It can avoid the premature convergence and local optimization,the effectiveness of this method is verified by practical application.Therefore,it provides a new method for reservoir operation optimization.