基于文化粒子群算法的水库发电调度图绘制

Reservoir Generation Scheduling Study by Particle Swarm Optimization Based on Cultural Algorithm

为了解决使用常规方法绘制水库发电调度图时,典型水文年的样本容量有限、水文特征的代表性具有局限性的问题,引入了文化粒子群算法,采用信仰空间吸收种群的知识经验,形成规则引导种群进化,充分利用历史实测资料绘制调度图。通过实例研究,获得了较常规方法更优的结果,为优化方法在水电站中长期调度中的应用提供了一条新途径。

The drawing of conventional generation scheduling chart is constrained by limited hydrology samples and typical hydrological features.In order to solve this problem,the Particle Swarm Optimization based on Culture Algorithm（PSOCA） is introduced for making full use of all historical data.After practical application,the PSO-CA is better than conventional method and can be used for medium and long-term operation optimization of hydropower station.