基于改进蝙蝠算法的水火电力系统短期优化调度

Short-term Scheduling of Hydrothermal Power Systems Based on Enhanced Bat Algorithm

提出了一种求解水火电力系统短期优化调度问题的改进蝙蝠算法(EBA)。EBA算法在标准蝙蝠算法(BA)的基础上,采用反向学习初始化蝙蝠位置和动态自适应更新蝙蝠速度以改善种群多样性,同时采用Tent混沌映射更新脉冲发射率以提高算法的全局收敛性。在一个含4个水电厂的梯级水电站和3台火电机组的典型测试系统上进行仿真计算,结果表明相对于BA算法和其他智能优化算法,EBA算法可获得更优的发电费用。

An enhanced bat algorithm(EBA)is proposed to solve the short-term scheduling of hydrothermal power system.Based on the basic bat algorithm(BA),the initialization of population using opposition based learning and self-adaption of bat s velocity is introduced to enhance the diversity of population.In addition,the EBA algorithm implements Tent map to update the pulse emission rate,which can increase the global search ability of population.The proposed algorithm is evaluated on one hydrothermal power system consisting of four hydro plants and three thermal plants.The comparative result analysis shows that the EBA algorithm has better solution results than the BA algorithm and other approaches.