基于改进粒子群的水火电力系统发电调度  

Hydrothermal Generation Scheduling Based on Enhanced PSO

作　　者：刘双全[1,2] 邹立峰[3] 张海龙 王金文[2] 

机构地区：[1]云南电网公司博士后科研工作站,云南昆明650217 [2]华中科技大学水电与数字化工程学院,湖北武汉430074 [3]云南电网公司,云南昆明650011 [4]国电新疆艾比湖流域开发有限公司,新疆乌鲁木齐830063

出　　处：《水电能源科学》2010年第7期153-156,共4页Water Resources and Power

基　　金：国家自然科学基金资助项目(50909044)

摘　　要：在标准粒子群优化算法中引入最差粒子和自适应惯性权重,使粒子随进化进度自适应调整飞行方向和速度,向其自身和种群最优位置收敛的同时背离二者的最差位置,且避免了算法过早收敛和限于局部最优。将改进后的粒子群优化算法用于求解水火电力系统发电调度问题,仿真结果表明该算法可行有效。The effect of the worst particle and self-adaptive inertia weight are introduced into the classical particle swarm optimization algorithm(PSO),which adjusts the direction and velocity of the particle to converge to the cognitive and social best positions in swarm while deviating from the worst position between local and global particles.The self-adaptive inertia weight helps to avoid the premature convergence and falling into the local optima for PSO.The enhanced PSO is applied to solve the hydrothermal generation scheduling problem.The simulation results show that the proposed PSO approach is feasible and effective.

关 键 词：改进 粒子群优化算法 水火电力系统 发电调度 PSO 自适应调整 最优位置 过早收敛 局部最优 惯性权重 仿真结果 调度问题 种群 速度 求解 进化 进度 飞行 标准 

分 类 号：TK79[动力工程及工程热物理—流体机械及工程] TV7[水利工程—水利水电工程]