基于改进粒子群算法梯级水电站短期优化调度研究  

Research on the Short-term Optimal Scheduling of Cascade Hydropower Plants based on Improved Particle Swarm Optimization

作　　者：冯雁敏 李承军[2] 张雪源 

机构地区：[1]东北电力科学研究院有限公司,辽宁沈阳110006 [2]华中科技大学,湖北武汉430074

出　　处：《水力发电》2009年第4期24-28,共5页Water Power

摘　　要：应用改进粒子群算法求解梯级水电站短期优化调度问题。考虑发电效益和存水效益结合峰谷电价建立综合效益最大模型,针对粒子群算法存在的后期收敛速度慢和易陷入局部最优等缺点,引入收缩因子和杂交算子对其进行改进。应用改进粒子群算法对"水布垭水电站-隔河岩水电站-高坝洲水电站"进行短期优化调度,分别采用传统优化模型和峰谷优化模型进行实例计算,结果表明实施峰谷电价,对于提高梯级水电站综合效益,同时缓解高峰期用电紧张局面有更高的应用价值;应用改进粒子群算法求解梯级水电站短期优化调度问题在求解时间、求解精度上都得到了较满意的效果。Improved Particle Swarm Optimization is applied to short-term optimal scheduling of the cascade hydropower plants. Maximum integrated profit model of short-term optimal scheduling of cascade hydropower plants based on peak and valley price considering both the profit of generation and the water-effective is established. In order to overcome the shortcomings of standard Particle Swarm Optimization, for example, precocity and slow later convergence, shrinkage factor and across operator are adopted in the study, hnproved Particle Swarm Optimization is applied to short-term optimal scheduling of the cascade hydropower plants of the Qingjiang River, it calculate by the traditional model and the modle based on peak and valley price, the results show that implementing peak and valley price has a higher value for improv- ing the integrated profit of cascade hydropower plants, reasonable use of water resources and easing the tensions in the peak period of electricity consumption; it has a satisfactory effect both in the solving time and the accuracy of the results for applying the improved Particle Swarm Optimization to solve the problem of the short-term optimal scheduling of cascade hydropower plants.

关 键 词：短期优化调度 峰谷电价 粒子群算法 综合效益最大模型 梯级水电站 

分 类 号：P339[天文地球—水文科学] TV697.12[水利工程—水文学及水资源]