作　　者： ; ; ; ;

机构地区： 华南理工大学

出　　处： 《水力发电》 2014年第2期83-87,共5页

摘　　要： 为提升水火电力系统运行的综合性能,对含有梯级水电站的水火电力系统,构建兼顾经济、用水和环保的多目标优化调度模型。针对各目标的量纲不同、权重系数难以合理确定的多目标优化问题,运用满意度函数和欧式距离函数对其进行归一化处理,并采用改进粒子群算法对处理后的目标进行优化求解。以广西某个由10个火电厂和8个梯级水电站所组成的水火电力系统平水期日发电优化调度计划为例进行仿真分析,优化结果表明在调度期内水力资源获得了充分利用,水电站总出力大于火电厂总出力,从而实现以水代煤,有效减少了煤炭的使用,降低了污染物的排放,同时也进一步验证了本文所提多目标优化求解方法的有效性。 In order to improve the comprehensive performance of hydro-thermal power system with cascade hydroelectric stations, a multi-objective optimization model which can make the coordination among economy, water resources and environmental protection is established. The multi-objective optimization problem, in which, three targets have different dimension and weight coefficient is difficult to determine, is normalized by using satisfaction function and Euclidean distance function, and then is solved by using improved particle swarm algorithm. A hydro-thermal power system with eight cascade hydroelectric stations and ten thermal plants in Guangxi is studied as an example to simulate the scheduling optimization of daily power generation in normal water period. The results show that the hydropower output is greater than the output of thermal power plants, which reduces coal consumption and pollutant emissions. The case study also verifies the effectiveness of multi-objective optimization method.

关 键 词： 优化调度 多目标 改进粒子群 水火电力系统

领　　域： [电气工程]