含风电场的电力系统多目标优化调度
麻利新，翟帅华，李萍
（宁夏大学 物理与电子电气工程学院，宁夏 银川 750021）
摘 要：针对火力发电对环境造成的严重污染问题，建立了含风电场的电力系统多目标优化调度模型。以火电机组燃料费用和污染气体排放量最低为目标，用虚拟解理论将多目标优化问题转化为单目标优化问题，以降低问题的复杂性；用动态搜索步长及动态搜索概率对布谷鸟算法改进，用改进后的算法求解所建立调度模型。仿真结果表明，改进算法在符合有功平衡约束、机组出力约束及机组爬坡约束等同样的前提条件下，具有节约发电成本，减少污染物排放，加快系统运行速度的优点。
关键词：风电场；污染物排放；多目标优化；虚拟解；布谷鸟算法
中图分类号：TM614 文献标识码：A 文章编号：1007-3175(2019)08-0007-04
Multi-Objective Optimal Scheduling of Power System Including Wind Farm
MA Li-xin, ZHAI Shuai-hua, LI Ping
（School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China）
Abstract: Aiming at the serious pollution problem caused by thermal power generation, this paper established a multi-objective optimization scheduling model of power system including wind farms. In order to reduce the complexity of the problem, the multi-objective optimization problem was transformed into a single-objective optimization problem by using the virtual solution theory, aiming at the lowest fuel cost and the lowest emission of polluted gases. The cuckoo algorithm was improved by using dynamic search step size and dynamic search probability, and the improved algorithm was used for solving the established scheduling model. The simulation results show that the improved algorithm has the advantages of saving power generation costs, reducing pollutant emissions and speeding up the system operation under the same preconditions as active power balance constraints, unit output constraints and unit climbing constraints and so on.
Key words: wind farm; pollutant emissions; multi-objective optimization; virtual solution; cuckoo algorithm
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