多目标遗传算法求解电力系统经济负荷分配

摘要

提出应用多目标遗传算法解决电力系统经济负荷分配问题。对负荷分配的数学模型进行了分析,将这一带约束的单目标优化问题转换成总煤耗函数和违反约束条件的程度函数两个目标函数优化问题。该算法采用实数编码技术,Pareto强度值作为个体的评价指标,利用遗传算法实现种群的进化,最终找到最优解。将该方法分别应用于某5台机组组成的发电系统和3台机组组成的发电系统进行负荷优化计算,结果与基于惩罚函数的单目标优化算法进行比较,分析表明该算法在确保满足各约束条件的前提下具备较好的寻优性能,证实了该算法的可行性与有效性。%A multi-objective genetic algorithm is proposed for solving power system economic load dispatch.Based on the analysis of mathematical model for economic load distribution,the constrained single-objective optimization is converted into the optimization of two objectives： the total coal consumption function and the constraint-violation degree function.The proposed algorithm adopts real number coding technique and genetic algorithm,and takes Pareto strength as evaluating indicator,ultimately to realize population evolution and work out the optimal solution.In order to prove the validity and effectiveness of the proposed algorithm,it was tested on five-unit and three-unit power systems respectively.Compared with the test results of single-objective algorithm based on penalty function,it is shown that the multi-objective genetic algorithm has good optimizing performance and can meet all constraints.