基于改进多目标引力搜索算法的电力系统环境经济调度

摘要

This paper establishes the environmental economic dispatch model of power system considering operating costs and polluted emissions, and proposes an improved gravity search algorithm (IGSA) to solve this problem.The algorithm applies Pareto sorting and crowded distance methods in the NSGA-II to the basic gravity search algorithm to process the in-dividual partial order .In order to solve the problem of slow convergence caused by basic gravity search algorithm , this algo-rithm improves the location updating formula according to the particle swarm algorithm .In addition, elitist conversation strategy is adopted to guide the group to the region near the Pareto optimal solution set and guarantee that the solution set can be distributed evenly.Finally, fuzzy set theory is utilized to produce the best compromise solution which can provide scheduling solutions for decision-makers.Cases studies demonstrate the feasibility and effectiveness of the proposed algo-rithm, which will provide a new method to balance the economy and environmental protection for power system .%建立了综合考虑系统运行成本和污染物排放成本的电力系统环境经济调度模型，并提出了一种改进多目标引力搜索算法（ IGSA ）对该模型进行求解。该算法将NSGA-II中的非劣解排序和拥挤距离的思想引入基本引力搜索算法用于处理个体偏序关系。其次针对基本引力搜索算法收敛速度慢的问题，在更新个体位置过程中受粒子群优化算法的启发对引力搜索算法的位置更新公式进行了改进；同时为了引导群体向Pareto最优解集区域靠近并保证算法解集均匀分布，采用精英保留策略；最后采用模糊集理论产生最佳折中解，为决策人员提供调度方案。算例分析验证了所提算法的可行性和有效性，为实现电力系统经济性与环保性的均衡优化提供了一条新的方法。