基于改进非支配排序遗传算法的电力系统无功–潮流多目标协同优化调度

Power System Reactive Power-Power Flow Multi-objective Cooperative Optimal Dispatch Based on Improved NSGA-Ⅱ

提出了一种改进非支配排序遗传(Non-dominated sorting genetic algorithms,NSGA)-Ⅱ算法,其种群局部搜索和外部种群的设置有效提高了算法的收敛性和解集的多样性。将该算法应用于电力系统无功–潮流多目标协同优化调度问题的求解。采用IEEE-14和IEEE-30母线系统进行算例分析。算例仿真的结果表明,应用所提方法能够兼顾电力系统运行的无功优化目标和潮流优化目标,实现无功最优和潮流最优的折中;同时,改进NSGA-Ⅱ算法在收敛性和解集多样性上都优于传统NSGA-Ⅱ算法。

An improved Non-dominated Sorting Genetic Algorithm(NSGA)-Ⅱis proposed.The local search of population and the setting of external population effectively improve the convergence of the algorithm and the diversity of the solution set,and it is applied for solving the power system reactive power-power flow multi-objective cooperative optimal dispatch problem.The IEEE-14 and IEEE-30 bus systems are used for case studies.The simulation results show that the proposed method can take into account the reactive power optimization and power flow optimization objectives of power system operation,and achieve the compromise between reactive power optimization and power flow optimization;At the same time,the improved NSGA-Ⅱis superior to the traditional NSGA-Ⅱin convergence and diversity of solution sets.