多目标电能质量监测器的优化配置

针对电能质量监测器的优化配置问题,建立了以监测程度和监测器个数为指标的多目标优化配置模型。采用带精英策略的快速非支配排序遗传算法(non-domtnated soring genetic algorithm,NSGA-Ⅱ),获得此多目标优化问题的Pareto最优解集。该方法能保证种群的多样性,避免传统加权求解时权值的选择和解的偏好性。最后,对Pareto最优解集的各个目标函数进行归一化处理,将最大值对应的方案作为合适的最优解。通过对2个算例进行仿真,得到了合理的电能质量监测器的配置方案,验证了该方法的可行性和有效性。

Optimal Placement of Power Quality Monitors Based on Multi-objective Evolutionary Algorithm

In allusion to the optimal placement of power quality monitors in power system,a multi-objective optimal placement model,in which the monitoring extent and the numbers of monitors are taken as objects,is built.The fast Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ) with elitist strategy is adopted to obtain Pareto optimal solutions of this multi-objective optimization problem.The proposed method can ensure the diversity of populations and avoid the selection of weight and the preference of the solution when traditional weighed solving is utilized.The objective functions in Pareto optimal solution set are normalized and the scheme corresponding to the maximum value is chosen as the appropriate optimal solution.Through the simulation of a 5-bus system and IEEE 37-bus system,a reasonable scheme for the placement of power quality monitors is obtained;meanwhile the feasibility and effectiveness of the proposed method are verified.