基于NSGA-Ⅱ算法的多目标静态无功优化

Multi-objective Static Reactive Power Optimization Based on NSGA-Ⅱ Algorithm

由于静态无功优化目标函数大多是单目标或者人为赋予权重系数的多目标函数的组合,本文提出了一种综合优化网损、电压水平和电压稳定性的多目标无功优化模型。为了避免求解时的目标偏好性,引入了快速非支配排序遗传算法,设计了基于实数、整数编码的混合编码方式,通过非支配排序算子和拥挤度算子来协调各目标之间的关系,实现了计及变量约束和潮流约束的静态无功优化。采用方案校验模块完成对Pareto最优解集的校验。以IEEE30节点系统和IEEE118节点系统为算例进行仿真,多次无功优化计算的结果表明了该方法的有效性。

The objective function of static reactive power optimization is mostly single target or a combination of multi-objective function with artificially given weight coefficients. This paper presents a comprehensive multi-objective reactive power optimization model of network losses,voltage level and voltage stability. In order to avoid solving goal preferences,a fast non-dominated sorting genetic algorithm is introduced,and a hybrid coding approach is designed based on real numbers and integers. By the non-dominated sorting operator promoter and congestion operator to coordinate the relationship between the various targets,the paper completed reactive power optimization by taking account of trend constraints and the variables constraints. The program verification module checksum of Pareto optimal solution set was completed. And simulation was made using IEEE 30 node system and IEEE 118 node system,repeated reactive power optimization calculation results show the effectiveness of the method.