电力系统多目标无功优化调度问题的非支配排序遗传算法III

Sabhan Kanata, S. Suwarno, G. H. Sianipar, Nur Ulfa Maulidevi
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引用次数: 1

摘要

引入非支配排序遗传算法(NSGA-III)求解多目标最优无功调度问题。MORPD是一个非线性、多目标的优化问题,具有非凸、多约束、多变量(离散变量和连续变量混合)的特点。其目的是尽量减少实际功率损失和电压偏差。在IEEE 57总线电力系统上验证了该方法的可行性。将仿真结果与前人采用连续与离散混合变量的研究结果进行比较,结果表明,与多目标增强粒子群优化(MOEPSO)、多目标粒子群优化(MOPSO)和多目标蚁狮优化(MOALO)相比,所提出的优化方法在实际功率损耗和计算周期上都更加高效可靠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-dominated Sorting Genetic Algorithm III for Multi-objective Optimal Reactive Power Dispatch Problem in Electrical Power System
The non-dominated sorting genetic algorithm (NSGA-III) was introduced to solve multi-objective optimal reactive power dispatch (MORPD) problems. MORPD as a non-linear, multi-objective optimization problem has the characteristics of non-convex, multi-constraint, and multi-variable (mix of discrete and continuous variables). The aim is to minimize the real power losses and voltage deviations. The feasibility of the proposed method was tested on the IEEE 57-bus power systems. The comparison of simulation results with the previous studies which applied the mixed variables of continuous and discrete showed that the proposed optimization method is more efficient and reliable in minimize the real power losses and computing period compared to multi-objective enhanced particle swarm optimization (MOEPSO), multi-objective particle swarm optimization (MOPSO) and multi-objective ant lion optimization (MOALO).
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