Optimal Power Flow Analysis with Circulatory System-Based Optimization Algorithm

Hüseyin BAKIR
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Abstract

Optimal power flow (OPF) is one of the most challenging optimization problems of power engineering. Owing to the high computational complexity of the OPF problem, a powerful and robust optimization algorithm is required to solve it. This paper has been centered on the optimization of OPF problem using circulatory system-based optimization (CSBO) algorithm. The solution quality of CSBO is compared with the recently introduced state-of-the-art metaheuristic algorithms i.e., artificial rabbits optimization (ARO), african vultures optimization algorithm (AVOA), and chaos game optimization (CGO). The practicability of the algorithms was evaluated on the IEEE-57 and 118-bus power networks for the optimization of various objectives, i.e., fuel cost, power loss, voltage deviation, and enhancement of voltage stability. Based on OPF results of the IEEE 57-bus power system, it is seen that the best fuel cost and voltage deviation results are calculated to be 41666.2344 $/h and 0.5871 p.u with the CSBO method. Given the OPF results of the IEEE 118-bus power network, it is observed that the CSBO algorithm presented the best fuel cost and active power loss values of 134934.3140 $/h, and 16.4688 MW. Moreover, OPF solutions obtained from 30 algorithm runs were analyzed using the Wilcoxon statistical test method. Consequently, the present paper reports that the CSBO algorithm produces better-quality OPF solutions compared to its competitors and other literature studies.
基于循环系统优化算法的最优潮流分析
最优潮流是电力工程中最具挑战性的优化问题之一。由于OPF问题的计算复杂度很高,需要一种强大的鲁棒优化算法来求解。本文主要研究了基于循环系统优化(CSBO)算法的OPF优化问题。将CSBO的解质量与最近引入的最先进的元启发式算法,即人造兔子优化算法(ARO)、非洲秃鹫优化算法(AVOA)和混沌博弈优化算法(CGO)进行了比较。在IEEE-57和118母线电网上对算法的实用性进行了评估,以优化燃料成本、功率损耗、电压偏差和增强电压稳定性等多个目标。基于IEEE 57总线电力系统的OPF结果可以看出,采用CSBO方法计算得到的最佳燃料成本和电压偏差分别为41666.2344美元/h和0.5871 p.u。结合IEEE 118总线电网的OPF结果可知,CSBO算法的燃油成本和有功损耗分别为134934.3140 $/h和16.4688 MW,最优。利用Wilcoxon统计检验方法对30次算法运行得到的OPF解进行分析。因此,本文报告了CSBO算法比其竞争对手和其他文献研究产生更好质量的OPF解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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