Optimal Power Flow Analysis with Circulatory System-Based Optimization Algorithm
Turkish journal of engineering(2023)
摘要
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.
更多查看译文
关键词
optimal power flow analysis,optimization,system-based
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要