Optimal Power Flow Analysis with Circulatory System-Based Optimization Algorithm

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.