Multi-Objective Optimal Power Flow Incorporating Flexible Alternating Current Transmission Systems: Application of a Wavelet-Oriented Evolutionary Algorithm

• Published in: Electric power components and systems Vol. 52; no. 5; pp. 766 - 795
• Main Authors: Naderi, Ehsan, Mirzaei, Lida, Trimble, Jonas P., Cantrell, Denae A.
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 15.03.2024; Taylor & Francis Ltd
• Subjects: Algorithms; Alternating current; Compensators; Evolutionary algorithms; Flexible AC power transmission systems; Heuristic methods; Hybrid wavelet mutation based shuffled frog leaping algorithm-wavelet mutation based particle swarm optimization (HWM; multi-objective optimal power flow (MOOPF); Multiple objective analysis; Mutation; Pareto archived evolution strategy (PAES); Particle swarm optimization; Power; Power flow; SFLA-PSO; thyristor controlled series compensator (TCSC); Thyristors; Transmission loss; unified power flow controller (UPFC)
• ISSN: 1532-5008; 1532-5016
• DOI: 10.1080/15325008.2023.2234378

This article presents a meta-heuristic hybrid algorithm to solve multi-objective optimal power flow (MOOPF) taking into account multi-fuel constraint. Four different objective functions, which comprise total generation cost, emission, real power transmission losses, and voltage deviation, are simultaneously considered in the proposed MOOPF. Furthermore, two types of flexible alternating current transmission system (FACTS) devices are utilized including thyristor controlled series compensator (TCSC) and unified power flow controller (UPFC). Considering all of the aspects referred to above makes the traditional OPF problem more complicated; hence, it is necessary to approach the problem by a powerful optimization algorithm. Toward this end, this article develops a hybrid algorithm oriented to shuffled frog leaping algorithm (SFLA) and particle swarm optimization (PSO), called hybrid wavelet mutation (WM) based SFLA-wavelet mutation based PSO (HWM 2 SFLA-PSO). Obtained results validate the effectiveness of the proposed hybrid algorithm in solving different forms of the OPF problem on IEEE test systems compared to those available in the literature. Moreover, the comparison substantiates the superiority of the proposed HWM 2 SFLA-PSO algorithm in terms of execution time, quality of solution as well as preventing from convergence to local optima, to name but three.