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

Abstract

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 (HWM²SFLA-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 HWM²SFLA-PSO algorithm in terms of execution time, quality of solution as well as preventing from convergence to local optima, to name but three.

Keywords:

• Hybrid wavelet mutation based shuffled frog leaping algorithm-wavelet mutation based particle swarm optimization (HWM²SFLA-PSO)
• multi-objective optimal power flow (MOOPF)
• Pareto archived evolution strategy (PAES)
• thyristor controlled series compensator (TCSC)
• unified power flow controller (UPFC)

Disclosure Statement

The authors declare no conflict of interest.

Additional information

Notes on contributors

Ehsan Naderi

Ehsan Naderi received the Ph.D. degree in Electrical Engineering from Southern Illinois University (SIU), Carbondale, IL, USA, in May 2023. He was the recipient of the Dissertation Research Fellowship award from the College of Engineering, Computing, Technology, and Mathematics for the academic year of 2022-2023. Moreover, his dissertation has been nominated for the Richard and Donna Falvo Outstanding Dissertation award at SIU. In addition to several best paper awards from IEEE conferences (e.g., 2022 IGESSC, 2022 AIIoT, etc.), he also received four outstanding reviewer awards from top-field journals (e.g., IJEPES, EAAI, etc.) in recognition of his professional services. Dr. Naderi is currently an Assistant Professor with the Department of Electrical Engineering, College of Engineering and Computer Science, Arkansas State University, Jonesboro, AR, USA. He is an editor of Frontiers in Smart Grids - Grid Efficiency and a reviewer for more than 40 scientific journals in addition to being an IEEE member as well as a member of the power & energy, industrial electronics, power electronics, and industry applications societies. The focus of his research is on the application of machine learning to smart grid security and operation of modern cyber-physical power systems (CPPSs).

Lida Mirzaei

Lida Mirzaei is an award-winning freelance researcher who specializes in Electrical Engineering with concentration on the operation of smart power systems. As a pivotal team member to overseas research projects, she has a wide range of international collaborations with different institutions in the field of power systems operation, control, and optimization. She is a member of IEEE and power & energy society (PES). Her current research focuses on the application of optimization techniques and artificial intelligence to electric power systems in general, and in particular on the integration of clean electric energy and eco-friendly energy storage systems into modern power grids.

Jonas P. Trimble

Jonas P. Trimble received the B.Sc. degree in Electrical Engineering from Southern Illinois University, Carbondale, IL, USA in December 2021. From 2019 to 2022, he was an electrical engineering intern with Mt. Carmel Public Utility Company (MCPU), Mount Carmel, IL, USA. He is currently a control engineer with Automation Solution of America, Beloit, WI, USA. His research interests include power system operation, control, and optimization, renewable energy integration, and flexible AC transmission systems (FACTS).

Denae A. Cantrell

Denae A. Cantrell is currently working toward the B.Sc. degree with the School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA. She received the University Excellence Scholar award for the academic years of 2020-2024. In addition, she was the recipient of Dr. Glafkos Galanos Memorial Scholarship from the School of Electrical, Computer, and Biomedical Engineering for the academic year of 2022-2023 in recognition of her outstanding academic achievements. Her current research interests comprise the applications of metaheuristic optimization algorithms applied to power and control systems.