Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Ahmed M. Nassef, Mohammad Ali Abdelkareem, Hussein M. Maghrabie, Ahmad Baroutaji

Research output: Contribution to journalReview articlepeer-review


Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field.
Original languageEnglish
Article number9434
Number of pages27
Issue number12
Early online date12 Jun 2023
Publication statusPublished - 12 Jun 2023

Bibliographical note

Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( Funding Information: This study was sponsored by the Prince Sattam bin Abdulaziz University via project number 2023/RV/016.


  • Management, Monitoring, Policy and Law
  • Renewable Energy, Sustainability and the Environment
  • Geography, Planning and Development
  • Building and Construction


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