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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem


Ahmadipour, Masoud and Ali, Zaipatimah and Othman, Muhammad Murtadha and Bo, Rui and Javadi, Mohammad Sadegh and Ridha, Hussein Mohammed and Alrifaey, Moath (2024) A high-performance democratic political algorithm for solving multi-objective optimal power flow problem. Expert Systems with Applications, 239. art. no. 122367. pp. 1-22. ISSN 0957-4174


The optimal power flow (OPF) is one of the most noticeable and integral tools in the power system operation and control and aims to obtain the most economical combination of power plants to exactly serve the total demand of the system without any load shedding or islanding through adjusting control variables to meet operational, economic, and environmental constraints. To achieve this goal, the successful implementation of an expeditious and reliable optimization algorithm is crucial. To solve this issue, this research proposes an enhanced democratic political algorithm (DPA), which can effectively solve multi-objective optimum power flow problems. The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. For the sake of practicality, the objectives with innate differences such as total emission, active power loss, and fuel cost are selected. Due to the practical limitations in real power systems, additional restrictions including valve-point effect, multi-fuel characteristics, and forbidden operational zones, are also considered. The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. The study results illustrate the effectiveness of the proposed method in handling different scales, non-convex, and multi-objective optimization problems. © 2023 Elsevier Ltd

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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1016/j.eswa.2023.122367
Publisher: Elsevier
Keywords: Emission control; Enhanced political optimizer; Multi-objective optimization; Optimal power flow problem; Pareto optimal technique; Practical constraints
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 08 Feb 2024 02:37
Last Modified: 08 Feb 2024 02:37
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.eswa.2023.122367
URI: http://psasir.upm.edu.my/id/eprint/105663
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