Swarm intelligence technique for solving optimal power flow problem in the Nigeria power system
Department of Electrical Engineering, Nnamdi Azikiwe University, Awka, Nigeria.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2023, 10(02), 133–140.
Article DOI: 10.30574/wjaets.2023.10.2.0297
Publication history:
Received on 22 October 2023; revised on 05 December 2023; accepted on 08 December 2023
Abstract:
This paper deals on the implementation of the particle swarm optimization method for solving power flow problems in the Nigeria power system. The difficulty of solving optimal power flow (OPF) problems increases significantly with increasing network size and complexity. Some of the weakness of the conventional methods include: limited ability in solving real-world large scale optimization problems, weakness in handling constraints, poor convergence and slow computational time. The results gotten by implementing the Particle Swarm Optimization (PSO) algorithm in Nigeria 330kV 52-Bus network show that the total active power and reactive power losses were substantially reduced to 0.03MW and 0.05MVAR. The system time of convergence was faster at 0.5seconds. Also, the maximum line active and reactive power losses on line 1 to 2 were reduced greatly to 0.00MW and 0.01MVAR respectively. These show that the system was better optimized with the PSO algorithm than the conventional method.
Keywords:
Swarm; Particle; Optimization; Optimal; Constraints; Variable; Convergence
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0