Hybrid Optimization Technique for Solving Economic Dispatch Problem: A Case Study of Nigerian Thermal Power System

Authors

  • Gafari Abiola Adepoju Electronic and Electrical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • Muniru Olajide Okelola Electronic and Electrical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
  • Muhammed Adekilekun Tijani Electrical and Electronic Engineering Department, Federal Polytechnic, Ede, Nigeria

Keywords:

Economic Dispatch, Particle Swarm Optimization, Bat Algorithm, Hybrid Optimization Techniques, Generation Costs.

Abstract

Economic Dispatch Problem (EDP) is a power system optimization problem that is required to be solved accurately using an efficient optimization technique. Hybrid optimization solutions have provided better optimum results than either deterministic or non-deterministic optimization methods. The hybridization of both Particle Swarm Optimization (PSO) and Bat Algorithm (BA) to for Hybrid Particle Swarm Bat Algorithm (H-PS-BA) optimization technique for solving EDP of Nigerian 21 thermal generating station power system was carried out in this work. The result of the work revealed that H-PS-BA performed better and gave the best optimal generation costs when compared to other methods such as PSO, Interior Point Method and BA.

Dimensions

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Published

2022-08-29

How to Cite

Hybrid Optimization Technique for Solving Economic Dispatch Problem: A Case Study of Nigerian Thermal Power System. (2022). African Scientific Reports, 1(2), 81–87. https://doi.org/10.46481/asr.2022.1.2.28

Issue

Volume 1, Issue 2, August 2022

Section

Original Research
Copyright & Licensing

Copyright (c) 2022 Gafari Abiola Adepoju, Muniru Olajide Okelola, Muhammed Adekilekun Tijani

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Hybrid Optimization Technique for Solving Economic Dispatch Problem: A Case Study of Nigerian Thermal Power System. (2022). African Scientific Reports, 1(2), 81–87. https://doi.org/10.46481/asr.2022.1.2.28