A modified grey wolf optimizer for improving wind plant energy production

Mohd Zaidi, Mohd Tumari and Mohd Helmi, Suid and Mohd Ashraf, Ahmad (2020) A modified grey wolf optimizer for improving wind plant energy production. Indonesian Journal of Electrical Engineering and Computer Science, 18 (3). pp. 1123-1129. ISSN 2502-4752. (Published)

[img]
Preview
Pdf (Open access)
A modified grey wolf optimizer for improving wind plant.pdf
Available under License Creative Commons Attribution Share Alike.

Download (467kB) | Preview

Abstract

The main problem of existing wind plant nowadays is that the optimum controller of single turbine degrades the total energy production of wind farm when it is located in a large wind plant. This is owing to its greedy control policy that can not cope with turbulence effect between turbines. This paper proposes a Modified Grey Wolf Optimizer (M-GWO) to improvise the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The modification employed to the original GWO is in terms of the updated mechanism. This modification is expected to improve the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-GWO is applied to maximize energy production of a row of ten turbines. The model of the wind plant is derived based on the real Horns Rev wind plant in Denmark. The statistical performance analysis shows that the M-GWO provides the highest total energy production as compared to the standard GWO, Particle Swarm Optimization (PSO) and Safe Experimentation Dynamics (SED) methods.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Wind farm; Wake interactions; Energy production; Metaheuristic algorithm; Nature inspired algorithm
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 27 Apr 2022 02:43
Last Modified: 27 Apr 2022 02:43
URI: http://umpir.ump.edu.my/id/eprint/30144
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item