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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Mohd Ashraf Ahmad
University Malaysia Pahang
Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Optimal tuning of a wind plant energy production based on improved grey wolf optimizer Mohd Zaidi Mohd Tumari; Mohd Muzaffar Zahar; Mohd Ashraf Ahmad
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2509

Abstract

The tuning of optimal controller parameters in wind plant is crucial in order to minimize the effect of wake interaction between turbines. The purpose of this paper is to develop an improved grey wolf optimizer (I-GWO) in order to tune the controller parameters of the turbines so that the total energy production of a wind plant is increased. The updating mechanism of original GWO is modified to improve the efficiency of exploration and exploitation phase while avoiding trapping in local minima solution. A row of ten turbines is considered to evaluate the effectiveness of the I-GWO by maximizing the total energy production. The proposed approach is compared with original GWO and previously published modified GWO. Finally, I-GWO produces the highest total energy production as compared to other methods, as shown in statistical performance analysis.
Metaheuristics algorithms to identify nonlinear Hammerstein model: a decade survey Julakha Jahan Jui; Mohd Ashraf Ahmad; Muhammad Ikram Mohd Rashid
Bulletin of Electrical Engineering and Informatics Vol 11, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i1.3296

Abstract

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, have gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. As such, this article serves as a guideline on the fundamentals of identifying nonlinear block-oriented models for new practitioners, apart from presenting a comprehensive summary of cutting-edge trends within the context of this topic area.
Co-Authors Herlina Abdul Rahim Julakha Jahan Jui Md. Nazibul Hasan Mohamed Sultan Mohamed Ali Mohd Muzaffar Zahar Mohd Zaidi Mohd Tumari Muhammad Ikram Mohd Rashid