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ARTICLE

Energy Management Control Strategy for Renewable Energy System Based on Spotted Hyena Optimizer

Hegazy Rezk^1,2,*, Ahmed Fathy^3,4, Mokhtar Aly^5,6, Mohamed N. Ibrahim^7,8,9

1 College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Wadi Addawaser, 11991, Saudi Arabia
2 Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, 61111, Egypt
3 Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka, Saudi Arabia
4 Electrical Power and Machine Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt
5 Department of Electrical Engineering, Aswan University, Aswan, 81542, Egypt
6 Electronics Engineering Department, Universidad Tecnica Federico Santa Maria, Valparaiso, 2390123, Chile
7 Department of Electromechanical, Systems and Metal Engineering, Ghent University, Ghent, 9000, Belgium
8 FlandersMake@UGent–corelab EEDT-MP, 3001, Leuven, Belgium
9 Electrical Engineering Department, Kafrelshiekh University, Kafr el-Sheikh, 33511, Egypt

* Corresponding Author: Hegazy Rezk. Email:

(This article belongs to the Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)

Computers, Materials & Continua 2021, 67(2), 2271-2281. https://doi.org/10.32604/cmc.2021.014590

Received 01 October 2020; Accepted 21 November 2020; Issue published 05 February 2021

Abstract

Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management strategy (EMS) is essential. In this research work, an optimal EMS based on a spotted hyena optimizer (SHO) for hybrid PEM fuel cell/BS/SC is proposed. The main goal of an EMS is to improve the performance of hybrid FC/BS/SC and to reduce the amount of hydrogen consumption. To prove the superiority of the SHO method, the obtained results are compared with the chimp optimizer (CO), the artificial ecosystem-based optimizer (AEO), the seagull optimization algorithm (SOA), the sooty tern optimization algorithm (STOA), and the coyote optimization algorithm (COA). Two main metrics are used as a benchmark for the comparison: the minimum consumed hydrogen and the efficiency of the system. The main findings confirm that the minimum amount of hydrogen consumption and maximum efficiency are achieved by the proposed SHO based EMS.

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Citations