Optimal Sizing of Isolated Hybrid Microgrid for Residential Community in Saudi Arabia

This paper mainly focuses on the optimal design of microgrid hybrid renewable energy system (RES). The developed system in this work includes photovoltaic (PV), wind turbine (WT), diesel generator (DG), along with an energy storage component comprising a battery system. The optimal components sizes of the proposed hybrid generating system has been achieved using a recent metaheuristic optimization technique called artificial rabbits optimization (ARO). The presented algorithm aims to address a multi-objective optimization challenge, seeking to minimize the cost of energy (COE), the reliability index characterized by the loss of power supply probability (LPSP), and excess energy within specified constraints. The hybrid system is developed for deployment in the coastal residential community of Yanbu, located in the Medina province of Saudi Arabia (at 24.16° north latitude and 37.32° east longitude), with a planned operational lifespan of 25 years. To ensure the precision, stability, and robustness of the developed algorithm in addressing the optimization problem, a comprehensive comparison is conducted with the results generated by well-established optimization algorithms, including the Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA). This comparative study assesses the impact of reliability indices on the optimal sizing of the proposed isolated hybrid RES, highlighting that the ARO algorithm excels in identifying the most efficient system configuration to be the most cost-effective and eco-friendly option.

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Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/aupec62273.2024.10807632
Citations
5
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.64
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article

Optimal Sizing of Isolated Hybrid Microgrid for Residential Community in Saudi Arabia

Salah Kamel, Hamdy M. Sultan, I.O. Habiballah, Ahmed S. Menesy et al.
5 citations
Microgrid Control and Optimization
1.64
article

Optimal Sizing of Isolated Hybrid Microgrid for Residential Community in Saudi Arabia

Salah Kamel, Hamdy M. Sultan, I.O. Habiballah, Ahmed S. Menesy, Waleed M. Hamanah, M. A. Abido
article en
5 citations

Abstract

This paper mainly focuses on the optimal design of microgrid hybrid renewable energy system (RES). The developed system in this work includes photovoltaic (PV), wind turbine (WT), diesel generator (DG), along with an energy storage component comprising a battery system. The optimal components sizes of the proposed hybrid generating system has been achieved using a recent metaheuristic optimization technique called artificial rabbits optimization (ARO). The presented algorithm aims to address a multi-objective optimization challenge, seeking to minimize the cost of energy (COE), the reliability index characterized by the loss of power supply probability (LPSP), and excess energy within specified constraints. The hybrid system is developed for deployment in the coastal residential community of Yanbu, located in the Medina province of Saudi Arabia (at 24.16° north latitude and 37.32° east longitude), with a planned operational lifespan of 25 years. To ensure the precision, stability, and robustness of the developed algorithm in addressing the optimization problem, a comprehensive comparison is conducted with the results generated by well-established optimization algorithms, including the Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA). This comparative study assesses the impact of reliability indices on the optimal sizing of the proposed isolated hybrid RES, highlighting that the ARO algorithm excels in identifying the most efficient system configuration to be the most cost-effective and eco-friendly option.

King Fahd University of Petroleum and Minerals (SA), Aswan University (EG), Minia University (EG)
Sustainable cities and communities
Openalex Percentile: Top 15%
Microgrid Control and Optimization
1.64
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Optimal Sizing of Isolated Hybrid Microgrid for Residential Community in Saudi Arabia — Salah Kamel, Hamdy M. Sultan, et al. · (2024) | TGRS Research Map | TGRS