Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification

Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based e...

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Main Authors: Ramia Ouederni, Innocent E. Davidson
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/18/13/3456
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author Ramia Ouederni
Innocent E. Davidson
author_facet Ramia Ouederni
Innocent E. Davidson
author_sort Ramia Ouederni
collection DOAJ
description Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote areas. In this case study, an isolated village in Namibia, characterized by high levels of solar irradiation and limited wind availability, is identified. Using NASA data, an autonomous hybrid system incorporating a solar photovoltaic array, a wind turbine, storage batteries, and a backup generator is designed. The local load profile, solar irradiation, and wind speed data were employed to ensure an accurate system model. Using HOMER Pro software V 3.14.2 for system simulation, a more advanced AI optimization was performed utilizing Grey Wolf Optimization and Harris Hawks Optimization, which are two metaheuristic algorithms. The results obtained show that the best performance was obtained with the Grey Wolf Optimization algorithm. This method achieved a minimum energy cost of USD 0.268/kWh. This paper presents the results obtained and demonstrates that advanced optimization techniques can enhance both the hybrid system’s financial cost and energy production efficiency, contributing to a sustainable electricity supply regime in this isolated rural community.
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spelling doaj-art-868095492b9f4e769e4b18512e1b73232025-08-20T03:50:16ZengMDPI AGEnergies1996-10732025-07-011813345610.3390/en18133456Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote ElectrificationRamia Ouederni0Innocent E. Davidson1Computer Laboratory for Electrical Systems, LR11ES26, INSAT, University of Carthage, Tunis 1080, TunisiaAfrica Space Innovation Centre, French-South African Institute of Technology, Department of Electrical, Electronic and Computer Engineering, Cape Peninsula University of Technology, Cape Town 7535, South AfricaOff-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote areas. In this case study, an isolated village in Namibia, characterized by high levels of solar irradiation and limited wind availability, is identified. Using NASA data, an autonomous hybrid system incorporating a solar photovoltaic array, a wind turbine, storage batteries, and a backup generator is designed. The local load profile, solar irradiation, and wind speed data were employed to ensure an accurate system model. Using HOMER Pro software V 3.14.2 for system simulation, a more advanced AI optimization was performed utilizing Grey Wolf Optimization and Harris Hawks Optimization, which are two metaheuristic algorithms. The results obtained show that the best performance was obtained with the Grey Wolf Optimization algorithm. This method achieved a minimum energy cost of USD 0.268/kWh. This paper presents the results obtained and demonstrates that advanced optimization techniques can enhance both the hybrid system’s financial cost and energy production efficiency, contributing to a sustainable electricity supply regime in this isolated rural community.https://www.mdpi.com/1996-1073/18/13/3456hybrid systemcost of energysmart energyGrey Wolf OptimizationHarris Hawks Optimizationartificial intelligence
spellingShingle Ramia Ouederni
Innocent E. Davidson
Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
Energies
hybrid system
cost of energy
smart energy
Grey Wolf Optimization
Harris Hawks Optimization
artificial intelligence
title Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
title_full Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
title_fullStr Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
title_full_unstemmed Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
title_short Co-Optimized Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification
title_sort co optimized design of islanded hybrid microgrids using synergistic ai techniques a case study for remote electrification
topic hybrid system
cost of energy
smart energy
Grey Wolf Optimization
Harris Hawks Optimization
artificial intelligence
url https://www.mdpi.com/1996-1073/18/13/3456
work_keys_str_mv AT ramiaouederni cooptimizeddesignofislandedhybridmicrogridsusingsynergisticaitechniquesacasestudyforremoteelectrification
AT innocentedavidson cooptimizeddesignofislandedhybridmicrogridsusingsynergisticaitechniquesacasestudyforremoteelectrification