Feasibility design, comparative evaluation, and energy consumption prediction of standalone hybrid energy system for rural electrification in Ghana using machine learning models

• Novel integration of machine learning models enhance energy consumption predictions, improving the accuracy of system design and optimization. • Innovative hybrid system's Levelized Cost of Energy (LCOE) is $0.0263/kWh, with a renewable fraction of 91.5 %. • The optimal system comprises a 112 kW SPV array, 80 kW DG, 342 kWh BS, and a 54-kW converter. • This solution is economically viable and environmentally sustainable for Ghana's off-grid communities. • Insights from Electric Distance Limit (7.5 km) shows the hybrid system is more viable than grid extension for rural Ghana. This study investigated the feasibility and sustainability of standalone hybrid energy systems for rural electrification in Ghana. The problem addressed was the lack of electricity access in rural areas of Ghana, despite progress in increasing access rates in urban areas. The importance of this study lies in identifying a reliable, affordable, and environmentally sustainable solution to bridge the electrification gap. This study employed a comprehensive analysis of different system configurations, including Solar Photovoltaic (SPV), Diesel Generators (DG), and Battery Storage (BS), using the Hybrid Optimization of Multiple Electric Resources (HOMER) software. The integration of machine learning models into the design process was also explored to enhance the accuracy of energy consumption predictions. The economic, technical, and environmental aspects of each alternative are evaluated. The significant results obtained from the analysis showed that the optimal design for the standalone hybrid energy system consisted of a 112 kW SPV array, 80 kW DG, 342 kWh BS, and a 54-kW converter. The Levelized Cost of Energy (LCOE) obtained from this configuration was $0.0263/kWh, with a renewable fraction of 91.5 %. The Net Present Cost (NPC) of the system was also the lowest among the alternatives, amounting to $244,937. Further investigation of the Electric Distance Limit (EDL) of the optimal solution is 7.5 km which depicts that, although grid-connected electricity may seem more affordable, the proposed standalone hybrid energy system is a more viable option for remote communities that are far from the grid and makes it a suitable solution for addressing the electricity access gap in Ghana's rural areas.

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Publication Details

Journal
Results in Engineering
Published
2025-02-06
DOI
https://doi.org/10.1016/j.rineng.2025.104269
Citations
9
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
4.79
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article

Feasibility design, comparative evaluation, and energy consumption prediction of standalone hybrid energy system for rural electrification in Ghana using machine learning models

Sarfaraz Kamangar, Ravi Samikannu, Abid Yahya, Nyagong Santino David Ladu et al.
9 citations
Results in Engineering
Hybrid Renewable Energy Systems
4.79
article

Feasibility design, comparative evaluation, and energy consumption prediction of standalone hybrid energy system for rural electrification in Ghana using machine learning models

Sarfaraz Kamangar, Ravi Samikannu, Abid Yahya, Nyagong Santino David Ladu, Maruliya Begam Kadarmydeen, Maxmilian Kwarteng, Sufyan Yakubu, Irfan Anjum Badruddin, Samuel Dodobatia Wetajega
article en
9 citations

Abstract

• Novel integration of machine learning models enhance energy consumption predictions, improving the accuracy of system design and optimization. • Innovative hybrid system's Levelized Cost of Energy (LCOE) is $0.0263/kWh, with a renewable fraction of 91.5 %. • The optimal system comprises a 112 kW SPV array, 80 kW DG, 342 kWh BS, and a 54-kW converter. • This solution is economically viable and environmentally sustainable for Ghana's off-grid communities. • Insights from Electric Distance Limit (7.5 km) shows the hybrid system is more viable than grid extension for rural Ghana. This study investigated the feasibility and sustainability of standalone hybrid energy systems for rural electrification in Ghana. The problem addressed was the lack of electricity access in rural areas of Ghana, despite progress in increasing access rates in urban areas. The importance of this study lies in identifying a reliable, affordable, and environmentally sustainable solution to bridge the electrification gap. This study employed a comprehensive analysis of different system configurations, including Solar Photovoltaic (SPV), Diesel Generators (DG), and Battery Storage (BS), using the Hybrid Optimization of Multiple Electric Resources (HOMER) software. The integration of machine learning models into the design process was also explored to enhance the accuracy of energy consumption predictions. The economic, technical, and environmental aspects of each alternative are evaluated. The significant results obtained from the analysis showed that the optimal design for the standalone hybrid energy system consisted of a 112 kW SPV array, 80 kW DG, 342 kWh BS, and a 54-kW converter. The Levelized Cost of Energy (LCOE) obtained from this configuration was $0.0263/kWh, with a renewable fraction of 91.5 %. The Net Present Cost (NPC) of the system was also the lowest among the alternatives, amounting to $244,937. Further investigation of the Electric Distance Limit (EDL) of the optimal solution is 7.5 km which depicts that, although grid-connected electricity may seem more affordable, the proposed standalone hybrid energy system is a more viable option for remote communities that are far from the grid and makes it a suitable solution for addressing the electricity access gap in Ghana's rural areas.

Results in EngineeringVol. 25
Periyar Maniammai Institute of Science & Technology (IN), Botswana International University of Science and Technology (BW), University of Abou Bekr Belkaïd (DZ), Rumbek University (SS), Pan African University Institute of Water and Energy Science, Bolgatanga Technical University, King Khalid University (SA), Saveetha University (IN)
Affordable and clean energy
Openalex Percentile: Top 5%
Hybrid Renewable Energy Systems
4.79
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