September 25, 2025EnergiesOpen Access

Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems for Sustainable Agricultural Development in Sub-Saharan Africa

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Authors

TBTom Cherif Bilio MAMahamat Adoum Abdoulaye SWSebastian Waita

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Implication

This analysis demonstrates multi-objective optimization in renewable energy systems for agriculture, indicating enhanced economic and social outcomes.

Key Points

The optimal renewable energy configuration reduced CO2 emissions by 9.58 × 10^8 kg and reached the lowest LCOE of $0.0948/kWh.
The particle swarm optimization algorithm effectively minimized costs while maximizing social benefits and environmental sustainability in rural settings.
Three system architectures were analyzed under different reliability levels, with the PV–Wind–Battery design proving most advantageous overall.
Policymakers can use this methodology for improving access to clean energy in underserved regions, fostering agricultural development and social inclusion.

Cite This Study

Bilio et al. (2025) studied this question.

synapsesocial.com/papers/68d5d0d7ddad3c16d4635dc2 https://doi.org/10.3390/en18195058

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Implication

This analysis demonstrates multi-objective optimization in renewable energy systems for agriculture, indicating enhanced economic and social outcomes.

Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems for Sustainable Agricultural Development in Sub-Saharan Africa

Discussion

Member takes

Implication

Key Points

Cite This Study

Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems for Sustainable Agricultural Development in Sub-Saharan Africa

Discussion

Member takes

Implication

Key Points

Cite This Study

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