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Article
2024
Computational sizing of solar powered peanut oil extraction in Senegal using a synthetic load profile
Computational sizing of solar powered peanut oil extraction in Senegal using a synthetic load profile
Abstract (English)
This paper presents an approach for sizing a hybrid photovoltaic system for a small-scale peanut oil processing company (Yaye Aissatou, Passy) in rural Senegal using a synthetic load profile. In this study, a predictive model of the electrical load of a service-based plant oil processing company was developed through a diagnosis, to evaluate the extraction process. The mass and energy balance were measured, and the process was implemented into MATLAB Simulink. The simulated load profile was implemented in HOMER Pro and the characteristics of the most profitable hybrid systems were identified. The results showed that the lowest net present cost over 25 years was found with a PV/battery/grid-system with 18.6 kWp solar panels, 16 kWh of storage, and an initial investment of 20,019 €. Compared to a grid-only scenario, this solution reduces the net present cost from an initial 72,163 € to 31,603 €, the operating cost from 3675 € per year to 590 € per year, and the cost of energy from 0.29 to 0.13 €/kWh. The renewable fraction of the proposed system is 90.0 % while the expected payback period is 6.2 years. The study demonstrates the economic feasibility of using solar energy for plant oil processing.
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Energy for sustainable development, 79 (2024), 101391.
https://doi.org/10.1016/j.esd.2024.101391.
ISSN: 0973-0826
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English
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620 Engineering
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Sustainable Development Goals
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@article{Wiomou Joévin Bonzi2024,
url = {https://www.sciencedirect.com/science/article/pii/S0973082624000176},
author = {Wiomou Joévin Bonzi and Sebastian Romuli and Djicknoum Diouf et al.},
title = {Computational sizing of solar powered peanut oil extraction in Senegal using a synthetic load profile},
journal = {Energy for Sustainable Development},
year = {2024},
volume = {79},
}