A Data-Driven approach for optimizing renewable energy production periods using meteorological modeling: Application to solar and wind systems in Benin
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Author |
Mèhundo Walix Leslie De, Patrice Koffi Chetangny, Victor Zogbochi, Gérald Barbier, Macaire Agbomahena and Didier Chamagne
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e-ISSN |
1819-6608 |
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On Pages
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1876-1890
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Volume No. |
20
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Issue No. |
21
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Issue Date |
January 25, 2026
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DOI |
https://doi.org/10.59018/1125211
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Keywords |
photovoltaic, wind, periods, optimal production.
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Abstract
The efficient integration of renewable energy sources into electrical grids requires precise scheduling of the most favourable production periods to maximize energy yield and grid stability. This study proposes a novel methodology for determining the optimal operational periods of photovoltaic (PV) and wind power systems at any geographical location. The approach is based on meteorological modeling and historical data analysis, leveraging past meteorological records to identify both seasonal and diurnal patterns that influence renewable energy generation. The proposed technique was applied to a site in Benin, where key parameters impacting PV output, such as solar irradiation, ambient temperature, and clearness index, were identified, while wind speed was determined to be the primary driver of wind power generation. Data spanning from January 1, 2013, to December 31, 2023, were retrieved from the NASA POWER database. A set of assessment criteria was developed to evaluate the renewable energy potential of a given site and to define the most suitable production windows. These production periods are governed not only by the inherent energy potential of the location but also by the temporal fluctuations of the meteorological parameters influencing PV and wind system performance. The results demonstrate that the proposed method provides a robust framework for characterizing any geographical site in terms of its suitability for standalone PV, standalone wind, and hybrid PV-wind systems. Additionally, it facilitates the determination of optimal production seasons, thereby contributing to improving energy planning and enhanced integration of renewable resources into power systems.
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