Détails Publication
Validation of Global Solar Radiation Models on a Horizontal Surface in the Climatic Zones of Burkina,
Lien de l'article: DOI: 10.9734/PSIJ/2022/v26i5742
Discipline: Sciences physiques
Auteur(s): Nana Goumwêndkouni Gilbert , Konfé Amadou , Ouédraogo Souleymane , KyThierry Sikoudouin Maurice , Kam Sié and Bathiébo M. J. Dieudonné
Renseignée par : BATHIEBO Dieudonné Joseph
Résumé

The evaluation of the solar deposit is essential for the sizing of photovoltaic systems. This requires the availability of radiation data. In Burkina Faso, weather data doesn’t cover all the country. That makes that solar radiation measured are not available for the all country. Theorical methods can help about it. This paper is written to fill the gap of adapted solar models for the country. In this work, an analysis of the results provided by four models for the estimation of hourly values of global radiation on a horizontal plane was made. The radiation data for the year 2017 comes from the Burkina weather forecast. The validation of the models is carried out by a comparison between the radiation measured and that given by the various models provided by MATLAB code. The different models have been validated by several statistical indicators (RMSE and normalized MAE) and graphs for a clear sky. Scoring criteria have been established to assess the relative quality of each model. The models retained for the study are the Bird and Hulstrom model, the Davy and Hay model, the Capderou model and the Liu and Jordan model. Three sites were affected: Ouagadougou, Dori and Gaoua. We found that for some models, there is a good agreement between the measured values and those estimated by some models for the Dori site, while they are not with the values measured for the Ouagadougou and Gaoua sites. In the town of Dori, the most appropriate model for estimating solar radiation is that of Bird and Hulstrom. For the cities of Ouagadougou and Gaoua, the different models are not suitable.

Mots-clés

Solar radiation, semi-empirical model, statistical indicators, estimate

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