One day ahead prediction of PV power production: case study of Oued-Elkebrit’s station (Algeria)

dc.contributor.authorNedjem Eddine Benchouia
dc.contributor.authorMohamed SAAIDIA
dc.contributor.authorTalal Belhouchet
dc.contributor.authorKaltoum Achibi
dc.date.accessioned2023-09-03T13:23:37Z
dc.date.available2023-09-03T13:23:37Z
dc.date.issued2019-12-05
dc.description.abstractThe research work presented hereafter is based on a real recorded database of a PV plant in production and in connection with a classical electrical grid. Datasets were processed through two types of techniques. The first one, a classical type, is based on a predictive predefined model, however, the second one is an artificial intelligent method based on neural networks. Based on the carried out experiences, we proposed a new strategy to implement the proposed techniques. The results obtained through the two methods were compared which demonstrate the superiority of the AI method in terms of precision, generalization, and robustness. Obtained results for each method were recorded, analyzed, and compared.
dc.identifier.urihttps://dspace.univ-soukahras.dz/handle/123456789/1470
dc.language.isoen
dc.publisher2019 1st International Conference on Sustainable Renewable Energy Systems and Applications (ICSRESA)
dc.titleOne day ahead prediction of PV power production: case study of Oued-Elkebrit’s station (Algeria)

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