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Chapitre d'ouvrage

A GRNN Based Algorithm for Output Power Prediction of a PV Panel

Abstract : In this paper we investigated the reliability of a GRNN algorithm for the power prediction of a PV panel in order to minimize the effect of fast changing of the meteorological conditions. An experimental database of meteorological data (irradiance and module temperature) as input and electrical measure (power delivered by PV Panel) as output has been used. A database composed of two sets 97 values each one is used for training and validating the proposed GRNN model. The data used to develop the proposed algorithm are attained during two separated days from a PV panel within the MIS-Lab of UPJV, France. According to the gained results the algorithm can help to predict real instantaneous power even during temporary change in meteorological data.
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Chapitre d'ouvrage
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Contributeur : Louise Dessaivre Connectez-vous pour contacter le contributeur
Soumis le : mercredi 6 avril 2022 - 18:57:11
Dernière modification le : vendredi 8 avril 2022 - 03:30:56



Kamal Kerbouche, S. Haddad, A. Rabhi, A. Mellit, M. Hassan, et al.. A GRNN Based Algorithm for Output Power Prediction of a PV Panel. Hatti, M. ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS: SMART SUSTAINABLE ENERGY SYSTEMS, 35, pp.291-298, 2018, Lecture Notes in Networks and Systems, 978-3-319-73192-6; 978-3-319-73191-9. ⟨10.1007/978-3-319-73192-6\_30⟩. ⟨hal-03633230⟩



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