MODÈLE DE SYSTÈME D'INFÉRENCE FOU ADAPTATIVE BASÉ SUR UN RÉSEAU NON LINÉAIRE POUR L'ESTIMATION HORAIRE DE L'IRRADIATION SOLAIRE
DOI :
https://doi.org/10.59277/RRST-EE.2023.68.1.1Mots-clés :
Solar irradiation, ANFIS, grid partitioning, fuzzy C-means, subtractive clusteringRésumé
L'énergie solaire occupe une place importante parmi les différentes sources d'énergie renouvelable. Une connaissance précise de la répartition du rayonnement solaire dans un lieu déterminé est nécessaire avant toute installation de système de rayonnement solaire. Cet article présente un modèle de système d'inférence floue basé sur un réseau adaptatif (ANFIS) de clustering non linéaire pour estimer les données d'irradiation solaire horaire à l'aide d'entrées météorologiques et d'algorithmes de clustering : partitionnement de grille, clustering soustractif et c-means flous. La comparaison de ces algorithmes de clustering est étudiée pour classer les entrées en clusters, ce qui aide à mieux construire le modèle d'estimation de l'irradiation solaire. L'avantage de cette méthode est de comprendre et de simplifier la non-linéarité présentée dans les jeux de données d'entrée. De plus, l'algorithme FCM donne les meilleurs résultats en comparant les données de test ; le RMSE est de 43,2274 W/m2 et le MSE est égal à 2001,34 W/m2 avec un R2 égal à 0,9893.
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