Long-term power forecasting using FRNN and PCA models for calculating output parameters in solar photovoltaic generation

Long-term power forecasting using FRNN and PCA models for calculating output parameters in solar photovoltaic generation

This paper evaluated a 1.4 kW grid-connected photovoltaic system (GCPV) using two neural network models based on experimental data for one year. The novelty of this study is to propose and compare full recurrent neural network (FRNN), and principal component analysis (PCA) models based on entire yea...

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Bibliographic Details
Main Authors: Hussein A. Kazem, Jabar H. Yousif, Miqdam T. Chaichan, Ali H.A. Al-Waeli, K. Sopian
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Heliyon
Subjects:
Grid connected PV
Recurrent neural
Principal component analysis
Desert type PV
ANN
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844022000913

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