Training and Testing of a Single-Layer LSTM Network for Near-Future Solar Forecasting

Training and Testing of a Single-Layer LSTM Network for Near-Future Solar Forecasting

Increasing integration of renewable energy sources, like solar photovoltaic (PV), necessitates the development of power forecasting tools to predict power fluctuations caused by weather. With trustworthy and accurate solar power forecasting models, grid operators could easily determine when other di...

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Bibliographic Details
Main Authors: Naylani Halpern-Wight, Maria Konstantinou, Alexandros G. Charalambides, Angèle Reinders
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Applied Sciences
Subjects:
solar forecasting
machine learning
artificial neural networks
LSTM networks
Online Access:https://www.mdpi.com/2076-3417/10/17/5873

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https://www.mdpi.com/2076-3417/10/17/5873

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