Applications of Machine Learning Algorithms in Renewable Energies
LSTM and XGBoost models for 24-hour photovoltaic power forecasting from direct irradiation data

Kossoko Babatoundé Audace DIDAVI; Richard Gilles AGBOKPANZO; Bienvenu Macaire AGBOMAHENA

Articles in Press, Accepted Manuscript, Available Online from 16 September 2023

  In this work, the photovoltaic power forecast for the next 24 hours by combining a time series forecasting model (LSTM) and a regression model (XGBoost) from direct irradiation only is performed. Several meteorological parameters such as irradiance, ambient temperature, wind speed, relative humidity, ...  Read More