Enhanced Random Forest Model for Robust Short-Term Photovoltaic Power Forecasting Using Weather Measurements

Enhanced Random Forest Model for Robust Short-Term Photovoltaic Power Forecasting Using Weather Measurements

Short-term Photovoltaic (PV) Power Forecasting (STPF) is considered a topic of utmost importance in smart grids. The deployment of STPF techniques provides fast dispatching in the case of sudden variations due to stochastic weather conditions. This paper presents an efficient data-driven method base...

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Bibliographic Details
Main Authors: Mohamed Massaoudi, Ines Chihi, Lilia Sidhom, Mohamed Trabelsi, Shady S. Refaat, Fakhreddine S. Oueslati
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Energies
Subjects:
smart grid
Photovoltaic (PV) Power Forecasting
weather sensors
random decision forest
feature importance
energy management
Online Access:https://www.mdpi.com/1996-1073/14/13/3992

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https://www.mdpi.com/1996-1073/14/13/3992

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