A Hybrid Method for the Run-Of-The-River Hydroelectric Power Plant Energy Forecast: HYPE Hydrological Model and Neural Network

A Hybrid Method for the Run-Of-The-River Hydroelectric Power Plant Energy Forecast: HYPE Hydrological Model and Neural Network

The increasing penetration of non-programmable renewable energy sources (RES) is enforcing the need for accurate power production forecasts. In the category of hydroelectric plants, Run of the River (RoR) plants belong to the class of non-programmable RES. Data-driven models are nowadays the most wi...

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Bibliographic Details
Main Authors: Emanuele Ogliari, Alfredo Nespoli, Marco Mussetta, Silvia Pretto, Andrea Zimbardo, Nicholas Bonfanti, Manuele Aufiero
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Forecasting
Subjects:
hydropower production forecast
Artificial Neural Networks
run of the river hydroelectric plants
seasonal decomposition
HYPE model
RES generation
Online Access:https://www.mdpi.com/2571-9394/2/4/22

Internet

https://www.mdpi.com/2571-9394/2/4/22

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