Analyzing the Applicability of Random Forest-Based Models for the Forecast of Run-of-River Hydropower Generation

Analyzing the Applicability of Random Forest-Based Models for the Forecast of Run-of-River Hydropower Generation

Analyzing the impact of climate variables into the operational planning processes is essential for the robust implementation of a sustainable power system. This paper deals with the modeling of the run-of-river hydropower production based on climate variables on the European scale. A better understa...

Full description

Bibliographic Details
Main Authors: Valentina Sessa, Edi Assoumou, Mireille Bossy, Sofia G. Simões
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Clean Technologies
Subjects:
energy modeling
machine learning
hydropower generation
Online Access:https://www.mdpi.com/2571-8797/3/4/50

Similar Items

Similar Items