Ensemble of machine learning and spatiotemporal parameters to forecast very short-term solar irradiation to compute photovoltaic generators’ output power-Reference-Cited by-同舟云学术

Ensemble of machine learning and spatiotemporal parameters to forecast very short-term solar irradiation to compute photovoltaic generators’ output power

Published:2021-08 Issue: Volume:229 Page:120647
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Rodríguez Fermín,Martín Fernando,Fontán Luis,Galarza Ainhoa

Funder

Basque Government

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference53 articles.

1. New approach to estimate 5-min global solar irradiation dataon tilted planes from horizontal measurement;Takilalte,2020

2. Wind power generation: a review and a research agenda;Aguilar;J Clean Prod,2019

3. In photovoltaic applications,2018

4. Ren21, advancing the global renewable energy transition. https://www.ren21.net/wp-content/uploads/2019/08/Highlights-2018.pdf. (Accessed 25 November 2019).

5. Solar irradiation prediction with machine learning: forecasting models selection method depending on weather variability;Fouilloy,2018

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