Forecasting photovoltaic production with neural networks and weather features-Reference-Cited by-同舟云学术

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Forecasting photovoltaic production with neural networks and weather features

Published:2024-11 Issue: Volume:139 Page:107884
ISSN:0140-9883
Container-title:Energy Economics
language:en
Short-container-title:Energy Economics

Author:

Goutte Stéphane,Klotzner Klemens,Le Hoang-Viet^ORCID,von Mettenheim Hans-Jörg

Publisher

Elsevier BV

Reference26 articles.

1. Implications of poorly designed climate policy on energy poverty: Global reflections on the current surge in energy prices;Belaïd;Energy Res. Soc. Sci.,2022

2. Balancing climate mitigation and energy security goals amid converging global energy crises: The role of green investments;Belaïd;Renew. Energy,2023

3. PVHybNet: A hybrid framework for predicting photovoltaic power generation using both weather forecast and observation data;Carrera;IET Renew. Power Gener.,2020

4. Comparison of machine learning and statistical methods in the field of renewable energy power generation forecasting: a mini review;Dou;Front. Energy Res.,2023

5. Solar photovoltaic energy production forecast using neural networks;Dumitru;Proc. Technol.,2016

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