A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space-Reference-Cited by-同舟云学术

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A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space

Published:2024-08 Issue: Volume:367 Page:123375
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Kirchner-Bossi Nicolas,Kathari Gabriel^ORCID,Porté-Agel Fernando

Publisher

Elsevier BV

Reference96 articles.

1. The Paris agreement;United Nations,2016

2. Global energy transformation: A roadmap to 2050;Gielen,2019

3. World energy scenarios: composing energy futures to 2050;Frei,2013

4. Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices;Maciejowska;Energy Econ,2021

5. Sources of uncertainty in long-term global scenarios of solar photovoltaic technology;Jaxa-Rozen;Nature Clim Change,2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Low-Carbon Park Integrated Energy System Scheduling Based on Day-Ahead and Intra-Day Optimization;2024 6th International Conference on Energy Systems and Electrical Power (ICESEP);2024-06-21

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