Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review

Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review

Renewable energy sources, particularly photovoltaic and wind power, are essential in meeting global energy demands while minimising environmental impact. Accurate photovoltaic (PV) and wind power (WP) forecasting is crucial for effective grid management and sustainable energy integration. However, t...

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Bibliographic Details
Main Authors:	Ferial ElRobrini, Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Nedaa Al-Tawalbeh, Naureen Akhtar, Filippo Sanfilippo
Format:	Article
Language:	English
Published:	Elsevier 2024-12-01
Series:	Energy and AI
Subjects:	Privacy-preserving Federated learning Transfer learning PV power forecasting Wind power forecasting Deep learning
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666546824001046
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