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

被引：0
|
作者：
ElRobrini, Ferial [1 ]
Bukhari, Syed Muhammad Salman [2 ]
Zafar, Muhammad Hamza [3 ]
Al-Tawalbeh, Nedaa [4 ]
Akhtar, Naureen [3 ]
Sanfilippo, Filippo [3 ,5 ]
机构：
[1] Department of Renewable Energies, Saad Dahlab University, Blida,09000, Algeria
[2] Department of Electrical Engineering, Capital University of Science and Technology, Islamabad,44000, Pakistan
[3] Department of Engineering Sciences, University of Agder, Grimstad,4879, Norway
[4] Department of Renewable Energy Engineering, Al al-Bayt University, Mafraq,25113, Jordan
[5] Department of Software Engineering, Kaunas University of Technology, Kaunas,44029, Lithuania
来源：
Energy and AI | / 18卷
关键词：
Deep learning - Forecasting models - Grid management - Photovoltaic power - Photovoltaic power forecasting - Photovoltaics - Power forecasting - Privacy preserving - Transfer learning - Wind power forecasting;
D O I：
100438
中图分类号：
学科分类号：
摘要：
205
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