Improving supervised wind power forecasting models using extended numerical weather variables and unlabelled data
Author:
Affiliation:
1. School of Electrical Engineering and AutomationTianjin UniversityTianjinPeople's Republic of China
2. School of Electrical and Computer EngineeringCornell UniversityIthacaNYUSA
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Renewable Energy, Sustainability and the Environment
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2016.0339
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