Daily prediction of solar power generation based on weather forecast information in Korea
Author:
Affiliation:
1. Department of Industrial and Management EngineeringIncheon National UniversityIncheonRepublic of Korea
2. Innovative Technology Research DivisionGumi Electronics and Information Technology Research InstituteGumiRepublic of Korea
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.2016.0698
Reference12 articles.
1. Online short-term solar power forecasting
2. Neural network ensemble‐based solar power generation short‐term forecasting;Chaouachi A.;Int. J. Inf. Math. Sci.,2009
3. Short‐mid‐term solar power prediction by using artificial neural networks;İzgi E.;Sol. Energy,2012
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