A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy …

Open AccessThis article is freely available re-usable Energies 2016, 9(1), 55; doi:10.3390/en9010055 (registering DOI) Article 1 Mechanical Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA 2 Texas Sustainable Energy Research Institute, San Antonio, TX 78249, USA † These authors contributed equally to this work. * Author to whom correspondence should be addressed. Received: 15 October 2015 / Revised: 28 December 2015 / Accepted: 11 January 2016 / Published: 19 January 2016 No We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used…


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