Title A Review of Classification Problems and Algorithms in Renewable Energy Applications
Authors PÉREZ ORTIZ, MARÍA, Jimenez-Fernandez, Silvia, Gutierrez, Pedro A., Alexandre, Enrique, Hervas-Martinez, Cesar, Salcedo-Sanz, Sancho, PÉREZ ORTIZ, MARÍA
External publication No
Means Energies
Scope Review
Nature Científica
JCR Quartile 2
SJR Quartile 1
JCR Impact 2.26200
SJR Impact 0.66200
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-84982947739&doi=10.3390%2fen9080607&partnerID=40&md5=a8f9a720a82c444277b11e31d3f201d4
Publication date 01/08/2016
ISI 000383547400037
Scopus Id 2-s2.0-84982947739
DOI 10.3390/en9080607
Abstract Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy ( RE) has gained significant attention in the last few years, contributing to the deployment, management and optimization of RE systems. The main objective of this paper is to review the most important classification algorithms applied to RE problems, including both classical and novel algorithms. The paper also provides a comprehensive literature review and discussion on different classification techniques in specific RE problems, including wind speed/power prediction, fault diagnosis in RE systems, power quality disturbance classification and other applications in alternative RE systems. In this way, the paper describes classification techniques and metrics applied to RE problems, thus being useful both for researchers dealing with this kind of problem and for practitioners of the field.
Keywords classification algorithms; machine learning; renewable energy; applications
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