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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

External publication

No

Means

Energies

Scope

Review

Nature

Científica

JCR Quartile

SJR Quartile

JCR Impact

2.262

SJR Impact

0.662

Publication date

01/08/2016

ISI

000383547400037

Scopus Id

2-s2.0-84982947739

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