reviewEnergiesApr 4, 2019GOLD OA

State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

Obuda University · Oxford Brookes University · +6 more institutions

Indexed incrossrefdoaj

Abstract

Machine learning (ML) models have been widely used in the modeling, design and prediction in energy systems. During the past two decades, there has been a dramatic increase in the advancement and application of various types of ML models for energy systems. This paper presents the state of the art of ML models used in energy systems along with a novel taxonomy of models and applications. Through a novel methodology, ML models are identified and further classified according to the ML modeling technique, energy type, and application area. Furthermore, a comprehensive review of the literature leads to an assessment and performance evaluation of the ML models and their applications, and a discussion of the major…

Citation impact

547
total citations
FWCI
29.42
Percentile
100%
References
113
Citations per year

Authors

6

Topics & keywords

Keywords
  • Computer science
  • Renewable energy
  • Robustness (evolution)
  • Artificial intelligence
  • Wind power
  • Energy (signal processing)
  • Sustainability
  • Machine learning
UN Sustainable Development Goals
  • Affordable and clean energy
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