학술논문

Machine Learning-Based Condition Monitoring of Solar Photovoltaic Systems: A Review
Document Type
Conference
Source
2022 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Electrical and Computer Engineering (CCECE), 2022 IEEE Canadian Conference on. :49-54 Sep, 2022
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Condition monitoring
Photovoltaic systems
Industries
Costs
Bibliographies
Gaussian noise
Machine learning
Photovoltaic
condition monitoring
machine learning
shallow
hybrid
deep networks
Language
ISSN
2576-7046
Abstract
Due to independency from physical models and low cost of implementation, machine learning-based condition monitoring methods for solar photovoltaic (PV) systems have recently gained attentions from academia and industry. In this paper, a literature review is conducted on machine learning applications in condition monitoring of PV systems. Different types of faults in PV systems and the general categorization of PV condition monitoring are firstly introduced. Machine learning-based PV condition monitoring are discussed in three groups, shallow, hybrid, and deep networks. The future research direction in this area is also provided in the paper.