Fault Classification in Photovoltaic Arrays Using Graph Signal Processing

Jie Fan, Sunil Rao, Gowtham Muniraju, Cihan Tepedelenlioglu, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper, we address the problem of fault classification in PhotoVoltaic (PV) arrays using a semi-supervised graph signal processing approach. Traditional fault detection and classification methods require large amounts of labeled data for training. In utility scale solar arrays, obtaining labeled data for different fault classes is resource intensive. We propose a graph based classification technique that relies on a limited amount of labeled data. We compare our results with the well known supervised machine learning classifiers such as the K-nearest neighbour classifier, random forest classifier, support vector machines, and artificial neural networks. We also show that the graph-based classifiers require lower training computational cost compared to the standard supervised machine learning algorithms. The proposed method also achieves good classification performance with unseen data. We validate our method on a real-time dataset and show significant improvements over existing approaches.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages315-319
Number of pages5
ISBN (Electronic)9781728163895
DOIs
StatePublished - Jun 10 2020
Event3rd IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020 - Virtual, Tampere, Finland
Duration: Jun 10 2020Jun 12 2020

Publication series

NameProceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020

Conference

Conference3rd IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020
Country/TerritoryFinland
CityVirtual, Tampere
Period6/10/206/12/20

Keywords

  • Graph Signal Processing
  • Machine Learning
  • Photovoltaic Array
  • Solar Array Fault Classification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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