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Intelligent and data-driven fault detection of photovoltaic plants
Siya Yao
, Qi Kang
,
Mengchu Zhou
, Abdullah Abusorrah
, Yusuf Al-Turki
Electrical and Computer Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
19
Scopus citations
Overview
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Dive into the research topics of 'Intelligent and data-driven fault detection of photovoltaic plants'. Together they form a unique fingerprint.
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Keyphrases
Photovoltaic Power Plant
100%
Data-driven Fault Detection
100%
Non-continuous
66%
Predictive Models
33%
Photovoltaic System
33%
Performance Data
33%
Performance Evaluation
33%
Intelligent Data
33%
Photovoltaic Panel
33%
Evaluation Results
33%
Performance Monitoring
33%
Transition Period
33%
Threshold Range
33%
Failure Identification
33%
Unsupervised Method
33%
System Fault
33%
Ensemble Algorithm
33%
Photovoltaic Data
33%
Photovoltaic Power Generation
33%
Continuous Regression
33%
Data-driven Maintenance
33%
Periodic Inspection
33%
Intelligent Performance
33%
Regression Prediction Model
33%
Tree Ensembles
33%
Monitoring Data
33%
Reference Baseline
33%
Computer Science
Fault Detection
100%
And-States
50%
Predictive Model
50%
Performance Data
50%
Performance Evaluation
50%
Prediction Model
50%
Evaluation Result
50%
Performance Monitoring
50%
Unsupervised Method
50%
Conduct Operation
50%
Monitoring Data
50%
Timely Maintenance
50%
Engineering
Photovoltaics
100%
Operation and Maintenance
75%
Photovoltaic System
25%
Photovoltaic Panel
25%
Solar Power Generation
25%
Monitoring Data
25%
Conduct Operation
25%