An unsupervised monitoring procedure for detecting anomalies in photovoltaic systems using a one-class Support Vector Machine

Engineering

• Anomaly Detection 33%
• Experimental Result 33%
• Grid-Connected Plant 33%
• Nonlinear Feature 33%
• One-Diode Model 33%
• Photovoltaic System 100%
• Photovoltaics 100%
• Real Data 33%
• Simulation Model 33%
• Solar Power Generation 33%
• Support Vector Machine 100%

Computer Science

• Agglomerative Clustering 33%
• Anomaly-Based Detection 33%
• Clustering Scheme 33%
• Data Distribution 33%
• Detecting Anomaly 100%
• Experimental Result 33%
• Fault Detection 66%
• mean shift 33%
• Simulation Model 33%
• Support Vector Machine 100%
• Underlying Data 33%

Keyphrases

• Agglomerative Clustering 33%
• Binary Clustering 33%
• Mean Shift Clustering 33%
• Model Detection 33%
• Operating Profitability 33%