Nontechnical loss detection for metered customers in power utility using support vector machines

• Main Authors: Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Mohamad M.
• Other Authors: 25825455100
• Format: Article
• Published: 2023
• Subjects: Electricity theft; Intelligent system; Load profiling; Nontechnical loss; Pattern classification; Customer satisfaction; Electric load forecasting; Feature extraction; Gears; Inspection; Intelligent systems; Multilayer neural networks; Sales; Support vector machines; Abnormal behavior; Customer consumption data; Customer load profiles; Distribution sector; Electricity consumers; Electricity-consumption; Fraud detection; Fraud detection system; Highly-correlated; Malaysia; Model testing; New approaches; Non-technical loss; On-site inspection; Power utility; Research areas; Research studies; Crime
• Institution: Universiti Tenaga Nasional

Electricity consumer dishonesty is a problem faced by all power utilities. Finding efficient measurements for detecting fraudulent electricity consumption has been an active research area in recent years. This paper presents a new approach towards nontechnical loss (NTL) detection in power utilities...