Machine Learning Algorithm for Efficient Power Theft Detection using Smart Meter Data - J, Jeyaranjani; D, Devaraj (International Journal of Engineering and Technology, 2018)
Electricity theft is one of the major problems of electric utilities. The dishonest electric power users produce financial loss to the utility companies. It is not possible to inspect the manually. The electricity consumption energy data obtained from the Smart Meter installed at customer premise have the information that is used for identifying the anomaly customers. This paper proposes an approach to identify the suspect customers using the customer power usage pattern. Machine learning algorithm is used for this purpose. The trustworthiness of customers is verified and is selected for theft program. This analysis is carried out by tweaking the actual Smart Meter data to create fraudulent data. The ANN classification model is developed using supervised learning algorithm that helps to discriminate the customers profile based on their genuine activity and fraudulent activity in electricity power usage. Simulation result shows that the proposed system is efficient in identifying the suspects with high accuracy.Â Â