Electricity Theft Detection in India Using Big Data Analytics and Machine Learning

Abstract

Electricity theft is a longstanding concern in India, leading to significant revenue losses and disparities in energy distribution. With the growing digital transformation in the energy sector, there's an emerging opportunity to leverage Big Data Analytics(BDA), Internet of Things (IoT), and Machine Learning (ML) to address this challenge.This article presents a comprehensive system designed to detect electricity theft using data analytics and anomaly detection. Drawing on a rich dataset from electricity metres and IoT devices, our model applies MLalgorithms to identify suspicious patterns indicative of theft.By integrating this model with Tableau-based reporting tools, utilities can visualise theft-prone regions and take corrective action. While the potential benefits are substantial, implementing such a system in the diverse Indian landscape presents its own set of challenges, from infrastructure constraints to ethical considerations.The article concludes with future directions, emphasising scalability, real-time detection capabilities, and expanding the model's applicability beyond electricity theft.