Enhanced Theft Mitigation on Electrical Power using Smart Metering Infrastructure

Abstract

Electricity theft remains a significant challenge for power distribution networks worldwide, particularly in regions with limited enforcement and out-dated infrastructure. This illicit activity results in substantial financial losses, operational inefficiencies, and compromised grid reliability, ultimately impacting both utility companies and honest consumers. Traditional methods of detecting electricity theft, such as physical inspections and manual audits, have proven insufficient in addressing increasingly sophisticated theft techniques. However, advancements in smart metering infrastructure offer new possibilities for enhancing theft detection and mitigation. This paper explores the development of an enhanced theft mitigation strategy leveraging smart metering technology to detect and prevent unauthorized electricity consumption more effectively. The study proposes a comprehensive framework of developed algorithm which was implemented using python programming and the algorithm's performance evaluated under different conditions and parameter such as intrusion detection status which monitors whether the metre is powered on or powered off, Time step error which is the error in monitoring the progression of electricity supply to customers at regular increments, real time pricing plays a crucial role in identifying deviations in the price of electricity, the central observer metre status which checks if the power supply at the source corresponds to the total sum of electricity supplied to customers, accounting for expected technical losses. This Model is validated by comparing it’s predictions with observations from real field data collected from AEDC Bwari Abuja. Data’s of a sample size of 98 customer meters were collected and the validation step showed that greater than 83% prediction accuracy of the model to respect with the real data.