Fraud detection in registered electricity time series

• The analysis of anomalous time series is useful to detect of suspicious customers.
• XMR control charts are adapted to time series analysis of suspicious customers.
• Energy drop in the last series is dominant sign in suspicious customer’s detection.
• RT1-4 tests on X, and RT1,4 tests on R chart have the highest percentage of success.
• In series of suspicious customers it is noticed alternating positive autocorrelation.

This paper analyses time series without the seasonal component of consumers’ power consumption at low voltage in order to detect fraud and illogical consumption by customers. Statistical process control is used, where the process represents the process of using electricity. XMR charts are used to indicate major changes (decrease) in registered customers’ consumption. Verification of this method was tested on time series of a set of customers who were caught stealing during a time series. It shows that symptoms of non-random factors in time series of customers are revealed in a high percentage, which indirectly confirms the method’s ability to successfully detect electricity fraud.