Identification of suspicious electricity customers

Abstract

In this paper, customer’s invoiced energy time series in the recent past is analyzed in order to detect the cause of increased total electricity losses in the low voltage network. Period from 2003 to 2017 is included in the recent past. This period is organized in five successive decades whose beginnings are shifted for one year. Fuzzy logic is used asa method for determining a set of suspicious electricity customers in the first phase of electricity fraud detecting. At this phase, every customer located in the area of increased total electricity losses is analyzed. For each customer, a time series of invoiced energy are formed. Selected time series data and their relations are used to create fuzzy sets of suspicion. Then, total suspicion value of each customer is determined by using fuzzy logic. Based on the estimated total and technical energy losses in the customer’s area (region that is supplied by one or more MV/LV transformer stations) and the balance of total, invoiced and energy of losses, a boundary value of suspicion percentage is determined. All customers, whose percentage suspicion value is greater than the boundary value, are declared suspect. Thus, suspicious customers with their locations which need inspection are obtained. On-site inspection of suspected customers is not performed and is not the subject of this paper.