Non-Technical Loss Identification by Using Data Analytics and Customer Smart Meters

Abstract

The smart meters installed at the customer premises are one of the main apparatuses promoting the modernization of the distribution systems. These devices collect a huge amount of data, demanding the development of analytic techniques to transform these data into useful information. In addition, by proposing new applications to data supplied by smart meters, more value is added to this equipment, allowing higher return on the associated investments. Utilities can have a business case by increasing their operational efficiency if smart meters are used, for instance, to identify non-technical losses, which represent an important cause of revenue losses. This paper presents a new data analytic technique for detection and location of non-technical losses caused by illegal connections of loads to distribution systems in the presence of smart meters. The data analytic technique relies on bad data analysis, similar to the ones used in state estimation methods, developed specifically for this application. A real 34-bus low voltage system is used to illustrate the main concepts of the proposed algorithm. Systematic tests are also conducted on a real 1682-bus distribution system to evaluate the method performance considering electricity theft caused by medium and low voltage customers.