Abstract
The digitization of distribution networks enables the collection of big data from which it is necessary to draw conclusions and detect anomalies among electricity consumers. This paper explains methodologies to detect non-technical losses, commercial losses, and electricity theft. Based on monthly electricity consumption measurements, possible and prevalent cases of anomalies and theft among consumers are identified. Indicators that can detect anomalies have been proposed for such types of load diagrams. The sensitivity of the indicators to different types of consumers was analyzed. The applicability of this methodology was examined for a set of real measurements, and its advantages were pointed out. This concept represents a good recommendation, as it is possible to observe and detect irregularities in electricity consumption.
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