Black Hole Algorithm for Non-technical Losses Characterization

Abstract

With the consolidation of Smart Grids, a considerable amount of works can be noticed, mainly with respect to the application of several artificial intelligence techniques in order to automatically identify non-technical losses, but the problem of selecting the most representative features has not been widely discussed. In this work, we make a parallel among the problem of non-technical losses and the task of irregular consumers characterization by means of a recent meta-heuristic optimization technique called Black Hole Algorithm (BHA). The experimental setup is conducted over two private datasets provided by a Brazilian electric power company, and it shows the importance of selecting the most relevant features in the context of nontechnical losses identification, as well as the suitability of BHA to this task.