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BORGES, Fábbio Anderson Silva. Hybrid Method Based on k-means Algorithm and Decision Rules for Short-Duration Voltages Source Location in the Context of Smart Grid. 2017. Tese (Doutorado) – Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos, 2017. In the Smart Grids context, the correct location of short-duration voltage variations sources is not a trivial task, because of the short duration of these events and for rapid propagation in the distribution feeder. In this sense, aiming to develop a recursive hybrid method based on machine learning area tools (clustering algorithm and rule base) that is able to locate the sources of short-duration voltage variations, it was used data from smart meters installed along the distribution feeder. The recursive hybrid method, as input, received the disturbance characteristics provided by the meters installed in the system. Thus, this thesis aimed to development of a measurement hardware for signal acquisition, detection, classification through a realtime operating system. Then, k-means clustering algorithm grouped the meters data in order to define two clusters, where one of them corresponded to the meters that were distant from the region that occurred the disturbance and the other one corresponded to the meters, which were located near to the disturbance occurrence region. In a second step, a rule-based system determined which of the clusters corresponded to the source node. When the algorithm determined a very large region, that region was recursively introduced as input of the developed methodology to decrease its size. The resulting system was able to estimate the location region with a accuracy above 90%. Therefore, this method showed a suitable design for employment by operation control centers of power sector concessionaires, aiming to support technical staff decision to stablish assertive corrective actions.

Método híbrido baseado no algoritmo &lt;i&gt;k-means&lt;/i&gt; e regras de decisão para localização das fontes de variações de tensões de curta duração no contexto de &lt;i&gt;Smart Grid&lt;/i&gt;