Identificação inteligente de cargas elétricas similares em smart grid

• Ano de defesa: 2018
• Autor(a) principal: Barcelos, Rayana Kristina Schneider
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Energia; UFES; Programa de Pós-Graduação em Energia
• Palavras-chave em Português: Smart grid; Load identification; Load signature; Identificação de carga; Assinatura de carga; Redes inteligentes de energia; Carga e distribuição elétrica; Engenharia/Tecnologia/Gestão; 620.9
• Link de acesso: http://repositorio.ufes.br/handle/10/10462

This work shows the result of applying characterization techniques to define load signatures in Smart Grids. The differential of this work is that the loads have the same technical data and are from the same manufacturer (loads with a high degree of similarity), making the identification process more difficult and describing a challenging condition. The prototype is a platform with four technically identical fluorescent lamps, allowing 16 possible operation configurations, this means, from no one lamp turned on to all the lamps turned on. Two techniques are tested to define the load signature: one with 14 simple features to represent each one of the 16 possible configurations; and another form based on the Shannon and Renyi entropy. Next, the signature sets, classified through Case-Based Reasoning (RBC), are submitted to an optimizer aiming to find the highest possible accuracy for the identification system. The lowest error rate obtained in this work is 22.69% and represents a good performance of the identification system, given the complexity of the problem. These initial results will serve as a reference for new solutions to this new problem.