Agradecimentos A princípio, agradeço a Deus por me dar forças para a realização deste trabalho. Agradeço a toda minha família por ter me dado todo o apoio necessário para que eu alcançasse meus objetivos. Agradeço a minha prima, Profa. Roberta Date, pelas correções de todos os meus trabalhos. Agradeço a minha mãe, que sempre me incentivou e me deu forças para continuar até o final do doutorado. Ao meu pai que contribuiu na minha formação. Ao meu irmão Marcelo Date que esteve presente em todas as etapas da minha vida. Aos meus avós, que contribuíram na minha formação desde a infância.
The Smart Meter technology has become a trend in the future of power distribution systems and some applications should be provided with its installation in residential consumers. Thus, this paper presents a method of residential loads identification using data provided by a smart meter. In this sense, the ZigBee communication technology is proposed to exchange data between smart meter and consumer. Hence, a consumer-side software could be installed in a consumer device, such as: tablet, smartphone, microcomputer, etc. This software receive some measurements in order to show the loads identified. Moreover, this software is able to furnish the actual residential consumption. The identification method was developed using intelligent systems (neural networks, neuralfuzzy and neural-genetic) and its results were compared in order to determine its applicability.
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