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Economía de la tierra y la energía(3)
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Innovative methodology to identify errors in electric energy measurement systems in power utilities
ArticleAbstract: Many electric utilities currently have a low level of smart meter implementation on traditional distPalabras claves:Artificial intelligence, Consumption patterns, data analytics, Electrical energy losses, Machine Learning, outlier detectionAutores:Bel C.A., Carlos Arias-Marin, Diego Morales-Jadan, Eddy Bravo-Padilla, Marco Toledo-Orozco, Rodriguez-Garcia J.Fuentes:googlescopusMethodology for the disaggregation and forecast of demand flexibility in large consumers with the application of non-intrusive load monitoring techniques
ArticleAbstract: Technological advances, innovation and the new industry 4.0 paradigm guide Distribution System OperaPalabras claves:BIG DATA, Combinatorial optimization, Factorial hidden Markov model, Machine Learning, Non-intrusive load monitoring, Time of use tariffsAutores:Alvarez-Bel C., Arturo Geovanny Peralta Sevilla, Bel C.A., C. Celi, Carmen J. Celi, Diego Morales-Jadan, F. Guartan, Marco Toledo-OrozcoFuentes:scopusMethodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor
ArticleAbstract: Detecting fraudulent behaviors in electricity consumption is a significant challenge for electric utPalabras claves:data analytics, energy measurement, Machine Learning, non-technical electrical losses, UtilityAutores:Carlos Arias-Marin, Edgar Antonio Barragán-Escandón PhD., Marco Toledo-Orozco, Xavier Serrano-GuerreroFuentes:scopus