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Heterogeneous data source integration for smart grid ecosystems based on metadata mining

 

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Opened Access Heterogeneous data source integration for smart grid ecosystems based on metadata mining
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Author: Guerrero Alonso, Juan Ignacio
García Delgado, Antonio
Personal Vázquez, Enrique
Luque Rodríguez, Joaquín
León de Mora, Carlos
Department: Universidad de Sevilla. Departamento de Tecnología Electrónica
Date: 2017
Published in: Expert Systems with Applications, 79 (August 2017), 254-268.
Document type: Article
Abstract: The arrival of new technologies related to smart grids and the resulting ecosystem of applications andmanagement systems pose many new problems. The databases of the traditional grid and the variousinitiatives related to new technologies have given rise to many different management systems with several formats and different architectures. A heterogeneous data source integration system is necessary toupdate these systems for the new smart grid reality. Additionally, it is necessary to take advantage of theinformation smart grids provide. In this paper, the authors propose a heterogeneous data source integration based on IEC standards and metadata mining. Additionally, an automatic data mining framework isapplied to model the integrated information.
Cite: Guerrero Alonso, J.I., García Delgado, A., Personal Vázquez, E., Luque Rodríguez, J. y León de Mora, C. (2017). Heterogeneous data source integration for smart grid ecosystems based on metadata mining. Expert Systems with Applications, 79 (August 2017), 254-268.
Size: 2.272Mb
Format: PDF

URI: https://hdl.handle.net/11441/77082

DOI: 10.1016/j.eswa.2017.03.007

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