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

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 seve...

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Detalles Bibliográficos
Autores: Guerrero Alonso, Juan Ignacio, García Delgado, Antonio, Personal Vázquez, Enrique, Luque Rodríguez, Joaquín, León de Mora, Carlos
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2017
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/77082
Acceso en línea:https://hdl.handle.net/11441/77082
https://doi.org/10.1016/j.eswa.2017.03.007
Access Level:acceso abierto
Palabra clave:Smart grids
Large-scale integration
Data mining
Standards
Metadata mining
Big data
Descripción
Sumario: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.