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

•A new technique based on metadata is proposed: metadata mining.•An intelligent integration system for heterogeneous data sources is described.•An adaptive data mining tool for the integrated data sources is proposed.•Successful results are obtained in application in real data bases from research pr...

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Bibliographic Details
Published in:Expert systems with applications 2017-08, Vol.79, p.254-268
Main Authors: Guerrero, Juan I., García, Antonio, Personal, Enrique, Luque, Joaquín, León, Carlos
Format: Article
Language:English
Subjects:
Big Data
Data mining
Large scale integration
Management systems
Metadata
Metadata mining
New technology
Smart grid
Smart grid technology
Smart grids
Upgrading
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Summary:•A new technique based on metadata is proposed: metadata mining.•An intelligent integration system for heterogeneous data sources is described.•An adaptive data mining tool for the integrated data sources is proposed.•Successful results are obtained in application in real data bases from research projects. The arrival of new technologies related to smart grids and the resulting ecosystem of applications and management systems pose many new problems. The databases of the traditional grid and the various initiatives 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 to update these systems for the new smart grid reality. Additionally, it is necessary to take advantage of the information 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 is applied to model the integrated information.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2017.03.007