JOURNAL ARTICLE

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

Juan Ignacio GuerreroAntonio GarcíaEnrique PersonalJ. LuqueCarlos León

Year: 2017 Journal:   Expert Systems with Applications Vol: 79 Pages: 254-268   Publisher: Elsevier BV

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.

Keywords:
Metadata Computer science Metadata management Smart grid Semantic grid Grid Data integration Information integration Database Data science Data mining Distributed computing World Wide Web Semantic Web

Metrics

36
Cited By
2.38
FWCI (Field Weighted Citation Impact)
118
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Smart Grid and Power Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Smart Grid Security and Resilience
Physical Sciences →  Engineering →  Control and Systems Engineering
Power Systems and Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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