Designing an integrated knowledge graph for smart energy services

Sejin Chun, Jooik Jung, Xiongnan Jin, Seungmin Seo, Kyong Ho Lee

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


The sharp growth of distributed energy-related resources requires an efficient energy management for future grids. The traditional power grid that highly depends on information model standards collects energy data depending on them and creates energy services. Nowadays, decentralized grids utilize information schema generated by reusing standards as well as existing schemas. The schema helps implement smart energy services in the future grids. To meet such requirements, domain experts proposed upper-level schemas that manage a wide range of energy-related knowledge resources. However, their schemas could not conduct an effective reuse of energy-related knowledge resources due to their unsuitable schema development methodologies. Moreover, there is a lack of vocabularies that satisfy critical requirements for decentralized grids. To cope with these problems, we propose an energy knowledge graph (EKG) as an upper schema for the integration of knowledge resources in energy systems. First, we utilize the existing methodology that offers guidelines for reusing existing knowledge resources. Second, EKG supports concepts of energy trading and communities to satisfy the requirements of decentralized grids. Third, EKG presents compliant concepts that are compatible with existing schemas. Fourth, we modeled the use cases using the EKG and evaluated them according to the scenario specification of energy services. Last, to demonstrate the benefits of the EKG, we implemented key components such as semantic mashup and complex event processing.

Original languageEnglish
Pages (from-to)8058-8085
Number of pages28
JournalJournal of Supercomputing
Issue number10
Publication statusPublished - 2020 Oct 1

Bibliographical note

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture


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