A Decentralised Relational Data Model for Reliability Studies of Medium-Voltage Cable

Konrad Sundsgaard, Lunodzo Justine Mwinuka, Massimo Cafaro, Jens Zoëga Hansen, Guangya Yang

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

The distribution grid is evolving into a multilateral cyber-physical system where efficient data sharing and management across stakeholders are fundamental. Consequently, many applications benefit from collecting data from decentralised sources, as in the case of data-driven reliability prediction of medium-voltage cables, where distribution grid operators expect more accurate results through data sharing and joint model development. However, challenges arise when transitioning from centrally stored data to distributed data handled by decentralised peers. Current data collection processes often involve manual and static data requests, requiring additional efforts in data combination or harmonisation. To address these challenges, this study proposes a relational database model tailored for the reliability prediction of medium-voltage cables, and discusses its evolution into a decentralised database design. Eventually, such a setup may not only facilitate the development of ML applications but also guide the way for more standardised and dynamic data sharing among distribution grid operators.
Original languageEnglish
Title of host publicationProceedings of 2024 IEEE PES ISGT Europe
Number of pages5
PublisherIEEE
Publication statusAccepted/In press - 2025
EventIEEE PES Innovative Smart Grid Technologies Europe 2024 - Dubrovnik, Croatia
Duration: 14 Oct 202417 Oct 2024

Conference

ConferenceIEEE PES Innovative Smart Grid Technologies Europe 2024
Country/TerritoryCroatia
CityDubrovnik
Period14/10/202417/10/2024

Keywords

  • Cable networks
  • Distributed systems
  • Reliability
  • Data models
  • Machine learning
  • Entity relatons
  • SQL
  • P2P

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