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Knowledge engineering for wind energy

  • Yuriy Marykovskiy*
  • , Thomas Clark
  • , Justin Day
  • , Marcus Wiens
  • , Charles Henderson
  • , Julian Quick
  • , Imad Abdallah
  • , Anna Maria Sempreviva
  • , Jean Paul Calbimonte
  • , Eleni Chatzi
  • , Sarah Barber
  • *Corresponding author for this work
  • Swiss Federal Institute of Technology Zurich
  • Eastern Switzerland University of Applied Sciences
  • Octue Ltd
  • Pacific Northwest National Laboratory
  • Fraunhofer Institute for Wind Energy Systems
  • Stacker Group
  • University of Applied Sciences and Arts Western Switzerland

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

With the rapid evolution of the wind energy sector, there is an ever-increasing need to create value from the vast amounts of data made available both from within the domain and from other sectors. This article addresses the challenges faced by wind energy domain experts in converting data into domain knowledge, connecting and integrating them with other sources of knowledge, and making them available for use in next-generation artificial intelligence systems. To this end, this article highlights the role that knowledge engineering can play in the digital transformation of the wind energy sector. It presents the main concepts underpinning knowledge-based systems and summarises previous work in the areas of knowledge engineering and knowledge representation in a manner that is relevant and accessible to wind energy domain experts. A systematic analysis of the current state of the art on knowledge engineering in the wind energy domain is performed with available tools put into perspective by establishing the main domain actors and their needs, as well as identifying key problematic areas. Finally, recommendations for further development and improvement are provided.
Original languageEnglish
JournalWind Energy Science
Volume9
Issue number4
Pages (from-to)883-917
ISSN2366-7443
DOIs
Publication statusPublished - 2024

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