Demonstration of a Standalone, Descriptive, and Predictive Digital Twin of a Floating Offshore Wind Turbine
Not on the map. Why?
Abstract (arXiv)
Digital Twins bring several benefits for planning, operation, and maintenance of remote offshore assets. In this work, we explain the digital twin concept and the capability level scale in the context of wind energy. Furthermore, we demonstrate a standalone digital twin, a descriptive digital twin, and a prescriptive digital twin of an operational floating offshore wind turbine. The standalone digital twin consists of the virtual representation of the wind turbine and its operating environment. While at this level the digital twin does not evolve with the physical turbine, it can be used during the planning-, design-, and construction phases. At the next level, the descriptive digital twin is built upon the standalone digital twin by enhancing the latter with real data from the turbine. All the data is visualized in virtual reality for informed decision-making. Besides being used for data bundling and visualization, the descriptive digital twin forms the basis for diagnostic, predictive, prescriptive, and autonomous tools. A predictive digital twin is created through the use of weather forecasts, neural networks, and transfer learning. Finally, digital twin technology is discussed in a much wider context of ocean engineering.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 2; 2024: 1.
3 papers.
- 2023Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directionscited by 7
- 2024Diagnostic Digital Twin for Anomaly Detection in Floating Offshore Wind Energycited by 1
- 2023Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approachcited by 0
- 2024Diagnostic Digital Twin for Anomaly Detection in Floating Offshore Wind Energy4 Jun 2024
- 2023Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach18 Sep 2023
- 2023Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions16 Apr 2023