Digital Twin for Wind Energy: Latest updates from the NorthWind project
| Title: | Digital Twin for Wind Energy: Latest updates from the NorthWind project |
|---|---|
| Authors: | Rasheed, Adil, Stadtmann, Florian, Fonn, Eivind, Tabib, Mandar, Tsiolakis, Vasileios, Panjwani, Balram, Johannessen, Kjetil Andre, Kvamsdal, Trond, San, Omer, Tande, John Olav, Barstad, Idar, Christiansen, Tore, Rishoff, Elling, Frøyd, Lars, Rasmussen, Tore |
| Publication Year: | 2024 |
| Collection: | Computer Science |
| Subject Terms: | Computer Science - Computers and Society |
| More Details: | NorthWind, a collaborative research initiative supported by the Research Council of Norway, industry stakeholders, and research partners, aims to advance cutting-edge research and innovation in wind energy. The core mission is to reduce wind power costs and foster sustainable growth, with a key focus on the development of digital twins. A digital twin is a virtual representation of physical assets or processes that uses data and simulators to enable real-time forecasting, optimization, monitoring, control and informed decision-making. Recently, a hierarchical scale ranging from 0 to 5 (0 - Standalone, 1 - Descriptive, 2 - Diagnostic, 3 - Predictive, 4 - Prescriptive, 5 - Autonomous has been introduced within the NorthWind project to assess the capabilities of digital twins. This paper elaborates on our progress in constructing digital twins for wind farms and their components across various capability levels. |
| Document Type: | Working Paper |
| Access URL: | http://arxiv.org/abs/2403.14646 |
| Accession Number: | edsarx.2403.14646 |
| Database: | arXiv |
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