Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions

April 16, 2023 Β· Declared Dead Β· πŸ› IEEE Access

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Authors Florian Stadtman, Adil Rasheed, Trond Kvamsdal, Kjetil AndrΓ© Johannessen, Omer San, Konstanze KΓΆlle, John Olav GiΓ¦ver Tande, Idar Barstad, Alexis Benhamou, Thomas Brathaug, Tore Christiansen, Anouk-Letizia Firle, Alexander Fjeldly, Lars FrΓΈyd, Alexander Gleim, Alexander HΓΈiberget, Catherine Meissner, Guttorm NygΓ₯rd, JΓΈrgen Olsen, HΓ₯vard Paulshus, Tore Rasmussen, Elling Rishoff, Francesco Scibilia, John Olav SkogΓ₯s arXiv ID 2304.11405 Category cs.HC: Human-Computer Interaction Cross-listed cs.LG Citations 58 Venue IEEE Access Last Checked 3 months ago
Abstract
This article presents a comprehensive overview of the digital twin technology and its capability levels, with a specific focus on its applications in the wind energy industry. It consolidates the definitions of digital twin and its capability levels on a scale from 0-5; 0-standalone, 1-descriptive, 2-diagnostic, 3-predictive, 4-prescriptive, 5-autonomous. It then, from an industrial perspective, identifies the current state of the art and research needs in the wind energy sector. The article proposes approaches to the identified challenges from the perspective of research institutes and offers a set of recommendations for diverse stakeholders to facilitate the acceptance of the technology. The contribution of this article lies in its synthesis of the current state of knowledge and its identification of future research needs and challenges from an industry perspective, ultimately providing a roadmap for future research and development in the field of digital twin and its applications in the wind energy industry.
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