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. It is concluded that the main challenges hindering the
realization of highly capable digital twins fall into one of the four categories; standards-related, data-related,
model-related, and industrial acceptance related. The article proposes approaches to the identified challenges
from the perspective of research institutes and offers a set of recommendations for various 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
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. It is concluded that the main challenges hindering the
realization of highly capable digital twins fall into one of the four categories; standards-related, data-related,
model-related, and industrial acceptance related. The article proposes approaches to the identified challenges
from the perspective of research institutes and offers a set of recommendations for various 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