Preprints
https://doi.org/10.5194/wes-2023-108
https://doi.org/10.5194/wes-2023-108
30 Aug 2023
 | 30 Aug 2023
Status: this preprint was under review for the journal WES but the revision was not accepted.

Industry 4.0 Digital Twins in Offshore Wind Farms

Evi Elisa Ambarita, Anniken Karlsen, Francesco Scibilia, and Agus Hasan

Abstract. The use of digital twins in offshore wind farms presents a major opportunity to advance autonomous operations and optimize productivity. By creating virtual replicas of physical assets and systems, digital twins allow for real-time monitoring, predictive maintenance, and efficient decision-making. In the context of Industry 4.0, wind turbines are required not only to be remotely monitored and controlled through real-time data during operation, but also to manage the whole life cycle within the entire value chain. To accomplish this, the implementation of digital twin frameworks in accordance with Industry 4.0 standards is crucial. Motivated by the advanced technologies related to industrial digital twins in the context of Industry 4.0 implemented in the manufacturing sector, this paper presents findings from a study investigating the potential for transferring knowledge of industrial digital twins to offshore wind farm context. To gain a deeper understanding of the digital twin concept in the context of offshore wind applications, we conducted extensive literature studies. Specifically, we examined frameworks used in both the manufacturing industry and offshore wind industry. Our goal is to identify commonalities and differences between these frameworks, and to determine how they could be adapted to the unique requirements of the offshore wind sector. The Asset Administration Shell (AAS), which is a key concept of the Reference Architecture Model for Industry 4.0 (RAMI 4.0), provides a standardized and modular approach to representing and managing assets in industrial systems. By adopting AAS, offshore wind farms could improve the scalability, adaptability, and interoperability of their digital twin systems, and also enable more efficient and effective operation and maintenance of the turbines. Based on our findings, we concluded that implementing the AAS could be a promising option for enhancing the functionality of digital twins in offshore wind farms, and for achieving interoperability in line with the standards of Industry 4.0.

Evi Elisa Ambarita, Anniken Karlsen, Francesco Scibilia, and Agus Hasan

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2023-108', Anonymous Referee #1, 12 Sep 2023
    • AC1: 'Reply on RC1', Evi Elisa Ambarita, 27 Oct 2023
  • RC2: 'Comment on wes-2023-108', Anonymous Referee #2, 13 Sep 2023
    • AC2: 'Reply on RC2', Evi Elisa Ambarita, 27 Oct 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2023-108', Anonymous Referee #1, 12 Sep 2023
    • AC1: 'Reply on RC1', Evi Elisa Ambarita, 27 Oct 2023
  • RC2: 'Comment on wes-2023-108', Anonymous Referee #2, 13 Sep 2023
    • AC2: 'Reply on RC2', Evi Elisa Ambarita, 27 Oct 2023
Evi Elisa Ambarita, Anniken Karlsen, Francesco Scibilia, and Agus Hasan
Evi Elisa Ambarita, Anniken Karlsen, Francesco Scibilia, and Agus Hasan

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Short summary
Our study investigated the potential for knowledge transfer of industrial digital twins from the advanced manufacturing industry to offshore wind farms context, in alignment with Industry 4.0 standards. We conducted a literature review in both sectors and followed it up with a case study on offshore wind farms. Our findings provide valuable insight for the improvement of digital twins in offshore wind farms to perform interoperability, based on Industry 4.0 standards.
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