Enhancing wind-farm operation with Asset Administration Shell-based digital twins

In this article, we present findings from a pioneering study on implementing Asset Administration Shell (AAS)-based digital twins to achieve data interoperability for wind-farm applications. Utilising real data from the Hywind Scotland floating wind farm and using the digital twin framework called Fraunhofer Advanced AAS Tools (FA3ST) Service, our main contribution lies in bridging the gap between theory and practice by demonstrating how to technically implement AAS-based digital twins of wind farms. Three objectives are in focus: (1) storing wind-farm documentation and non-updated data within internal AAS, (2) retrieving historical time series data using the FA3ST Service, and (3) establishing asset synchronisation for real-time monitoring. Through the establishment of handover documentation submodel, technical data submodel, time series data submodel, and asset synchronisation, AAS Types 1 and 2 are effectively implemented. From a user-centred perspective, our study demonstrates the flexibility of the FA3ST Service in terms of supporting various data formats and communication methods making it effortless for clients to access data without having a detailed data-source insight. The findings highlight the feasibility of implementing AAS-based digital twins within the wind-farm sector through FA3ST Service, facilitating smooth data interoperability across stakeholders throughout the asset lifespan.

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Publication Details

Journal
Digital Twin
Published
2026-08-27
DOI
https://doi.org/10.1080/27525783.2026.2717969
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Enhancing wind-farm operation with Asset Administration Shell-based digital twins

Agus Hasan, Evi Elisa Ambarita, Steffan Sørenes, Francesco Scibilia et al.
Digital Twin
Machine Fault Diagnosis Techniques
article

Enhancing wind-farm operation with Asset Administration Shell-based digital twins

Agus Hasan, Evi Elisa Ambarita, Steffan Sørenes, Francesco Scibilia, Anniken Karlsen
article en

Abstract

In this article, we present findings from a pioneering study on implementing Asset Administration Shell (AAS)-based digital twins to achieve data interoperability for wind-farm applications. Utilising real data from the Hywind Scotland floating wind farm and using the digital twin framework called Fraunhofer Advanced AAS Tools (FA3ST) Service, our main contribution lies in bridging the gap between theory and practice by demonstrating how to technically implement AAS-based digital twins of wind farms. Three objectives are in focus: (1) storing wind-farm documentation and non-updated data within internal AAS, (2) retrieving historical time series data using the FA3ST Service, and (3) establishing asset synchronisation for real-time monitoring. Through the establishment of handover documentation submodel, technical data submodel, time series data submodel, and asset synchronisation, AAS Types 1 and 2 are effectively implemented. From a user-centred perspective, our study demonstrates the flexibility of the FA3ST Service in terms of supporting various data formats and communication methods making it effortless for clients to access data without having a detailed data-source insight. The findings highlight the feasibility of implementing AAS-based digital twins within the wind-farm sector through FA3ST Service, facilitating smooth data interoperability across stakeholders throughout the asset lifespan.

Digital Twin
Norwegian University of Science and Technology (NO), Digital Science (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 14%
Machine Fault Diagnosis Techniques
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Enhancing wind-farm operation with Asset Administration Shell-based digital twins — Agus Hasan, Evi Elisa Ambarita, et al. · Digital Twin (2026) | TGRS Research Map | TGRS