Preprints
https://doi.org/10.5194/wes-2022-29
https://doi.org/10.5194/wes-2022-29
28 Apr 2022
 | 28 Apr 2022
Status: a revised version of this preprint was accepted for the journal WES and is expected to appear here in due course.

Grand Challenges in the Digitalisation of Wind Energy

Andrew Clifton, Sarah Barber, Andrew Bray, Peter Enevoldsen, Jason Fields, Anna Maria Sempreviva, Lindy Williams, Julian Quick, Mike Purdue, Philip Totaro, and Yu Ding

Abstract. The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelized cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as "Grand Challenges" in the digitalisation of wind energy. They are, first, the need to create reusable data frameworks; secondly, the need to connect people to data to foster innovation; and finally, the need to enable collaboration and competition between organisations. The Grand Challenges thus include a mix of technical and cultural aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

Andrew Clifton et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-29', Jethro Browell, 02 Aug 2022
  • RC2: 'Comment on wes-2022-29', Anonymous Referee #2, 18 Dec 2022
  • AC1: 'Comment on wes-2022-29', Andrew Clifton, 07 Mar 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-29', Jethro Browell, 02 Aug 2022
  • RC2: 'Comment on wes-2022-29', Anonymous Referee #2, 18 Dec 2022
  • AC1: 'Comment on wes-2022-29', Andrew Clifton, 07 Mar 2023

Andrew Clifton et al.

Andrew Clifton et al.

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Short summary
Wind energy creates huge amounts of data, which can be used to improve plant design, raise efficiency, reduce operating costs, and ease integration. These all contribute to cheaper and more predictable energy from wind. But realising the value from data requires a digital transformation that brings challenges around data, culture, and coopetition. This paper describes potential ways that the wind energy industry could work with R&D organisations, funding agencies and others to overcome them.