Artificial intelligence for superconducting transformers

Yazdani Asrami, M., Taghipour-Gorjikolaie, M., Song, W. , Zhang, M., Chakraborty, S. and Yuan, W. (2021) Artificial intelligence for superconducting transformers. Transformers Magazine, 8, pp. 4-12.

Abstract

Artificial intelligence (AI) techniques are currently widely used in different parts of the electrical engineering sector due to their privileges for being used in smarter manufacturing and accurate and efficient operating of electric devices. Power transformers are a vital and expensive asset in the power network, where their consistent and fault-free operation greatly impacts the reliability of the whole system. The superconducting transformer has the potential to fully modernize the power network in the near future with its invincible advantages, including much lighter weight, more compact size, much lower loss, and higher efficiency compared with conventional oil-immersed counterparts. In this article, we have looked into the perspective of using AI for revolutionizing superconducting transformer technology in many aspects related to their design, operation, condition monitoring, maintenance, and asset management. We believe that this article offers a roadmap for what could be and needs to be done in the current decade 2020-2030 to integrate AI into superconducting transformer technology.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Song, Dr Wenjuan
• Authors: Yazdani Asrami, M., Taghipour-Gorjikolaie, M., Song, W., Zhang, M., Chakraborty, S., and Yuan, W.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Transformers Magazine
• Publisher: Merit Media International
• ISSN: 1849-3319
• ISSN (Online): 1849-7268
• Published Online: 20 August 2021
• Copyright Holders: Copyright © 2021 Merit Media
• First Published: First published in Transformers Magazine 8: 4-12
• Publisher Policy: Reproduced in accordance with the publisher copyright policy