Artificial intelligence for superconducting transformers

Yazdani-Asrami, Mohammad and Taghipour-Gorjikolaie, Mehran and Song, Wenjuan and Zhang, Min and Chakraborty, Sruti and Yuan, Weijia (2021) Artificial intelligence for superconducting transformers. Transformers Magazine. pp. 4-12.

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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.

ORCID iDs

Yazdani-Asrami, Mohammad ORCID logoORCID: https://orcid.org/0000-0002-7691-3485, Taghipour-Gorjikolaie, Mehran, Song, Wenjuan, Zhang, Min ORCID logoORCID: https://orcid.org/0000-0003-4296-7730, Chakraborty, Sruti and Yuan, Weijia ORCID logoORCID: https://orcid.org/0000-0002-7953-4704;
CORE (COnnecting REpositories)