Digital twins used for condition assessment of transformer fleets - the challenges of turning data into reality
Author
Abstract

Today, Distribution System Operators (DSO) face numerous challenges, such as growth of decentralized power generation, increasing unconventional demands, active network management for peak load- and congestion management. Moreover, DSO also face an accelerated asset ageing while confronted with tight budgets and a strong ROI business case justification. The Digital Transformer Twin is the digital representation of real physical assets and enables the operators to evaluate the Transformer Asset Condition by leveraging software capabilities, AI insights from large datasets as well as academic research results in order to turn data into reality. Thus, trusted and consistent results over the entire transformer life span require also a faithful Digital Transformer Twin over the entire physical transformer life cycle from inception to retirement.

Year of Publication
2023
Date Published
jun
URL
https://ieeexplore.ieee.org/document/10267399
DOI
10.1049/icp.2023.0552
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