PhD Studentship - Digital Twin of Power Transformers

How to apply: uom.link/pgr-apply-fap

This project will be funded by industry and will cover tuition fees and provide a tax free stipend set at the UKRI rate (£19,237 for 2024/25). This is open to UK and overseas.

While the condition monitoring and data analytics have been implemented to some extent in transformer asset management in the past decades, development of transformer digital twin with integrated modelling capability is the key to optimise the transformer operation in the future power networks. The concept of Digital Twin, proposed nearly two decades ago, can be broadly defined as a virtual replica that mirrors a physical product lifecycle, simulating its visual aspect and behaviour based on bidirectional data transmission between the physical and the digital space. Utilities in the UK and across the world have recognised digital twining as a core objective of their digitalisation and innovation strategies. Furthermore, CIGRE has recently initiated a new working group A2/D2.65 on Transformer Digital Twin – concept and future perspectives.

Currently, there is a limited number of publications that focuses on the development of transformer digital twin. Most of the published studies only focused on partial capability of a digital twin or put together a set of disconnected models without synergetic interaction among them.

This PhD project aims to discuss and develop a comprehensive transformer Digital Twin framework by defining its scope and constructing multi-layers of functionality. It is envisaged that the established framework will involve multiple layers for different functions, e.g., real-time monitoring, physical modelling, data exchanging, health indexing and fault forecasting. Outcome of the PhD will have direct implications for the development of new international standards on transformer digital twin.

Applicants should have, or expect to achieve, first class honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Applicants must be able to demonstrate their research experience through contribution to international journal or conference publications.

Before you apply please contact the supervisors, Prof Zhongdong Wang and Prof Qiang Liu: zhongdong.wang@manchester.ac.uk qiang.liu@manchester.ac.uk

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