英国埃克塞特大学申舒航老师课题组诚招博士研究生（国际学生全额奖学金）
博士课题-移相变压器的结构优化及关键性能评估：
要求：硕士毕业（或可于2025年1月前入学），硕士研究方向为电力变压器，变压器多物理场仿真，电力设备结构优化等相关方向，硕士期间有发表相关方向论文发表。雅思均分6.5，单科不低于6.0.
奖学金情况：学费全免，每年生活费补助为£19,237（免税）。额外支持: 参加国际会议、研讨会和其他专业发展机会的资助。（每月生活费用示例：住宿约£600; 食物约£300; 交通约£100）
宝贵机会：与英国国网NGET专家直接交流，获得领域内的实践经验；可能的实习机会和与NGET的合作项目；英国就业前景光明。
申请截止日期：2024年10月25日
申请链接(阅读原文)：
https://www.exeter.ac.uk/study/funding/award/?id=5274
如有意申请，请联系申舒航博士：s.shen@exeter.ac.uk
埃克塞特大学简介：
埃克塞特大学是罗素集团中的全球领先的研究型大学。在2024年QS排名中位列第153位，并在《泰晤士报》2024年英国大学排名中位列第11位。
项目简介：
我们正在寻找一名有动力和才华的博士研究生加入我们在变压器和移相变压器(PST)方面的开创性研究项目。该项目旨在深入探讨这些电网关键设备的结构设计优化和性能分析。目标是结合有限元法（FEM）建模和机器学习技术来优化PST的尺寸，从而实现紧凑设计。
团队简介：
申舒航博士是英国埃克塞特大学智能电网讲师，智能电网硕士课程主任，获得曼彻斯特大学博士学位。他是CIGRE JWG A2.D1.67工作组的英国代表之一，是Universities High Voltage Network的委员会成员，也是University Transformer Research Alliance的成员。他近期的研究方向旨在将系统运行控制和规划与设备特性相结合，以最大化网络性能。这一新颖的研究方向目前正在取得可喜的成果，并吸引了工业界的关注。Peter Crossley教授是英国埃克塞特大学智能电网教授，获得剑桥大学博士学位，并拥有超过40年的工业界合作工作经验。他是中国电机工程学会会士和IEEE杰出讲师，曾任英国自然科学基金电力网络博士培训中心主任，以及清华大学及中国国家电网客座教授。团队拥有充足的科研经费和实验室资源，与英国国家电网保持良好的合作关系。
招聘广告：
Size Optimisation and Operational Performance Evaluation of Phase Shifting Transformers, Electrical and Electronic Engineering – PhD (Funded)
About the award
Supervisors
Dr Shuhang Shen ,
University of Exeter
Professor Peter Crossley, University of Exeter
Location: Department of Engineering, Streatham Campus, Exeter
The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully-fundedto commence on 23 September 2024 or as soon as possible thereafter. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study. The student would be based in Centre for Smart Grid in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.
Project Description:
Phase Shifting Transformers (PSTs) are critical components of modern electrical grids, offering powerful control over power flow and enabling the efficient management of electricity transmission. As the global energy landscape transitions towards renewable energy sources, the need for advanced power control devices like PSTs becomes increasingly critical. PSTs, with their ability to adjust phase angles and redistribute power flows, provide a solution to the challenges in accommodating the variability and unpredictability of renewable energy sources. However, the conventional design of PSTs has limitations of massive size and certain operational constraints such as core saturation. This project seeks to address these limitations by exploring innovative approaches to PST design, with a particular emphasis on size optimisation.
The research will employ a multidisciplinary approach, integrating Finite Element Method (FEM) modelling and Machine Learning (ML) techniques to achieve the project's objectives. The first phase will involve a comprehensive review of existing PST designs, focusing on their operational constraints. Following this, advanced FEM simulations will be conducted to model the electromagnetic behaviour of PSTs under various load conditions. These simulations will provide detailed insights into the factors influencing PST performance. In parallel, Machine Learning algorithms will be developed that can inform the design optimisation process. By leveraging the predictive capabilities of ML, the project aims to propose innovative PST designs that are not only compact but also superior in performance.
This award provides annual funding to cover Home tuition fees and a tax-free stipend. For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £19,237 per year tax-free stipend.
The studentship will be awarded on the basis of merit for 3.5 years of full-time study, expected to commence on23 September 2024. The collaboration involves a project partner who is providing funding [and other material support to the project], this means there are special terms that apply to the project, these will be discussed with Candidates at Interview and fully set out in the offer letter.
International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.
Entry requirements
Applicants for this studentship must have obtained, or be
about to obtain, a First or Upper Second Class UK Honours degree, or the
equivalent qualifications gained outside the UK, in Electrical and Electronic
Engineering or an appropriate area of science or technology.
If English is not your first language you will need to meet the required level
as per our guidance at https://www.exeter.ac.uk/pg-research/apply/english/
How to apply
In the application process you will be asked to upload several documents
•CV
•Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
•Research proposal
•Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
•Two references from referees familiar with your academic work. If your referees prefer, they can email the reference direct to PGRApplicants@exeter.ac.uk quoting the studentship reference number.
If you have any general enquiries about the application process please emailPGRApplicants@exeter.ac.uk or phone 0300 555 60 60 (UK callers) +44 (0) 1392 723044 (EU/International callers). Project-specific queries should be directed to Dr Shuhang Shen by s.shen@exeter.ac.uk.
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