Arc Fault Location for Power Electronic based Distribution Systems (ENG1382)

Electricity distribution systems are rapidly evolving to meet the challenges of a more sustainable future – for example developing the supply grid to incorporate renewable energy systems and the increasing electrification of heating systems. Electrical systems providing partial or full propulsion for aircraft, ships and trains are also increasing in complexity. This project will research new, low cost technologies to improve the resilience of these electrical distribution systems through accurate detection and location of series arc faults, enabling the development of “self-healing” power systems. These new technologies can also be embedded into aging systems (aircraft and rail) where wiring/connector faults are likely to occur.

The project aims to demonstrate that power system impedance estimation can be used as the basis of arc-fault detection and location in complex electrical distribution systems, especially those with a high penetration of power electronic sub-systems. Previous work has demonstrated that conventional signal processing techniques can be employed on point-to-point power systems, however these are challenged when branches appear in the circuit, as multiple potential fault locations could be identified. The focus of this research will be to explore approaches such as pattern recognition and artificial intelligence to discriminate between multiple potential fault locations. 

The project will involve extensive experimental work to characterise arc faults so that they can be accurately modelled. These arc fault models can then be embedded into complex electrical system simulations which will be used to evaluate candidate fault detection and location algorithms.

The successful applicant will be based within the Power Electronics, Machines and Control Research Group at The University of Nottingham but will also work closely with members of the Applied Optics Research Group and the George Green Institute for Electromagnetics Research. 

The ideal candidate will have:

a first or upper second-class honours or master’s degree in electrical and electronic engineering or an equivalent degree from a recognised institution.A good knowledge or experience in electrical and power electronic systems.Experience of designing and using microprocessor-based data acquisition equipment in electrical and power electronic systems.Knowledge or experience of signal processing and artificial intelligence.Excellent analytical and numerical skills, as well as problem solving skills.Strong programming skills in Matlab, C/C++, or Python. Very good written and communication skills and fluency in English.

 

EPSRC DTP studentships are fully funded (fees and maintenance) for UK students or provide fees only for EU students from outside the UK, subject to eligibility requirements. The funding is for 3.5 years with a stipend of £15,285.  (details about eligibility can be found at: https://epsrc.ukri.org/skills/students/help/eligibility/).

Applications should be submitted via the University of Nottingham Applicant Portal http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx, with Mark Sumner identified as the potential supervisor. Your application should include;

a cover letter that describes your reasons for wishing to pursue a PhD and your suitability for this project. Please include the reference number (beginning ENG) in the cover letter;a copy of your CV, including a transcript of all University results, a list of publications, and contact details for two academic referees;copies of any publications or an example of your technical writing, such as a project dissertation;

Shortlisted candidates will be invited for a Skype interview.

Contact details

Name: Prof. Mark Sumner

Email:  mark.sumner@nottingham.ac.uk

Closing Date: 07 May 2020
Category: Studentships