EPSRC Funded Studentship: Optimal control of electricity networks with intelligent agents (2018)

What you get

You will get:

• home/EU PhD fees
• a tax-free living expenses at Research Council UK rates (£14,777 per year for 2018/19)
• research/training expenses for three and a half years.

Type of award

PhD

PhD project

The aim of the project is to utilise the distributed analysis and computation capabilities of large numbers of control hardware and software in future electricity networks, to optimise network resilience, cost and emissions.

You will investigate to what extent large-scale electricity network problems can be solved using artificial intelligence and distributed optimal control techniques.

Resilient electrical distribution networks are necessary for integrating more renewable energy and reducing emissions. The proportion of energy supplied by renewable energy in the UK is expected to increase, in view of the EU target of 27% renewable energy penetration by 2030 and the UK government target of reducing greenhouse gas emissions by 80% by 2050.

Electricity networks are very complex, and several decisions must be taken in milliseconds, ranging from isolating a single domestic customer, to re-distributing the power of a whole city.

These decisions must be taken optimally and involve many "players", i.e. network equipment, generators, human operators, etc.

One example is contingency analysis, where an algorithm analyses all possible combinations of failures to derive the optimal response. Such problems are solvable in small systems, but do not scale up very easily.

In this project, it is proposed that optimal control techniques can be integrated in electrical networks through intelligent control software and hardware, thus making it easier to undertake electricity network analysis calculations.

You will participate in an interdisciplinary collaboration between the Engineering and Mathematics departments at the University of Sussex, and the Engineering department at Durham University.

You will also engage with a wide network of leading academics and industrialists in the UK, the EU and worldwide.

You will play an active role in the development of exciting research activities within the Future Energy and Transport (FET) Laboratory, which is part of the School's Dynamics, Control and Vehicle (DCV) Research Group.

You will benefit from hands-on training on state-of-the-art real-time Hardware-in-the-Loop (HiL) laboratory equipment, including a range of industrial controllers.

The School is committed to equality and valuing diversity, and currently holds an Athena SWAN Bronze Award.

Applications are particularly welcomed from women and black and minority ethnic candidates, who are under-represented in science and engineering at Sussex. The University offers various schemes to provide real benefits to parents.

Eligibility

To be eligible, you need to:

• have an excellent academic record and should have received or be expected to receive a relevant first or upper-second class honours degree
• be a UK or EU student who has been ordinarily resident in the UK for the previous three years. If you are from the EU and you do not meet this criteria, you will only be eligible for a fee waiver
• be enthusiastic, self-driven and independent, be able to work well in a team as well as individually, and committed to excellent research. 

Familiarity with electrical power systems, Smart Grids or optimal control is desirable but not essential.

Modelling experience and programming skills in languages such as Java, Python, MATLAB, or C++ would be useful.

Applicants with significant relevant non-academic experience are also encouraged to apply.

If you are an overseas (non-EU) student, you are not eligible to apply.

Deadline

30 June 2018 17:00

How to apply

You need to apply for a PhD in Engineering via the University of Sussex postgraduate application system.

When you apply, include a brief statement of your scientific interests and skills/experience for the mandatory "research proposal" section, including how they relate to this project (maximum two pages).

You should also indicate Dr Spyros Skarvelis-Kazakos as your preferred advisor and clearly state the title of the studentship in the finance section.

Contact us

Email Dr Spyros Skarvelis-Kazakos at S.Skarvelis-Kazakos@sussex.ac.uk

 

Timetable

The deadline is 02/03/2018.