The proposed research in this PhD project builds on an existing collaboration with the National Grid ESO’s Electricity National Control Centre (ENCC) where a decision-support tool is collaboratively developed to enable ENCC to use a very large number of units to balance electricity demand and generation in real-time operation of the system. The decision-support tool is based on a mathematical programming model where various constraints of dispatch electricity generators to meet demand are expressed mathematically. While the tool provides theoretical guarantees of converging to an optimal solution, the computational times to reach a solution may be very large. Given the nature of real-time balancing of the British system, there is a desire to reduce the computational time and be able to manage the accuracy versus time trade-off.

For this exciting and important PhD we are seeking a student with an interest in applying advanced mathematical and computational techniques to electricity system problems. The project will require candidates to have excellent mathematical and/or computational skills and an interest in the energy sector. Prospective candidates should have or are about to receive a good Honours degree (a first class or a 2:1), an MEng or MSc with Distinction or with Merit in Electrical Engineering, Mechanical Engineering, Control Engineering, Computer Science, Mathematics, Physics or other related disciplines.

The PhD position is fully funded (tuition fees plus a stipend for living expenses) for UK home students through the Research Excellence Framework of the University of Strathclyde. Overseas students may apply and make use of the provided scholarship, though we note that they would need to provide their own funding to make up the difference between the UK and overseas tuition fees. The student will be supervised by Dr Waqquas Bukhsh and co-supervised by Prof Keith Bell. Dr Andrei Bejan, Optimisation Delivery Lead for the National Grid ESO Balancing Programme, is industrial supervisor on the project and will provide guidance on application of the research.

We anticipate competition for this studentship to be intense and encourage interested candidates to apply early. Interviews will take place during April and the expected start date is October 2023.