The Institute for Energy Systems at the University of Edinburgh invites applications for a PhD studentship in “Quantum Computing for Power Systems Optimisation”. The aim of the project will be to investigate whether quantum computing can support the large-scale optimal deployment and coordination of renewable generation, energy storage and demand flexibility within electrical power systems.
Power systems are undergoing a fundamental transition due to the large-scale integration of renewable generation, coupled with the electrification of transportation and heating. In the UK, it is expected there will be 15 million electric vehicles by 2030 and the deployment of 600,000 heat pumps per year from 2028. The optimal deployment and coordination of these technologies is critical for achieving a low-cost transition to a reliable decarbonised power system. However, the computational complexity of these problems is pushing against the limits of even state-of-the-art high-performance computing facilities. In addition, modelling approximations that have long been used for network optimisation are increasingly unsuitable for resources embedded within local distribution networks due to their nonlinear characteristics and extensive topologies.
Over the last 20 years, there has been significant progress in the development of quantum devices which offer a fundamentally new computing architecture compared with classical silicon-based computers. A major milestone towards this was the recent achievement of quantum supremacy with a 54-qubit device, i.e. the practical demonstration of a quantum computer solving a problem that would be infeasible for classical computers. This has been described as the start of the Noisy Intermediate-Scale Quantum (NISQ) era, where medium-scale quantum computers with moderate error rates for the first time can outperform classical computers for specific applications.
Motivated by these advances, the project will investigate the opportunity for problem-specific quantum computing algorithms to address the scalability challenges associated with power system optimisation problems that are key for the net-zero transition. This will bring together research across quantum computing, mathematical optimisation, and power systems engineering. The project will explore different quantum computing architectures (including gate-based and annealing-based), as well as hybrid approaches which leverage the complementary advantages of both classical and quantum computing.
*Please note that this position may be closed early if a suitable candidate is identified.
Successful candidates will join the Institute for Energy Systems within the School of Engineering at the University of Edinburgh and will involve close collaboration with Edinburgh’s Quantum Informatics Group.
The Institute for Energy Systems has links with industry partners across the UK energy sector as well as leading energy system researchers from multiple disciplines through projects such as “EnergyREV – Market Design for Scaling Up Local Clean Energy Systems”, which is being completed as part of the UK’s £100m Prospering from the Energy Revolution Challenge initiative.
- T. Morstyn, “Annealing-based Quantum Computing for Combinatorial Optimal Power Flow”, in IEEE Trans. on Smart Grid, 2022, doi: 10.1109/TSG.2022.3200590.
- F. Feng, P. Zhang, M. A. Bragin, and Y. Zhou, “Novel Resolution of Unit Commitment Problems Through Quantum Surrogate Lagrangian Relaxation”, IEEE Trans. Power Syst., 2022, doi: 10.1109/TPWRS.2022.3181221.
- A. Ajagekar and F. You, “Quantum computing for energy systems optimization: Challenges and opportunities”, Energy, 2019, doi: 10.1016/j.energy.2019.04.186.
The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.
It is expected that candidates will have a first-class (or expected first-class) bachelors or master’s level degree in a relevant discipline, such as electrical engineering, computer science, applied mathematics or physics.
Experience in the following areas is essential:
- Quantum computation; or quantum mechanics; or a strong background in linear algebra and probability theory.
- Programming using languages such as Python, MATLAB or Julia.
Experience in one or more of the following areas is highly desirable:
- Power systems modelling.
- Optimisation, game theory and/or machine learning.
- Quantum computing software such as Qiskit, Cirq, or D-wave Ocean.
- Relevant industry or research experience.
Tuition fees + stipend are available for Home/EU students (International students can apply, but the funding only covers the Home/EU fee rate)