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  Resilience of Future Power Distribution Networks

   Department of Electronic, Electrical and Systems Engineering

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  Dr Daniel Donaldson, Dr A Quinn  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Project Description

The growing societal dependence on electricity has heightened the need for resilient power system infrastructure. Infrastructure owners face the task of successfully decarbonising the grid while meeting demand for electricity in a safe and affordable fashion. The transition from the current electrical distribution grid to the future is complicated by uncertainty in the future demand, the exposure to natural hazards and other operational threats.

This PhD research will explore future demand (including electric vehicles and heat pumps) alongside the threat posed by natural hazards (e.g. flooding, wildfires, and/or windstorms) to propose methods to enhance distribution network planning. Statistical and machine learning algorithms will be developed to support optimal decision making in the face of uncertainty.

Project Benefits

  • The studentship will cover home tuition fees plus an annual tax-free stipend for 3.5 years. (International applicants from outside the UK are welcome to apply, but will need to secure additional funding to cover the difference between international and UK fees.)
  • Opportunity to engage with industry stakeholders and present actionable research findings
  • Conference attendance: Funding is allocated to enable the student to attend and present research at key conferences during their PhD.

Student Profile

Applicants should have (or are about to obtain):

  • An undergraduate degree (2:1 or higher) and preferably a Master's degree in engineering, computer science, statistics, physics, geography, earth and environmental sciences or a related field.
  • Familiarity with at least one programming language (Python, R, etc.)
  • Relevant industry or research experience

Strong knowledge in one or more of the following areas is desirable:

  • Electricity distribution networks
  • Familiarity with spatial, time series, and meteorological data.
  • Machine learning
  • Reproducible research (GitHub, machine learning pipelines, LaTeX/Markdown etc.)

Application Details

To apply, send the following materials to Dr. Daniel Donaldson d.l.donaldson(at) with the subject line 'Prospective PhD Student':

  1. A statement explaining your motivation for pursuing a PhD and why you would like to undertake this research (1 page A4)
  2. A short research proposal describing how you would tackle the challenges above (maximum 2 pages A4)
  3. CV containing academic record and relevant experience

The deadline for applications is April 29th, with interviews taking place in May. The PhD is anticipated to commence in October 2023.

Computer Science (8) Engineering (12) Environmental Sciences (13) Geography (17) Mathematics (25) Physics (29)

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 About the Project