PhD Studentship - A chess-computing analogy for resilience decision support of electricity networks

About the Project

Summary of Award (Web Text)

100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate).

Overview of Project

This PhD will develop a data-driven framework to understand how climate-driven extreme weather affects electricity distribution networks and how targeted interventions can reduce disruption. Using high-resolution climate data, fault records and network models, the project will quantify how hazard conditions interact with asset characteristics and network structure to produce service losses. The research will move beyond conventional stress testing by identifying which infrastructure upgrades deliver the greatest resilience benefits under future climates. The outcomes will support industry and regulators in designing cost-effective adaptation strategies, helping to reduce outages, improve reliability, and strengthen societal resilience to increasingly severe weather events.

Research questions

• Can an Alpha-zero type chess-engine paradigm be used for making more effective infrastructure investment decisions
• Does a multi-dimensional fragility surface approach significantly reduce the uncertainty associated with single variable fragility curves.
• Can we use network topology and other asset information to get a better relationship between network faults and service losses 1.3

Methodology

The methodology develops a quantitative framework linking hazard to consequences through a multi-dimensional fragility/consequence surface capturing the full hazard–asset–network interaction and translating it into Customer Minutes Lost (CML). The system performance (CML) can be expressed as:

 CML =f (H, A, T, O), representing the hazard environment, asset characteristics, network topology and operational capability.

First, the drivers of asset faults will be modelled. NaFIRS fault records will be combined with high-resolution weather data and a GIS asset database describing asset location, type and network topology. Meteorological variables will be mapped onto the network using the hazard grid, which defines the spatial resolution of the hazard–asset interaction. For each historical event, faults/ will be associated with the meteorological conditions at the asset location, allowing failure probability to be estimated as a function of the hazard.

Each fault will be propagated through a network topology model to estimate CMLs. The model will include feeder configuration, downstream customers, protection systems and alternative supply paths. This allows identical asset failures to produce different outcomes depending on their position within the network.

A multi-dimensional fragility/consequence surface will then be derived mapping hazard and system configuration directly to expected service consequences CMLs. Candidate interventions (e.g. vegetation management, asset replacement etc) will be evaluated through counterfactual re-simulation of historical storms. In chess terms, the storm (white) moves first, the analysis determines which changes to infrastructure configuration (black pieces) most reduce the probability of unacceptable CMLs.

1.4 Anticipated outcomes & benefits for the sponsoring organisation and other stakeholders

• A better understanding of how different weather variables affect fragility
• A better understanding of the relationship between climate hazard, network assets, network topology and operational capability, and societal consequences
• An insight into a possible framework for proposing and assessing resilience enhancements

Start Date

21st September 2026

Duration of Award

3.5 years

Sponsor (Web Text)

NERC

Eligibility Criteria (Web Text)

A 2:1 Honours degree, or international equivalent, in a subject relevant to the proposed PhD project (inc. geography, earth sciences, engineering, computing and mathematics).

Relevant skills are: GIS, computing, statistics, Artificial Neural Networks, climate projections

Home and international applicants (inc. EU) are welcome to apply and if successful will receive a full studentship. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills.

International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.

How to Apply

You must apply through the University’s Apply to Newcastle Portal.

Once registered select ‘Create a Postgraduate Application’.

Use ‘Course Search’ to identify your programme of study:

• search for the ‘Course Title’ using the programme code: 8040F
• select ‘PhD Civil Engineering – Civil Engineering (Structural) (full time)' as the programme of study

You will then need to provide the following information in the ‘Further Details’ section:

• a ‘Personal Statement’ (this is a mandatory field) - upload a document or write a statement directly into the application form
• the studentship code IRISK02 in the ‘Studentship/Partnership Reference’ field
• when prompted for how you are providing your research proposal - select ‘Write Proposal’. You should then type in the title of the research project from this advert. You do not need to upload a research proposal.