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  Electric Vehicles as a Resilient Resource within Coupled Power and Transport Networks


   School of Engineering

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The increasing penetration of Electric Vehicles (EVs) is significantly impacting both power distribution networks and transport networks. The interaction between electric power distribution, transport demand, and EV charging behaviour, especially under contingency scenarios, presents complex challenges that are not well-explored in current literature. While high EV penetration poses challenges for real-time operation of transport and power systems, it also offers opportunities to enhance resilience through Vehicle-to-Grid (V2G) applications. For instance, individual EVs can power homes during outages, ensuring critical loads are maintained. Clustered EVs can support nearby facilities, such as hospitals or emergency centres, providing crucial backup power during grid failures. Additionally, these clusters can be used to assist in restarting substation transformers after significant events, effectively helping to restore power distribution networks more rapidly. This project is dedicated to developing a holistic analytical framework to model and implement EVs as a resilient resource within coupled grid and transport networks. Our approach aims to be applicable to both current and future contexts, offering a forward-looking perspective on resilient and sustainable transport and energy systems.

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.

Application enquires:

Dr Duo Li,  

Engineering (12) Mathematics (25)

Register your interest for this project


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