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  Optimal Planning and Operation of Social and Responsible V2G hubs at Motor-Retail Sites for a Net-Zero Power Grid


   Department of Electronic and Electrical Engineering

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  Dr Safak Bayram, Prof Stuart Galloway  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

In line with the Scottish Government’s net-zero policies, the motor retail (MR) business is under transformation to only sell electric vehicles (EV). Vehicle-to-grid (V2G) chargers enable large collections of EV batteries at MRs to support ancillary grid services and reduce wind curtailment. Unlike existing V2G applications, MRs can dynamically manage their inventories, promote social and responsible charging in congested areas via offered services, and advance social equity by enabling charging service in low-income regions. Therefore, this project will develop modelling and optimisation frameworks to investigate techno-economic and social trade-offs in V2G hub planning to improve the stability of electrical networks. 

This project aims to transform motor retail business into V2G hubs with the following objectives:

Carry out a data-driven assessment to model and quantify the role of V2G hubs in energy markets and renewable energy curtailment.

Develop a mathematical framework to choose optimal sites to deploy V2G hubs and investigate the trade-off between economic benefits and widened access to chargers in deprived areas.

Develop an optimal inventory model to optimise the number of EVs at a specific site by moving inventory between sites and complement it by allowing private EV owners to participate in V2G events via auction mechanisms

Design a smart charging algorithm for EVs located in retail sites optimally charge and discharge by considering associated battery degradation cost.


Engineering (12) Mathematics (25)

References

To be considered for the project, candidates must possess an undergraduate MEng, first-class BSc/BEng Honours or postgraduate MSc degree in Electrical Engineering, Operational Research, Applied Mathematics, Mechanical engineering, Physics, or similar. The candidate must have a strong background in electrical power engineering, data analytics, and operational research (optimisation and modelling) and be able to demonstrate the ability to lead the project independently. This 3.5years project covers UK Home Fees and Stiped (~£18.5k per annum (tax free).

Where will I study?

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 About the Project