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Flexibility provision from energy systems integration

Project Description

As part of this project, novel methodologies and modelling tools will be developed to analyse integrated energy systems and optimise their operation. The project will provide detailed understandings about cost-effective solutions for tackling the need for flexibility in the GB power system.

Developing such a modelling framework involves several fundamental scientific contributions:
•Novel statistical methods will be developed to characterise uncertainties in energy systems.
•Innovative mathematical methods will be used for modelling interdependent energy vectors with different temporal granularities.
•Advanced optimisation algorithms are essential to achieve a reliable optimum solution for the large-scale optimisation problem in complex integrated energy systems.

This is an inter-disciplinary research project that requires the PhD candidate to develop skills and obtain specialist knowledge in the area of power systems, thermodynamics, mathematical programming and modern control theory.

The main tasks are:
1.Detailed dynamical models of the selected flexibility technologies will be developed to characterise their time-dependent behaviour. The models will be developed using MATLAB/Simulink and/or the Dymola platform, which is designed for modelling of complex multi-disciplinary systems. In order to accurately represent the flexibility technologies in the whole-system flexibility quantification, and at the same time to address the computational expenses, key technical characteristics and operational specifications of the flexibility technologies will be formulated through developing reduced order models (ROM) and validating them using the detailed dynamical models.
2.Different forms of flexibility services (eg frequency response, reserves, load shifting, peak shaving) that can be provided by the heat sectors will be identified. Based on the physical characteristics and dynamic behaviour of different flexibility technologies and their operating boundaries, the type and magnitude of flexibility services that different technologies can offer will be quantified.
3.Using the models developed in Task 1, model predictive control will be employed to ensure the optimal operation of an integrated electricity and heat system. To this end, forecasting tools will be also adopted to predict the future behaviour of the system.


You should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.

Applicants with a Lower Second Class degree will be considered if they also have a master’s degree. Applicants with a minimum Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

Funding Notes

Full awards, including the Tuition fee and maintenance stipend (Approx. £14,777 in 2018/19), are open to UK Nationals and EU students who can satisfy UK residency requirements. To be eligible for the full award, EU Nationals must have been in the UK for at least 3 years prior to the start of the course for which they are seeking funding, including for the purposes of full-time education.


Applications should be made online at:

Please note the following when completing your online application:

The Programme name is Doctor of Philosophy in Engineering with an October 2019 start date.

In the "Research proposal and Funding" section of your application, please specify the project title, supervisors of the project and copy the project description in the text box provided.

Please select “No, I am not self-funding my research” when asked whether you are self-funding your research.

Please quote “project ID” when asked "Please provide the name of the funding you are applying for".

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