FLEXIBILITY PROVISION FROM ENERGY SYSTEMS INTEGRATION

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.