1. To develop and study models of an electrical power grid operating under various future energy scenarios including a high level of renewables, including using electricity price as a control parameter.
2. To investigate the roles of electricity storage, interconnectors and demand-side management in the control of the electricity system.
3. To investigate the challenges and opportunities of high levels of electric vehicles for the transmission and distribution systems and as a resource for power-system stability.
Methodology and innovation
The dynamics of AC power flow has been much studied by power systems engineers and control theorists. The AC power flow equations are computationally intensive for realistic networks, so it is common to approximate AC flow by proxy models, such as DC power flow, in which the transmission lines are assumed to be purely reactive, and the voltage is fixed at each bus. The model then reduces to the specification of real-power inputs at the buses together with a matrix giving the transmission line flows in terms of the powers at the buses. The so-called swing bus is used to balance network power.
The project will develop a differential-equation DC power flow transmission model of generation, storage, interconnectors, and demand-side management, modulated by price as an adaptive control mechanism, and will investigate its properties, both theoretical and in practice on real data, including the effects of system noise. Focus will be on studying the effect of high penetration of renewables as well several other future energy scenarios.
Depending on student preferences, the project will either expand the model to include aspects of physical AC flow, in particular voltage and frequency maintenance, or it will build a fully networked model (incorporating transmission losses), allowing an analysis of the effect of variable pricing at buses (individual or grouped), including nodal and zonal pricing.
Finally, the project will study the effect of high penetration of EV on transmission networks and distribution networks, using the models to understand how EV might be used as a resource for system stability and how such use might be effectively incentivised.
Applicants must apply using the online form on the University Alliance website at https://unialliance.ac.uk/dta/cofund/how-to-apply-2/
. Full details of the programme, eligibility details and a list of available research projects can be seen at https://unialliance.ac.uk/dta/cofund/
The final deadline for application is 12 April 2019.