Improving the security of uncertain power systems (FULLY FUNDED)

Student background required:
Interested students should have either electrical engineering, physics, or computer science degrees with good mathematics skills.

Benefit to / Impact on Industry:
Power system operators are increasingly troubled by ever-increasing numbers of interdependent and uncertain devices and controllers which have an effect on the performance and security of the network. This project will develop new tools that can describe this uncertainty and incorporate it into analysis to improve the security of modern power systems.

What novelty will the student base their PhD on?
The understanding and modelling of uncertainty and its impacts on power system stability and security is an emerging topic with great scope for new contributions. Investigations into the security (particularly the dynamic security) of power systems with uncertainties will be extremely novel.

Project overview:
Power system security is the ability of electrical networks to keep operating following disturbances. Modern power systems contain large numbers of uncertainties including large numbers of new and uncontrolled loads like electric vehicles and lots of weather-dependent renewable energy sources. Current security analysis techniques do not adequately represent these uncertainties, and therefore we don’t have a clear picture of how secure our power systems really are. This project will develop new models and analysis techniques to overcome this limitation and convey critical information about system security to power system operators.

Outline of Proposed Project Plan:
Year 1: Taught courses and preparatory study
Year 2: The main output from this year will be new models that can be used to represent systems uncertainty for power system security analysis. The models should be flexible enough to include different levels of detail (depending on what is known about the system uncertainties). These models will be thoroughly tested to ensure they integrate with established system security analysis techniques.
Year 3: The models from Year 2 will be investigated for a wide variety of case studies. Sensitivity analysis will be performed to determine how different uncertainties affect different system outputs and to establish critical uncertainties within power systems with respect to system security.
Year 4: In the final year, the aim will be to extend traditional security analysis to more effectively incorporate uncertainty. Particular emphasis will be placed on the visualisation of complex statistical results to ensure that critical system information is conveyed.