Power grid is increasingly penetrated by renewable and distributed energy resources, aiming to achieve the net-zero emissions by 2050. The integration of renewable energy will increase the volatility and reduce the stability of power grid operation. On 09 August 2019, approximately 1 million customers lost power as a result of a series of events (National Grid ESO LFDD Incident Report), which caused significant disruption to many people in their homes and businesses as well as public services such as trains and airports. One key challenge of the stability power grid operation is the lack of ‘smart grid’. The existing physical grid is passively controlled by a centralised control centre, with limited flexibility to cope with distributed renewable energy, and lack of smart algorithms leading to the sub-optimal grid operating strategy.

This PhD project will investigate the converter-controlled renewable generation with AI-enabled network control, which will enhance the frequency stability and voltage regulation in the future power grid. This will transform the traditional grid to an integrated ‘cyber-physical power system’ with physics-controlled and AI-networked autonomous and distributed operating strategy.

The following objective are:

1. Model the smart converter-based energy techniques to achieve the flexible power-controlled and digital communication-enabled renewable power generation.

2. Develop power network models with AI-based algorithms for network control.

3. Integrate AI-enabled network control (cyber) with physical-control of renewable generation (physical) for a novel cyber-physical grid operation.

4. Validate with numerical simulations and industrial power systems for voltage and frequency stability enhancement.

The student will conduct joint research work in Control and Power Systems Laboratory (AI-enabled network control) and Electrical Machines and Drive Group (converter-based renewable generation, conversion and storage). At the end of the PhD project, the student is expected to develop: 1. Novel physical control methods to improve the flexibility and digitalisation of smart energy assets, 2. Advanced models to simulate the cyber-physical power grid, 3. AI-based control strategy to improve the grid stability operation.

Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.

We require applicants to have either an undergraduate honours degree (1st/2:1) or MSc (Merit or Distinction) in a relevant science or engineering subject from a reputable institution.

Please refer to the EPSRC DLA webpage for detailed information about the EPSRC DLA and how to apply. On the DLA application, make sure that you enter the code from the project title. Do not apply for the standard School PhD.

The award will fund the full (UK or Overseas) tuition fee and UKRI stipend (currently £19,237 per annum) for 3.5 years, as well as a research grant to support costs associated with the project. The amount available from the EPSRC grant for research costs is £4,500 total across the lifetime of the award.