PhD Studentship: PhD in Renewable Energy (Funded)

This PhD studentship, based at the University of Exeter's Penryn Campus (Cornwall), offers an opportunity to conduct research at the intersection of wind energy, power systems, and advanced control, addressing engineering questions in how future electricity networks can remain stable and resilient as renewable generation grows. Grid-forming (GFM) control is increasingly recognised as a critical enabling technology for future low-inertia power systems, and wind energy, as one of the largest and fastest-growing sources of clean electricity, occupies a significant role in this transition.

The integration of grid-forming wind turbines into power systems raises a broad set of interconnected questions, ranging from how individual turbines interact with the wider network to how large-scale wind generation can contribute to system-level services such as frequency regulation, voltage support, and fault recovery. Understanding and enabling these contributions is critical to ensuring that future power systems can operate securely under both normal and fault/disturbance conditions. In this project, you will investigate how GFM control can be applied to wind turbine systems to support the stability and resilience of power grids. The project is well-suited to students with backgrounds in electrical engineering, renewable energy, control engineering, or a closely related discipline, and can be tailored to your interests, whether you prefer system-level analysis, control design, simulation-based investigation, or a combination of these.

The specific research direction will be developed in collaboration with the successful candidate, taking into account their skills and interests as well as emerging priorities in the field. The successful candidate will join the Renewable Energy research group at the University of Exeter's Penryn Campus (Cornwall), working within a vibrant interdisciplinary team. Applicants should hold, or expect to obtain, a first-class or upper second-class honours degree (or equivalent) in a relevant discipline. Experience with modelling or simulation tools (e.g., MATLAB/Simulink, PSCAD, PowerFactory, or Python) is desirable.

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