PhD: Renewable Integration in Power Systems: Challenges in Estimation and Control

A fully-funded 3-year PhD studentship on Renewable Integration in Power Systems at the University of Southampton, a top university for Electrical Power Engineering in the UK and worldwide.

A transition from coal and gas based non-renewable generation to wind and solar based renewable generation is necessary to ensure a sustainable low-carbon future. But this transition introduces several challenges to power system operation. One of the challenges is to find the impact of stochastic and intermittent dynamics of renewable sources of energy on power grid, and how these dynamics can be better controlled to ensure global system stability. This is not a trivial problem given that the available integrated models of wind farms or solar parks do not correctly represent the dynamics of the constituent turbines or photovoltaic panels. Another challenge is a fall in system inertia for grids with large-scale integration of renewable sources, since renewable energy sources do not contribute to system inertia (which is the rotating mass in the system). A direct impact of low system inertia is to make the grids unstable as system inertia is needed to resist disturbances (such as a fault or a sudden load change) occurring in the system and to maintain the frequency of the system.

This project will find solutions to such challenges related to maintaining the stability of power grids in light of renewable integration. Towards this broad goal, the student will explore various ideas, such as developing an accurate model for a wind farm or solar park that preserves the underlying oscillatory dynamics, while reducing complexity, thereby eliminating the use of inaccurate substitute models. Such a model will then be used to design dynamic and optimal control schemes for wind farms or solar parks in order to assist in global power system stability. An idea to address the impact of renewables on system inertia is to accurately estimate the rate of change of frequency (RoCoF) in the system – as low inertia translates to high RoCoF – and use it to provide ‘synthetic inertia’ to the system using energy from high capacity storage devices or through intelligent control of wind farms and solar parks.

Further details and how to apply here.