PhD student, Department of Computer Science and Technology
E-Mail: [email protected]
Research Topic: Complementarity of distributed renewables and its effect on the transmission grid
Research interests: renewable forecasting, energy transmission grid, climate models, probabilistic modelling, artificial intelligence
Biography: Petr is a PhD student at the AI for Environmental Risk research (AI4ER) CDT, University of Cambridge (since October 2019). He previously studied Physics (MSci) at the University of Cambridge as well.
He’s looking at the possibility of using multiple renewable energy sources, distributed spatially across large areas, to complement each other and reduce the uncertainty of the total energy supply in an electric grid. To assess this, he uses AI methods learned on meteorological data and the newest climate models.
The goal is to quantify the stability gained by connecting existing grids into a larger super-grid. Also, to analyze how connected the grid needs to be to harness this complementarity.