Pierre Haessig, assistant professor in Electrical Engineering & Control
My research interests include the sizing and the management of Energy Storage Systems, for mitigating the fluctuations of renewable energies (wind and solar), and more generally the stochastic optimal control of such dynamical systems.
Tools & Methods I used for my research
- Dynamic stochastic optimization (with dynamic programming, or model predictive control), for the optimal control of dynamical systems, in the presence of uncertainties
- Statistics (time series analysis), for modelling the stochastic inputs, in particular wind and solar power generation.
Practically, I work most of the time with the Python scientific ecosystem (IPython/Jupyter, numpy, pandas, matplotlib, see the software page). I've also started to experiment with Julia, in particular with the optimization package JuMP.
- Dynamic CV (updated November 2020, can be switched beween long and short format)
- Short CV (PDF, 2020)
- Long CV (PDF, 2020)
PhD in Electrical Engineering
From September 2011 to August 2014, I was a PhD student in Electrical Engineering in Rennes, France. My work was funded by EDF R&D, the biggest French electric utility, and I worked at SATIE, the electrical engineering lab of ENS Cachan.
The focus of my research was on Electricity Storage related to Wind Power generation. That is, the energy storage is used to mitigate the inherent variability in electricity production due to wind speed fluctuations.
Previous Research activities
Before starting PhD on electricity storage, I did research on Real-time Power Electronics Simulation. This work is now carried on by Typhoon HIL, Inc., a company which produces Hardware-In-the-Loop emulators of power electronics hardware, with a simulation timestep of 1 μs or less. More details on Typhoon HIL page.