About the Seminar
EDF, the main French electricity utility, is one of the European leaders in the energy sector and a major actor of the electrical nuclear industry in the world. EDF has so numerous and various open real-life problems with very challenging associated scientific problems. Focusing on energy management of power systems in the framework of clean energy transition, we present some open and emerging problems such like the daily unit commitment, the integration of renewable energies and electrical vehicles in the distribution network, the smart charging, the modelling of the behavior of customers and taking it into account in energy management and pricing. We illustrate how these problems lead to a wide variety of challenging optimization problems where nonlinearity, nonconvexity, uncertainties, binary variables and high dimension interact, rendering their resolution difficult to handle. Finally, we present some research work carried out by EDF, in connection with academics.

About the Speaker

Dr. Riadh Zorgati is a research engineer at EDF, Research & Development Division since 1990. He was a project manager and a researcher on signal processing and inverse problems applied to nondestructive testing of nuclear power plants during 8 years. He joined the department OSIRIS (Optimization, Simulations, Risks & Statistics) in 2000 where he was a project manager on weekly electricity management. His current research activity is related to optimization under uncertainty and inverse problems and their application to energy management with an emphasis on probabilistic, robust and conic optimization methods. His research activities have been awarded in 1994 and 2010.

Riadh ZORGATI received his PhD degree in Physical Sciences from the Université de Paris-Diderot in 1990. He taught Optimization and its applications to power systems at the Université de Paris-Orsay from 2005 to 2016. He was Associate Director of Research at the French national research center (CNRS), from 2003 to 2008 and carried out research on inverse methods applied to non-destructive evaluation.