Mean Field Control and Disorder for Efficient Mixing of Energy Loads
Virtual Informal Systems Seminar (VISS) Centre for Intelligent Machines (CIM) and Groupe d'Etudes et de Recherche en Analyse des Decisions (GERAD)
Speaker: David M茅tivier
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The introduction of renewable energies in power systems has forced electricity management to become more flexible both for generation and consumption. Demand Response (DR) is a control strategy aiming to address this challenge by adapting and controlling in real-time resources to the demand.聽Ensembles of cycling electrical devices are good candidates to be used in DR schemes.聽Approached from the standpoint of Statistical Physics, an ensemble of cycling devices represents a non-equilibrium system driven away from its natural steady-state by DR perturbations.聽After introducing the model describing large aggregate of devices via coupled Fokker-Planck equations, we will explore the following points: i) how randomness makes the system resilient, mixing it toward a steady-state; ii) how a Mean-Field Control, simple and private, can be implemented to improve the ensemble resiliency even more; iii) how disorder (variability) in the devices ensemble affects the system.
Bio:
David M茅tivier received his PhD in 2017 at University of Nice C么te d'Azur in France working on the dynamics of mean field particles systems. He did a 3 year postdoc at Los Alamos National Laboratory where he used methods from statistical physics (and mean field dynamics) applied to sustainable devlopment thematics. In particular he worked on the dynamics of thermostatic controlled loads and uncertainty quantification in electrical networks. He is since September a postdoc at the CMAP (applied mathematics) of 脡cole Polytechnique in France where he work on the resiliency of the French production system against climate change.聽
