Abstract:

Energy storage capable electric loads such as heating-cooling and water heating loads have long been identified as presenting a promising potential in load shaping, as their electric state can be partially decoupled from user consumption actions. These thermostat-controlled loads are typically represented individually by hybrid-state (continuous-discrete) stochastic processes. Statistical mechanics-inspired aggregation approaches lead to PDE-based models of their macroscopic behavior.
We review the basic aggregate uncontrolled load modeling methodology for the special case of heating-cooling loads. Subsequently, we illustrate how a new type of aggregator-customer contract, involving probabilistic discrete set point switching actions, can lead to desired global results through local control actions. The computation of aggregator-dictated switching statistics is achieved through sequential interleaving of a numerically based PDE computational time step, and the solution of a second-degree algebraic equation. The coefficients of the latter are built based on the results of the PDE forward propagation step. Numerical results illustrating the potential of the approach are presented.

Bio:

Roland Malhamé received the Bachelor’s, Master’s and Ph.D. degrees in Electrical Engineering from the American University of Beirut, the University of Houston, and the Georgia Institute of Technology in 1976, 1978 and 1983 respectively.
After single year stays at University of Quebec, and CAE Electronics Ltd (Montreal), he joined in 1985 École Polytechnique de Montréal, where he is Professor of Electrical Engineering. In 1994, 2004, 2012, 2018 he was on sabbatical leave respectively with LSS CNRS (France), École Centrale de Paris, University of Rome Tor Vergata, and National Technical University of Athens.
His interest in statistical mechanics inspired approaches to the analysis and control of large-scale systems has led him to contributions in the area of aggregate electric load modeling, and to the early developments of the theory of mean field games. His current research interests are in collective decentralized decision-making schemes, and the development of mean field-based control algorithms in the area of smart grids. From June 2005 to June 2011, he headed GERAD, the Group for Research on Decision Analysis. He is past Associate Editor of IEEE Transactions on Automatic Control. He was elected Fellow of IEEE in 2022 and is a recipient of the 2024 Isaacs award.