Professor Steven A. Gabriel is an internationally renowned researcher in optimization, game theory/equilibrium modeling with many applications in energy, transportation, and the environment. His research has both a focus on methodologies as well as using state-of-the-art techniques in applied settings and has been active in both the public and private sectors.  

He is a Full Professor in the Department of Mechanical Engineering  as well as the Applied Mathematics, Statistics and Scientific Computing Program at the University of Maryland-College Park (USA).  In addition, he is an Adjunct Professor in the Department of Industrial Economics and Technology Management at the Norwegian University of Science and Technology (Norway)and a Research Professor at the German Institute for Economic Research (Germany).  He is spending his sabbatical year 2021-2022 as a Visiting Professor at Aalto University (Finland) and Chalmers University of Technology (Sweden) working on operations research problems in a variety of fields.

Lecture: Demand Response for Residential Power Loads

Due to increased use of variable renewable energy sources such as wind and solar power, demand response, i.e., temporal load-shifting can be an effective tool for power system flexibility. In this lecture we describe the motivations for demand response and then highlight two approaches in recent work to figure out optimal scheduling and implementation of demand response events by a load aggregator. The work involves both Monte Carlo simulation as well as stochastic dynamic programming (SDP) and some machine learning techniques as well. We provide some technical examples on both the simulation and SDP approaches for those not already familiar with these techniques. We focus on the Texas market (ERCOT) model as the testbed and report the results from several recent papers.