Chance Constrained Games for Energy Management under Uncertainty

PIs:

• Jianqiang Cheng, Systems and Industrial Engineering, UArizona
• Abdel Lisser, University of Paris Sud

We focus on applied problems where it is necessary to make optimal decisions in the presence of risk and uncertainty together with dependence between the random events, where the source of uncertainty is twofold. One component of uncertainty is exogenous and results from substantially incomplete knowledge of important dependent problem data, like demand for goods and services, weather conditions, prices for commodities, high-impact technical failures, and other disruptions occurring with low probability. If only this kind of uncertainty is present, then the adequate methodology for modeling and solving such decision problems is stochastic optimization using copulae. This is an active and dynamic field of research for both applicants, who are among the leading international contributors. The second component of uncertainty is endogenous and comes from the actions of independent actors who constitute the system under study. This component adds another level of complexity to an already difficult problem that makes it difficult to solve numerically. We will address this uncertainty from the viewpoint of multistage optimization and probabilistic constraints, mobilizing our experience in stochastic programming and game theory. This project aims to set up a joint collaboration between the research groups from the University of Arizona and Université Paris Saclay, CentraleSupelec in developing a methodology for games in energy market under risk and uncertainty and for closely related problems of evaluation of industrial projects in energy.