The global energy system is going through massive changes for many reasons including ever-increasing energy demand, climate change mitigation, and large-scale electrification. These changes have widespread implications in how we think of energy production and distribution, as well as on process operation, economics, and sustainability. In addition, due to increasing pressure to reduce costs in the process industries to remain competitive, decision-making levels that were previously considered separate, including process design, planning, scheduling, and real-time control are becoming ever-more tightly integrated. While this has significant potential to improve operations and reduce costs it brings about many challenges in modeling, process design and operation, and computational complexities. Our research group addresses these challenges through the following research areas:

Integrated Decision Making: The process industries can reduce costs by integrating information and decision-making activities across functions and decision-making levels. Our interests lie in coupled decision-making including topics such as demand side management, condition-based maintenance, integrated production and maintenance scheduling, and closed-loop planning and scheduling.

Power Systems Engineering: Design, simulation, and optimal operation of power systems and how they interact with the process industries including demand response, economic dispatch and redispatch, and power system planning.

Integrated Energy Systems: design, simulation, and optimal operation (both economic and sustainable) of systems with multiple energy pathways/components including energy storage methods, biofuels, etc.

Data-Driven Decision Making: The internet of things has enabled large-scale data collection from industrial processes and power systems. Our work focuses on utilizing data to make informed decisions in areas including condition-based maintenance, and alarm management.