At the Energy Systems Optimization and Control Lab, we combine modeling of thermal and fluid systems with model reduction and control and optimization theory to reduce the impact of buildings and transportation on the environment. We are advancing the state of the art in system dynamic and optimization by bridging the gap between the state of the art in optimization and control theory and the first-principle models describing thermo-fluid systems.
Research Areas and Applications
Model Order Reduction of Nonlinear Partial Differential Equations
- Application of conventional MOR techniques is limited to very few classes of systems;
- No proof that the reduced model will be stable and optimal in terms of accuracy;
- Selection of the technique is currently made based on prior experience
Current research is focusing on streamlining the process of deriving control-oriented models starting from first-principle models.
IC engine air path systems, turbochargers, gas turbine engines, aftertreatment.
Coordination and Optimization of Distributed and Large Scale Systems
Energy systems like district heating systems or residential buildings are large scale interconnected systems that can lead to significant energy consumption reduction when there is a coordinator in the loop. However, the systematic optimization of large scale systems, particularly when including thermo-fluid processes, poses significant challenges:
- Model complexity limits the choice of control techniques that can be applied;
- Mathematical framework for coordinated control is limited to linear
Current research is focusing on streamlining the process of deriving model-based and scalable controllers for large scale systems.
We are grateful for the support of our sponsors:
Department of Energy’s Advanced Research Projects Agency – Energy (ARPA-E)