Evaluation of linear and nonlinear system models in hierarchical model predictive control of HVAC systems

Journal of Physics Conference Series, vol. 2042, pp. 012032

Abstract

Abstract Buildings are responsible for one third of the global final energy consumption. Model predictive control (MPC) can reduce their energy consumption and improve thermal comfort. However, designing the required models can be time consuming. Splitting the control problem into smaller subproblems could make the modeling process more modular and therefore cheaper. A hierarchical MPC structure is proposed in this work, where the building model is divided into a lower layer consisting of the producer side and an upper layer consisting of the consumers. Linear and non-linear model equations as well as a cost-based and a control quality-based cost function for a building energy system are developed. In a simulation, the nonlinear controller outperforms the linear controller in both constraint satisfaction and energy costs.

Authors 4

1. Steffen Eser corresponding Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Germany

2. Phillip Stoffel Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Germany

3. Alexander Kümpel Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Germany

4. Dirk Müller Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Germany