TY - GEN A1 - Reimann, Ansgar A1 - Rose, Max A1 - Küpper, Jan A1 - Schiffer, Johannes T1 - Nonlinear system identification and predictive control for waste heat recovery with heat pumps T2 - IFAC-PapersOnLine N2 - The utilization of low-temperature waste heat, particularly from electrolyzers, in district heating networks via heat pumps presents a promising approach to accelerate the decarbonization of the heat sector. However, managing the electrolyzer’s specific temperature requirements and dynamic waste heat output, while simultaneously meeting the district heating network’s variable temperature demands, requires the implementation of an advanced control system for the heat pump cycle. For this, model predictive control is a promising approach since it not only ensures the satisfaction of constraints, but also facilitates a direct optimization of the heat pump’s operational efficiency. Nevertheless, model predictive control requires a dynamic heat pump model. In this context, first-principles models are often used. However, they are very complex and difficult to parameterize for real heat pumps. Therefore, in the present paper, a data-based system identification is carried out to obtain a reduced-order heat pump model from a high-fidelity first-principles simulation model. Based on the identified model, a predictive controller is implemented. The effectiveness of the obtained controller for operating the first-principles model is demonstrated in a numerical case study. Y1 - 2024 U6 - https://doi.org/10.1016/j.ifacol.2024.07.103 SN - 2405-8963 VL - 58 IS - 2 SP - 130 EP - 135 PB - Elsevier BV ER - TY - GEN A1 - Rose, Max A1 - Hans, Christian A. A1 - Schiffer, Johannes T1 - A Predictive Operation Controller for an Electro-Thermal Microgrid Utilizing Variable Flow Temperatures T2 - IFAC-PapersOnLine N2 - We propose an optimal operation controller for an electro-thermal microgrid. Compared to existing work, our approach increases flexibility by operating the thermal network with variable flow temperatures and in that way explicitly exploits its inherent storage capacities. To this end, the microgrid is represented by a multi-layer network composed of an electrical and a thermal layer. We show that the system behavior can be represented by a discrete-time state model derived from DC power flow approximations and 1d Euler equations. Both layers are interconnected via heat pumps. By combining this model with desired operating objectives and constraints, we obtain a constrained convex optimization problem. This is used to derive a model predictive control scheme for the optimal operation of electro-thermal microgrids. The performance of the proposed operation control algorithm is demonstrated in a case study. Y1 - 2023 U6 - https://doi.org/10.1016/j.ifacol.2023.10.195 SN - 2405-8963 VL - 56 IS - 2 SP - 5444 EP - 5450 ER -