Optimal control of a fourth generation district heating network using an integrated non-linear model predictive controller. (25th March 2023)

• Record Type: Journal Article
• Authors: Jansen, Jelger; Jorissen, Filip; Helsen, Lieve
• Is Part Of: Applied thermal engineering. Volume 223(2022)
• Publication Date: 2023-03-25
• Subjects: Fourth generation district heating -- Heritage buildings -- System integration -- Non-linear optimisation -- Model predictive control; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2023.120030
• Languages: English
• ISSNs: 1359-4311

Abstract

Abstract: District heating (DH) can help increasing the share of renewable and residual energy sources in the heating sector. Usually a rule-based controller (RBC) is used for controlling these networks while more advanced control strategies like model predictive control (MPC) can support the transition to a decarbonised heating sector. In this paper, an integrated non-linear MPC approach for the control of DH networks is presented. The main novelties are the consideration of the system as a whole (including the heat demand side) and the inclusion of important non-linearities and all types of flexibility in the controller model of the MPC. A simulation-based methodology and dedicated solver are used in which the MPC is applied to an existing fourth generation DH network. The results of a three-day simulation in both a winter and spring period show that the MPC outperforms the currently used RBC: the thermal discomfort is lower in the winter period and comparable in the spring period while the electrical energy use of the DH system is reduced by 3% and 17%, respectively. The MPC achieves these results by lowering the network temperatures, using its anticipatory ability, and exploiting the flexibility of the building thermal inertia. Highlights: Development and assessment of a non-linear MPC as system integrator for a district heating system. The MPC can exploit all types of flexibility in the district heating system. The MPC is applied to an emulator model of a real-life district heating system. Simulation results show that MPC outperforms the existing rule-based controller.