Simplifying decision-making in the model-based co-design of building energy systems through automatically generated optimal controllers

Energy-efficient technologies and efficient engineering processes are two major prerequisites for the fast and cost-efficient energy transition of the built environment. This study analyzes the potential of automatically generated optimal controls to not only enable high-performing building operation but also to simplify and streamline the decision-making process in the design phase. As a case study, the re-design of the energy supply system for a historic neighborhood in Bruges, Belgium, fully based on renewable and residual energy sources (R2ES) with air-source and ground-source heat pumps, photovoltaic thermal (PVT), and photovoltaic (PV) systems is used. Two design procedures, either using manually generated Rule-Based Control (RBC) or automatically generated Optimal Control (OC), using the Toolchain for Automated Control and Optimization (TACO), are compared in terms of the engineering workflow and the system performance. The results illustrate that, for this case study, an optimally controlled system uses around 30 % less electricity compared to rulebased control. Moreover, the potential of automatically generated OC to simplify the decision-making process in model-based co-design processes and as system integrator is highlighted.