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Die fluktuierende Verfügbarkeit regenerativer Energiequellen stellt eine Herausforderung bei der Planung und Auslegung regenerativer Gebäudeenergiesysteme dar. Die in einem System benötigten Speicherkapazitäten hängen dabei sowohl von der eingesetzten Regelungsstrategie als auch von den temperaturabhängigen Wirkungsgraden der Anlagenkomponenten ab. Genauere Einblicke in das Betriebsverhalten eines Gesamtsystems können dynamische Simulationen liefern, die eine Analyse der Systemtemperaturen und von Teilenergiekennwerten ermöglichen.
Drawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this original work, an economic-MPC-based optimal scheduling of a real-world building energy system is demonstrated and its performance is evaluated against a conventional controller. The demonstration includes the steps to integrate an optimisation-based supervisory controller into a standard building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms for solving complex nonlinear mixed integer optimal control problems. With the MPC, quantitative benefits in terms of 6–12% demand-cost savings and qualitative benefits in terms of better controller adaptability and hardware-friendly operation are identified. Further research potential for improving the MPC framework in terms of field-level stability, minimising constraint violations, and inter-system communication for its deployment in a prosumer-network is also identified.
The contribution of the RoofKIT student team to the SDE 21/22 competition is the extension of an existing café in Wuppertal, Germany, to create new functions and living space for the building with simultaneous energetic upgrading. A demonstration unit is built representing a small cut-out of this extension. The developed energy concept was thoroughly simulated by the student team in seminars using Modelica. The system uses mainly solar energy via PVT collectors as the heat source for a brine-water heat pump (space heating and hot water). Energy storage (thermal and electrical) is installed to decouple generation and consumption. Simulation results confirm that carbon neutrality is achieved for the building operation, consuming and generating around 60 kWh/m2a.