Prof. Dr.-Ing. Christoph Nytsch-Geusen

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1 Co-Simulation of Building Energy Systems between Modelica and other (Simulation) Environments Prof. Dr.-Ing. Christoph Nytsch-Geusen Universität der Künste Berlin Technische Universität Berlin, Campus El Gouna EnTool 2013 Symposium, TU Dresden, June 10 14

2 Comparison of different model scales (0D, 1D, 3D) Comparative 3D-CFD analysis of the pressure losses for standard hydraulic components (ANSYS CFD) Comparative 3D-CFD Analysis of the thermo-hydraulic hydraulic behaviour of thermal storages (ANSYS CFD) Comparative multi-zonal analysis of the energetic behaviour of buildings (ECOTECT/EnergyPlus) 0D/1D - component-based simulation analysis of Building Energy Systems (Modelica-simulation tool + domain specific Modelica-libraries + Modelica-system model) Comparative 3D-CFD analysis of the air flow within and around buildings (ANSYS CFD)

3 Model integration by Co-Simulation EnTool 2013 Symposium, TU Dresden Use of the 1D-model part of the Modelica system model as intelligent boundary conditions for the 3D-CFD model

4 Four reasons for a Modelica Co-Simulation Realistic boundary conditions for CFD models or 1D-system models with local refined (3D) component models e.g. combination of a 1D-Modelicamodel with a high resolution 3D-model from ANSYS CFD ANSYS CFD Modelica models greater 15,000 states becomes very slow (numerical effort n states2 ), states more than 100,000 are to large e.g. de-composition of a large system model in several weak-coupled Modelica sub-models Integration of present building and plant simulation sub-models into a common system model e.g. combination of a Modelica HVACplant model with the fast multi-zone thermal building model from EnergyPlus Real system Hardware experiments with technical systems offers to less flexibility or some real technical components are not available Combination of a real photovoltaic system with a Modelica model of an air-conditioning system in a real time experiment (HIL simulation)

5 Used tools for Modelica Co-Simulation Numerical coupling of Modelica models with other dynamic simulation tools Co-Simulation with TISC* *TLK Inter Software Connector Commercial development (TLK-Thermo GmbH) Client /server-oriented framework with interfaces to different simulation tools: Modelica, ANSYS CFD, MatLab/Simulink, Variable time step size controller for the tool-combination ANSYS CFD / Dymola Co-Simulation with BCVTB* *Building Control Virtual Test Bed Open-Source development of the LBNL Graphical modelling of the co-simulation Integration of HIL-components Fixed time step size Coupling of Modelica/Dymola + EnergyPlus Co-simulation framework TISC (Source: TLK Thermo) Co-simulation framework BCVTB (Source: LBNL)

6 The Base: Modelica-library BuildingSystems Modelica-library library BuildingSystems for integrated energetic building and plant simulation (Development at UdK Berlin) Building models: Thermal and hygro-thermal building model in different detail levels Plant models: solar collectors, photovoltaic modules, chillers, pumps, tubes, fans, air ducts, thermal and electrical storages Component models with adaptive 1D- discretisation (e.g. tubes and thermal storages) or concentrated parameters (e.g. elbows or branches) Developed with Dymola for Modelica 3.x Evaluation with other Modelica tools in progress (e.g. OpenModelica) System Solar heating system Sub-system Collector field Sub-sub sub-system system Collector group Component Single solar thermal collector

7 Modelica-BuildingSystems Exemplary applications Complex thermo-hydraulic network HVAC-System, e.g. adiabatic evaporation cooling system Solar thermal plant for hot water generation Local district heating system

8 Co-Simulation Modelica-EnergyPlus

9 Application: PV-cooling systems for the MENA region City El Gouna Present situation: Repeated cut-offs induced by electrical chillers Technology approach Autonomous PV Cooling PV-Cooling technology El Gouna, Egypt Location El Gouna (Egypt) with 2,400 kwh/m 2 a solar irradiation Technology development at TU Berlin, Campus El Gouna

10 1 st step: Co-Simulation for the design of the PV cooling test beds Building model of the test rooms, based on EnergyPlus Co-Simulation of Modelica and EnergyPlus with BCVTB PV cooling plant model, based on Modelica

11 2 nd step: Co-Simulation of PV cooling systems for real buildings Modelica plant model Input: Output: Air Input: temperature Cooling power of Zonetemperatures each zone energies/ power for each zone EnergyPlusbuilding model Input: Output: Cooling power Output: energies/ power Air Zonetemperatures temperature of each zone for each zone Building model with four thermal zones BCVTB: Building Control Virtual Test Bed Co-simulation of a Modelica sub-model (PV cooling plant) and an EnergyPlus sub-model (residential building)

12 2 nd step: Co-Simulation of PV cooling systems for real buildings Exemplary simulation results: Temperature in C Temperatur[ C] Tag 200 Tag 201 Tag 202 Tag 203 Tag 204 Tag 205 Tag 206 Tag 207 Tag 208 Tag 209 External temperature Zone temperatue, Modelica building model EnergyPlus, area weighted average zone temperature Zeit,Tag200bisTag209 [s imjahr] Dif usstrahlung in Kollektorebene[W/m2] Gesamtstrahlung auf die Kollektorebene, dif +dir [W/m2] adiation W/m2] m 2 Soar ra in W/m Solare Einstrahlung[W Room air temperature of the PV cooled residential building during a hot summer period of 10 days for the location Hastgerd in North Iran (outside air temperatures up to 41 C)

13 Co-Simulation Modelica-ANSYS CFD ANSYS CFD

14 Application: Controlled air heating for a thermal model house Thermal model house ( Mobile test bed (scale 1:6), which can demonstrate the essential functions of a building air-conditioning (heating, cooling, ventilation, ) Compact dimensions: 1m x 0,5m x 0,5m Building construction is similar to a real building Walls, floor, roof from wood and Styrodur Windows with single glazing High flexibility for experiments Facade / roof constructions can be exchanged optional Inside wall, which divides the building in two single attached thermal zones Measurement acquisition/controlling with LEGO Mindstorms Measured values: Outer and inner air temperatures, Thermal model house with cooling ceiling Evaluation of control algorithms (e.g. controlled heating and cooling power or adapted shading device positions) IR-photography of a heating experiment

15 Application: Controlled air heating for a thermal model house 1st step: Pure Modelica system simulation Modelica system model of the PI-controlled air heating and the thermal model house, based on the BuildingSystems-library

16 Application: Controlled air heating for a thermal model house 1st step: Pure Modelica system simulation Start and boundary conditions Start temperatures: 20 C Supply air temperature: 35 C Controlled air mass flow: kg/s PI-controller Simulation experiment Duration: 600 s Air is warmed up to 25 C, after 200 s further warming to 27 C Simulation results Air temperature Air mass flow Experiment shows typical PI-controller behaviour Air temperature (above) and controlled air mass flow (below)

17 Application: Controlled air heating for a thermal model house 2nd step: Co-Simulation of Modelica and ANSYS CFD with TISC Co-Simulation of a Modelica sub-model (PI-controlled air heating) and ANSYS CFD sub-model (thermal model house)

18 Application: Controlled air heating for a thermal model house Analysis about different fine discretized meshes for the room air volume kg/s kg/s 0.01 kg/s 28,929 Nodes 177,619 Nodes 2,636,934 Nodes Temperature distribution in the middle cut (stationary solution)

19 Application: Controlled air heating for a thermal model house 3D-CFD model of the room air and the building envelope Building envelope 3D transient heat conduction Modelling of the layered building construction incl. The heat bridges ca. 127,000 nodes Air volume Transient room air ventilation k-epsilon-model approx. 180,000 nodes (resolution estimated in pre-studies) Tetrahedron elements deep in the air volume Boundary model with flat hexahedron elements Meshes in ANSYS CFD for the building envelope (above) and the air volume (below)

20 Application: Controlled air heating for a thermal model house Co-Simulation of Modelica and ANSYS CFD Two different positions of the room air temperature sensor Effort for the Co-Simulation Problem: > 1,6 Million equations Physical duration: 1,100s Maximum residue: 10 ³ Calculation duration> 1 day 8 Xeon-E5462-CPUs with 2,8 GHz Effort of the pure Modelica simulation Problem: 329 equations Calculation duration < 1 Minute Mean air temperature of the pure Modelica simulation (blue) and sensor temperatures of the Co-Simulation (red, green) Time steps in the Co-Simulation experiment

21 Co-Simulation Modelica-Modelica

22 Co-Simulation Modelica - Modelica EnTool 2013 Symposium, TU Dresden CPU time (Dymola) for a simple thermo-hydraulic loop of four tubes (n nodes = ,000) CPU time n nodes 2 nodes CPU ti ime [s] Number of nodes Source: PhD Ljubijankic

23 Co-Simulation Modelica - Modelica EnTool 2013 Symposium, TU Dresden Pseudo Modelica parallelization with TISC for a simple thermo-hydraulic loop (n = 25 10,000) Sub-model 1 Sub-model 2 Sub-model 3 Sub-model 4 Integrated system simulation on 1 core Co-simulation with 4 sub-models on 4 cores Source: PhD Ljubijankic

24 Co-Simulation Modelica - Modelica EnTool 2013 Symposium, TU Dresden 8,00 sync-rate = 0.5s 7,00 Integrated system simulation on 1 core Relative acceleration 6,00 5,00 4,00 3,00 2,00 two cores (CoSim) four cores (CoSim) 1,00 0, Number of nodes 8,00 sync-rate = 0.1 s Co-simulation on 4 cores, sync-rate = 0,5 s 7,00 Relative accelaration 6,00 5,00 4,00 3,00 2,00 two cores (CoSim) four cores (CoSim) 1,00 Co-simulation with 4 cores, sync-rate = 0,1 s 0, Number of nodes Heat up process of one of the tube models: higher calculation precision needs reduced sync-rates Relative acceleration of the pseudo parallelized model in comparison to the integrated system model Source: PhD Ljubijankic

25 Next steps in Co-simulation EnTool 2013 Symposium, TU Dresden Co-simulation Modelica <-> Real Hardware (HIL) within test beds for PV-Cooling Co-simulation Modelica <-> ANSYS CFD for heat stress calculation in indoor climates Modelica: Physiological human body model (Picture: RWTH Aachen) CFD: Detailed indoor climate room model

26 Summary EnTool 2013 Symposium, TU Dresden Co-Simulation can integrate Modelica with other simulation environments can integrate 3D-points of interest into Modelica system models can accelerate complex Modelica system models by de-composition can make Modelica as a part of a real technical system (HIL)

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