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Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering,

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Presentation on theme: "Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering,"— Presentation transcript:

1 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 1 TECHNIQUE OF UNCERTAINTY AND SENSITIVITY ANALYSIS FOR SUSTAINABLE BUILDING ENERGY SYSTEMS PERFORMANCE CALCULATIONS Petr KOTEK Filip JORDÁN, Karel KABELE, Jan HENSEN poster P3-16 Czech Technical University in Prague, Faculty of Civil Engineering, Czech Republic Technische Universiteit Eindhoven, Building Physics & Systems, Netherlands 9

2 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 Introduction 2 The crucial in the optimization methods of energy consumption are uncertainty and sensitivity analyses (UA & SA) and their results. The MonteCarlo (MCA) method was used to find out the most influential parameters of a thermal energy simulation model and simple analytical model of HVAC system repeated simulations 9

3 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 3 Procedure – case study sampling software procedure ASHREA BESTEST case600 was chosen x 48 random sampling (crude MonteCarlo method) S = 6 simulations sample matrix 9

4 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 3 Procedure – case study sampling software procedure ASHREA BESTEST case600 was chosen x 48 LatinHypercube sampling reduce number of simulations sample matrix S = 6 simulations

5 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 Softwares for UA & SA - procedure 4 sampling software procedure IES SimLab pre-processor model execution post-processor UA & SA y k outputs x n inputs with uncertainty outputs.out MS Excel sample matrix.sam Inputs for simulations outputs from simulations 200 automatic simulations external model heat losses heat gains 9

6 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 5 THERMAL SIMULATION heating and cooling demand during the whole year gains [kw] losses the coldest day time results for main values of inputs heat losses heat gains 9

7 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 THERMAL SIMULATION heating and cooling demand during the whole year with uncertainty results with uncertainty bound from 200 simulations SA from SimLab heat losses heat gains 9 5

8 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 HVAC SYSTEMS AND CALCULATIONS 6 heat losses heat gains FCU VAV 9

9 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 HVAC SYSTEMS AND CALCULATIONS heat losses heat gains FCU VAV AHU VAV-box AHU FCU LOADS with uncertainty bound 9 7

10 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 9 RESULTS by using VAV system we save energy, but according to the uncertainty in inputs it can be less effective than FCU with combination of energy simulation and MonteCarlo simulations we can find out the most sensitive parameters for constructions and for HVAC components and settings. These parameters can be optimized with GenOpt (TrnOpt), BeOpt,… SA UA 8

11 Technique of uncertainty & sensitivity analysis for building performance simulation and calculations Petr Kotek, CTU in Prague, Faculty of Civil Engineering, Czech Republic INTRODUCTION HVAC SYSTEMS CONCLUSION PROCEDURE OF MONTE CARLO DISCUSSION THERMAL SIMULATION ID609 9 THANK YOU FOR YOUR ATTENTION DANK U WEL VOOR UW AANDACHT DĚKUJI ZA POZORNOST International end of presentation


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