TRNSYS 건물 에너지 시뮬레이션 모델 캘리브레이션: GenOpt를 이용한 사례 연구 (A Model Calibration for Residential Building Energy Simulation : A Case Study with TRNSYS and Optimization Tool GenOpt)

서지정보

· 발행기관 : 한국건축친환경설비학회
· 수록지 정보 : 한국건축친환경설비학회 논문집 / 13권 / 4호 / 234 ~ 245페이지
· 저자명 : 임흥빈, 이경호, 공민석, 서동현

초록

This paper demonstrates a calibration methodology for adjusting model parameters and factors using assistant tools ― python and GenOpt. In this study, a building simulation model is developed for a demonstration building for a low-energy solar house. The model is composed of a 3D model describing building architecture and HVAC system model using TRNSYS simulation program.
In this study, model calibration methodology consists of two phases in order to improve the accuracy of building energy model and reduce errors of simulation results: Parameter adjustment phase and factor optimization phase. Trial and error approach is used for the first phase and GenOpt tool is employed for the second phase to improve the model performance. Based on American Society of Heating, Refrigerating and Air-conditioning Engineers (ASHRAE) Guideline 14 indices, the performance of the calibrated building simulation model is evaluated to obtain Normalized Mean Bias Error (NMBE)hourly, values within ±10% and Coefficient Variation of Root Mean Square Error (CV (RMSE))hourly, values within 30%. The performance indices are calculated with simulated and measured temperatures of each indoor zone and buffer tank.
Daily data is used for calibrating heat pump (HP) electrical energy consumption because it is hard to fit the operating time of HP which can be different to time that heating load occurs. As a result of the calibration process, it is found that the values of NMBEhourly and CV (RMSE)hourly achieves within followings: Average indoor temperature 一 NMBEhourly is 1.2% and CV (RMSE)hourly is 2.2%. Buffer tank temperature NMBEhourly is 1.5% and CV (RMSE)hourly is 8.2%.
And the value of NMBEdaily and CV (RMSE)daily are used for HP electrical use as following: NMBEdaily is 9.5%, CV (RMSE) is 23.4%.

영어초록

This paper demonstrates a calibration methodology for adjusting model parameters and factors using assistant tools ― python and GenOpt. In this study, a building simulation model is developed for a demonstration building for a low-energy solar house. The model is composed of a 3D model describing building architecture and HVAC system model using TRNSYS simulation program.
In this study, model calibration methodology consists of two phases in order to improve the accuracy of building energy model and reduce errors of simulation results: Parameter adjustment phase and factor optimization phase. Trial and error approach is used for the first phase and GenOpt tool is employed for the second phase to improve the model performance. Based on American Society of Heating, Refrigerating and Air-conditioning Engineers (ASHRAE) Guideline 14 indices, the performance of the calibrated building simulation model is evaluated to obtain Normalized Mean Bias Error (NMBE)hourly, values within ±10% and Coefficient Variation of Root Mean Square Error (CV (RMSE))hourly, values within 30%. The performance indices are calculated with simulated and measured temperatures of each indoor zone and buffer tank.
Daily data is used for calibrating heat pump (HP) electrical energy consumption because it is hard to fit the operating time of HP which can be different to time that heating load occurs. As a result of the calibration process, it is found that the values of NMBEhourly and CV (RMSE)hourly achieves within followings: Average indoor temperature 一 NMBEhourly is 1.2% and CV (RMSE)hourly is 2.2%. Buffer tank temperature NMBEhourly is 1.5% and CV (RMSE)hourly is 8.2%.
And the value of NMBEdaily and CV (RMSE)daily are used for HP electrical use as following: NMBEdaily is 9.5%, CV (RMSE) is 23.4%.

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