Pub Date : 2023-08-03DOI: 10.1080/19401493.2023.2243602
Charalampos Vallianos, Matin Abtahi, A. Athienitis, B. Delcroix, Luis Rueda
{"title":"Online model-based predictive control with smart thermostats: application to an experimental house in Québec","authors":"Charalampos Vallianos, Matin Abtahi, A. Athienitis, B. Delcroix, Luis Rueda","doi":"10.1080/19401493.2023.2243602","DOIUrl":"https://doi.org/10.1080/19401493.2023.2243602","url":null,"abstract":"","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"32 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86063750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-14DOI: 10.1080/19401493.2023.2232341
M. Piller, G. Bulian, C. A. Stival
{"title":"Assessment of infection probability indices for airborne diseases in confined spaces: combination of CFD and analytical modelling","authors":"M. Piller, G. Bulian, C. A. Stival","doi":"10.1080/19401493.2023.2232341","DOIUrl":"https://doi.org/10.1080/19401493.2023.2232341","url":null,"abstract":"","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"11 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88664688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Importance of measuring the temperature of paved surfaces to study the changes in the microclimate of an urban area","authors":"Ankit Kumar, Jyoti Ranjan Mishra, Suresh Pandian Elumalai","doi":"10.1080/19401493.2023.2232336","DOIUrl":"https://doi.org/10.1080/19401493.2023.2232336","url":null,"abstract":"","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"11 5 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78314300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.1080/19401493.2023.2227605
F. Ochs, N. Franzoi, G. Dermentzis, W. Monteleone, M. Magni
{"title":"Monitoring and simulation-based optimization of two multi-apartment NZEBs with heat pump, solar thermal and PV","authors":"F. Ochs, N. Franzoi, G. Dermentzis, W. Monteleone, M. Magni","doi":"10.1080/19401493.2023.2227605","DOIUrl":"https://doi.org/10.1080/19401493.2023.2227605","url":null,"abstract":"","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"31 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74844016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-05DOI: 10.1080/19401493.2023.2208558
Zhihong Pang, Xing Lu, Pingfan Hu, Zheng O’Neill, Qingsheng Wang
The COVID-19 pandemic has underscored the need for effective ventilation control in public buildings. This study develops and evaluates a smart ventilation control algorithm (SIREN) that dynamically adjusts zone and system-level HVAC operation to maintain an acceptable COVID-19 infection risk and HVAC energy efficiency. SIREN uses real-time building operation data and Trim & Respond control logic to determine zone primary and system outdoor airflow rates. An EnergyPlus and CONTAM co-simulation framework was developed to assess its performance across various control scenarios and US climate zones. Results show that SIREN can flexibly control infection risk within a customized threshold (e.g. 3%) for every zone, while traditional controls cannot. At the building level, SIREN’s HVAC energy consumption is comparable to a fixed 70% outdoor airflow fraction scenario, while its infection risk is lower than the 100% outdoor airflow scenario, illustrating its potential for safe and energy-efficient HVAC operation during pandemics.
{"title":"SIREN – smart ventilation for infection risk mitigation and HVAC energy efficiency: a case study amid the COVID-19 pandemic","authors":"Zhihong Pang, Xing Lu, Pingfan Hu, Zheng O’Neill, Qingsheng Wang","doi":"10.1080/19401493.2023.2208558","DOIUrl":"https://doi.org/10.1080/19401493.2023.2208558","url":null,"abstract":"The COVID-19 pandemic has underscored the need for effective ventilation control in public buildings. This study develops and evaluates a smart ventilation control algorithm (SIREN) that dynamically adjusts zone and system-level HVAC operation to maintain an acceptable COVID-19 infection risk and HVAC energy efficiency. SIREN uses real-time building operation data and Trim & Respond control logic to determine zone primary and system outdoor airflow rates. An EnergyPlus and CONTAM co-simulation framework was developed to assess its performance across various control scenarios and US climate zones. Results show that SIREN can flexibly control infection risk within a customized threshold (e.g. 3%) for every zone, while traditional controls cannot. At the building level, SIREN’s HVAC energy consumption is comparable to a fixed 70% outdoor airflow fraction scenario, while its infection risk is lower than the 100% outdoor airflow scenario, illustrating its potential for safe and energy-efficient HVAC operation during pandemics.","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"15 1","pages":"797 - 825"},"PeriodicalIF":2.5,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86760491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-29DOI: 10.1080/19401493.2023.2200377
Alice Maury-Micolier, Lei Huang, O. Jolliet
We develop a numerical model coupling heat and chemical transfers in the building envelope to predict human exposure to pollutants and heating load as affected by changes in temperature and building design. We characterize the effect of temperature variation by season and location on chemical emission dynamics from building materials and the resulting human exposure. Peak concentrations of organics are sensitive to temperatures, and increasing indoor temperature by 10°C doubles the maximum indoor air concentration reached by both VOCs and SVOCs contained in a vinyl flooring. SVOCs mean concentration over the flooring lifetime increases by a factor of 2, and, as a result, the fraction of chemical taken in by the occupants increases by 50%. Occupants’ exposure to SVOCs emission in the city of Lille is likely to increase by 20% in 2050 because of temperature increase induced by climate change.
{"title":"Coupled mass and heat transfer modelling in building envelopes to consistently assess human exposure and energy performance in indoor environments","authors":"Alice Maury-Micolier, Lei Huang, O. Jolliet","doi":"10.1080/19401493.2023.2200377","DOIUrl":"https://doi.org/10.1080/19401493.2023.2200377","url":null,"abstract":"We develop a numerical model coupling heat and chemical transfers in the building envelope to predict human exposure to pollutants and heating load as affected by changes in temperature and building design. We characterize the effect of temperature variation by season and location on chemical emission dynamics from building materials and the resulting human exposure. Peak concentrations of organics are sensitive to temperatures, and increasing indoor temperature by 10°C doubles the maximum indoor air concentration reached by both VOCs and SVOCs contained in a vinyl flooring. SVOCs mean concentration over the flooring lifetime increases by a factor of 2, and, as a result, the fraction of chemical taken in by the occupants increases by 50%. Occupants’ exposure to SVOCs emission in the city of Lille is likely to increase by 20% in 2050 because of temperature increase induced by climate change.","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"5 1","pages":"734 - 748"},"PeriodicalIF":2.5,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84604043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1080/19401493.2023.2201816
M. Van Hove, M. Delghust, J. Laverge
Despite broad recognition of the need for applying Uncertainty (UA) and Sensitivity Analysis (SA) to Building-Stock Energy Models (BSEMs), limited research has been done. This article proposes a scalable methodology to apply UA and SA to BSEMs, with an emphasis on important methodological aspects: input parameter sampling procedure, minimum required building stock size and number of samples needed for convergence. Applying UA and SA to BSEMs requires a two-step input parameter sampling that samples ‘across stocks’ and ‘within stocks’. To make efficient use of computational resources, practitioners should distinguish between three types of convergence: screening, ranking and indices. Nested sampling approaches facilitate comprehensive UA and SA quality checks faster and simpler than non-nested approaches. Robust UA-SA's can be accomplished with relatively limited stock sizes. The article highlights that UA-SA practitioners should only limit the UA-SA scope after very careful consideration as thoughtless curtailments can rapidly affect UA-SA quality and inferences. Abbreviations, definitions and indices BEM: Building Energy Model; BSEM: Building-Stock Energy Model; UA: Uncertainty Analysis focuses on how uncertainty in the input parameters propagates through the model and affects the model output parameter(s); SA: Sensitivity Analysis is the study of how uncertainty in the output of a model (numerical or otherwise) can be apportioned to different sources of uncertainty in the model input factors; GSA: Global Sensitivity Analysis (e.g. Sobol’ SA);LSA: Local Sensitivity Analysis (e.g. OAT); OAT: One-At-a-Time; LOD: Level of Development; : The model output; : The -th model input parameter and denotes the matrix of all model input parameters but ; : The first-order sensitivity index, which represents the expected amount of variance reduction that would be achieved for , if was specified exactly. The first-order index is a normalized index (i.e. always between 0 and 1); : The total-order sensitivity index, which represents the expected amount of variance that remains for , if all parameters were specified exactly, but . It takes into account the first and higher-order effects (interactions) of parameters and can therefore be seen as the residual uncertainty; : The higher-order effects index is calculated as the difference between and and is a measure of how much is involved in interactions with any other input factor; : The second order sensitivity index, which represents the fraction of variance in the model outcome caused by the interaction of parameter pair ( , ); M: Mean (µ); SD: Standard deviation (σ); Mo: Mode; n: number of buildings in the modelled stock;N: number of samples (i.e. matrices of or stock model runs; batches of or are required to calculate Sobol’ indices); K: number of uncertain parameters; ME: number of model evaluations (i.e. stocks to be calculated); *: Table 1: Aleatory uncertainty: Uncertainty due to inherent or natural variatio
{"title":"Uncertainty and sensitivity analysis of building-stock energy models: sampling procedure, stock size and Sobol’ convergence","authors":"M. Van Hove, M. Delghust, J. Laverge","doi":"10.1080/19401493.2023.2201816","DOIUrl":"https://doi.org/10.1080/19401493.2023.2201816","url":null,"abstract":"Despite broad recognition of the need for applying Uncertainty (UA) and Sensitivity Analysis (SA) to Building-Stock Energy Models (BSEMs), limited research has been done. This article proposes a scalable methodology to apply UA and SA to BSEMs, with an emphasis on important methodological aspects: input parameter sampling procedure, minimum required building stock size and number of samples needed for convergence. Applying UA and SA to BSEMs requires a two-step input parameter sampling that samples ‘across stocks’ and ‘within stocks’. To make efficient use of computational resources, practitioners should distinguish between three types of convergence: screening, ranking and indices. Nested sampling approaches facilitate comprehensive UA and SA quality checks faster and simpler than non-nested approaches. Robust UA-SA's can be accomplished with relatively limited stock sizes. The article highlights that UA-SA practitioners should only limit the UA-SA scope after very careful consideration as thoughtless curtailments can rapidly affect UA-SA quality and inferences. Abbreviations, definitions and indices BEM: Building Energy Model; BSEM: Building-Stock Energy Model; UA: Uncertainty Analysis focuses on how uncertainty in the input parameters propagates through the model and affects the model output parameter(s); SA: Sensitivity Analysis is the study of how uncertainty in the output of a model (numerical or otherwise) can be apportioned to different sources of uncertainty in the model input factors; GSA: Global Sensitivity Analysis (e.g. Sobol’ SA);LSA: Local Sensitivity Analysis (e.g. OAT); OAT: One-At-a-Time; LOD: Level of Development; : The model output; : The -th model input parameter and denotes the matrix of all model input parameters but ; : The first-order sensitivity index, which represents the expected amount of variance reduction that would be achieved for , if was specified exactly. The first-order index is a normalized index (i.e. always between 0 and 1); : The total-order sensitivity index, which represents the expected amount of variance that remains for , if all parameters were specified exactly, but . It takes into account the first and higher-order effects (interactions) of parameters and can therefore be seen as the residual uncertainty; : The higher-order effects index is calculated as the difference between and and is a measure of how much is involved in interactions with any other input factor; : The second order sensitivity index, which represents the fraction of variance in the model outcome caused by the interaction of parameter pair ( , ); M: Mean (µ); SD: Standard deviation (σ); Mo: Mode; n: number of buildings in the modelled stock;N: number of samples (i.e. matrices of or stock model runs; batches of or are required to calculate Sobol’ indices); K: number of uncertain parameters; ME: number of model evaluations (i.e. stocks to be calculated); *: Table 1: Aleatory uncertainty: Uncertainty due to inherent or natural variatio","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"62 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83974144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19401493.2023.2201818
Tuule-Mall Parts, A. Ferrantelli, H. Naar, M. Thalfeldt, J. Kurnitski
This paper investigates how a simulated room’s energy and temperature performance are affected if its underfloor heating control is modelled with increasing detail. Experiments were performed to develop and calibrate an empirical model of wax motor and to calibrate the valve curve. These models were used to implement and test the On/Off and proportional-integral (PI) control processes at various levels of modelling detail. Controllers were implemented by gradually adding optimized control parameters, signal delay, calibrated valve curve, signal modulation, and actuator modelling. The On/Off control dead band and PI parameters exhibited the largest impact, reducing energy use (1%–5%) and temperature fluctuations (ca 1 K). Modulating the PI output signal increased temperature fluctuations to the same amplitude as On/Off with 0.5 K dead band, increasing space heating demand by 1.3%. The wax actuator counted for less than 1%; however, it increased time delays to maximally 7 min and remarkably changed the mass flows.
{"title":"Wax actuator’s empirical model development and application to underfloor heating control with varying complexity of controller modelling detail","authors":"Tuule-Mall Parts, A. Ferrantelli, H. Naar, M. Thalfeldt, J. Kurnitski","doi":"10.1080/19401493.2023.2201818","DOIUrl":"https://doi.org/10.1080/19401493.2023.2201818","url":null,"abstract":"This paper investigates how a simulated room’s energy and temperature performance are affected if its underfloor heating control is modelled with increasing detail. Experiments were performed to develop and calibrate an empirical model of wax motor and to calibrate the valve curve. These models were used to implement and test the On/Off and proportional-integral (PI) control processes at various levels of modelling detail. Controllers were implemented by gradually adding optimized control parameters, signal delay, calibrated valve curve, signal modulation, and actuator modelling. The On/Off control dead band and PI parameters exhibited the largest impact, reducing energy use (1%–5%) and temperature fluctuations (ca 1 K). Modulating the PI output signal increased temperature fluctuations to the same amplitude as On/Off with 0.5 K dead band, increasing space heating demand by 1.3%. The wax actuator counted for less than 1%; however, it increased time delays to maximally 7 min and remarkably changed the mass flows.","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"02 1","pages":"772 - 796"},"PeriodicalIF":2.5,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86089923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-12DOI: 10.1080/19401493.2023.2195828
A. Carratt, G. Kokogiannakis, D. Daly
{"title":"Development and performance evaluation of a minimum input model calibration methodology for residential buildings","authors":"A. Carratt, G. Kokogiannakis, D. Daly","doi":"10.1080/19401493.2023.2195828","DOIUrl":"https://doi.org/10.1080/19401493.2023.2195828","url":null,"abstract":"","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"51 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73563689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1080/19401493.2023.2196971
Mona Subramaniam A., Tushar Jain, Joseph J. Yamé
In this paper, we propose a novel bilinear observer-based robust fault detection, isolation and adaptive fault estimation methodology to precisely estimate a class of actuator faults, namely bias in damper position and lock-in-place faults, in Variable-Air-Volume (VAV) terminal units of Heating Ventilation and Air-Conditioning (HVAC) systems. The proposed adaptive fault estimator is robust in the sense that the fault estimates are not affected by the unmeasured disturbance variable and that the effects of measurement noises on fault estimates are attenuated. The fault estimation algorithm with the integrated building control system improves occupants comfort and reduces the operation, maintenance, and utility cost, thereby reducing the impact on the environment. The effectiveness of the methodology for adaptive estimation of multiple or single VAV damper faults is successfully demonstrated through different simulation scenarios with SIMBAD (SIMulator of Building And Devices), which is being used in industries for testing and validation of building energy management systems.
{"title":"Bilinear observer-based robust adaptive fault estimation for multizone building VAV terminal units","authors":"Mona Subramaniam A., Tushar Jain, Joseph J. Yamé","doi":"10.1080/19401493.2023.2196971","DOIUrl":"https://doi.org/10.1080/19401493.2023.2196971","url":null,"abstract":"In this paper, we propose a novel bilinear observer-based robust fault detection, isolation and adaptive fault estimation methodology to precisely estimate a class of actuator faults, namely bias in damper position and lock-in-place faults, in Variable-Air-Volume (VAV) terminal units of Heating Ventilation and Air-Conditioning (HVAC) systems. The proposed adaptive fault estimator is robust in the sense that the fault estimates are not affected by the unmeasured disturbance variable and that the effects of measurement noises on fault estimates are attenuated. The fault estimation algorithm with the integrated building control system improves occupants comfort and reduces the operation, maintenance, and utility cost, thereby reducing the impact on the environment. The effectiveness of the methodology for adaptive estimation of multiple or single VAV damper faults is successfully demonstrated through different simulation scenarios with SIMBAD (SIMulator of Building And Devices), which is being used in industries for testing and validation of building energy management systems.","PeriodicalId":49168,"journal":{"name":"Journal of Building Performance Simulation","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136002062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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