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ASHRAE OR-16-C067

Virtual Outdoor Air Flow Meter for the Ongoing Commissioning of HVAC Systems: Lessons from a Case Study Building

Organization:
ASHRAE - American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
Year: 2016

Abstract: The use of trend data from Building Energy Management Systems (BEMS) is a cost-effective solution to provide the necessary data for ongoing commissioning. This paper presents the use of three different virtual air flow meters, along with trend data, recorded every 15 minutes for the estimation of the outdoor air flow rate brought in the air-handling units. A virtual flow meter estimates the value of a physical variable in the heating, ventilating and air-conditioning system where a physical sensor does not exist. For this purpose, a mathematical model is used along with measurements from available sensors in the system. In this study, the results are presented as the ratio α of the outdoor air flow rate to the supply air flow rate. Three mathematical models are applied to the mixing box to calculate α: (a) a simplified energy balance equation along with air temperature measurements, (b) the air mass, water mass and energy balance equations along with measurements of air temperature and relative humidity, and (c) the energy balance equation along with measurements of air temperature and relative humidity. The uncertainty propagation due to measurement errors is also estimated. The case study building is a new research center of a university in Montreal. The paper presents results from April 7 to May 12, 2014. For each mathematical model a regression model is developed to be used by the virtual flow meter. The regression models based on a and b give good estimates with R2 = 0.97, with the verification data set; while the regression model based on c has low performance with R2 = 0.19. Due to the error propagation through the detailed equations, the uncertainty of estimates is much higher in the second and third case. The regression model based on a is the best candidate for the virtual air flow meter.
URI: http://yse.yabesh.ir/std;query=autho162sear79D/handle/yse/229735
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contributor authorASHRAE - American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
date accessioned2017-09-04T18:48:26Z
date available2017-09-04T18:48:26Z
date copyright2016.01.01
date issued2016
identifier otherKOXPOFAAAAAAAAAA.pdf
identifier urihttp://yse.yabesh.ir/std;query=autho162sear79D/handle/yse/229735
description abstractThe use of trend data from Building Energy Management Systems (BEMS) is a cost-effective solution to provide the necessary data for ongoing commissioning. This paper presents the use of three different virtual air flow meters, along with trend data, recorded every 15 minutes for the estimation of the outdoor air flow rate brought in the air-handling units. A virtual flow meter estimates the value of a physical variable in the heating, ventilating and air-conditioning system where a physical sensor does not exist. For this purpose, a mathematical model is used along with measurements from available sensors in the system. In this study, the results are presented as the ratio α of the outdoor air flow rate to the supply air flow rate. Three mathematical models are applied to the mixing box to calculate α: (a) a simplified energy balance equation along with air temperature measurements, (b) the air mass, water mass and energy balance equations along with measurements of air temperature and relative humidity, and (c) the energy balance equation along with measurements of air temperature and relative humidity. The uncertainty propagation due to measurement errors is also estimated. The case study building is a new research center of a university in Montreal. The paper presents results from April 7 to May 12, 2014. For each mathematical model a regression model is developed to be used by the virtual flow meter. The regression models based on a and b give good estimates with R2 = 0.97, with the verification data set; while the regression model based on c has low performance with R2 = 0.19. Due to the error propagation through the detailed equations, the uncertainty of estimates is much higher in the second and third case. The regression model based on a is the best candidate for the virtual air flow meter.
languageEnglish
titleASHRAE OR-16-C067num
titleVirtual Outdoor Air Flow Meter for the Ongoing Commissioning of HVAC Systems: Lessons from a Case Study Buildingen
typestandard
page8
statusActive
treeASHRAE - American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.:;2016
contenttypefulltext
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