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Title: Development and Calibration of an Online Energy Model for AHU Fan

Abstract

The model development is necessary for the study of the energy consumption of Heating, Ventilation, and Air Conditioning (HVAC) systems. To predict the HVAC energy consumption accurately, one needs to model the individual HVAC components either from the measured data or based on the knowledge of the underlying physical phenomenon. Online model characterization is critical for improving the performance of real-time model-based fault detection and diagnosis (FDD) strategies. For HVAC control, models can be used to optimize the supervisory and local feedback control strategies to improve the energy consumption efficiency, or for providing ancillary services to the grid. It has been reported that, fans in HVAC systems of commercial buildings alone can provide substantial frequency regulation service, with little change in the indoor environment. In this paper, a real-time data-driven Air Handling Unit (AHU) fan model was developed based on recursive multi regression model. A generic nonlinear polynomial model has been studied to cover scenarios with different combinations of measurement variables, variable orders as well as different training and prediction horizons. Typical measurements including static pressure, mass flow rate, and damper positions are utilized as inputs to model the power consumption of the fan. The developed models have been validatedmore » both with simulation data from EnergyPlus-Dymola co-simulation model and with field measurement data for small to medium commercial buildings. The validation results show that the online model proposed can provide an effective prediction of the AHU fan power consumption.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [2];  [2]; ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
  2. Pacific Northwest National Laboratory (PNNL)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1504013
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ASHRAE 2019 Winter Conference - Atlanta, Georgia, United States of America - 1/12/2019 10:00:00 AM-1/16/2019 10:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Dong, Jin, Im, Piljae, Huang, Sen, Chen, Yan, Munk, Jeffrey D., and Kuruganti, Teja. Development and Calibration of an Online Energy Model for AHU Fan. United States: N. p., 2019. Web.
Dong, Jin, Im, Piljae, Huang, Sen, Chen, Yan, Munk, Jeffrey D., & Kuruganti, Teja. Development and Calibration of an Online Energy Model for AHU Fan. United States.
Dong, Jin, Im, Piljae, Huang, Sen, Chen, Yan, Munk, Jeffrey D., and Kuruganti, Teja. Tue . "Development and Calibration of an Online Energy Model for AHU Fan". United States. https://www.osti.gov/servlets/purl/1504013.
@article{osti_1504013,
title = {Development and Calibration of an Online Energy Model for AHU Fan},
author = {Dong, Jin and Im, Piljae and Huang, Sen and Chen, Yan and Munk, Jeffrey D. and Kuruganti, Teja},
abstractNote = {The model development is necessary for the study of the energy consumption of Heating, Ventilation, and Air Conditioning (HVAC) systems. To predict the HVAC energy consumption accurately, one needs to model the individual HVAC components either from the measured data or based on the knowledge of the underlying physical phenomenon. Online model characterization is critical for improving the performance of real-time model-based fault detection and diagnosis (FDD) strategies. For HVAC control, models can be used to optimize the supervisory and local feedback control strategies to improve the energy consumption efficiency, or for providing ancillary services to the grid. It has been reported that, fans in HVAC systems of commercial buildings alone can provide substantial frequency regulation service, with little change in the indoor environment. In this paper, a real-time data-driven Air Handling Unit (AHU) fan model was developed based on recursive multi regression model. A generic nonlinear polynomial model has been studied to cover scenarios with different combinations of measurement variables, variable orders as well as different training and prediction horizons. Typical measurements including static pressure, mass flow rate, and damper positions are utilized as inputs to model the power consumption of the fan. The developed models have been validated both with simulation data from EnergyPlus-Dymola co-simulation model and with field measurement data for small to medium commercial buildings. The validation results show that the online model proposed can provide an effective prediction of the AHU fan power consumption.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {1}
}

Conference:
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