Component-wise optimization for a commercial central cooling plant

Vakiloroaya, V; Samali, B; Madadnia, J; Ha, QP

Component-wise optimization for a commercial central cooling plant

Vakiloroaya, V Samali, B

Madadnia, J Ha, QP

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Publication Type:: Conference Proceeding
Citation:: IECON Proceedings (Industrial Electronics Conference), 2011, pp. 2769 - 2774
Issue Date:: 2011-12-01

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Field	Value	Language
dc.contributor.author	Vakiloroaya, V	en_US
dc.contributor.author	Samali, B https://orcid.org/0000-0002-3426-7745	en_US
dc.contributor.author	Madadnia, J	en_US
dc.contributor.author	Ha, QP https://orcid.org/0000-0003-0978-1758	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	IECON Proceedings (Industrial Electronics Conference), 2011, pp. 2769 - 2774	en_US
dc.identifier.isbn	9781612849720	en_US
dc.identifier.uri	http://hdl.handle.net/10453/19322
dc.description.abstract	Thermal comfort and energy savings are two main goals of heating, ventilation and air conditioning (HVAC) systems. In this paper, the optimization-simulation approach is proposed for effective energy saving potential in a commercial central cooling plant by refining the model of optimal operation for system components and deriving optimal conditions for their operation subject to technical and human comfort constraints. To investigate the potential of energy savings and air quality, a real-world commercial building, located in a hot and dry climate region, together with its central cooling plant is used for experimentation and data collection. Both inputs and outputs of the existing central cooling plant are measured from the field monitoring in one typical week in the summer. Optimization is performed by using empirically-based models of the central cooling plant components. Optimization algorithms implemented on a transient simulation software package, are used to solve the minimization problem of energy consumption for each considered control strategies and predict the HVAC system optimized set-points under transient load. The integrated simulation tool was validated by comparing predicted and measured power consumption of the chiller during the first day of July. Results show that between 3.2% and 11.8% power savings can be obtained by this approach while maintaining the predicted mean vote (PMV) from -0.5 to +1 for most of the summer time. © 2011 IEEE.	en_US
dc.relation.ispartof	IECON Proceedings (Industrial Electronics Conference)	en_US
dc.relation.isbasedon	10.1109/IECON.2011.6119750	en_US
dc.title	Component-wise optimization for a commercial central cooling plant	en_US
dc.type	Conference Proceeding
utslib.for	0905 Civil Engineering	en_US
dc.location.activity	Melbourne, Australia	en_US
dc.location.activity	Melbourne, AUSTRALIA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Thermal comfort and energy savings are two main goals of heating, ventilation and air conditioning (HVAC) systems. In this paper, the optimization-simulation approach is proposed for effective energy saving potential in a commercial central cooling plant by refining the model of optimal operation for system components and deriving optimal conditions for their operation subject to technical and human comfort constraints. To investigate the potential of energy savings and air quality, a real-world commercial building, located in a hot and dry climate region, together with its central cooling plant is used for experimentation and data collection. Both inputs and outputs of the existing central cooling plant are measured from the field monitoring in one typical week in the summer. Optimization is performed by using empirically-based models of the central cooling plant components. Optimization algorithms implemented on a transient simulation software package, are used to solve the minimization problem of energy consumption for each considered control strategies and predict the HVAC system optimized set-points under transient load. The integrated simulation tool was validated by comparing predicted and measured power consumption of the chiller during the first day of July. Results show that between 3.2% and 11.8% power savings can be obtained by this approach while maintaining the predicted mean vote (PMV) from -0.5 to +1 for most of the summer time. © 2011 IEEE.

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http://hdl.handle.net/10453/19322