Evaluating the Need and Potential of Equipping North American Houses with Multi-Zone VAV Systems

Abstract:

To identify potential energy savings and improvements to thermal comfort in the Canadian residential sector, a survey on occupant behaviour and control of thermal environment was conducted from April-June 2009 in low-rise dwellings in Ontario, Canada. A total of 396 completed responses were received. Survey results show that approximately 20% of the respondents were not satisfied with their room temperature in the winter. Inadequate level of controllability to room temperature is perceived as the most serious problem. Problems associated with overheating during the winter and overcooling during the summer was also identified. Observations from the survey results helped identify the deficiencies of the heating equipments built today and suggest improvements should be made to increase the controllability of current systems. Thermal simulation was then conducted to identify the problems with single-zone systems commonly built today, and to investigate the potential retrofit alternative. Simulation results show that a multi-zone system can effectively mitigate the deficiencies suffered by existing systems and can drastically improve the energy performances of houses.

• Periodical: Advanced Materials Research (Volumes 361-363)
• Pages: 22-30
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.361-363.22
• Online since: October 2011
• Authors: Ka Long Ringo Ng, Zai Yi Liao
• Keywords: Controllability, Detached Houses, Energy Model, Space Heating, Survey, Thermal Comfort

References

[1] Canada Mortgage Housing Corporation. (2011). Preliminary Housing Start Data. Document # 64695

[2] Natural Resources Canada. (2006). Comprehensive Energy Use Database Tables

[3] Redfern A., Koplow M., Wright P. (2006). Design architecture for multi‐zone HVAC control systems from existing single‐zone systems using wireless sensor networks Proceedings of the SPIE ‐ The International Society for Optical Engineering, v 6414, 2006, p 64140Y

DOI: 10.1117/12.695963

[4] Wang S., Jin X. (2000). Model‐based optimal control of VAV air‐conditioning system using genetic algorithm. J. Building and Environment 35 (2000) 471‐48

DOI: 10.1016/s0360-1323(99)00032-3

[5] Canada Mortgage and Housing Corporation (1996). Optimizing Residential Forced-Air HVAC Systems. Technical Series 96-218

[6] Liang J., Du R. (2005). Thermal comfort control based on neural network for HVAC application. In proceedings IEEE Conference on Control Applications Toronto, Canada, August 28-31, 2005 pp.819-824

DOI: 10.1109/cca.2005.1507230

[7] Kulkarni M.R., Hong F. (2004). Energy optimal control of a residential space-conditioning system based on sensible heat transfer modeling. J. Building and Environment 39 (2004) 31-38

DOI: 10.1016/j.buildenv.2003.07.003

[8] Freire R.Z., Oliveira G.H.C. Mendes N. (2008). Predictive controllers for thermal comfort optimization and energy savings. J. Energy and Buildings 40 (2008) 1353-1365

DOI: 10.1016/j.enbuild.2007.12.007

[9] Dounis A.I., Caraiscos C. (2009). Advanced control systems engineering for energy and comfort management in a building environment – a review. J. Renewable and Sustainable Energy Reviews 13 (2009) 1246-1261

DOI: 10.1016/j.rser.2008.09.015

[10] Statistics Canada. (2006). 2006 Census. Ottawa: Statistics Canada