This paper presents a ventilation control strategy for multi-zone variable air volume (VAV) air-conditioning systems; integrating the sequential split-range control strategy for air-handing units with an aim to optimise the fresh air flow rate by compromising the indoor air quality and energy consumption. In this strategy, a CO2 -based adaptive demand-controlled ventilation scheme would employ a dynamic multi-zone ventilation equation for multi-zone air-conditioning systems, in which a CO2-based dynamic occupancy detection scheme would be used for online occupancy detection. The strategy would identify the critical zones online, and fully consider the outdoor air demand of critical zones, while, a model-based fresh air flow rate optimal control scheme is employed for VAV air-conditioning systems with the primary air handling units. An adaptive optimisation algorithm would be used for optimising the fresh air flow rate to minimise the energy consumption. The energy saving potentials in the Hong Kong climate condition by optimising fresh air ventilation and the practical implementation of the control strategy are also discussed in this paper.
Noh KC, Hwang J.: The effect of ventilation rate and filter performance on indoor particle concentration and fan power consumption in a residential housing unit: Indoor Built Environ2010;19(4):444-452.
2.
Yang JH, Seok HT, Lee SJ: A study on the application of a ceiling plenum ventilation system in an apartment house: Indoor Built Environ2009;18(3):234-244.
3.
Mui KW, Wong LT, Hui PS: Indoor environmental quality benchmarks for air-conditioned offices in the sub-tropics: Indoor Built Environ2009 ;18(2):123-129.
4.
Lai JH, Yik FWH: Perceived importance of the quality of the indoor environment in commercial buildings: Indoor Built Environ2007;16(4):311-321.
5.
Hui PS, Wong LT, Mui KW: An epistemic indoor air quality assessment protocol for air-conditioned offices : Indoor Built Environ2007;16(2):139-147.
6.
Chao CYH , Hu JS: Development of an enthalpy and carbon dioxide based demand control ventilation for indoor air quality and energy saving with neural network control: Indoor Built Environ2004;13:463-475.
7.
Chao CY, Chan GY, Ho L.: Feasibility study of an indoor air quality management protocol on 12 parameters in mechanically ventilated and air-conditioned buildings: Indoor Built Environ2001;10(1):3-19.
8.
The Government of Hong Kong Special Administrative Region: Guidance notes for management of indoor air quality in offices and public places. HKSAR, Indoor Air Management Group, 2003.
9.
Ashrae 62-1990: Ventilation for Preservation of Occupants’ Health, Safety and Wellbeing - Specify Indoor Air Quality, Minimum Ventilation Rate Acceptable for Human Occupants and will not Impair Health. Atlanta, GA , ASHRAE, 1990.
10.
Elovitz D.: Minimum outside air control methods for VAV systems: ASHRAE Trans 1995;101:613-618.
11.
Chan MY: Commuters’ exposure to carbon monoxide and carbon dioxide in air-conditioned buses in Hong Kong: Indoor Built Environ2005 ;14:397-403.
12.
Liu J., Liu GQ: Some indoor air quality problems and measures to control them in China: Indoor Built Environ2005;14:75-81.
13.
Chao CYH , Hu JS: Development of a dual-mode demand control ventilation strategy for indoor air quality control and energy saving: Building Environ2004;39:385-397.
14.
Yik FWH , Lun YF: Energy saving by utilising natural ventilation in public housing in Hong Kong: Indoor Built Environ2010;19(1):73-87.
15.
Fong KF, Chow TT, Li C.: Comfort zone of air speeds and temperatures for air-conditioned environment in the sub-tropical Hong Kong: Indoor Built Environ2010;19(3):375-381.
16.
Li X., Zhu F.: Response coefficient: A new concept to evaluate ventilation performance with ‘‘Pulse’’ boundary conditions: Indoor Built Environ2009;18(3):189-204.
17.
Daghigh R., Adam NM, Sahari BB: Ventilation parameters and thermal comfort of naturally and mechanically ventilated offices: Indoor Built Environ2009 ;18(2): 113-122.
18.
Budaiwi I., Al-Homoud M., Abdou A.: Implementation of a multi-phase approach for investigating and remedying a thermal comfort problem in an office building: Indoor Built Environ2009;18(1):52-65.
19.
Persily A.: Ventilation, carbon dioxide and ASHRAE Standard 62-1989: ASHRAE J1993;35(7):40-44.
20.
Kusuda T.: Control of ventilation to conserve energy while maintaining acceptable indoor air quality: ASHRAE Trans1976;82(1): 1169-1181.
21.
Elovitz D.: Minimum outside air control methods for VAV systems: ASHRAE Trans1995;101(2):613-618.
22.
Ashrae: ASHRAE Standard 62-2001: Ventilation for acceptable indoor quality. Atlanta, ASHRAE, 2001 .
23.
Zaheer-uddin M., Zheng GR: Optimal control of time-scheduled heat, ventilating and air conditioning process in building: Energy Convers Manage2000;41(1):49-60.
24.
Ardehali MM , Smith TF: Evaluation of HVAC system operational strategies for commercial buildings: Energy Convers Manage1997;38(3):225-236.
25.
Spitler J., Hittle D., Johnson D., Pederson C.: A comparative study of the performance of temperature-based and enthalpy-based economy cycles: ASHRAE Trans1987;93(2):13-22.
26.
Hydeman M., Taylor S., Stein J., Kolderup E., Hong T.: Advanced variable air volume system design guide: Technical Report , California Energy Commission, Sacramento, 2003.
27.
Xu XH, Wang SW: An adaptive demand-controlled ventilation strategy with zone temperature reset for multi-zone air-conditioning systems: Indoor Built Environ2007;16(5): 426-437.
28.
Xu XH, Wang SW, Sun ZW, Xiao F.: A model-based optimal ventilation control strategy of multi-zone VAV air-conditioning systems: Appl Therm Eng2009;29(1):91-104.
29.
Sun ZW, Wang SW, Ma ZJ: In-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation strategy in a multi-zone office building: Building Environ2011;46(1):124-133.
30.
Ashrae: Energy Standard for Buildings Except Low-rise Residential Buildings: ANSI/ASHRAE/IESNA standard90.1-2004, Atlanta, GA, American Society of Heating, Refrigerating and Air-conditioning Engineers, Inc. 2004 .
31.
Wang SW, Jin XQ: Model-based optimal control of VAV air-conditioning system using genetic algorithm : Building Environ2000 ;35: 471-487.
