Recognition and Analysis of Air‐conditioner Operation Based on Basic IAQ‐monitoring

Abstract

Building performance simulations are particularly important for the development of various building energy efficiency strategies. However, the accuracy of these building simulations is often greatly influenced by real occupant behaviour, which leads to deviations between expected and measured performance. The occupant behaviour varies greatly from region to region and even within the same region due to the differences in cultural, climatic and socioeconomic contexts and building characteristics. Therefore, typical occupant behaviours and usage patterns in local buildings should be considered to improve the accuracy of the building simulations. To achieve this purpose, sufficient occupant data is needed to derive these typical behaviours. The cost of data collection and analysis as well as privacy concerns, are the main challenges that must be addressed. This study proposed a simple method to recognise the use of individual split-air-conditioning units based on basic environmental parameters (indoor air temperature, humidity and CO2-concentration) collected by IAQ-sensors in residential buildings. This method was used to analyse the air-conditioning (AC) usage patterns of 98 rooms in 49 residential apartments over one year in Hanoi, Vietnam and validated through comprehensive occupant surveys and on-site measurements. While deriving typical behaviours, deviations from measured room temperature and AC set temperature were observed and discussed in detail. The highlights of the proposed method are as follows: a) The data on AC operation can be determined without labour-intensive manual processing; b) The necessary input data can be collected by using standard IAQ-monitoring instruments, which minimises the cost of data collection and the invasion of occupant privacy; c) Missing information about AC usage can be added to data sets of previous studies for further analysis.