Promoting Energy Efficiency of HVAC Operation in Large Office Spaces with a Wi-Fi Probe enabled Markov Time Window Occupancy Detection Approach

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)

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Author(s)

Detail(s)

Original languageEnglish
Publication statusPublished - 20 Jul 2017

Conference

TitleWorld Engineers Summit 2017 – Applied Energy Symposium & Forum: Low Carbon Cities & Urban Energy (WES-CUE 2017) Joint Conference
LocationSuntec Singapore
PlaceSingapore
Period18 - 21 July 2017

Abstract

In recent years, demand-based control in HVAC systems have achieved a great amount energy saving by providing precise services in according to actual demand. As the premise of determining actual demand, occupancy information has a significant impact on building heating, cooling and ventilation in building control and energy auditing. In this paper, a Wi-Fi probe based occupancy detection method is applied to detect the occupancy in typical office buildings. Given the Wi-Fi coverage and smart devices are widely used in modern buildings, Wi-Fi probe requires no initial investment and could scan the Internet connection request and response of occupants. Previous studies suggest time-series and stochastic characteristics of occupancy information, this research proposed a Time-Window based Markov Chain (TWMC) model to detect occupancy. An on-site experiment was conducted in this study to validate the proposed method. The results report an accuracy of over 80% (x-accuracy when x equals 4). Compared to actual occupancy profile, the proposed model shows over 88% of supply air amount reduction in energy simulation with an absolute deviation less than 20%. By integrating the proposed TWMC model based on Wi-Fi probe and demand-based control system, the energy consumption of HVAC system could be significantly reduced.

Bibliographic Note

Information for this record is provided by the author(s) concerned.

Citation Format(s)

Promoting Energy Efficiency of HVAC Operation in Large Office Spaces with a Wi-Fi Probe enabled Markov Time Window Occupancy Detection Approach. / WANG, Wei; Lin, Zhenghang; CHEN, Jiayu.

2017. Paper presented at World Engineers Summit 2017 – Applied Energy Symposium & Forum: Low Carbon Cities & Urban Energy (WES-CUE 2017) Joint Conference, Singapore.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)