HVAC Energy Saving in IPS-enabled Large Space: An Occupancy Distribution Based Demand-driven Control Approach

Wei WANG; Yujie Lu; Gongsheng HUANG; Xiaowei LUO; Jiayu CHEN

doi:10.1016/j.egypro.2017.03.587

Author(s)

Related Research Unit(s)

Department of Architecture and Civil Engineering

Detail(s)

Original language	English
Pages (from-to)	2083-2088
Journal / Publication	Energy Procedia
Volume	105
Publication status	Published - 1 Jun 2017

Conference

Title	8th International Conference on Applied Energy – ICAE 2016
Location	Beijing, China
Place	China
City	Beijing
Period	9 - 11 October 2016

Link(s)

DOI	DOI https://doi.org/10.1016/j.egypro.2017.03.587 Final Published version
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Attachment(s)	Documents 14015055.pdf Final Published version, 905 KB, PDF Publisher's Copyright Statement This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/
Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-85020739432&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(af7f668f-3c54-4905-bc91-5fa0cc5923f1).html

Abstract

Occupancy attracts an increasing attention in recent building energy efficiency research through enabling more sophisticated control strategies. With the development of latest indoor positing systems (IPS), the facility managers are able to detect the geospatial distribution of building occupants. Based on such information, this paper proposes a demand-driven control system for HVAC control in large spaces to reconcile occupants’ thermal comfort demand and energy consumption. Comparing to conventional temperature and CO2 based HVAC control systems, the new approach integrates the indoor positions of occupants and a demand-oriented and PID-based ventilation control mechanism. An computational fluid dynamic simulation is constructed to valid the proposed control system. Air supply flow rate and temperature distribution are captured for three sample cases that have even and uneven occupancy distributions in the simulation. By avoiding overcooling and unnecessary cooling, the proposed approach could save a significant amount of electrical consumption from HVAC operation.