A dynamic thermal management in buildings for comfort enhancement and energy conservation : from sensor networking to user participation

Pao Yue-kong Library Electronic Theses Database

A dynamic thermal management in buildings for comfort enhancement and energy conservation : from sensor networking to user participation

 

Author: Lam, Hang Yat
Title: A dynamic thermal management in buildings for comfort enhancement and energy conservation : from sensor networking to user participation
Degree: Ph.D.
Year: 2015
Subject: Dwellings -- Energy conservation
Buildings -- Energy conservation
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Computing
Pages: xvi, 122 pages : color illustrations ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2816355
URI: http://theses.lib.polyu.edu.hk/handle/200/8084
Abstract: Nowadays, buildings occupy a significant portion of global energy consumption.Sustainable efforts and measures have been carried out to reduce the energy consumption in buildings. Yet, buildings are not only a shelter for people, they also serve to provide people with comfort and safety; otherwise, turning off every power consuming equipment can maximize the energy conservation. Balancing the energy consumption and human comfort is challenging since it is hard to evaluate the satisfaction of occupants.This thesis presents a user-participatory framework, and models the thermal comfort of individuals by using mobile devices with minimal manual input. The framework connects with the building management system (BMS) to adjust the temperature setting; the mobility of underlying controllers is thus important to the framework applicability. An asynchronous-response design is developed to dewiring existing controllers into wireless while keeping the communication protocols intact. A modular design for wireless data plane is used to selectively prioritize and schedule data transmission in case of link quality and throughput variations. The feasibility of the design is tested by comprehensive experiments and field deployments in the University.A temperature-comfort correlation model is developed to estimate the individual comfort based on a collection of parameters and sensors data. In addition, a setpoint optimization algorithm is developed to find out the temperature that maximizes the group comfort. Field experiments in the University and a commercial office show the improvement of thermal comfort by 63% and 33.8% respectively, while reducing 18% of energy consumption in the experiment of commercial office.

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