An Experimental Design for Implementation of HVAC

By

ACKNOWLEDGEMENT

I would first like to express my gratitude for my research supervisor, colleagues, and peers and family whose immense and constant support has been a source of continuous guidance and inspiration.

DECLARATION

I hereby certify that the work described in this thesis is my own work, except where otherwise acknowledged, and has not been submitted previously for a degree at this or any other university.

Signature:

Dated:

TABLE OF CONTENTS

ACKNOWLEDGEMENT2

DECLARATION3

CHAPTER 1: INTRODUCTION5

Review of analytical approaches in modeling and optimization6

Thesis Structure7

CHAPTER 2: LITERATURE REVIEW9

Background9

Heating11

Central heating unit11

Ventilation13

Mechanical or Forced Ventilation14

Natural Ventilation14

Airborne Illnesses15

Energy efficiency19

Short-Term Prediction of HVAC Energy with a Clustering Approach19

HVAC system structure description20

Multi-Objective Optimization of HVAC System with an Evolutionary Computation21

Simple to Implement: Advanced HVAC components22

CHAPTER 3: METHODOLOGY25

Data Description and Optimization Methodology26

Modeling of AHU system and AQI sensors27

Parameter selection27

Work plan / Gantt Chart30

REFERENCES32

CHAPTER 1: INTRODUCTION

Heating, ventilating and air-conditioning (HVAC) system is a complex non-linear system with multi-variables simultaneously contributing to the system process. It poses challenges for both system modeling and performance optimization. Traditional modeling methods based on statistical or mathematical functions limit the characteristics of system operation and management. Data-driven models have shown powerful strength in non-linear system modeling and complex pattern recognition. Sufficient successful applications of data mining have proved its capability in extracting models that accurately describe the relation of inner system. The heuristic techniques such as neural networks, support vector machine, and boosting tree have largely expanded to the modeling process of HVAC system.

Evolutionary computation has rapidly merged to the center stage of solving the multi objective optimization problem. Inspired from the biology behavior, it has shown the tremendous power in finding the optimal solution of complex problem. Different applications of evolutionary computation can be found in business, marketing, medical and manufacturing domains. The focus of this thesis is to apply the evolutionary computation approach in optimizing the performance of HVAC system. Energy saving can be achieved by implementing the optimal control set points with IAQ maintained at an acceptable level. A trade-off between energy saving and indoor air quality maintenance is also investigated by assigning different weights to the corresponding objective function. The major contribution of this research is to provide the optimal settings for the existing system to improve its efficiency and different preference-based operation methods to optimally utilize the resources.

HVAC system is designed to provide a comfortable and desired environment for the occupants, in addition to meeting any special process requirements, such as indoor air quality. The maintenance of a healthy indoor condition of HVAC system is significant since people spend more than half of their time indoors. The issue of growing energy use has merged to the stage which draws sufficient attentions of not only commercial managers, but also researchers. According to the published statistics, HVAC system frequently consumes over 60% of the energy use in buildings [1, 2]. Therefore, the operation effectiveness and efficiency of HVAC system has become a focus.

The operation of HVAC system is a multi-angle problem. Simply minimizing the energy consumption without considering the indoor air ...