(HVAC) System Configurations - AIT Austrian Institute of Technology

251 Pages·2013·7.44 MB·English

by  Hiscock, Deborah

Optimization of Heating, Ventilation, and Air-Conditioning
(HVAC) System Configurations

By

Muzaffar Ali
08-UET/PhD-ME-45

Supervised by
Prof. Dr. Mukhtar Hussain Sahir

Department of Mechanical Engineering
Faculty of Mechanical and Aeronautical Engineering
University of Engineering & Technology Taxila, Pakistan
2013
Optimization of Heating, Ventilation, and Air-Conditioning
(HVAC) System Configurations

By

Muzaffar Ali
08-UET/PhD-ME-45
Supervised by
Prof. Dr. Mukhtar Hussain Sahir

A dissertation submitted in partial fulfilment of the requirements for the
degree of

Doctor of Philosophy

In

Mechanical Engineering

Department of Mechanical Engineering
Faculty of Mechanical and Aeronautical Engineering
University of Engineering & Technology Taxila, Pakistan
2013
Optimization of Heating, Ventilation, and Air-Conditioning
(HVAC) System Configurations

A dissertation submitted in partial fulfilment of the requirements for the
degree of Doctor of Philosophy (PhD) in Mechanical Engineering

Author
Muzaffar Ali
08-UET/PhD-ME-45

Checked and Recommended by:

Research Monitoring Committee:

Prof.Dr. Mukhtar Hussain Sahir
Research Supervisor

Prof.Dr. Arshad Qureshi Prof. Dr. Khalid Akhtar
Member Research Committee Member Research Committee
National University of Science and Technology
(NUST)

Dr. Irfan Gondal
Member Research Committee
National University of Science and Technology
(NUST)
DECLARATION
The substance of this dissertation is original work of the author. Due reference and
acknowledgement has been made, where necessary, to the work of the others. No part of
dissertation has already been accepted for any degree, and it is not being currently
submitted in candidature of any degree.

Author
Muzaffar Ali
08-UET/PhD-ME-45
ABSTRACT
Today, a substantial amount of world‘s energy is being consumed by the building
sector. In buildings, energy share of Heating, Ventilation and Air-Conditioning (HVAC)
systems is dominant. Various aspects of HVAC system optimization are analyzed in
several studies; however the optimization of HVAC system configurations is rarely
analyzed. Moreover, no systematic approach is developed for evaluating different
HVAC system design alternatives to decide the optimal configuration for a specific
building load demand and climate conditions.
The thesis is aimed to develop a methodical simulation-based optimization approach for
the effective and efficient evaluation of various HVAC system alternatives at the initial
system design stage to result in an optimal configuration. The approach is implemented
at both system design level as well as at the configuration level. It is concluded from
literature review that the equation-based object-oriented (EOO) modeling and
simulation approach provides a conducive environment for evaluating HVAC system
configurations.
In the developed approach, two methods are proposed with respect to HVAC system
modeling and simulation characteristics. The first method ‗conditional declaration of
component models‘ is used for automated selection of optimal system configurations. It
uses the coupling between modeling tool Dymola/Modelica and the optimization tool
GenOpt through an appropriate algorithm. The second method
‗redeclaration/replaceable component models‘ is also proposed for HVAC system
modeling in which several types of a specific component class can be varied to define
various system configurations It includes empty component models of all system
component with connecting ports and without heat and mass transfer. Such
multifunctional modeling enables to simulate variety of component models for
performance analysis of different HVAC system configurations that can be considered
in the future research. However, the method has the limitation that the component class
cannot be changed automatically in the current version of Modelica language. Though,
the improvement in the language is underway to incorporate such feature.
In the current work, both methods are implemented for the performance optimization of
two real HVAC systems: chilled water system installed in Symantec Corporation
building in South California, USA and desiccant cooling system operating in
ENERGYbase building in Vienna, Austria.
The implementation of the first method established an incremental development of the
methodology for chilled water system design optimization. The optimization is
performed at the system design as well as configuration level through development of a
dynamic chilled water system model in Dymola/Modelica capable of varying system
design and configuration parameters. The approach proved efficient in terms of
estimating time and labor. The overall optimization of chilled water system at system
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design and configuration level with fixed building load demands resulted in 17-43%
reduction of power consumption. In addition, estimated initial cost of each chilled water
system configuration is also evaluated for economic considerations.
For performance analysis of desiccant evaporative cooling system, a desiccant wheel
model is developed in EOO program, Dymola/Modelica. The existing wheel models in
other modeling environments lack the capabilities to handle real-time control strategies
with respect to wheel operational modes and sensor functionalities. Therefore, the
developed model incorporates real-time control strategies for both dehumidification and
enthalpy modes under the transient operating conditions that are encountered in the
commercial systems. The model is calibrated and validated under the transient
measurements obtained from ENERGYbase building desiccant wheel installation.
However, the other available component models of desiccant cooling system are
designed for ideal behavior. Therefore all relevant component models, such as
humidifier and heat wheel are modified to match the real system operation. The
modified component models are calibrated and validated under the transient
measurements obtained from ENERGYbase monitoring system. Afterwards, the
validated component models are used to develop desiccant evaporative cooling system
model. Then validation is performed at the system level based on ENERGYbase system
measurements.
The second proposed method is applied on the validated desiccant cooling system
model for an appropriate selection of desiccant cooling system configuration. Five
system configurations consist of ventilation, standard recirculation, standard dunkle,
ventilated recirculation, and ventilated dunkle cycles are evaluated in five climate
zones: Vienna, Karachi, Sao Paulo, Shanghai, and Adelaide. The evaluation resulted
that the ventilated dunkle cycle is the most efficient in terms of high COP system
configuration in three climate zones except Karachi and Shanghai climates that are more
suitable for the ventilation system configuration. Moreover, the estimated initial cost of
each configuration is also provided that could be further helpful for overall
configuration evaluation.
To conclude, the presented systematic simulation-based optimization approach
significantly helps to handle the complex task of optimal selection of HVAC system
configurations. Such development would be supportive for the HVAC design
practitioners to evaluate various system alternatives and select the optimal system
configuration and design parameters at the initial design stage under various building
load demands and climate conditions. Moreover, the methodology signifies a step
forward toward the design of software systems able to synthesize new and optimal
system configurations.

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ACKNOWLEDGEMENTS
This research work was carried out at Mechanical Engineering Department of
University of Engineering and Technology Taxila, Pakistan (UETT) in collaboration
with Energy Department of Austrian Institute of Technology (AIT), Austria.
First, I would like to express my sincere gratitude to Prof.Dr. Mukhtar Hussain Sahir for
his consistent guidance, support and patience in last five years. He always trusted and
encouraged me during the ups and downs of my research duration. In addition, I am
really appreciate and thank all my research monitoring committee (MRC) members for
their kind support and fruitful discussions that include Prof. Arshad Qureshi, Prof.
Khalid Akhtar, and Dr. Irfan Gondal.
I spent three years of my PhD study in Energy Department of AIT where I performed
core of my research work under the supervision of Dr.Vladimir Vukovic. He has always
believed in me, and has been boosting me during all research activities. Without his
guidance and support there would not be this thesis. I learnt a lot from him, especially
the efficient and effective approaches for research problem solving and technical
writing skills. On the personal side, the company of Vladimir and his wife, on several
occasions was really refreshing for me; especially our visit to Belgrade was very
memorable. I greatly appreciated their warm hospitality during my whole stay in
Vienna.
I would also like to thank my all colleagues and friends at AIT who always supported
me technically and morally on every step of my research, especial thanks to Dr. Peter
Palensky, Dr. Gerhard Zucker, Daniele Basciotti, Giuliano Fontanella, Florian Dubisch,
Florian Stift, Markus Brychta, Markus Jones, Marek Kreman, Anita, Sergio Leal and
Tim Selke. Additionally, I am really thankful to Dr. Tarik Ferhatbegovic, Najd, Dr.
Atihya, Awais, and Ishtiaq for fruitful and entertaining discussions on several issues. On
the AIT management side, I am grateful to Doris Osterrticher and Julia Schebach for
their kind and supportive attitude. Moreover, I would also like to thank my all office
friends in Mechanical Engineering Department for numerous life-enriching discussions.
At last, but certainly not the least, I pay my special gratitude to my late parents for their
prayers for my success from the eternal life. Moreover, I am truly thankful to my all
other family members, brothers and sisters for their support and kind attitude, especially
to my beloved nieces and nephews; Harram Noor, M. Hassaan, Hudda Noor, M. Aayan,
and little angel Marryam Fatimha for their ever refreshing smiles and naughty activities.

Author

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TABLE OF CONTENTS
ABSTRACT ...................................................................................................................... i
ACKNOWLEDGEMENTS ............................................................................................ iii
TABLE OF CONTENTS ................................................................................................. v
LIST OF FIGURES ......................................................................................................... ix
LIST OF TABLES ....................................................................................................... xvii
LIST OF ABBREVIATIONS .......................................................................................... 1
1 INTRODUCTION ......................................................................................................... 3
1.1 Motivation .............................................................................................................. 3
1.1.1 Energy demand in buildings ............................................................................ 3
1.1.2 Energy Demand of HVAC systems ................................................................. 7
1.1.3 HVAC equipment demand ............................................................................ 11
1.2 Problem Statement ................................................................................................ 12
1.2.1 Problem Background ..................................................................................... 12
1.2.2 Problem Definition ........................................................................................ 14
1.3 Scientific Approach .............................................................................................. 16
1.3.1 HVAC system modeling and simulation ....................................................... 16
1.3.2 Automated Simulation-based Optimization .................................................. 17
1.4 Research Aims and Objectives: ............................................................................ 18
1.5 Scientific Contribution ......................................................................................... 19
1.6 Thesis Outline ....................................................................................................... 21
2 LITERATURE REVIEW ............................................................................................ 23
2.1 HVAC system modeling and simulation .............................................................. 23
2.2 HVAC design optimization .................................................................................. 26
2.3 Modeling, simulation, and optimization of HVAC system configurations .......... 29
2.4 Summary ............................................................................................................... 30
3 HVAC SYSTEM CONFIGURATIONS ..................................................................... 32
3.1 Classification of HVAC systems .......................................................................... 32
3.1.1 All-air systems ............................................................................................... 33
3.1.2 Air-water systems .......................................................................................... 33
3.1.3 Water systems ................................................................................................ 34
3.1.4 Refrigerant-based systems (Unitary systems) ............................................... 34
3.2 HVAC system equipment ..................................................................................... 34
3.2.1 HVAC primary equipment ............................................................................ 36
3.2.2 HVAC secondary equipment ......................................................................... 39
3.3 HVAC system configuration analysis .................................................................. 41
3.3.1 Primary system configurations ...................................................................... 41
3.3.2 Secondary system configurations .................................................................. 44
3.3.3 Alternative and innovative system configurations ........................................ 45
3.4 Conclusions .......................................................................................................... 52
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4 RESEARCH METHODOLOGY ................................................................................ 54
4.1 Why Equation-based object-oriented modeling and simulation approach ........... 54
4.1.1 Limitations of traditional building simulation programs ............................... 55
4.1.2 Characteristics of the equation-based object-oriented physical-modeling and
simulation ............................................................................................................... 56
4.2 Overview of modeling, simulation and optimization tools .................................. 57
4.2.1 Modelica- an equation-based object-oriented modeling language ................ 57
4.2.2 Dymola- Dynamic Modeling Laboratory ...................................................... 59
4.2.3 GenOpt- Generic Optimization Program ....................................................... 60
4.3 HVAC system configurations modeling and simulation ...................................... 61
4.3.1 Available component models in Modelica .................................................... 61
4.3.2 Inputs of HVAC system model ..................................................................... 63
4.3.3 Methods for the development of HVAC system configurations model ........ 64
4.3.4 Array of component models .......................................................................... 68
4.3.5 HVAC system sizing ..................................................................................... 70
4.3.6 Simulation of HVAC system model .............................................................. 71
4.4 Optimization of HVAC system configurations .................................................... 72
4.4.1 Optimization algorithms ................................................................................ 73
4.4.2 Optimization variables and constraints ......................................................... 74
4.4.3 The objective function ................................................................................... 75
4.4.4 GenOpt optimization setup ............................................................................ 76
5 DEVELOPMENT OF DESICCANT WHEEL MODEL ............................................ 81
5.1 Basic Concepts ..................................................................................................... 81
5.2 Adsorption Characteristics ................................................................................... 82
5.2.1 Adsorption Equilibrium and relations ........................................................... 82
5.2.2 Real and ideal desiccant wheel behavior ....................................................... 84
5.2.3 Potential theory of adsorption ....................................................................... 86
5.3 Operating modes of desiccant wheels .................................................................. 86
5.4 Desiccant wheel model development ................................................................... 88
5.4.1 Mathematical Model ...................................................................................... 89
5.4.2 Optimal rotation speed .................................................................................. 92
5.4.3 Pressure drop ................................................................................................. 93
5.4.4 Dymola/Modelica Model ............................................................................... 94
5.5 Model parametric performance analysis ............................................................... 95
5.5.1 Effect of process air inlet conditions ............................................................. 97
5.5.2 Effect of regeneration air inlet conditions ..................................................... 99
5.5.3 Effect of rotation speed ................................................................................. 99
5.6 Model Calibration and Validation ...................................................................... 101
5.6.1 Model Calibration ........................................................................................ 101
5.6.2 Model Validation ......................................................................................... 106
5.6.3 Validation of optimal rotation speed ........................................................... 107
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