Modeling and control in Air-conditioning sysytems

Energy and Environment Research in China

Ye Yao

Yuebin Yu

Modeling and

Control in Air￾conditioning

Systems

Energy and Environment Research in China

More information about this series at http://www.springer.com/series/11888

Ye Yao • Yuebin Yu

Modeling and Control

in Air-conditioning Systems

123

Ye Yao

Shanghai Jiao Tong University

Shanghai

China

Yuebin Yu

University of Nebraska–Lincoln

Lincoln

USA

ISSN 2197-0238 ISSN 2197-0246 (electronic)

Energy and Environment Research in China

ISBN 978-3-662-53311-6 ISBN 978-3-662-53313-0 (eBook)

DOI 10.1007/978-3-662-53313-0

Jointly published with Shanghai Jiao Tong University Press, Shanghai, China

Library of Congress Control Number: 2016948282

© Shanghai Jiao Tong University Press and Springer-Verlag GmbH Germany 2017

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Preface

With the global warming and the rapid improvement of people’s living standards,

energy consumption by air-conditioning (AC) systems in buildings is on the rise.

According to the US Energy Information Administration (EIA) and the US

Department of Energy, the consumption of electrical energy by HVAC (heating,

ventilation, and air-conditioning) systems in the residential, commercial, and

industrial sectors corresponds to 18.62 %, 16.20 %, and 2.34 % of the total elec￾trical energy consumed in the USA, respectively (totalizing 37.16 %). In China,

building sector accounted for 23.4 % and 28 % of total energy use in 2011 and

2012, respectively, and about half of total building energy is consumed by HVAC

systems. Thus, energy conservation in HVAC systems will play an important role

in search of solutions to meet the growing global energy demand. Any techno￾logical measures for HVAC systems’ energy consumption reduction require

effective models based on which the high-performance HVAC systems and optimal

control schemes for highly efficient operations can be designed.

This book mainly concerns about modeling and control in air-conditioning

systems. Some advanced modeling methods including state-space method,

graph-theory method, and structure-matrix method, as well as combined forecasting

method, are employed for the modeling of air-conditioning systems. The virtual

sensor calibration and virtual sensing methods (which will be very useful for the

real system control) are illustrated together with the case study. The model-based

predictive control and the state-space feedback control are introduced to the

air-conditioning systems for a better local control, and the air-side synergic control

scheme and the global optimization strategy with the decomposition-coordination

method are developed aiming at energy conservation of the entire system. Lastly,

control strategies for VAV systems including the total air volume control and the

trim-and-response static pressure control are investigated with practice. The book

comprises ten chapters that are summarized as below:

Chapter 1 (written by Dr. Ye Yao and Dr. Yuebin Yu) introduces background

of the topic related to this book, gives a literature overview about modeling

approaches in HVAC field, and presents proposed methods to be used in this book.

v

Chapter 2 (written by Dr. Ye Yao) illustrates in detail the modeling process for

HVAC components and system with the state-space modeling method.

Chapter 3 (written by Dr. Ye Yao) presents simulation results on transient

responses of HVAC components with the state-space models under different per￾turbations and initial conditions.

Chapter 4 (written by Dr. Ye Yao and Dr. Yuebin Yu) is related to development

of graph-theory approach for modeling HVAC components and system, and

introduces the structure-matrix analysis method to study control characteristics of

HVAC state-space models.

Chapter 5 (written by Dr. Yuebin Yu and Dr. Ye Yao) deals with the virtual

sensor calibration and virtual sensing methods.

Chapter 6 (written by Dr. Yuebin Yu and Dr. Ye Yao) is about control design

based on the state-space model.

Chapter 7 (written by Dr. Ye Yao) is about forecasting models for

air-conditioning load prediction. The two original forecasting models based on the

combined principle are introduced.

Chapter 8 (written by Dr. Ye Yao) deals with energy models for HAVC com￾ponents based on which the energy analysis program is developed and used for the

energy analysis on variable-air-volume (VAV) air-conditioning systems.

Chapter 9 (written by Dr. Ye Yao and Dr. Yuebin Yu) is about optimal control

of HVAC system aiming at energy conservation.

Chapter 10 (written by Dr. Ye Yao and Dr. Yuebin Yu) mainly deals with

modular modeling, control strategies, and sequences as well as test script for VAV

system.

Acknowledgement

The study work related to the book has been financially supported by several

National Nature Science Foundations (No. 50708057; No. 51110105012).

Shanghai, China Ye Yao

June 2016

vi Preface

Contents

1 Introduction............................................. 1

1.1 Background ........................................ 1

1.2 Modeling Approaches in HVAC Field .................... 2

1.2.1 Physics-Based Modeling Approach ................ 2

1.2.2 Data-Driven Modeling Approach.................. 7

1.2.3 Hybrid Modeling Approach...................... 10

1.3 Proposed Methods ................................... 11

1.3.1 State-Space Modeling .......................... 11

1.3.2 Graph-Theory Modeling ........................ 11

1.3.3 Combined Forecasting Modeling .................. 12

1.3.4 Decomposition–Coordination Algorithm for Global

Optimization Model............................ 13

1.3.5 Virtual Calibration for HVAC Sensors ............. 14

1.3.6 Model-Based Predictive Control (MPC) ............ 17

1.4 Organization of This Book ............................. 18

References............................................... 21

2 Component Modeling with State-Space Method ................ 29

2.1 Basic Knowledge About State-Space Modeling Method....... 29

2.2 Modeling for HVAC Components ....................... 30

2.2.1 Water-to-Air Heat Exchanger .................... 30

2.2.2 Chiller ...................................... 44

2.2.3 Cooling Tower ............................... 60

2.2.4 Duct (Pipe) and Fan (Pump) ..................... 71

2.2.5 Air-Conditioned Room Modeling ................. 85

2.3 Modeling for HVAC System ........................... 96

2.3.1 Component Model Connection ................... 96

2.3.2 State-Space Representation for HVAC System ....... 100

2.3.3 Case Study .................................. 103

References............................................... 108

vii

3 Dynamic Simulations with State-Space Models................. 109

3.1 On Water-to-Air Surface Heat Exchanger.................. 109

3.1.1 Subjected to Different Perturbations ............... 109

3.1.2 For Different Initial Conditions ................... 113

3.2 On Chiller.......................................... 124

3.2.1 Subjected to Different Perturbations ............... 124

3.2.2 For Different Initial Conditions ................... 128

3.3 On Cooling Tower ................................... 141

3.3.1 Subjected to Different Perturbations ............... 141

3.3.2 For Different Initial Conditions ................... 143

3.4 On Duct and Pipe .................................... 147

3.4.1 On Straight-Through Duct....................... 147

3.4.2 On Straight-Through Pipe ....................... 150

3.5 On Air-Conditioned Room ............................. 152

3.5.1 Basic Conditions .............................. 152

3.5.2 Subjected to Different Perturbations ............... 152

4 Graph-Theory Modeling and Structure-Matrix Analysis ......... 159

4.1 Graph-Theory Modeling for HVAC Component State-Space

Models ............................................ 159

4.1.1 Fundamental Rules ............................ 159

4.1.2 Case Study .................................. 160

4.2 Graph-Theory Modeling for HVAC System ................ 172

4.2.1 Basic Method ................................ 172

4.2.2 Case Study .................................. 173

4.3 Structure-Matrix Analysis Approach...................... 176

4.3.1 Model Structural Matrix ........................ 176

4.3.2 Reachability Analysis of Model Input–Output........ 176

4.3.3 Controllability/Observability Analysis of Model ...... 178

4.3.4 Case Study .................................. 180

References............................................... 188

5 Virtual Measurement Modeling ............................. 189

5.1 Virtual Calibration ................................... 189

5.1.1 Conventional Calibration ........................ 189

5.1.2 Methodology of Virtual In Situ Calibration.......... 192

5.1.3 Case Study .................................. 200

5.2 Virtual Sensing ...................................... 203

5.2.1 Development Methodology for Virtual Sensing....... 204

5.2.2 Case Study .................................. 207

5.2.3 Model Development ........................... 210

References............................................... 218

viii Contents

6 Control Design Based on State-Space Model................... 221

6.1 Model-Based Predictive Control (MPC) ................... 221

6.1.1 Introduction of MPC ........................... 221

6.1.2 MPC in Broad Definition ....................... 222

6.2 Applications of MPC in HVAC Field..................... 229

6.2.1 Control of a Hybrid Ventilation Unit............... 229

6.2.2 Control of Space Thermal Conditioning ............ 266

6.3 State-Space Feedback Control System Design .............. 285

6.3.1 Basic Principle................................ 285

6.3.2 Control System Design for Water-to-Air Heat

Exchanger ................................... 287

6.3.3 MATLAB Simulation of the Control System ........ 289

6.3.4 Control System Design for Refrigeration System ..... 291

References............................................... 295

7 Combined Forecasting Models for Air-Conditioning

Load Prediction .......................................... 297

7.1 Typical Methods..................................... 297

7.1.1 MLR Modeling ............................... 297

7.1.2 ARIMA Modeling ............................. 299

7.1.3 GM Modeling ................................ 301

7.1.4 ANN Modeling ............................... 302

7.2 Combined Forecasting Model Based on Analytic Hierarchy

Process (AHP) ...................................... 304

7.2.1 Principles of the Combined Forecasting Method ...... 304

7.2.2 Determining Weights by Analytic Hierarchy

Process (AHP)................................ 305

7.2.3 Combined Forecasting Model for Hourly Cooling

Load Prediction Using AHP ..................... 308

7.3 Forecasting Model Based on Neural Network and Combined

Residual Error Correction .............................. 316

7.3.1 Model Development ........................... 316

7.3.2 Case Study .................................. 323

References............................................... 327

8 Energy Analysis Model for HVAC System .................... 329

8.1 Energy Models for HVAC Components ................... 329

8.1.1 Chiller ...................................... 329

8.1.2 Boiler ...................................... 331

8.1.3 Pump and Fan ................................ 332

8.1.4 Cooling Tower ............................... 332

8.1.5 Water-to-Air Heat Exchanger .................... 333

8.2 Energy-Saving Analysis on VAV Air-Conditioning System .... 335

Contents ix

8.2.1 Evaluation Program for Energy Saving

of VAV System............................... 336

8.2.2 Case Study .................................. 339

8.3 Energy Analysis on VAV Air-Conditioning System

with Different Air-Side Economizers ..................... 346

8.3.1 Scheme for Air Economizer Cycle [27]............. 347

8.3.2 Case Study .................................. 351

References............................................... 356

9 Optimal Control of HVAC System Aiming at Energy

Conservation ............................................ 359

9.1 Air-Side Synergic Control ............................. 359

9.1.1 Background and Basic Idea ...................... 359

9.1.2 Mathematic Deduction of Synergic Control Model .... 361

9.1.3 Control Logic Details .......................... 373

9.1.4 Case Study .................................. 376

9.2 Global Optimization Control............................ 387

9.2.1 Model Development ........................... 387

9.2.2 Decomposition–Coordination Algorithm for Model

Solution..................................... 393

9.2.3 Case Study .................................. 399

Appendix ............................................... 413

References............................................... 420

10 Modeling and Control Strategies for VAV Systems ............. 423

10.1 Background and Research Status ........................ 423

10.2 Modular Modeling with Simulink Tool ................... 429

10.3 Model Library for Components of VAV System ............ 432

10.3.1 VAV Terminal Unit ........................... 432

10.3.2 Variable Speed Fan ............................ 434

10.3.3 Air Ducts.................................... 436

10.3.4 Other Local Resistance Components ............... 444

10.3.5 Application of Component Model Library:

Case Study .................................. 445

10.4 Control Strategies for VAV System ...................... 449

10.4.1 Constant Static Pressure Method .................. 450

10.4.2 Total Air Volume Method ....................... 453

10.4.3 Variable Static Pressure Method Based

on Trim-and-Respond Logic ..................... 458

10.5 Control Sequences for VAV System with Different

Terminal Units ...................................... 464

10.5.1 For Cooling-Only Terminal Unit .................. 464

10.5.2 For Reheat Terminal Unit ....................... 465

10.5.3 For Series Fan-Powered Terminal Unit ............. 467

x Contents

10.6 Test Script for VAV Control Study ...................... 468

10.6.1 Preparation .................................. 468

10.6.2 General Inspection of Air-Handling and Distribution

System...................................... 469

10.6.3 Trend Data Review ............................ 473

References............................................... 477

Contents xi

About the Authors

Dr. Ye Yao is an Associate Professor at the School of Mechanical Engineering,

Shanghai Jiao Tong University, China. He received his Ph.D. from Shanghai Jiao

Tong University (SJTU), China. He was promoted as Associate Professor of SJTU

in December 2008. From September 1, 2009 to September 1, 2010, he performed

his research work in Ray W. Herrick Lab at Purdue University (PU), USA. He was

awarded as Excellent Reserve Youth Talent and SMC Excellent Young Faculty by

SJTU, respectively, in the year 2009 and 2015, and got Shanghai Pujiang Scholars

Talent Program in the year 2012. His current research interests mainly include

(a) HVAC modeling and optimal control for energy conservation; (b) Heat and

mass transfer enhancement assisted by ultrasound. He has successfully published

about 100 academic publications and two academic books (first author) and owns

30 Chinese patents. He is now the peer reviewer of many international academic

journals such as ‘International Journal of Heat and Mass Transfer’, ‘International

Journal of Thermal Sciences’, ‘International Journal of Refrigeration’, ‘Energy’,

‘Building and Environment’, ‘Energy and Buildings’, and ‘Applied Energy’.

Dr. Yuebin Yu is an Assistant Professor in the Durham School of Architectural

Engineering and Construction at University of Nebraska-Lincoln, USA. He received

his Ph.D. degree in Building Performance and Diagnostics from Carnegie Mellon

University, Pittsburgh, PA, USA. He devotes his research efforts to the fields

including (a) smart building technology, including automated continuous commis￾sioning and advanced controls, automated fault detection and diagnosis, virtual

sensing and virtual calibration; (b) active utilization of renewable energy for heating,

ventilation and air-conditioning, including low-grade energy, solar and geothermal

thermal energy, active phase change material, bionic building enclosure; and

(c) built environment modeling and evaluation. At UNL, he maintains a

state-of-the-art laboratory with well-instrumented facilities and advanced web-based

AFDD platform for smart buildings and advanced building envelope studies. He is

an active and voting member in the Technical Committee TC7.5 for Smart Building

xiii

Systems and serves as the sub-committee chair of Fault Detection and Diagnostics in

ASHRAE. He participated in the revision of ASHRAE Handbooks on Fault

Detection and Diagnostics and Energy Estimating and Modeling Methods. He has

published about 50 academic publications.

xiv About the Authors

Abbreviations

ACH Air change rate

AFDD Automated fault detection and diagnostics

AHU Air handling unit

CLFTOT Glass total cooling load factor

COP Coefficient of Performance

DDC Direct digital control

DX Direct expansion

EEV Electronic expansion valve

ERV Enthalpy recovery wheel

FIR Finite impulse response

FP First principle

FPS Fraction of possible sunshine

HVAC Heating ventilation and air-conditioning

HW Hammerstein–Weiner structure

IAHU Integrated air handling unit system

IAQ Indoor air quality

inv Inverse function

LTI Linear time-invariant

MAT Mixed air temperature

MD Measured disturbance

MIMO Multiple input and multiple output

MO Measured output

MPC Model predictive control

MSHGF Maximum solar heat gain factor

MV Measured input

NL Nonlinear

OA Outside air

OAT Outdoor air temperature

OAD Outdoor air damper

PCA Principal component analysis

PID Proportional, integral, and derivative

xv