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## Über dieses Buch

This book investigates the latest modeling and control technologies in the context of air-conditioning systems. Firstly, it introduces the state-space method for developing dynamic models of all components in a central air-conditioning system. The models are primarily nonlinear and based on the fundamental principle of energy and mass conservation, and are transformed into state-space form through linearization. The book goes on to describe and discuss the state-space models with the help of graph theory and the structure-matrix theory.

Subsequently, virtual sensor calibration and virtual sensing methods (which are very useful for real system control) are illustrated together with a case study. Model-based predictive control and state-space feedback control are applied to air-conditioning systems to yield better local control, while the air-side synergic control scheme and a global optimization strategy based on the decomposition-coordination method are developed so as to achieve energy conservation in the central air-conditioning system. Lastly, control strategies for VAV systems including total air volume control and trim & response static pressure control are investigated in practice.

## Inhaltsverzeichnis

### Chapter 1. Introduction

With the development of economy and growth of people’s living standards, air-conditioning systems are increasingly popular for the improvement of thermal environment indoors, which results in ever-increasing energy consumption of buildings.
Ye Yao, Yuebin Yu

### Chapter 2. Component Modeling with State-Space Method

A state-space representation, also known as the ‘time-domain approach’, is a mathematical model of a physical system as a set of input, output, and state variables related to first-order differential equations.
Ye Yao, Yuebin Yu

### Chapter 3. Dynamic Simulations with State-Space Models

In the chapter, characteristics of dynamic thermal response of HVAC components are simulated with corresponding state-space model. The dynamic response characteristics are usually described by two parameters: One is amplification coefficient (i.e., proportionality coefficient of response parameters to the perturbation ones); the other is time constant (i.e., the time required for the response parameters to arrive at a newly steady state after the perturbation occurs).
Ye Yao, Yuebin Yu

### Chapter 4. Graph-Theory Modeling and Structure-Matrix Analysis

In this chapter, the graph theory is employed for modeling the HVAC components and system. By using the graph-theory models, the direct or indirect relationships among model’s input and output variables are clearly described. Meanwhile, the structure-matrix method is used to analyze the dynamic characteristics of various parts in the HVAC system, including reachability, controllability, and observability.
Ye Yao, Yuebin Yu

### Chapter 5. Virtual Measurement Modeling

Generally, a measurement is only an approximation of the ‘true’ value of a measurand. Because of the involved errors, i.e., systematic errors and random errors, such a measurement should always be accompanied by a statement of uncertainty [1].
Ye Yao, Yuebin Yu

### Chapter 6. Control Design Based on State-Space Model

In this chapter, the methodology of MPC in terms of the formulation, model structure, and solving method is first briefly reviewed. Then, Wiener, Hammerstein, and Hammerstein–Weiner structures are introduced, which can be used to handle the nonlinearity in a building system.
Ye Yao, Yuebin Yu

### Chapter 7. Combined Forecasting Models for Air-Conditioning Load Prediction

Air-conditioning load forecasting is prerequisite for the optimal control and energy-saving operation of HVAC systems. In particular for those systems that use thermal storage technology, air-conditioning load forecasting will be extremely important and indispensable.
Ye Yao, Yuebin Yu

### Chapter 8. Energy Analysis Model for HVAC System

This chapter firstly deals with energy models of HVAC components including chiller, boiler, pump/fan, cooling tower, and water-to-air surface heat exchanger.
Ye Yao, Yuebin Yu

### Chapter 9. Optimal Control of HVAC System Aiming at Energy Conservation

Although the efficiency of individual components has increased considerably in HVAC systems, there still exits much energy waste as much as 30 % of total energy consumption due to various non-optimal operations [1].
Ye Yao, Yuebin Yu

### Chapter 10. Modeling and Control Strategies for VAV Systems

In a heating, ventilating, and air-conditioning (HVAC) system, operation of the air-side system has a significant influence on the overall performance of a building energy system. For example, in a worst-case scenario instability in the air-side economizer could trigger instability at the central chilled water plant or vice versa.
Ye Yao, Yuebin Yu
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