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5、ng nor may any part of this book be reproduced, stored in a postmaster-Send form 3579 to: Cuslomrr S,nicc, ASHRAE, retrieval system, or transmitted in any form or by any means elec- 1791 Tullie Circle NE, Atlanta, GA 30329-2305, USA. Editorial: Sustainable Building Systems Require New Design Guideli
6、nes J. Srebric, PhD Member ASHRAE It is an exciting time to be an HVAC accepted June 29, 2007 WAC systems are the major energy consumers in buildings. Operation and control of HVAC sys- tems have signijicant impacts on the energy or cost eficiency of buildings besides their designs. Buildings nowada
7、ys are mostly equipped with comprehensive building automation systems (BASs) and building energy management control systems (EMCSs) that allow the possibility of enhancing and optimizing the operation and control of HVAC systems. Supervisory and optimal control, which addresses the energy or cost-ef
8、icient control of HVAC systems while providing the desired indoor comfort and healthy environment under the dynamic working conditions, is attracting more attention of the building professionals and the society and provides incentives to make more efforts in developing more extensive and robust cont
9、rol methods for HVAC systems. This paper provides a framework for categorizing the main supervisory and optimal control methods and optimization techniques developed and/or utilized in the HVAC$eld. The application characteristics of each control method and optimization technique are also identzjied
10、 and compared. A comprehensive overall review of the state of the art of the research and development, as well as application of supervisory and optimal control, in HVAC systems is also presented. INTRODUCTION The building automation system (BAS) is a tool that can be used for more effective and eff
11、i- cient management of building services systems (Carlson and Di Giandomenico 1991). One of the main achievable goals of effective use of BASS is to improve the building energy or cost efficiency and provide better performance. Control functions are the basic functions of BASs. Other major functions
12、 of BASs include risk management functions, information, and facilities management functions. Control functions of BASs can be divided into two categories, i.e., local control functions and supervisory control (or energy management) functions, as shown in Figure 1. Local control functions are the ba
13、sic control and automation that allow the building services systems to operate properly and provide adequate services. Local control functions can be further subdivided into two groups, including sequencing control and process control. Sequencing control defines the order and conditions associated w
14、ith bringing equipment online or moving them offline (ASHRAE 2003). The typical sequencing control in HVAC systems includes chiller sequencing control, cooling tower sequencing control, pump sequencing con- trol, and fan sequencing control, etc. Process control is to adjust the control variables to
15、achieve well-defined process objectives in spite of disturbances, using measurements of state andlor dis- turbance variables (Rarnirez 1994). The typical process control used in the HVAC field is pro- portional-integral-derivative (PID) control. ON/OFF control (or bang-bang control), step control, a
16、nd modulating control are the effective control actuation schemes of local process control loops in HVAC practice, and they have produced a great impact and profound significance on building Shengwei Wang is a professor and the acting head and Zhenjun Ma is a PhD student in the Department of Buildin
17、g Services Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong. Control functions I I 1 1 1 1 Modd-based Hybrid method method I Figure 1. Classification schematic of control functions in HVAC systems. automation. The control settings of these local controllers might be optimal and ener
18、gy efficient or cost effective when certain subsystems or certain subsystem performance criteria are con- cerned. However, they may not be energy efficient or cost-effective when the overall system and overall system performance are of concern. Supervisory control, often named optimal control, seeks
19、 to minimize or maximize a real function by systematically choosing the values of vari- ables within allowed ranges. It is the total system monitoring and overall control of the local subsystems (Levenhagen and Spethmann 1993). In the control of HVAC systems, supervisory and optimal control aims at
20、seeking the minimum energy input or operating cost to provide the satisfied indoor comfort and healthy environment, taking into account the ever-changing indoor and outdoor conditions as well as the characteristics of HVAC systems. It is worth noting that minimizing system operating cost is not alwa
21、ys equivalent to minimizing system energy input. Compared to the local control, supervisory control allows an overall consideration of the system level characteristics and interactions among all components and their associated variables. The knowledge of the system level characteristics and interact
22、ions can be utilized to minimize a well-defined cost function or objective function, which would lead to the improved system response and reduced operating cost. According to the classification scheme in Figure 1, super- visory and optimal control in HVAC systems could be classified into four catego
23、rizes, including model-based supervisory control method, hybrid supervisory control method, performance map-based supervisory control method, and model-free supervisory control method. For many years, control has been a very active area of the research and development in the HVAC field, aiming at op
24、eration of HVAC systems in terms of reducing overall system oper- ating cost, ensuring thermal comfort of occupants, and satisfying indoor air quality. Many efforts in the control of building HVAC systems have typically paid on the local level controls (Goswami 1986; Moore and Fisher 2003; Rishel200
25、3; Fredrik and Dennis 2004; Zhang et al. 2005; etc.). The success and popularity enjoyed by the application of PID control is one of the fruitful outputs of such efforts. While there are numerous effective optimal control strategies developed, growing concern on energy or cost efficiency, due to the
26、 extremely high fuel oil price and the shortage of energy supply, has evoked the society and building professionals to pay more attention on overall system optimal control and operation and provided incentives to develop the most extensive and robust supervisory and optimal control methodologies for
27、 HVAC systems. Over the last two decades or so, efforts have been undertaken to develop supervisory and optimal control strategies for building HVAC systems thanks to the growing scale of BAS integration and the convenience of collecting large amounts of online operating data by application of BASS.
28、 Depending on the situations and objectives to be achieved, supervisory control plays different roles at different time periods (Levenhagen and Spethrnann 1993). The earliest supervisory,con- trol stressed the building equipment automation, and the primary focus was on automating all equipment as mu
29、ch as possible to save labor. Later, supervisory control emphasized the building energy monitoring and automatic control, and the major concern was on energy efficiency by both automatic and manual control with the aid of system monitoring. However, the results obtained from both types of supervisor
30、y control are not likely to be energy efficient and cost-effective since much attention is paid to the automatic equipment with less consideration of their operating costs. Nowadays, the supervisory control highlights the importance of overall system performance involving energy or cost efficiency a
31、nd indoor environmental quality, etc. Therefore, supervisory control is to optimize the operation of HVAC systems using a system approach by considering the system level or subsystem level characteristics and interactions among the overall system. The control system in this kind of supervisory contr
32、ol generally pro- vides two levels of control, i.e., local control and supervisory control. Local control is the low level control, which is designed to guarantee the robust operation and keep track of the setpoint considering the dynamic characteristics of local process environment. Supervisory con
33、trol is the high level control, which is designed to utilize global optimization techniques to find energy or cost-efficient control settings (i.e., operation mode and setpoints) for all local controllers, taking into account the system level or subsystem level characteristics and interactions. Thes
34、e energy or cost-efficient control settings are optimized in order to minimize the overall system energy input or operating cost without violating the operating constraints of each component and with- out scarifying the indoor environmental quality provided. Chapter 41 of the 2003 ASHRAE Handbook-HV
35、AC Applications (ASHRAE 2003) provides a critical overview of supervisory control strategies and optimization for HVAC systems. This chapter consists of three major sections. The first section defines the system and control vari- ables considered. The general background on the effects and opportunit
36、ies related to adjust these control variables is also presented in this section. The second section presents a number of sim- ple strategies that can be implemented in practice for near-optimal control of HVAC systems. The third section provides basic methods for optimization of systems both with an
37、d without sig- nificant thermal energy storage. However, this chapter did not provide a basic classification scheme of supervisory control methods utilized in HVAC systems. The general information of optimization techniques used to formulate the supervisory control strategies is also not included. F
38、oremost, the references involved in this chapter were published before 2001, and most of them (83.6%) were published before 1997. With the rapid development of technologies, many new methods and techniques have recently been used to develop more advanced supervisory and optimal control strategies fo
39、r HVAC systems. Therefore, a comprehensive review of the research and development as well as application of supervisory and optimal control strategies in the HVAC field is essentially necessary to present the state of the art. The organization of this paper is presented as follows. In the next secti
40、on, “The General Opti- mal Supervisory Control Problem in HVAC Systems,“ the general optimal supervisory control problem for HVAC systems is presented and used as a context for understanding the contribu- tions of the others described in this paper. In the section that follows, “Supervisory Control
41、Methods,“ the framework for categorizing supervisory and optimal control methods in HVAC systems is provided in terms of what type of model is used in the control system. In this section, the advantages and disadvantages of the application of these methods are clearly identified. In the following se
42、ction, “Optimization Techniques Used in Supervisory Control,“ various optimi- zation techniques utilized in supervisory and optimal control are presented, and the benefits of the application of these techniques in HVAC systems are critically analyzed. In the section enti- tled, “Research and Applica
43、tion of Optimal Control Strategies for HVAC Systems,“ the research and development as well as the application of supervisory and optimal control strategies in HVAC systems are reviewed comprehensively according to the classification schematic of supervisory control methods. A brief assessment for ma
44、jor techniques is also provided in this section. Finally, the discussion and conclusion are presented. THE GENERAL OPTIMAL SUPERVISORY CONTROL PROBLEM IN HVAC SYSTEMS The optimal supervisory control for HVAC systems is to determine the optimal solutions (oper- ation mode and setpoints) that minimize
45、 overall system energy input or operating cost while still maintaining the satisfied indoor thermal comfort and healthy environment. For different types of HVAC systems (i.e., electric-driven system, gas-dnven system, hybrid gaslelectric-driven system, the systems with and without energy storage, et
46、c.), the optimal supervisory control problems are significantly different. For a particular optimization problem, different utility rate structures will lead to different solutions as well. Since the general optimal supervisory control problem for hybrid systems with significant energy storage is th
47、e most complicated system, the other systems can be considered simplifications of such systems. Therefore, the optimal supervisory control problem and cost function for hybrid systems with significant energy storage are presented in detail in the following. The optimal supervisory control for hybrid
48、 systems with significant energy storage is extremely complex, affected by many factors including electrical and gas energy costs, electrical demand charges, maintenance costs associated with different chillers (electric or gas), chiller characteristics, storage characteristics, weather condition, a
49、nd load profile, etc. For a utility rate structure that includes time-of-use differentiated electricity prices and demand charges and the fixed cost of natural gas over each billing period (e.g., a month), the overall optimization prob- lem of such systems is to minimize the utility cost over the billing period (e.g., a month), and the cost function can be mathematically described as in Equation 1. with respect to the N, control variables and subject to a series of constraints (i.e., basic energy and mass conse
