ASHRAE 4693-2004 Development and Implementation of HVAC-KBCD A Knowledge-Based Expert System for Conceptual Design of HVAC&R System - Part 2 Application to Office Buildings《制定和实施HV.pdf

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1、4693 Analysis of the Impact of C02-Based Deman d-Con t ro I led Vent i lati on Strateg es on Energy Consumption Moncef Krarti, Ph.D., P.E. Member ASHRAE ABSTRACT This paper presents an integrated IAQiHVAC simulation environment that can model the impact of contaminant-based demand-controlled ventila

2、tion (DCV) strategies on both indoor air quality and HVAC system energy use for multizone buildings. The predictions of the integrated IAQ/HVAC simu- lation environment are first validated against experimental data obtained from laboratory testing. Then the simulation environment is used to investig

3、ate the performance of three ventilation control strategies, namely: one conventional control using fixed-position for outside air damper and two DCV strategies, including on/of control and proportional- integral-derivative (PID) control. In particulal; a series of parametric analyses is conducted t

4、o determine the impact of selected design and operational features ofDCVstrategies on both indoor air quality and HVAC system energy use. The sensitivity analysis revealed that leakage from outside air dampers, use of a temperature economizers, selection of CO, sensors, tuning of PID controllers, an

5、d selection of CO, setpoints can have a signijicant impact on both indoor air qual- ity and energy consumption of HVAC systems. INTRODUCTION The performance of CO,-based demand-controlled venti- lation (DCV) strategies has been extensively investigated over the last decade. Most of the existing stud

6、ies on DCV are based on simulation analysis and have primarily focused on the potential energy savings of the C02-based demand-controlled ventilation systems (Knoespel et al. 1991; Vaculik and Plett 1993; Emmerich et al. 1994; Sorensen 1996). Only few DCV control strategies have been implemented and

7、 evaluated in real Mohsin Al-Alawi, Ph.D. buildings or under laboratory conditions. Studies have been reported for the following DCV strategies: Odoff controls (Davidge 199 1) Proportional controls (Fleury 1992; Donnini et al. 1991; Haghighat and Donnoni 1992) Step-flow controls (Fehlmann et al. 199

8、3; Zamboni et al. 1991) PID controls (Alawi and Krarti 2002) For most of the reported studies, energy savings of DCV strategies have been estimated relative to a fixed ventilation rate control strategy. The fixed ventilation rate is determined based on ASHRAE Standard 62-2001 (ASHRAE 2001), which sp

9、ecifies minimum ventilation flow rates for various building types and occupancy levels. While the existing field and simulation studies have provided useful insights on the potential benefits of demand- controlled ventilation, the impact of design andor operating parameters of DCV controls have not

10、been extensively explored. Various factors affect the performance of DCV controllers, such as CO, sensor selection, sampling rate of CO, concentration, outdoor air damper leakage, and use of temperature or enthalpy economizer controls. This paper presents a comprehensive simulation environ- ment cap

11、able of modeling the transient effects on both indoor air quality and HVAC system energy use of various design and operational parameters associated with DCV control strate- gies. First, the models and algorithms that constitute the simu- lation environment are briefly described. Then, the predictio

12、ns of the simulation environment are validated against laboratory testing data. Finally, the results of several parametric analyses are summarized. In particular, the effects on both indoor air Moncef Krarti is an associate professor at the University of Colorado, Boulder, Colo. Mohsin Al-Alawi is a

13、n assistant professor at the Univer- sity of Bahrain, Al-Manama, Bahrain. 274 02004 ASHRAE. quality and HVAC system energy use are determined for selected design and operational features, including leakage from outside air dampers, use of temperature economizers, selection of CO, sensors, tuning of

14、the PID controllers, and selection of CO, setpoints. DESCRIPTION OF THE IAQIHVAC SIMULATION ENVIRONMENT Figure 1 illustrates the basic models used to develop an TAQHVAC simulation environment suitable to investigate the performance of CO2-based demand-controlled ventilation strategies under various

15、design and operating conditions. A brief description of each model is given below. The DOE-2 program is used to determine hourly sensible and latent loads. Input parameters for the DOE-2 program include building characteristics and location, occupancy schedule, zone setpoint temperatures, and weathe

16、r. From the hourly results, the sensible and latent loads are deter- mined for any time step using linear interpolation. The VAV model reads the sensible and latent loads calcu- lated from the DOE-2 program and determines zone total supply air. At the same time, the CO, control program determines th

17、e fraction of outside air to be supplied during each time step based on the contaminant concentration in the zone and the CO2-based demand-controlled strategy used. The output variables of the VAV model include pre- heat, reheat, and cooling coil heat transfer rates and supply fan electrical power c

18、onsumption. I I VAV UODFL CON moi. MODEL Wrathsr data EQUIPMENTMODEL a Weatbar dala Chiller dal. Boiler dali coalrn1 %,ralc*y Powrr rooriomption Il CO, TRANSPORT Fgure I Basic models integrated within the IAQ/HVAC simulation module. The CO, transport model used in conjunction with the control progra

19、m provides the variation of indoor CO, concentration as zone outside air intake changes with time. The variation in the CO, concentration is then fed back to a control module that adjusts the outdoor airflow rates to be supplied to the zones depending on the C02-based demand- control ventilation str

20、ategy. The HVAC equipment models estimate the energy consumption for chillers, fans, and boilers based on the heating and cooling transfer rate data received from the VAV model. Input parameters of the HVAC equipment models include weather data and equipment performance data. A more detailed descrip

21、tion of the last three models is provided in the following sections. Air-Handling Unit (AHU) System Model A variable air volume (VAV) system is a single-path system that controls the indoor temperature within a zone by varying the amount of air supply. The damper of the VAV terminal unit adjusts the

22、 airflow rate supplied to the zone depending on heating or cooling loads. The discharge air temperature is kept constant and equal to the supply air temperature from the air-handling unit plus any temperature increase due to heat gains (for instance, from the supply fan motor). As indicated in Figur

23、e 2, a VAV system consists of a central air-handling unit and VAV terminal units with reheat coils located in the zones. The AH unit itself includes a supply fan, a cooling coil, a preheat coil, and an outside air economizer. The AHU delivers air at a controlled fixed temperature, while in the VAV u

24、nit terminals, the damperposi- tion is adjusted to supply the airflow rate needed to meet the thermal load for each zone. In particular, when the zone cool- Fgure 2 Diagram of the variable air volume (VAV) model. ASH RAE Transactions: Research 275 VAV MODFJ. i-i ,-I “ _+ Toother Con c, I I .Y . , “.

25、X “ CAW I II ! i s* IZftin i * . I i IN fi Cai IN6 C,i V,i Vm, 4 v v * I Figure 3 Modules used for VAV simulation model. Figure 4 Basic features of the contaminant transport model. ing load decreases, the damper closes until it reaches its mini- mum position to supply the minimum airflow rate. The r

26、eheat coil may be activated to meet the thermal load in the zone. A A more detailed description of each subroutine can be fmnd in the secondasr HVAC toolkit (Brandemuehl et al. 1993). variable-speed drive can be used to modulate the supply fan to vary the airflow rate according to the thermal load o

27、fthe zones. The outside air damper in the AHU can have a fixed posi- tion or a variable position, depending on the control strategy being implemented. For the base-case control strategy, the outdoor air damper position is fixed to satisfy ASHRAE venti- lation requirements (ASHRAE 1999). For any DCV

28、strategy, such as odoff or PID, the position of the outside air damper is modulated to maintain the desired CO, levels within the zones. In addition, the outdoor air damper position is controlled depending on ambient air temperatures when an economize cycle is used. The input variables for the AHU s

29、imulation model include supply air temperature setpoints, entering water temperatures for cooling or preheatheheat coils, outside airflow rates (determined by the control module), and econo- mizer temperature setpoints. Moreover, the AHU simulation model requires input variables specific to each zon

30、e, including sensible and latent loads, minimum zone supply airflow rates, and zone heating supply flow rates. The AHU model calls several modules and algorithms selected from the secondary HVAC toolkit (Brandemuehl et al. 1993). In particular, the VAV model calls three main modules, as illustrated

31、in Figure 3: 1. COILINV, which is the general routine for coils that calls either the cooling coil (CCDET) or the preheat/ reheat coils (HCDET) whenever any one is needed. FANSIM, which is the routine that models the supply fan to estimate the energy consumption. ECON, which is the routine that calc

32、ulates the mixed air temperature and enthalpy to determine whether an econo- mizer could be used. 2. 3. Multizone Contaminant TrancportControl Model The contaminant transport model used in the integrated IAQ/HVAC simulation is adapted from the work of Knoespel et al. (1991). In particular, the trans

33、port model is based on a nodal analysis applied to various building elements. The model assumes that the building nodes have a capacitance for pollutant and uses a pollutant mass balance for each node to solve for the pollutant concentrations. The main features of the transient contaminant transport

34、 model developed for this study are summarized below. Infiltration and interzonal flows are input variables to the program. Thus, they can be calculated outside the program or estimated from experimental tests. Ventila- tion requirements in the zones are calculated by another module, depending on th

35、e outdoor air control strategy. The model is capable of taking into account the time variation of the pollutant generation rate within each zone during the simulation period by adequately defin- ing the number of occupants (or any other pollutant-gen- erating sources) using an occupancy schedule. Di

36、fferent occupancy schedules during the weekday and the week- end can be simulated. The circulation time of the air traveling through the ven- tilation system is taken into account by sizing the ducts connecting the air-handling unit to the zones. Removal efficiency of the pollutant (due, for instanc

37、e, to air filters installed in the ductwork) can be an input vari- able in the model. The model can determine the time variation of contami- nant level for any time step (as short as one minute). Figure 4 shows a diagram for the contaminant transport model integrated with a VAV system serving severa

38、l zones. 9 276 ASH RAE Transactions: Research The pollutant balance equation for each zone is summarized by Equation 1. In particular, Equation 1 indicates that the transport of a pollutant can occur through three possible paths: Circulation flow in and out of the zones: Vs,i (supply airflow rate to

39、 zone i) and V,.et,i (return airflow rate from zone i). Air infiltration in and out of the zones: Qahi (infiltration flow rate associated with zone i). Interzonal flow in and out of the zones: CzAij) (flow rate from zone i to zonej). The flow of the pollutant can be determined by multiply- ing the a

40、irflow rates by the concentration of pollutant within the airstreams (COA for outside air, Csi for supply air, and C,.et,i for return air associated with zone 1). The zones may also have pollutant sources with a generation rate, Si. The model calculates the pollutant concentrations in three differen

41、t locations, namely, the concentration in the zones, the mixed return air concentration at the air-handling unit (Am), or the supply air concentration. Control of outside air intake can be performed based on any one of these concentrations (i.e., depending on where the sensor is located). Outdoor Ai

42、r Control Strategies A control module has been integrated with the contami- nant transport model. This control module can model three control strategies, as outlined in the following sections. Base-Case Control Strategy. For this work, the base- case control strategy is the fixed outside air damper

43、position since it is a common method used to meet minimum outside airflow intake rates in VAV systems (Schroeder et al. 2000). Under design flow conditions, the outside air damper is posi- tioned to meet minimum outside air requirements. The mini- mum ventilation rate requirements are determined usi

44、ng ASHRAE Standard 62-2001. For office buildings, the stan- dard specifies 20 cfdperson (10 L/s per person). For a multi- ple-zone system, the outdoor air fraction is calculated using the following equation (ASHRAE 2001): Z = V,JVsc = fraction of outdoor au in critical space V,t = corrected total ou

45、tdoor airflow rate, cfm vst = total supply flow rates, i.e., the sum of all supply for all branches of the system, ch v, = sum of outdoor airflow rates for all branches on system, cfm cc = outdoor airflow rate required in critical spaces, cfm vsc = supply flow rate in critical space, cfm Through Equ

46、ation 2, Standard 62-2001 attempts to provide adequate supply of ventilation for a multizone system with uneven pollutant loads. The correction of outside air frac- tion takes into account the critical zone (typically the zone with the highest occupant density). However, the fixed outdoor air damper

47、 position is not always an effective control strategy to maintain the minimum outside air requirements in all zones (Schroeder et al. 2000; Krarti et al. 2000; Reddy et al. 1998; Mudam et al. 1996). On/Off DCV Strategy. The odoff demand-controlled ventilation strategy uses the following operating mo

48、des: When the maximum concentration limit is exceeded, the outside damper is fully open, providing 100% outside air. When the concentration drops below the minimum con- centration limit, the outside damper is fully closed or supplying minimum outside air. The maximum and minimum limits can be any va

49、lues above and below the CO2 concentration setpoint. It should be noted that a fully open outside air damper may not necessarily provide 100% outside air. This case can occur when some of the return air mixes with the entering outside air due to leaky return dampers. The odoff DCV strategy has another feature to prevent the outside air damper from switching too frequently between on and off positions. That is, the outside air damper cannot close or open unless a preset time has already passed. This preset time is determined by the user, and can be any value between three to ten