energy implications of filtration in residential and light-commercial buildings.

by:Booguan     2020-09-06
Forced air heating, ventilation and efficient filtration in airconditioning (HVAC)
The building energy-saving system is used to protect the building equipment and occupants, but it also affects the building energy consumption.
With high MERV (
The minimum efficiency report value defined by ASHRAEStandard 52. 2-2007)
The filter, which is usually lower than the MERV, has a greater pressure drop.
The energy consequences of a greater pressure drop due to filtration are well known for large commercial systems where fan and motor controls typically maintain the required airflow rate.
A higher pressure drop filter will cause the fan motor to consume more power to overcome the pressure drop and deliver the required air, thereby increasing the energy consumption (
2000 for Chimack and sellers; Fisk et al. 2002).
It is generally believed that this association between energy use and filter pressure drop is for smaller homes and light
However, operational differences between small and large systems suggest that the consequences of energy are very different.
The main difference is that in most residential HVAC systems, increasing the pressure drop of the air conditioner usually results in a decrease in airflow, although the evidence is limited. Parker et al. (1997)
When replacing the standard disposable filter, the airflow rate reduction of 4 to 5% was measured
High efficiency folding filter in live test of residential air conditioner.
Air flow reduction usually reduces cooling capacity, power consumption of compressors, and system efficiency. Parker et al. (1997)
Predicted by computer simulation and laboratory testing, the airflow is 5% less than the value recommended by most manufacturers [ton. sup. -1](193 [m. sup. 3]* [h. sup. -1]* [kW. sup. -1])to 380CFM [ton. sup. -1](184 [m. sup. 3]* [h. sup. -1]* [kW. sup. -1])
The actual cooling capacity will be reduced by about 2%.
This shows that the system running time will be extended by 2% in order to meet the same cooling load.
In laboratory experiments, Rodriguez and others. (1996)tested 3. 5-ton (12. 3 kW)
Air conditioning and the report said that it was reduced by about 6 to 7%, inefficient, and the total capacity was reduced by 10% compared to the recommended airflow rate. Palani et al. (1992)
Measure the effect of airflow on 3-ton (10. 5 kW)
In a series of laboratory tests, the air conditioner also experienced a similar decline in capacity and a similar decline in airflow.
The same study shows that more serious energy consequences can occur when traffic is reduced to extremes. Parker et al. (1997)
If the flow is reduced from 20% CFM [about 40%], the system cooling energy consumption may increase by 400, the report said. ton. sup. -1](193 [m. sup. 3]* [h. sup. -1]* [kW. sup. -1]).
Previous surveys have shown that if there is a higher
The efficiency filter reduces the airflow and the reasonable cooling capacity decreases, which indicates that the energy consumption increases due to the increase in system running time.
However, the power consumption of fans and compressors is also decreasing, which may limit the impact of negative energy.
In addition, the change in the filter pressure drop can affect the pipe leakage by changing the pressure around the pipe leakage.
Although we know that there is no direct study of the impact of filtration on pipeline leakage, there is a large amount of literature on the energy consequences of leakage in residential and lighting pipelines
Business system (e. g. , Modera 1989; Modera1993; Parker et al. 1993; Jump et al. 1996; Walker et al. 1998;
Withers and camings 1998; Siegel et al. 2000;
Francisco and others2006).
One of the core challenges of associating energy results with filtering is the complexity of these interactions.
Many of the features of these effects are unclear, but may be very systematic --
Dependent and affected by parameters such as system pressure drop scores related to filters, fans, etc.
Speed setting, intersection of fan and pipe curve.
In order to explore these effects in the actual system, we monitored the residential and lighting
Commercial forced air cooling systems are installed at multiple sites in Austin, Texas.
The measured parameters include system airflow rate, power consumption, cooling capacity, pressure drop on filters and coils, and pipeline leakage.
For a year, regular measurements are made at each site, using off-the-shelf filters of different MERV categories, depending on the filter manufacturer\'s rating.
The aim of this study was to evaluate the use of the small air medium filter MERV and the corresponding measured pressure drop impact energy
Air conditioning system.
The specific goal is to allow system designers and users to evaluate the consequences associated with a higher version
Efficient filtering.
Methods site selection and description according to the willingness of construction owners and residents to install monitoring equipment and frequent visits of site personnel, 17 systems were selected as convenience samples.
Table 1 summarizes 17 test sites.
The first eight locations are residential buildings and the remaining nine are light buildings
Commercial building. Thelight-
Commercial buildings are all office space, and some offer limited retail functions.
Less than 2000 per system service [ft. sup. 2](186 [m. sup. 2])
Floor area and cooling capacity of rated air conditioner from 1. 5 to 5. 0 tons (5. 3 to 17. 6 kW).
Typical permanent split capacitors at 1 to 15 sites (PSC)
Fan and Station 16 and 17 electronic converter motors (ECM)fans.
Most plumbing works are located in an unconditional attic and there are some systems with pipes elsewhere.
The filter is located in the return grille or air handling unit.
All test systems rely on the penetration of fresh air rather than dedicated outdoor air ventilation.
Test methods visit test sites once a month a year, during which three types of filter efficiency are usually used in residential and lighting
Installation of commercial systems: low (MERV 2),medium (MERV 6-8), and high (MERV 11-12).
Each MERV Category filter is placed for three months and monitored four times: initially on the day of installation, after one, two, three months of use. The last three.
Repeat the installation of a MERV category using a month\'s time to evaluate the changes in the measurements.
Unlike other sites, site 12 is only high
Due to the requirements of the building owner, the efficiency filter is installed within the duration of the project.
During the monthly visit, measurements were made in the fan
Mode only by activating the switch on the thermostat.
Pressure Measurement using energy greenhouse DG
700 handheld digital force meter (uncertainty [+ or -]1% of reading)
, Including the pressure drop when C = the specific heat of the air, assuming a constant (0. 24 Btu/([lb. sub. m]*[degrees]F), 1. 005 kJ/(kg K)[DELTA]
T = temperature difference at both ends of the cooling coil ([degrees]F, K); [DELTA]
W = poor humidity ratio on the cooling coil ([lb. sub. m]/[lb. sub. m], kg/kg); and [h. sub. [Florin]g]
= Suppose constant, steam heat of water (
970 Btu/lb, 2257 kJ/kg).
The performance coefficient, COP, and calculation are shown as equations (2). COP = [[q. sub. t]/[[W. sub. on]+ [W. sub. fan]]](2)where [W. sub. ou]
= Outdoor unit, including compressor (W); and [W. sub. fan]
= Fan power pull (W).
The cooling capacity is calculated during each recorded period, only when the system reaches stability-Status operation.
In the analysis, the measured observations are marked as stable-
The state when the supply room temperature changes no more than 0 in at least 2 minutes. 9[degrees]F (0. 5 [degrees]C)
Start with the lowest temperature recorded in a cycle. Steady-
Due to the response time of the temperature and relative humidity instrument, the state period must also exceed at least 6 minutes.
Although the calculation of capacity and efficiency is in the equation (1)and (2)
Evaluating the cooling performance of the system, few people know how the change in reasonable capacity is actually converted into a thermal state reading that ultimately affects both runtime and energy consumption.
To solve this problem, we also measure the energy consumption and runtime of the test system.
[Amount of energy consumed during air conditioning cycleE. sub. cyc](watt-hours)
, Defined in the equation (3)
Because the total power of the cycle is multiplied by the length of the cycle ,[l. sub. cyc](hours). [E. sub. cyc]= ([W. sub. oil]+ [W. sub. fan])[l. sub. cyc](3)
The data analysis calculation is used as each access for two separate test generation filter replacements (
Do a test with 3-month-
The old filter is followed by a test of a brand new filter)
At sites 11 and 12, each site has a missed visit and a one-year monthly test at 17 sites, with a total of 270 visits.
About 43% of the visits took place during the cold season.
Analyze the data set and answer three specific research questions: 1.
What is the impact of filtering efficiency (MERV)
Airflow and parameters related to system energy use? 2.
How are the air flow and energy consequences directly related to the filtration pressure drop? 3.
What is the range of cooling energy consequences that can be generated by filtering in residential and lighting
Commercial building?
The analytical and statistical procedures for each issue are described below. 1.
Impact of filtration efficiency (MERV).
The dependent variables that may be related to energy results in this analysis include: system airflow rate, power consumption of air processor fans, external pipeline leakage, fan efficiency (i. e.
Volume flow per unit power)
Power consumption, total capacity, apparent capacity, potential capacity, performance coefficient, apparent heat ratio and pipeline delivery efficiency of outdoor units.
To address the impact of filter MERV on these quantities, these dependent variables are first averaged for each site visit, and then averaged again in a given filter MERV category, processing the duplicate filter installation separately
To evaluate the statistical difference between the filter MERV categories, two pairs of two-tailedt-
Test and Wilcoxon signature-ranked (non-parametric)
The test has been completed.
The test compares the average value of each dependent variable between each site :(1)high-and low-MERV filters, (2)high-andmid-
MERV filter and (3)mid-and low-MERV filters.
The statistical significance is assessed [alpha]< 0. 05.
By comparing the absolute size of the difference and the uncertainty of the instrument, and comparing the repetition of the same location and the same MERV-Category filter. 2.
Effect of filter pressure drop.
Filter pressure drop can only be associated with weak MERV category, especially for used filters with increased pressure drop due to load.
In order to evaluate the impact of filter pressure drop changes, regardless of the MERV category, each dependent variable is averaged for each visit to each site first, then the change of each dependent variable is calculated and standardized to a clean low-
The MERV filter is installed.
Linear regression of each normalized dependent variable with the measured filter pressure drop, where the filter pressure drop is also normalized to a clean low-MERVfilter.
Regression slope estimates the expected variable change due to an increase in filter pressure drop.
When the 95% confidence interval does not contain zero, the importance of the regression slope is determined, and an upper and lower limit estimate of the expected variable change due to the filter pressure drop change is established. 3.
Estimation of energy consequences in cooling mode.
The first two research questions try to separate the effects of filters on individual energy changes
Related parameters.
In this analysis, the range of changes in the actual cooling energy consumption (in kWh)
The dueto filter is estimated based on changes in the fan power map, outdoor unit power map, and system runtime measurements.
In theory, these parameters will capture any change in other energies
Relevant parameters including pipeline leakage impact.
This method is only low. and high-
MERV filter, used to evaluate the maximum possible impact in the measurement system. Forty-
Five low cold visits
MERV filter and 50-installed-
Four cooling visits
The MERV filter is installed.
Results and discussion this section begins with a detailed introduction to field measurements and then summarizes the results of each of the three research questions.
On-site measurement figures 1 a and 1b show the pressure drop measured on the filter, the corresponding airflow rate, and the filter MERV classification installed during each on-site visit during fan operationonly mode. Figure 1(A)
Display the measurement results of the residential system, Figure 1 (B)
Display the business system.
Filter pressure drop values average on the length of each fan-
Operation period only (
Usually about 15 minutes)
The airflow rate is based on the supply pressure measured at the beginning of each visit.
Each barrepresents represents a monthly site visit with filter changes in X-axis.
The error bar indicates a larger standard deviation of the measurement or the accuracy of the instrument.
Due to the limited channels placed by the sensor, site 9 and 12 reported the pressure drop measured in the return air chamber, rather than the pressure drop directly through the filter. [
Figure 1 slightly]
Over time, the pressure drop of the filter usually increases with the monthly life of the filter, although there are several sites (e. g.
, Sites1, 3, 8 and 17)
Accidents sometimes decrease.
This drop is caused by several factors, including the uncertainty of the pressure drop measurement or the complex turbulent airflow and other disturbances that are located in the airflow before and after the filter. High-and mid-
The filter pressure drop shown by the MERV Category filter is usually lower-
MERV Category filter, but high-and mid-
MERV classifies itself.
At low-, mid-, and high-
MERV filters for all sites (
Sites 9 and 12 are not included)during the fan-Only mode is 0. 137 IWC (34Pa), 0. 213 IWC (53 Pa), and 0. 221 IWC (55 Pa), respectively.
Low-medianairflow rate, mid-, and high-
MERV filters for all sites (
No site 12)during the fan-
Only 939 [mode]+ or -]47 CFM(1595 [+ or -]80 [m. sup. 3]* [h. sup. -1]), 988 [+ or -]CFM (1679 [+ or-]84 [m. sup. 3]* [h. sup. -1]), and 888 [+ or -]44 CFM (1509 [+ or -]75[m. sup. 3]* [h. sup. -1]), respectively. The fan-
Only stations 16 and 17 have a much lower airflow rate because they have ECM fans, while other sites have PSC fans. The fan-
Conditions shown in Figure 1 only (A)and (B)
Each site visit was present, but the test site was also measured during the cooling season.
Cooling season measurements account for about 43% of monthly visits, generating 115 total access data sets in cooling mode, 55 visits in residential systems, and 60 visits in light
Business system.
Figure 2 shows the fan and outdoor unit power chart for each system during the cooling season, averaging at low loadand high-
The MERV filter is installed.
The power consumption of the fan and outdoor unit is an important parameter to characterize the energy consumption of the system.
Figure 2 also shows the high-
MERV filter with low
Mervfilter for cooling season.
Each bar representative has 1 to 5 visits installed for a specific MERV category, and the wrong bar representative has a standard deviation from the average. [
Figure 2:
Residential and lighting
The total power of commercial systems is generally equal.
On average, the power consumption of outdoor units accounts for 85% of the power consumption of the entire system, and the power consumption of residential systems accounts for 80%.
Business system.
Most of this difference is due to light.
The power of the commercial system fan has increased by about 40%, while on average its airflow rate is about 35% higher than that of the conventional site.
The airflow rate of the median system in high cooling mode is about 9%
Install the MERV filter for verslow-MERV filters.
Site 13 is the only system with high traffic.
The MERV filter is installed, most likely because of the low
The Mervfilter is installed when the system usage is high, and the filter is finally loaded enough to have a greater pressure drop than at any time.
As shown in Figure 1, The MERV measurement for this site (B).
It can be time-consuming in evaluating the system. In addition to the power consumption of outdoor units and fans, the system operation time and cycle length are also important.
Residential and lighting
Commercial systems perform similarly when the termsof system is running.
The average cycle length of residential and light residential buildings is about 8 minutes
Business system.
Commercial sites show greater changes and longer running times, but residents and lights
Business Systems usually perform similarly.
About 25% of the recording cycles are less than 6 minutes, and since they have a shorter response time than the temperature and relative humidity sensors, they have to learn from some analysis.
Research Question 1: What is the impact of filtration efficiency on measurement parameters?
The purpose of this analysis is relatively low. MERV, mid-MERV, andhigh-
MERV filter to understand how filter efficiency affects parameters related to energy use in the test system.
Table 3 shows dependent variables that filter for statistically significant differences between MERV categories.
Table 3 the effect of filter efficiency on measured variable 3 also shows the median percentage difference and Median absolute difference between each filter type, as well as the number of systems used in the statistical test n.
Comparison between Midand high-
The MERV filter is not shown because the only significant difference in the fan
Only mode is a slight change in the leakage of the pipe, and only two or three sites can be compared in the cooling mode.
No significant difference between Midand low-
Probably because the sample size is small, MERV is filtered in cooling mode.
Results in Table 3 show, high
The MERV filter is about 45% larger than the low pressure dropMERV filters. High-
Mervfilter reduces the median airflow rate in the fan by about 4%
Cycle only and 10% in cooling mode relative to low temperatureMERVfilters. High-
The MERV filter reduces fan power consumption by about 1% in the fan
Only mode and 4% in cooling mode relative to lowMERVfilters.
The final result of the change in airflow and fan power is
The volume airflow capacity provided by the MERV filter in the fan is reduced by about 4%
Only mode in cooling mode, less than 5%.
The flow of supply and return pipe leakage is a falling resentment
Although the magnitude of these changes is small, they are not always significant.
Higher reduction in traffic-
Efficiency filters are often consistent with the reduction in traffic measured by Parker et al. (1997).
During the cooling time, the average reasonable capacity of the outdoor unitpower painting was not statistically significant, and the monthly and2 % was reduced.
MERV filter relative to low levelMERV filter.
The reduction in reasonable capacity and outdoor unit power consumption is usually consistent with the value of 10% reduction in flow in the literature.
The reduction in fan power consumption, outdoor unit power consumption, and pipeline leakage may reduce the energy consumption that increases with the decrease in cooling capacity, although the reduction in measurement is close to the range of instrument uncertainty, especially among fansonly mode.
All non-related variablesfan-
Only part of the energy performance of the air conditioner, including the cooling capacity and the power consumption of the outdoor unit, does not show a statistically significant difference between the filters, so it is not reported in Table 3.
One limitation of this analysis is that the cooling mode test does not take climate and behavioral conditions into account.
Enter the wet outdoor temperature and evaporator
As we all know, bulb temperature is two climatic conditions that affect capacity, power consumption and system running time.
The thermostat setting of the household is also a behavioral parameter that affects the energy consumption of the air conditioner.
Since these conditions are beyond control in field testing, a hierarchical analysis was conducted to try to isolate their effects from those that may be attributed to changes in the filter MERV category.
Binned analysis compared data from 6 and 12 ranges of similar outdoor dry ball and indoor wet ball entry conditions, and no significant relationship was found, although this may be due to the fact that in the same outdoor and indoor conditions, it is rare to compare two different filters on the same site.
We have some confidence that there is no significant relation nora deviation in the cooling mode data, as the filter type is only weakly correlated with the outdoor temperature.
Median outdoor drying
Bulband evaporator entering wet-
System with low bulb temperature
MERV filter operation is about 2. 5[degrees]F(1. 4[degrees]C)and 0. 9[degrees]F (0. 5[degrees]C)
Respectively higher than the record-MERV filters.
In addition, the non-parametric extension of Wilcoxon rank-
Sum test shows that there seems to be a beno statistical trend in the outdoor temperature of the MERV category, indicating a low
MERV filter and high
The MERV filter is installed under similar outdoor temperature conditions.
However, the same test also revealed a significant but slight obvious trend in entering wet bulb temperatures in the MERV category.
This can cause deviations to the thermostat settings, and the temperature is low
Mervfilter is installed in higher thermostat settings or higher indoor wet periods
Light bulb temperature, although very small.
Repeated testing with the same MERV filter at the same location did not statistically differ in the filter pressure drop, but did reveal some significant differences in the fan
Only schema parameters.
In the filter MERV repeat, the median fan power is reduced by 3% and the median airflow is reduced by about 5%. Supply-and return-
The pipeline leakage flow has increased by 26%.
These values are similar to the size of the effect shown in Table 3, so the effect of filtration efficiency on energy
The relevant parameters are usually small enough to meet changes in filters, installations, and other factors.
Therefore, the actual energy impact of the filter MERV may also be small.
Study Question 2: How is the filter pressure drop directly related to the measurement parameters?
The purpose of this analysis is to standardize the pressure drop of filters in each system, regardless of the MERV category, and to see how the pressure drop affects parameters related to energy consumption.
The analysis ignores sites 9 and 12 because only the return pressure drop was measured at the site (
Not really filter pressure down).
Normalization method for each dependent variable and independent variable (1)
Minus low with clean-
MERV is filtered out from the average variable measured on monthly access and (2)
Separate mean variables with clean low measured mean variablesMERV filter.
Table 4 summarizes important results and shows the regression slope of all statistically significant changes in dependent variables, based on the upper and lower limits of the 95% confidence interval, and the number of data points (i. e.
, Visit every month)
, N, for regression.
A slope is considered significant ([alpha]
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