### To: Anthony Balducci, DOE

From: Diane Fisher and Isaac Turiel, LBNL Subject: Distribution of Green Lights ballasts vs. operating hours, and Xenergy ballasts vs.

operating hours. Date: April 1, 1998
Introduction 

### This memo explains how distributions of the fraction of ballasts vs. annual operating hours were derived, using two different data sets, one from EPA's Green Lights program, and the other from Xenergy, a private firm which conducts energy audits. We are looking at the Green Lights Program to gain some insight into the range of operating hours found for fluorescent lamp ballasts in facilities which participate in voluntary lighting energy efficiency programs. Ideally, we would like to compare this distribution to the distribution of lighting hours for commercial fluorescent ballasts in all commercial buildings. However, the only source of such data we have been able to find' is dated (it's based on 1986 CBECS data), and uses a method for calculating lighting operating hours which is different from our method and may not be directly comparable. We are therefore using the Xenergy database as described below. Data Sources Xenergy, Inc., conducts energy audits of buildings at the request of either the building owner or the local utility. We obtained an extract of Xenergy's database of its audits in late January of 1995. The data obtained were for 1979 through early 1995. We used data from 1990-1995. The extract aggregated the data to the 3-digit zip code level and for each zip code included the number of buildings, building types (e.g. office, industrial, etc.), the quantity of fixtures installed by equipment types, lamps per fixture, and the average weekly lighting operating hours for each equipment type. 

### We obtained an extract of EPA's database on its Green Lights program in late August of 1997. This database is based on reports submitted by Green Lights program participants on completed upgrades. The data obtained were for the beginning of the program in 1990 through July 1997. Data were reported separately by project and by fixture type and included the facility type (e.g. office building, industrial), upgrade type (e.g. reballasting, relamping, delamping, etc.), lamp type, ballast type, fixture quantity, lamps per fixture, lamps per ballast, lamp watts, and lighting operating hours.

'EIA (1992) Lighting Consumption in Commercial Buildings

. Energy Information Administration, U.S. Department of Energy, Washington DC. DOE/EIA 0555(92)/1. 

# )
MEMO#c2-

To: Anthony Balducci, DOE 

### From: Diane Fisher and Isaac Turiel, LBNL 

### SUbject: Distribution ofGreen Lights ballasts vs. operating hours, and Xenergy ballasts vs. operating hours. 

### Date: April 1, 1998


### Introduction This memo explains how distributions ofthe fraction ofballasts vs. annual operating hours were derived, using two different data sets, one from EPA's Green Lights program, and the other from Xenergy, a private firm which conducts energy audits. We are looking at the Green Lights Program to gain some irisight into the range ofoperating hours found for fluorescent lamp ballasts in facilities which participate in voluntary lighting energy efficiency programs. Ideally, we would like to compare this distribution to the distribution oflighting hours for commercial fluorescent ballasts 

### in all commercial buildings. However, the only source ofsuch data we have been able to find! is dated (it's based on 1986 CBECS data), and uses a method for calculating lighting operating hours which is different from ourmethod and may not be directly comparable. We are therefore using theXenergy database as described below. 

### Data Sources Xenergy, Inc., conducts energy audits ofbuildings at the request ofeitherthe building owner or the local utility. We obtained an extract ofXenergy's database ofits audits in late January of 1995. The data obtained were for 1979 through early 1995. We used data from 1990-1995. The extract aggregated the datato the 3-digit zip code level and for each zip code included the number ofbuildings, building types (e.g. office, industrial, etc.), the quantity offixtures installed by equipment types, lamps perfixture, and the average weekly lighting operating hours for each equipment type. We obtained an extract ofEPA's database on its Green Lights program in late August of 1997. This database is based on reports submitted by Green Lights program participants on completed upgrades. The data obtained were for the beginning ofthe program in 1990 through July 1997. Datawere reported separately by project and by fixture type and included the facility type (e.g. office building, industrial), upgrade type (e.g. reballasting, relamping, delamping, etc.), lamp type, ballast type, fixture quantity, lamps perfixture, lamps per ballast, lamp watts, and lighting operating**h~urs.**

!EIA (1992) Lighting Consumption in Commercial Buildings. Energy Information Administration, U.S. Department ofEnergy, Washington DC. DOEIEIA 0555(92)/1.

### Page 2

April 1, 1998 Derivation of Distributions 

### The distributions from the two data sets were derived in very similar ways. In both data sets, the number of ballasts is not reported directly, but can be estimated based on other quantities. In the case of the Xenergy data, we used the number of fixtures and the. number of lamps per fixture to approximate the number of ballasts using the following assumptions: For electronic ballasts, we assumed that the number of ballasts was equal to the number of fixtures. For magnetic ballasts, we assumed that fixtures with 1 or 2 lamps per fixture contained one ballast per fixture, and that fixtures with 3 or 4 lamps per fixture contained 2 ballasts per fixture. The Green Lights data included the fixture quantity, the number of lamps per fixture, and the number of lamps per ballast. We calculated the number of ballasts per fixture by dividing the number of lamps per fixture by the number of lamps per ballast. We then multiplied ballasts per fixture by fixture quantity to obtain the ballast quantity for each record in the database. In a small number of records in the database, the number of lamps per ballast was not reported. In these cases, we used the number of fixtures and the lamps per fixture to estimate the number of ballasts, using the same assumptions described above for the Xenergy dataset. For each data set, we used information on technology types to group the ballasts into those which operate 4-foot lamps, 8-foot lamps, and 8-foot high output (HO) lamps. Ballasts that did not fit into these three categories were classed as "other". Since the Xenergy data included information about lamp lengths, separating ballasts into these three categories was straightforward. Since the Green Lights data did not report lamp lengths, we used the reported lamp types (e.g. T8, T12 slimline, etc.) and lamp watts to assign lamps and the ballasts which operate them into the three categories. For the Green Lights data, we included only new electronic ballasts installed in the retrofit, i.e. we did not include data for fixtures in which only the lamp was changed, or other upgrade types which do not result in the installation of a new electronic ballast (e.g. improved controls, delamping). For both data sets, we then summed the number of ballasts in each of 21 lighting operating hour "bins", 0-8 hrs/week, 8-16 hrs/week, etc. (or approximately 0-417 hrs/year, 418-834 hrs/year, etc.). We did the sums separately for each facility type, and for each of our three ballast categories (4ft, 8ft, and 8ftHO). We then combined the results for all commercial ballasts together, and in the case of the Xenergy data we weighted the results for each facility type by the square footage of that building type in the CBECS survey.' We then divided the number of ballasts in each bin by the total number of ballasts to get the fraction of ballasts in each bin. We then plotted the fraction of ballasts vs annual operating hours.

2 Weighting the Xenergy results by the CBECS square footage is done to make the Xenergy results, which we are using as a baseline, more representative of the general population of commercial buildings. Page 2 April 1, 1998 

### Derivation ofDistributions The distributions from the two data sets were derived in very similar ways. In both data sets, the number ofballasts is not reported directly, but can be estimated based on other quantities. Inthe case ofthe Xenergy data, we used the number offixtures and the number oflamps per fixture to approximate the number ofballasts using the following assumptions: For electronic ballasts, we assumed that the number ofballasts was equal to the number offixtures. For magnetic ballasts, we assumed that fixtures with 1 or 2 lamps per fixture contained one ballast per fixture, and that fixtures with 3 or 4 lamps per fixture contained 2 ballasts perfixture. The Green Lights data included the fixture quantity, the number oflamps perfixture, and the

. number oflamps per ballast. We calculated the number ofballasts per fixture by dividing the number oflamps perfixture by the number oflamps per ballast. We then multiplied ballasts per fixture by fixture quantity to obtain the ballast quantity for each record in the database. In a small number ofrecords in the database, the number oflamps per ballast was not reported. In these cases, we used the number offixtures and the lamps perfixture to estimate the number ofballasts, using the same assumptions described above for the Xenergy dataset.
For each data set, we used information ontechnology types to group the ballasts into those which operate 4-foot lamps, 8-foot lamps, and 8-foot high output (HO) lamps. Ballasts that did not fit into these three categories were classed as "other". Since theXenergy dataincluded information about lamp lengths, separating ballasts into these three categories was straightforward. Since the Green Lights data did not reportlamp lengths, we used the reported lamp types (e.g. T8, T12 slimline, etc.) and lamp watts to assign lamps and the ballasts which operate them into the three categories. For the Green Lights data, we included only new electronic ballasts installed inthe retrofit, i.e. we did not include data for fixtures in which only the lamp was changed, or other upgrade types which do not result inthe installation ofa new electronic ballast (e.g. imprOVed controls, delamping).
For both data sets, we then summed the number ofballasts in each of21 lighting operating hour "bins", 0-8 hrs/week, 8-16 hrs/week, etc. (or approximately 0-417 hrs/year, 418-834 hrs/year, etc.). We did the sums separately for each facility type, and for each ofour three ballast categories (4ft, 8ft, and 8ftHO). We then combined the results for all commercial ballasts together, and in the case ofthe Xenergy data we weighted the results for each facility type by the square footage ofthat building type in the CBECS survey. 2 We then divided the number of

. ballasts in each bin by the total number ofballasts to get the fraction ofballasts in each bin. We

then plotted the fraction ofballasts vs annual operatinghours.

2 Weighting the Xenergy results by the CBECS square footage is done to make the Xenergy results, which we are using as a baseline, more representative ofthe general population ofcommercialbuildings.

### Page 3

April 1, 1998 

### Discussion of Results The results are summarized in Table 1 and the distributions are shown in Figure 1. In all cases, the Green Lights distributions appear to be shifted to somewhat higher operating hours than the Xenergy distributions. For 8ft and 8ftHO ballasts, the Green Lights distributions are dominated by a few large peaks. This is because the total number of ballasts are small, and the distributions are dominated by the results for a few large projects. For all cases except 8ft commercial ballasts, the Green Lights distribution includes a large peak at 8760 hours/year (continuous operation) which is not seen in the Xenergy data.. EPA staff are not aware of any reason why this value would be over-reported, and it is not used anywhere as a default. On the other hand, since Green Lights data is self-reported there is a higher probability of error, and there may also be incentives for project managers to make their projects look good (higher lighting operating hours would lead to higher calculated energy savings ). It is also possible that Xenergy data somewhat under-reports fixtures operating at 8760 hours/year. According to their staff, if the lighting hours of most fixtures in a particular area of a building were operating at one lighting hour level (say 60 hrs/week), but a small fraction (say less than 10%) were operating at a different level (say 168 hrs/week, or 8760 hrs/year), it was considered acceptable practice for the auditor to ignore the small fraction and report the same operating hours for all of the fixtures in the area. If most fixtures that operate continuously are located in areas where they are a small fraction of all of the fixtures in that area, such fixtures would b undercounted by Xenergy. If EPA data over-reports or Xenergy under-reports ballasts at 8760 hrs/year, then correcting for this would make the Green Lights averages closer to Xenergy averages. For example, if the 8760 peak is left out of the Green Lights averages, they become, for Oft, 8ft, and 8ftHO ballasts, respectively, 3900, 5200, and 4100 hrs/year. For industrial Oft, 8ft, and 8fHO ballasts, respectively, the averages become 4800, 5600, and 5200 hrs/year. Page 3 April 1, 1998 

### Discussion ofResults The results are summarized in Table 1 and the distributions are shown in Figure 1. In all cases, the Green Lights distributions appear to be shifted to somewhat higher operating hours than the Xenergy distributions. For 8ft and 8ftHO ballasts, the Green Lights distributions are dominated by a few large peaks. This is because the total number ofballasts are small, and the distributions are dominated by theresults for a few large projects.
For all cases except 8ft commercial ballasts, the Green Lights distribution includes a large peak at 8760 hours/year (continuous operation) which is not seen inthe Xenergy data.. EPA staffare not aware ofany reason why this value woUld be over-reported, and it is not used anywhere as a default. Onthe other hand, since Green Lights data is self-reported there is a higher probability of error, and there may also be incentives for project managers to make their projects look good (higher lighting operating hours would lead to higher calculated energy savings). 

### Itis also possible that Xenergy data somewhat under-reports fixtures operating at 8760 hours/year. According to their staff, ifthe lighting hours ofmost fixtures in a particular area ofa building were operating at one lighting hour level (say 60 hrs/week), but a small fraction (say less than 10%) were operating at a different level (say 168 hrs/week, or 8760 hrs/year), it was considered acceptable practice for the auditor to ignore the small fraction and report the same operating hours for all ofthe fixtures in the area. Ifmost fixtures that operate continuously are located in areas where they are a small fraction ofall ofthe fixtures inthat area, such fixtures wouldb undercounted by Xenergy. IfEPA data over-:reports orXenergy under-reports ballasts at 8760 hrs/year, then correcting for this would make the Green Lights averages closer to Xenergy averages. For example, ifthe 8760 peak is left out ofthe Green Lights averages, they become, for 4ft, 8ft, and 8ftHO ballasts, respectively, 3900, 5200, and 4100 hrs/year. Forindustrial 4ft, 8ft, and 8ftHO ballasts, respectively, the averages become 4800,5600, and 5200 hrs/year.Page 4

April 1, 1998 

### Table 1. Average Annual Operating Hours and Ballast Quantities For Xenergy and Green Lights Data.
Xenergy 

### Green Lights Commercial Quantity (000) 1 Operating Hours Quantity (000) 

### Operating Hours 4FT 

### 63601 3600 9085 4300 8FT 572 1 3600 

### 161 5300 

### 8FTHO 85 1 4000 14 4700 Industrial, 4FT 774 4200 673 5800 8FT 

### 306 4000 41 6300 8FTHO 59 5000' 19 5600 

### Page 4 April 1, 1998 

### Table 1. Average Annual Operating Hours and Ballast Quantities ForXenergy and Green Lights Data. Xenergy Green Lights

Commercial Quantity (000) I 

### Operating Hours Quantity (000) Operating Hours 4FT 6360 3600 9085 4300 8FT 572 3600 161 5300 8FTHO 85 4000 14 4700 Industrial 4FT 774 4200 673 5800 8FT 306 4000 41 6300 8FTHO 59 5000 19 56000
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