Conversions + Conversations= Conservation

Joann Hensen is conservation manager of the Grays Harbor Public Utility District in Grays Harbor County, Wash.

Like most utilities in the Northwest, Grays Harbor Public Utility District (PUD) is seeking to meet its future load growth largely through energy conservation programs. While our utility (and indeed the region) has a strong background in weatherization, we have a limited understanding of electrical uses in the home aside from resistance heating.

This is especially true for lighting. Use of compact fluorescent lamps to save energy raises a lot of questions. How many can we install per house? How long on average are lights left on? Will homeowners remove them once the installer leaves? What is the best method of field delivery? These and other questions led us to launch the Grays Harbor PUD Compact Fluorescent Maximization Project (1).

Gray Areas in Grays Harbor

The most perplexing and difficult task of the study was to gain an understanding of how much electricity a typical Northwest family uses each year for lighting.In the Northwest, electrical use for lighting has most often been grouped with "miscellaneous" and "other" on the pie charts that demand-side planners carve up to depict the electrical usage of the average homeowner. The slice for lighting-if it has its own slice-usually represents 750Ð 1,500(killowatt-hours) per year, very small in comparison to space heat and water heating.

Usually these estimates are based on metered data for water heating and electric space heating subtracted from the house total electrical use. The balance is then divided up amongst the other uses such as appliances, lighting, water beds, and others. Complicating the issue further is a situation where the total lighting load is comprised of both hard-wired lights and plug-in fixtures. In addition, very few circuits are dedicated only to lighting, making sub-metering impossible.

Towards a better understanding of this issue, a large part of the project was designed to establish a baseline for residential lighting energy use. Specifically, the project analyzed existing installed wattages, watts per square foot by room type, and actual lighting use for six homes over a seven month time period.

The Maximization Study is a lighting product placement field study involving 19 homes, chosen on the basis of interest shown by the participants, in the town of Aberdeen in Grays Harbor County, Wash. The study, which is continuing, was a collaborative effort involving the Grays Harbor PUD, Delta-T Inc., and the Washington Energy Extension Service (2). The Bonneville Power Administration funded the project and Pacific Power loaned the light loggers used to monitor lighting.

Installers made initial house visits during the month of November 1991. Homeowners agreed to allow them to convert, at the homeowners' discretion, as many incandescent lamps as possible to compact fluorescents, and allowed the installers to collect data concerning the existing lighting. In each retrofit, consumer education and homeowner involvement, a critical component, was an integral part of the design of this project. Education included discussions that provided information about the characteristics of compact fluorescent lighting such as flickering, warm-up times, and color rendering.

The occupants' annual income range was $12,000-$60,000. Young singles, couples with children, single parents, couples with teenage children, empty nesters, and retired couples participated, with education levels ranging from high school to graduate school. The housing types ranged from a 70-year-old farmhouse to those meeting the new energy codes, from some built in the '40s and '50s and since remodeled to one mobile home, from spec-built homes to custom ones, two units of a duplex, and one unit of a fourplex apartment building. The floor area without the garages averaged about 1,600 ft2.

The project utilized 16 different styles and wattages of compact fluorescent lamps. These included lamps with magnetic as well as electronic ballasts. The installers always followed one simple guideline: They made sure the conversion produced equal (or greater) light levels than the existing incandescent, in the eyes of the homeowners. They used light meters to double-check the light levels before and after installations, and to convince homeowners that they weren't surrendering lumens in the change-outs. Using this approach, the project maintained a retention rate of 100% after six months.

In the course of making visits, the installers selected the homes of six particularly enthusiastic participants for light usage monitoring. The homeowners periodically reported the read-outs from the light loggers. The primary incentive for participation was free replacement of incandescent lights with compact fluorescents.

Shedding Light Usage

The project proved very successful at converting sockets from incandescent lamps to compact fluorescents, (see Table 1). Numbers for lighting wattages are based on manufacturer ratings. The researchers tabulated field data according to fixture type and room type. The fixture type that showed the greatest drop in installed wattage was the bare bulb, showing a decrease of 67%. The other fixture types where installed wattage dropped more than 50% were open ceiling fixtures, porch lamps, and yard lights. The fixtures with the lowest conversion rate-below 40%-were floorlamps, track lights, closed ceiling fixtures, and chandeliers.

Room by Room
The houses in this study averaged about 2,000 ft2 including garages, with an average of 11.5 rooms. Of these, an average of 8.1 rooms had at least one socket retrofitted. The houses were divided into ten different types of rooms, plus two exterior lighting areas. In addition to pre- and post-retrofit wattages, researchers calculated wattages per square foot, largely to establish a benchmark (see Table 2.) Bathrooms had by far the highest watts per square foot ratio of any room type. And the installers were most successful lowering the installed wattage in bedrooms.

Burn Time
In the six houses selected for monitoring, the installers placed 68 light loggers for 68 light fixtures, with 10-17 fixtures per house monitored. They originally attempted to monitor all lights in the house, but due to limitations of the light loggers, this was not possible. The light loggers were sensitive to daylight entering the house through windows. Safety and aesthetic concerns also limited the number of fixtures that could be monitored. Because of the sensitivity to daylight, no outside fixtures and only some indoor fixtues were monitored. The loggers collected data from late November 1991 to July 1992. The summary of data to date can be found in Table 3.

Due to light loggers not recording properly, daylight interference, and homeowner monkey wrenching, the number of useable data points varied each month. In some cases, homeowners had to mount ladders to read the displays on light loggers. In awkward circumstances like these, they sometimes repositioned the loggers in ways that prevented light from hitting the photodiodes. Also, because of the changing angle and duration of sunlight entering rooms from November to July, some loggers unexpectedly began registering on- time. A few loggers malfunctioned, while the velcro on others couldn't compete with gravity, and fell down. (One such logger fell onto a light, became lodged on a light fixture, and melted.)

For this study, logistical problems didn't allow logger placement at every fixture, a problem that could be overcome in future studies by utilizing more accurate CRT data loggers to monitor lighting energy use rather than light on-time duration. And utility personnel replacing homeowners for data collection could likewise provide more reliable readings.

The highest number of useable data points was 62 for the first month and the lowest was 42 for April. In addition, because the sample sizes for individual rooms and fixture types are so small, no statistically valid conclusions can be made concerning on-time factors for a particular room or fixture type. (See box, "Not Without Bias.")

Using the average installed lighting wattage of 2.7 kW and the average on-time of 2.5 hours per day, it is possible to extrapolate annual pre-retrofit lighting kWh use. This extrapolated average is about 2,500 kWh per year. Using the retrofitted house installed wattage of about 1.6 kW annually, the annual total lighting energy use after retrofit would be 1,400 kWh. This represents a savings of about 1,000 kWh per year.

Now What?

This of course is a very simplistic analysis of annual energy use. Actual usage would vary fixture by fixture. Nevertheless, the annual energy use numbers here are much larger than the conservation industry or utilities have typically assumed or estimated. It is important to remember that these fixtures were not randomly selected from the population as a whole. They represent a subset of fixtures that could be monitored using our light loggers. As discussed earlier, the homes themselves were not randomly selected, but were largely "self-selected."

These rates may be lower than we can expect because of the volunteers' energy-conscious behavior. Future studies with larger samples will tell us more about regional differences in lighting use patterns. (Editor's Note: The on-time hours reflected in this study are in fact higher than those found in a study now in progress. The Lighting Resource Center at Ressalear Polytechnic Institute will publish the results next year as Efficient Home Lighting Patterns.)

What the numbers do tell us is that lighting use may be significantly higher than previously thought, and that a comprehensive study that monitored all fixtures in a house is the next logical step. A full year after installation, an energy bill analysis will delineate the base load, supplementing the light logger data.

The Maximimazation Study proved that it is possible to convert half a house's fixtures to compact fluorescents. Linked to that is the single most impressive number in the entire study: 0. That is the "snap back effect," the number of compact fluorescent lamps that homeowners took out after six months, out of a total of 421 conversions.

The reason for this rate of success was homeowner education and homeowner involvement. The installer, knowing before the housecall what the use is for a particular fixture and then co-selecting the best conversion, will insure a high retention rate. The results will beat any combination of fancy packaging, brilliant marketing, and technical wizardry.

Based on this project, our utility will be including compact fluorescents in a new residential conservation program that we hope will present more answers to the questions raised at the beginning of this article.

Endnotes

1. "The Grays Harbor PUD Compact Fluorescent Maximization Study" is available from Delta-T Inc; P.O. Box 11622, Eugene, OR 97440. Tel.:(503)995-6105.

2. Collaborators in the study include Dale Dove, Tracy Bennett, and Sue Heiny of Grays Harbor Public Utility District, Mike Nelson and Bill Young of the Washington State Energy Extension Service, and Bruce Manclark of Delta-T Inc.

The homes in this study really constitute 19 case studies more than they do a statistically representative sample group. This type of study can still be useful to compare with other studies. The findings, for usage patterns and for installed wattages, in the Grays Harbor study agree closely with those from a 55-house study by Pacific Power and Light in Yakima, Wash. last year, lending some credence to both studies. (See "Of Sockets, Housecalls, and Hardware," HE Nov/ Dec '91, p. 22)

Gaining access to peoples' homes during work hours is a huge obstacle to obtaining a statistically valid sample. While the telephone numbers called might be random and free of bias, those homeowners who allow a visit are not. Statisticians call this process "self selection." Self selection usually produces a biased sample, even when quotas are used to insure so many from each constituent subgroup are selected.

In the Yakima study, participants were offered $50 to participate. How did this influence the study? Do people who need $50 have different habits and responses than do people who don't? All these issues present statistical challenges for researchers attempting to find a sample whose results can be accurately extrapolated to the entire population. While these case studies can give us snapshots of how people use energy in their homes and tell where to do further research, they are not an unbiased representation of the community as a whole.

- Bruce Manclark

Bruce Manclark is the head of Delta-T Inc., an energy consulting firm, based in Eugene, Ore., and a researcher in the Grays Harbor Public Utility District Compact Fluorescent Maximization Study.

Table 1. Lighting Retrofit Reductions
                                                     Reductions/   Percentage
                          Existing       Converted   Conversions     Change
_____________________________________________________________________________
Total sockets               845             421         424            50%
Average sockets per house   44.5 (45)*       22        22.5            50%
Total installed wattage     52W             30W         22W            42%
Average installed wattage 2.7kW (2.9kW)*   1.6kW       1.1kW           40%
_____________________________________________________________________________
* For comparison, average sockets and installed wattages found in 55 homes
in Yakima, Wash. study by Pacific Power.

              Square feet  Pre-retrofit Post-retrofit Pre-retrofit Post-retrofit           
                 (ft2)       Watts (W)    Watts (W)       W/ft2        W/ft2      Decrease   Percent
Bathrooms        2,000        6,000        3,800           3.0          1.9         1.1        37%
Dining Rooms     1,700        2,100        1,900           1.3          1.1          .2        15%
Bedrooms        10,300       11,800        6,100           1.1           .6          .5        48%
Garages          5,700        2,700        1,600            .5           .3          .2        40%
Family Rooms     1,700        2,700        1,800           1.6          1.0          .6        38%
Hallways         2,100        2,900        1,800           1.4           .9          .5        36%
Kitchens         3,200        6,100        4,500           1.9          1.4          .5        26%
Living Rooms     6,900        7,800        3,900           1.1           .6          .5        45%
Utility Rooms    4,000        4,600        2,100           1.1           .5          .6        54%
Porches                       4,400        2,200      
Yard Lights                     900          400
Whole House     37,600        52,00       30,100          1.4            .8          .6        43%

                            On-time hours
                        Average        Median
______________________________________________
Nov. '91-July '92       2.5 (2.0)*      1.8
January                   2.8           2.5
June                      2.2           1.2
Difference                23%          104%
______________________________________________
* For comparison, on-time found in 55 homes in 
Yakima, Wash. study by Pacific Power.