Estimating Energy Savings with Lighting Controls

A survey of two groups of professionals describing themselves as electrical contractors and energy consultants, conducted by the Lighting Controls Association from its lightingCONTROL newsletter database, suggests automatic lighting controls are becoming more popular in lighting retrofits. Respondents reported lighting controls were considered in over 50 percent and installed in over 30 percent of their projects in 2012. Forty percent of respondents said the percentage of their projects in which controls were installed was higher than the previous year, while about half reported it as the same.

Estimating energy savings resulting from installation of more-efficient light fixtures and lighting systems is fairly straightforward, being based on the difference in wattage. Estimating energy savings for lighting controls, however, can be challenging, as actual savings will depend on application characteristics such as occupant behavior, building design, site orientation, availability of daylight, device settings and level of commissioning. This variability presents risk, which can make owners balk at investment.

The cost savings impact of time-based automatic shutoff can be relatively simple to determine, with the major difference between System A and System B being not wattage, but operating hours. If these numbers are known, energy savings can be estimated fairly reliably. The average respondent to the Lighting Controls Association survey reported that intelligent (programmable scheduling) control was installed in about 30 percent of their lighting retrofit projects in 2012. Similarly, the economic value of institutional task tuning, in which the light level needs in different areas of a space can be satisfied via dimming for associated energy savings, can be fairly straightforward to predict.

Other automatic control strategies, from occupancy sensing to daylight harvesting, pose some uncertainty, being dependent on factors such as variable occupancy patterns and daylight availability. According to the Lighting Controls Association survey, the average respondent reported that wall-switch and “other” occupancy sensors were installed in more than 60 percent and 40 percent of their firm’s lighting retrofit projects, respectively, in 2012. Light sensors for daylight harvesting, meanwhile, was installed in more than 30 percent of their projects.

Making things more challenging, particularly in new construction, is the current trend toward more sophisticated lighting control systems in which strategies may be layered. For example, an open office may see deployed scheduling or zoned occupancy sensors for automatic shutoff, task tuning in some areas, daylight harvesting near windows, and personal dimming control for occupants.

According to the Lighting Controls Association survey, about 40 percent of respondents said they most often base their lighting control energy savings estimates on their evaluation of the application or personal experience.

What other resources are available that can help with strategies that involve a higher degree of variability?

There are several paths may be taken: trial installations, manufacturers, benchmarks, industry research and energy codes.

The trial installation is one of the most useful ways to predict energy savings. In this case, a partial installation is conducted in a typical space to produce data suggestive of typical energy savings. For spaces in which occupancy sensors may be appropriate, some manufacturers offer light loggers, which can be installed to generate data about how long the lights are left ON while the monitored space is unoccupied. Unfortunately, this opportunity is not always available; only eight percent of respondents in the Lighting Controls Association survey said they most often base energy savings for lighting controls on trial installations.

Manufacturers are another useful resource as they have a great deal of experience and may have hard data for monitored projects. Note their estimates and case study results are likely based on control systems designed to produce optimal results. Twenty-one percent of the survey respondents favor this method.

Benchmarks provide a guidepost of what others have achieved, and therefore can be useful; these can be learned through networking with industry colleagues and reading case studies in trade magazines and other media.

Another good source of information is industry research studies evaluating various control strategies. Eighteen percent of respondents to the Lighting Controls Association survey most often base their energy savings estimates for lighting controls on these studies, which may present demonstrated energy savings in a typical application, best estimates of average savings, or best estimates of savings potential (see Tables 1 and 2). Because these studies represent credible independent research, owners making investment decisions may regard them with a higher degree of confidence.

Table 1. Sampling of industry research indicating demonstrated, estimated or potential lighting energy savings for various control strategies and environments. Source: Lighting Controls Association.

Space Type	Controls Type	Lighting Energy Savings Demonstrated in Research or Estimated as Potential	Study Reference
Private Office	Occupancy sensor	38%	An  Analysis of the Energy and Cost Savings Potential of Occupancy Sensors for Commercial Lighting Systems, Lighting Research Center/EPA, August 2000.
	Multilevel switching	22%	Lighting Controls Effectiveness Assessment, ADM Associates for Heschong Mahone Group, May 2002.
	Manual dimming	6-9%	Occupant Use of Manual Lighting Controls in Private Offices, IESNA Paper #34, Lighting Research Center.
	Daylight harvesting (sidelighting)	50% (manual blinds) to 70% (optimally used manual blinds or automatic shading system)	“Effect of interior design on the daylight availability in open plan offices”, by Reinhart, CF, National Research Council of Canada, Internal Report NRCC-45374, 2002.
Open Office	Occupancy sensors	35%	National Research Council study on integrated lighting controls in open office, 2007.
	Multilevel switching	16%	Lighting Controls Effectiveness Assessment, ADM Associates for Heschong Mahone Group, May 2002.
	Daylight harvesting (sidelighting)	40%	“Effect of interior design on the daylight availability in open plan offices”, by Reinhart, CF, National Research Council of Canada, Internal Report NRCC-45374, 2002.
	Personal dimming control	11%	National Research Council study on integrated lighting controls in open office, 2007.
Classroom	Occupancy sensor	55%	An  Analysis of the Energy and Cost Savings Potential of Occupancy Sensors for Commercial Lighting Systems, Lighting Research Center/EPA, August 2000.
	Multilevel switching	8%	Lighting Controls Effectiveness Assessment, ADM Associates for Heschong Mahone Group, May 2002.
	Daylight harvesting (sidelighting)	50%	Sidelighting Photocontrols Field Study, Heschong Mahone Group, 2003.

The problem with industry studies is the broad range of numbers can be difficult to interpret, as different studies may present very different results. For example, a 2003 Lighting Research Center study in two New York City buildings demonstrated 53-60 percent energy savings for bilevel stairwell lighting using an occupancy sensor integrated into the fixture. A later Lawrence Berkeley National Laboratory study in four California buildings demonstrated 40-60 percent energy savings for this approach. And a Pacific Gas & Electric study at The Fillmore Center in San Francisco demonstrated 66 percent energy savings.

In an attempt to simplify things, in 2011, the Lawrence Berkeley National Laboratory published A Meta-Analysis of Energy Savings from Lighting Controls in Commercial Buildings (http://efficiency.lbl.gov), an analysis of 240 energy savings estimates from 88 papers and case studies, focusing on actual field installations as opposed to simulations. From this data, LBNL produced best estimates of average lighting energy savings for four primary lighting control strategies:

• Occupancy-based control (occupancy sensors, time scheduling): 24 percent
• Personal tuning (occupant control of light levels using dimmers, wireless switches, workstation-specific control, preset scene control): 31 percent
• Daylight harvesting (photosensors): 28 percent
• Institutional tuning (light levels tuned to space needs by application, reduction of ballast factor, task tuning, lumen maintenance, group controls): 36 percent
• Multiple strategies (any combination of the above): 38 percent

Table 2. LBNL best estimates of average lighting energy savings for various control strategies based on a review of 240 energy savings estimates published in 88 papers and case studies. Source: Lawrence Berkeley National Laboratory, 2011.

Strategy	Definition	Examples	Average Savings
Occupancy	Lighting status changes automatically based on presence of people	Occupancy sensors, timeclocks, energy management system	24%
Personal Tuning	Occupant control of light levels	Dimmers, wireless switches, workstation-specific control, preset scene control	31%
Daylight Harvesting	Lighting status changes automatically based on daylight levels	Photosensors	28%
Institutional Tuning	Light levels tuned to space needs by application, ballast tuning (reduction of ballast factor), task tuning, lumen maintenance, group controls	Dimmable ballasts, and dimmers and switches used to control group lighting	36%
Multiple Strategies	Any combination of the above		38%

While these estimates are meaningful, some oversimplification may have occurred. For example, occupancy sensors and time scheduling have been documented as producing markedly different levels of energy savings. And available research suggests bilevel switching can produce higher energy savings than personal dimming control.

Finally, energy codes may provide useful guidance that owners may accept because, like industry research studies, it too comes from a respected independent authority. Both the ASHRAE/IES 90.1-2010 energy standard and the California Title 24-2013 energy code identify “advanced” control options that can be installed in exchange for a higher interior lighting power allowance calculated using a power adjustment factor. This factor is suggestive of energy savings for the given strategy over its controlled lighting load.

For example, if occupancy sensing is installed in a large open plan office, and each sensor’s controlled area is 125 sq.ft. or smaller, the power adjustment factor if 0.40, which is suggestive of 40 percent estimated energy savings. A multiscene programmable dimming system in a restaurant, meanwhile, has a factor of 0.20, suggested of 20 percent savings.

Table 3. Excerpt from Table 140.6-A, Lighting Power Density Adjustment Factors in California Title 24-2013. Source: California Energy Commission.

 

TYPE OF CONTROL		TYPE OF AREA		FACTOR
Partial-ON Occupant Sensing Control		Any area <250 sq.ft. enclosed by floor-to-ceiling partitions; any size classroom, conference or waiting room		0.20
Occupant Sensing Controls in Large Open Plan Offices		In open plan offices >250 sq.ft.,: One sensor controlling an area that is:	< 125 sq.ft.	0.40
			126 to 250 sq.ft.	0.30
			251 to 500 sq.ft.	0.20
Dimming System	Manual Dimming	Hotels/motels, restaurants, auditoriums, theaters		0.10
	Multiscene Programmable			0.20
Combined Manual Dimming plus Partial-ON Occupant Sensing Control		Any area <250 sq.ft. enclosed by floor-to-ceiling partitions; any size classroom, conference or waiting room		0.25

On a final note, achieving energy savings estimates in practice may require commissioning, including a written controls narrative, verification equipment is installed and aimed in accordance with approved documents, programming and calibration, functional testing, Systems Manual, end-user training and a plan for periodic recalibration. In a 2012 study, the Energy Center of Wisconsin re-commissioned daylight harvesting controls in 20 spaces and found energy savings to increase from a median 23 percent to 43 percent.

Estimating lighting control energy savings poses more complexity than with light fixtures and lighting systems, but a number of resources are available to aid in producing estimates that offer confidence.