By Samantha Havassy and Cori Jackson T

RESEARCH

76 LD+A August 2015 www.ies.org

The retail sector, which represents 13 percent of California’s commercial

lighting electricity use, has historically not embraced the use of light-

ing controls. Reasons for this are many including perceived high cost,

system complexity, and the potential for negative impacts on custom-

ers and sales. California building lighting energy-eff iciency standards for the retail

sector have a higher lighting power density allowance and fewer requirements for

mandatory controls in sales areas than other commercial and industrial building

space types. The use of adaptive lighting systems, which automatically adjust their

output and operation based on occupancy, daylight availability and other appli-

cation-specific criteria, are underutilized in the retail sector, leaving a significant

quantity of energy reduction potential unrealized. Retailers who design and apply

an eff ective adaptive lighting control strategy could see a significant reduction in

annual electricity costs and a rapid return on the investment.

Researchers at CLTC are investigating strategies to optimize lighting designs

and lighting control systems in order to maximize energy savings, minimize cost

and reduce potential for negative impacts on business. Work is ongoing; how-

ever, preliminary findings demonstrate several benefits of adaptive lighting and

its ability to meet the needs of the retail sector in California.

To achieve savings, retailers must elect to complete lighting system upgrades;

however, most are hesitant to complete energy-eff iciency projects. A retail market

survey conducted in connection with this research identified several important

factors that influence a retailer’s decision to complete an energy-eff icient lighting

upgrade (Figure 1). Almost half of retailers surveyed stated they would upgrade

their lighting systems if it led to increased sales. Less than 20 percent of those sur-

veyed said they would upgrade their

system if it would only decrease their

electricity cost and not increase sales.

When asked “why” they held reserva-

tions about conducting eff iciency proj-

ects, lack of understanding was cited

as the number one reason. In addition,

53 percent responded that high first

cost was a primary concern regarding

lighting upgrades.

USING WHAT YOU NEED, NOT WHAT’S ALLOWED

To better understand the potential

of updated lighting design and con-

trols optimization in the retail sector,

researchers began by comparing the

illuminance levels resulting from appli-

cation of maximum energy-code light-

ing power allowances to those resulting

from designs conforming to industry

recommended illuminance levels. Il-

luminance levels for both scenarios

were estimated through building simu-

lations. Reductions between that al-

lowed by California’s building eff iciency

standards and that recommended in

modern designs represent clear elec-

tricity savings for retail businesses.

Researchers examined two building

types: a warehouse store and a depart-

ment store (Tables 1 and 2). Three sets

of lighting designs were completed for

each building type. Each set utilized a

diff erent source type and included one

design that utilized the maximum LPD

allowed by 2013 Title 24’s area catego-

ry method for retail merchandise sales

Adaptive Lighting for Retail EnvironmentsBy Samantha Havassy and Cori Jackson

Figure 1: Reservations regarding lighting upgrades - retail business owners.

Source: Consumer Preference Survey on Directional

LED Replacement Lam

ps for Retail Application

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www.ies.org August 2015 LD+A 77

and wholesale showroom areas, and

a second designed to achieve the illu-

minance recommended by the IES. For

both space types, and all sources mod-

eled, the code-based designs used

more energy and provided more light

than was necessary to reach industry

recommended light levels.

For the warehouse store, design-

ing to IES recommended light levels

provides 13-43 percent savings over

code. Savings in the department store

model ranged from 53-60 percent.

OPTIMIZING CONTROLSMany factors contribute to the suc-

cess of control strategies. To maxi-

mize the value of an investment in

adaptive lighting, systems must be

optimized in terms of their operation.

Optimizing control settings such as

sensor time-out periods and the size

of sensor coverage zones is critical

to achieve maximum energy savings.

Researchers completed two studies

to understand how changes in light-

ing control settings aff ect overall

lighting energy use.

Occupancy Time-out and Zoning.

Most occupancy sensors allow us-

ers to select a time-out period, usu-

ally between 0 and 30 minutes, which

controls how quickly luminaires are

extinguished aft er the sensor no lon-

ger detects occupants in the space.

The length of the time-out period has

a direct influence on the energy use of

a lighting system. Systems controlled

Table 2: Department store - Electricity savings potential of an updated retail lighting design as compared to a design using the maximum LPD allowed by Title 24.

Source:CLTC

Table 1: Warehouse store - Electricity savings potential of a modern, retail light-ing design as compared to a design using the maximum LPD allowed by Title 24.

Source:CLTC


RESEARCH


exceed 30 minutes. Savings between a

30-minute time-out period and a one-

minute time-out period, using a zoned

control approach, were found to be ap-

proximately 17 percent.

Modeling Zone Size and Occupancy

Controls. Coverage zone size has an ef-

fect on occupancy sensor performance

with respect to accurate occupant de-

tection. Accuracy translates directly to

energy use. False triggers can increase

lighting energy use, while failure to de-

tect occupants can result in increased

savings but at the expense of light qual-

ity, safety and potentially sales.

To understand the relationship

between sensor coverage area, cov-

erage zone size and energy use, re-

searchers simulated the eff ects of

various sensor zone sizes on lighting

energy use using models developed

from audits of multiple department

stores in Northern California.

Lighting control systems normally

utilize one of two approaches for occu-

pancy sensor coverage. The first is to

use the minimum number of sensors

needed for coverage of the desired

area. With this strategy, one or more

sensors are typically mounted on the

ceiling to create one or more zones of

control. In the second approach, one

sensor is installed in each luminaire to

create multiple, small zones of control,

regardless of any overlap in coverage

area between sensors. These strate-

gies are independent of the number of

luminaires in the space.

Researchers created a model light-

ing plan and operating schedule for a

typical retail department store using

by occupancy sensors with a long

time-out period use more energy

than those controlled by sensors with

short time-out periods. The challenge

in a retail environment, however, is

to reduce frequent switching, which

can negatively impact customers and

sales. This is achieved by lengthening

the time-out period at the expense of

energy savings. To better understand

the tradeoff s associated with the use

of occupancy sensors in retail spaces,

researchers recorded the occupancy

patterns in a typical retail space and

applied varied occupancy time-out

profiles to the data, resulting in a

spectrum of energy use correlated to

occupancy sensor time-out period.

Researchers installed more than 50

light and occupancy data loggers in a

midsized retail store, approximately

12,000 sq ft (Figure 2), to gather infor-

mation on occupancy as compared to

lighting system use. Loggers were set

to record occupancy and light-level

status in one-minute increments for a

period of 30 days. The store sales floor

was broken into 12 zones. Within each

zone, researchers selected one data

logger to represent the zone’s “occu-

pancy sensor.” Researchers compared

the data from all other sensors in the

zone to the “occupancy sensor” in

order to determine the diff erence in

actual occupancy and lighting energy

as compared to that sensed by the “oc-

cupancy sensor.” This data was used to

calculate the percent of ON hours.

This calculation was repeated, ap-

plying increasing time-out periods to

the “occupancy sensor” in order to

map the relationship between time-

out period and lighting energy use.

As the time-out period increased, so

did the percent of ON hours for the

lighting system. For both the absolute

occupancy (that sensed by the zonal

“occupancy sensor”) and the local oc-

cupancy, increases in the time-out

period increased lighting energy use

by up to 30 percent. In California, occu-

pancy sensor time-out settings cannot

Figure 2: Absolute occupancy rates during business (green) and non-business (red) hours with a five-minute time-out.

Source:CLTC

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RESEARCH


prototypical data collected through

on-site audit of three department

stores (Figure 3). Lighting consisted

of general area lighting for sales floors

and walkways, and track lighting for

wall displays and accents. The total

area of the model was approximately

48,000 sq ft . Luminaires simulated

were four-lamp 28-W 2x4 recessed

troff ers for the area lighting, one-

lamp 54-W T5HO recessed wall wash-

ers for decorative lighting and sets of

six 13-W halogen track lights for the

accent, display and feature lighting.

Luminaires were grouped together

into zones under four unique scenari-

os to simulate the eff ects of detected

occupancy and zone size on lighting

energy use. The first zoning scenario

utilized individual luminaire zones,

where each luminaire acted autono-

mously based on occupancy signals

from a sensor installed in the fixture.

The Small Zone grouping included

walkway troff ers and track controlled

in groups of three luminaires, and the

area troff ers controlled in groups of

six. The Medium Zone grouping includ-

ed walkway troff ers, area lighting and

track subdivided into approximately

10 zones. The Large Zone grouping

combined all of the walkway lighting

into one functional zone and subdi-

vided the remainder of the lighting

into four zones or quadrants, creating

a total of five control zones. All lumi-

naires within a zone react in tandem

based on the occupancy stimuli pro-

vided to the zone’s occupancy sensor.

Occupancy profiles were then ap-

plied to the space (Table 3). Through-

out the day, light levels varied to

accommodate diff erent occupancy

events within the store. During stan-

dard business hours, troff ers, walkway

lighting and track lighting dimmed to

20 percent when no store occupants

were detected. Lighting was also re-

duced before and aft er standard busi-

ness hours when employees were re-

stocking or doing other maintenance

tasks. During this time, the wall-wash

lighting remained off and the track

lights turned on only when triggered

by occupants. During all other times,

10 p.m. to 6 a.m., the wall washers and

track remained off and the troff er out-

put was reduced to 50 percent during

occupied periods and 20 percent dur-

ing unoccupied periods.

For each time period, and for each

zoning scenario, a high and low occu-

pancy map was applied (Figure 4). The

highest occupancy areas follow the

main paths within the store (red and

orange). When a zone had two or more

occupancy levels within its borders,

the higher occupancy rate was utilized

for the entire zone.

The use of large occupancy control

zones equated to increased lighting

energy use. Average annual savings

ranged from 13 percent to 23 percent

Table 3: Bi-level light level outputs for various store hours.

Source:CLTC

Figure 3: Zones for department store model.

Source:CLTC


RESEARCH


depending on the control zone size as

compared to the same store without

occupancy controls (Table 4). Control

zone size did not significantly impact

savings when zone size increased be-

yond approximately 500 sq ft .

RETAIL DEMONSTRATION Researchers utilized results from

these analyses as part of a demon-

stration project conducted to assess

the in-situ performance of adaptive

lighting systems in retail environ-

ments. The demonstration space was

composed of approximately 4,300 sq

ft of retail space in a multi-tenant light

commercial building.

The lighting demonstration pack-

age included LED area lighting and

a networked lighting control sys-

tem. The system was designed and

specified such that its performance

Figure 4: Occupancy profiles for high and low volume occupant scenarios.

Source:CLTC

Table 4: Control zone size and energy savings.

achieved IES recommended light

levels for retail applications. Existing

luminaire mounting locations were

maintained in most areas of the store.

Designs met LPD and controls re-

quirements contained in California’s

2013 Building Energy Eff iciency Stan-

dards (Title 24, Part 6). As of the time

of this demonstration, the allowed LPD

for the main retail merchandise sales

area was 1.2 watts per sq ft with two

“use it or lose it” allowances for accent,

display, feature and decorative lighting

for an additional total of 0.5 watts per

sq ft . A sales support area classified as

a general commercial and industrial

work area (in the demonstration, this

is a product repair area) had an al-

lowed LPD of 0.9 watts per sq ft .

Multi-level control strategies were

achieved by using two separate dim-

ming zones, one for the retail space and

another for the shop area. Additionally,

manual dimming did not override other

controls measures such as daylighting

and high-end tuning; however, man-

ual dimming did override scheduled

dimming or OFF periods for up to two

hours. Automatic shutoff control was

achieved through the use of zonal oc-

cupancy sensors and a scheduling

feature included with the digital con-

trol system. Daylighting controls were

also included, but were not required

by code for this alteration. Occupancy

sensors were used to control bi-level

dimming during vacant hours.

System Performance. Energy use

of the new system was monitored in

phases in order to attribute energy

savings to each of the control layers ap-


RESEARCH


Defining ‘Adaptive’An adaptive lighting system automatically adjusts its light output and

operation to provide targeted light levels based on environmental condi-

tions, user schedules or other application-specific criteria. The system can

include many diff erent types of products including dimmable lamps and

luminaires, occupancy sensors, photocontrols, time clocks, communica-

tion panels and wireless communication nodes. An adaptive system can

also oft en be manually tuned, over time, in terms of light level, and in some

cases, color, to provide optimal lighting conditions as designated by sys-

tem operators, building owners or occupants.

plied to the space. During phase one,

tuning, scheduling and occupancy con-

trol were enabled. Data was collected

for two weeks under these control

conditions. In the second phase, task

specific tuning was added. The new lu-

minaires, excluding application of con-

trol measures, saved 52 percent annu-

ally as compared to a Title 24 compliant

lighting system (Table 5). The addition

of bi-level, occupancy-based control

per the schedule resulted in an addi-

tional 10 percent energy savings, or 62

percent total savings annually. Applica-

tion of a 20 percent high-end trim to

tune the system to deliver light levels

consistent with industry recommenda-

tions resulted in a final system savings

of approximately 70 percent.

Applications. Many commercially

available advanced lighting control

systems contain functions and fea-

tures that show potential to bring

significant energy reductions to retail

environments. The projects described

address models and demonstrations

that can be applied to department

stores, warehouse stores, midsized re-

tail and small businesses located with-

in multi-tenant light commercial prop-

erties. Sub-sectors within retail with

specific lighting needs have yet to be

addressed, including restaurant and

grocery applications. While control

strategies will diff er among retail sites,

at a minimum, strategies should utilize

scheduling, high-end trim and occu-

pancy-based dimming. Control zones

and control device settings follow-

ing the guidelines developed through

this project can be expected to show

Table 5: Annual energy savings - retail demonstration site.

1 Based on 3,640 annual hours of use (actual business operating hours).2 Weighted average of 1.7 W/sf in main retail space and 0.9 W/sf in bike repair area.

similar savings results. Demonstration

showed that these recommendations

can result in significant energy savings

as compared to 2013 Title 24 building

energy-eff iciency standards.

For more information on the require-

ments of Title 24, Part 6 2013, visit cltc.

ucdavis.edu/title24 and download the

Retail Lighting Guide.

1

2

Samantha Havassy was an assistant development engineer with CLTC from April 2012 to April 2015.

Cori Jackson is the pro-gram director at CLTC.

THE AUTHORS

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