TABLE 6.1 Estimates for Lighting Electricity Consumption in 2010 by Sector and Technology Type (in terrawatt-hours (TWh) per year)

Residential Commercial Industrial Outdoor All Sectors
Incandescent 136 15 0 4 156
Halogen 12 15 0 1 28
Compacl fluorescent 15 16 0 1 32
Linear fluorescent 10 250 23 10 294
High intensity discharge 0 49 35 98 183
LED 0 3 0 2 5
Miscellaneous 1 0 1 3
TOTAL 175 349 58 118 700

SOURCE: DOE (2012).

TABLE 6.2 Average Efficacy, Power, Daily Usage, and Lamps Per Household in 2010

Incandescent Halogen CFLs Linear Fluorescents HID LED Other
Efficacy (lm/W) 12.1 14.3 52.1 67.3 62.4 40.7 37.5
Average wattage (W) 56 65 16 24 126 11 54
Average usage (h/day) 1.8 1.9 1.8 1.9 2.5 2.1 1.4
Average number of lainps per building 31.8 2.3 11.7 5.1 0 0.1 0.4

SOURCE: DOE (2012).

market applications14 from 100 percent LED replacement is 263 TWh per year. A previous report (Navigant Consulting, 2006) projected that electricity savings from LED adoption by 2027 could be larger than the energy used to illuminate all homes in the United States today (NRC, 2010).

The committee developed its own estimates of energy savings potential that might result from different scenarios for the transition to LEDs for general illumination purposes in the U.S. residential and commercial sectors and outdoor applications. These estimates and their derivation are discussed in the following sections.

Potential Energy Savings for the Residential Sector

Today the residential sector accounts for 39 percent (1,446 terawatt-hours [TWh]) of U.S. electricity use.15 Approximately 12 percent of residential electricity use is to power lights (DOE, 2012). Approximately 78 percent of lighting electricity use is attributable to incandescent lamps. For the committee’s estimates, the baseline assumptions for lighting technology characterization and lighting energy use in the residential sector rely on the 2010 U.S. lighting market characterization from DOE. Estimates from DOE’s market characterization for average efficacy, power, daily usage, and lamps per house in 2010 are shown in Table 6.2 for each technology type.

For the residential sector, it was assumed that usage patterns (hours per day for each technology type) will remain the same during the 2012-2020 time period. This excludes any potential direct “rebound effects”16 associated with lighting energy use or other changes in consumer behavior. It is further assumed that the demand for illumination (measured in lumens) will be proportional to population growth. Using these assumptions, residential lighting use would grow from roughly 173 TWh in 2010 to 187 TWh in 2020 in the base case (Table 6.3), where the base case does not account for the impact of EISA 2007.

The first scenario estimates the impacts of EISA 2007 standards. Given the limits for rated lumen ranges and

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14 Niche-application lighting includes under-cabinet kitchen lighting, under-cabinet shelf-mounted task lighting, portable desk task lights, outdoor wall-mounted porch lights, outdoor step lights, outdoor pathway lights, and recessed downlights, as defined for ENERGY STAR® Program Requirements for Solid State Lighting Luminaires Eligibility Criteria.

15 EIA, 2012, Electricity sales and revenue data: http://www.eia.gov/electricity/sales_revenue_price/index.cfm.

16Rebound effects include the following consumer responses to an increase in energy efficiency. The direct rebound effect means that efficiency gains lead to a lower price of energy services, leading to an expanded or intensified use of the energy consuming products or services. For example, when consumers switch from incandescent lamps to compact fluorescents, they may leave their lights on for more hours than they did previously because their operation costs less. The indirect rebound effect reflects the case where an additional income that is freed up by saving energy costs can be used for other energy- or carbon-intensive consumption. For example, the income gained by installing an efficient furnace and insulating one’s house could be bundled into additional air travel, leading possibly to an overall increase in energy consumption and greenhouse gas emissions (adapted from the definitions in Sorrell, 2010).



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