LEDs & Networked Lighting Controls: Maximizing Adoption, Savings Potential

Hpb 2020 Winter Mellinger Art Lighting Istock Explora 2005

Commercial and industrial (C&I) lighting technologies play a prominent role within utility-sponsored energy-efficiency (EE) programs throughout the United States. Initially, EE programs typically provided incentives for the installation of efficient fluorescent lighting systems as a replacement for less efficient fluorescent and incandescent lighting. In the past decade, the emphasis has shifted to replacing fluorescent and incandescent lighting with LED technologies (also known as solid-state lighting or SSL).

A rapid expansion of available LED products with ever-increasing efficiency has enabled utilities to promote, and their customers to install, energy-saving lighting in nearly any application. This shift often has ancillary benefits such as improved lighting quality (resulting in improved comfort, safety and productivity), longer operational life, and increased operational savings. The estimated current market saturations of various LED product groups are shown in Figure 1.

As the LED revolution has matured, the question of remaining savings potential has been a frequent consideration among EE program administrators. To address this unknown, the DesignLights Consortium (DLC) published a report in July 2018 that provided an estimate of remaining C&I lighting energy savings potential from LED and networked lighting controls.*

Figure 2 shows the key DLC finding that significant energy savings opportunities remain, particularly from indoor LED products and networked lighting controls (NLC).

The DLC analysis evaluated the annual, or first-year, savings potential from C&I lighting measures. This approach aligns with typical EE program convention, allowing the results to be easily understood and compared against EE program portfolio forecasts and plans. However, focusing on annual savings can significantly understate the lifetime benefit that these technologies provide. To accurately evaluate the economic and energy impact, the savings must be considered over the estimated useful life of the measure.

Building upon the DLC analysis from 2018, the Alliance to Save Energy, in partnership with DLC and GE Current, a Daintree company, collaborated to explore the extent to which the benefits of EE programs are underestimated, using traditional evaluation methods. The group investigated the following questions:

  • What measure assumptions are EE programs using for LED and NLC?
  • How are EE programs accounting for lifetime savings?
  • What is the savings potential for C&I lighting product types in terms of lifetime savings?
  • What are the cost effectiveness implications when considering lifetime savings for LED and NLC?
  • To what extent can C&I lighting technologies contribute to peak demand savings?
  • In the context of lifetime and peak demand savings, which C&I lighting technologies have the biggest potential impact?

Technical Reference Manual Research
Utility EE programs often use a document comprising a database of types of EE measures to develop the energy savings characterization for common products and technologies that they promote as “deemed” measures through new construction, prescriptive and/or midstream programs. Typically, this document is referred to as a technical reference manual (TRM).

TRMs provide the algorithms, values and assumptions necessary to calculate energy savings and evaluate measure cost-effectiveness. A review of twelve TRMs/databases from a geographically diverse set of EE programs was performed to understand the various assumptions used for C&I lighting measures (Table 1.)

Networked lighting controls was notably underrepresented with only one-third of the TRMs containing the measure. This technology is still emerging, and it can be difficult to characterize the energy savings from using NLC in general terms.

As a result, many EE programs limit NLC incentives to custom/calculated programs. The 2018 DLC research showed significant remaining energy savings are possible from networked lighting controls, but this potential can only be realized if EE programs can promote the measure through multiple avenues. With a TRM measure, EE programs can more easily and effectively promote NLCs through a broad range of programs.

Measure Lifetime
Measure lifetime, or estimated useful life (EUL), describes the length of time for which energy savings can be counted by an EE program. The average and range of measure lifetimes identified during the TRM analysis are shown in Figure 3.

Measure lifetimes for indoor LED fixtures average approximately 15 years, although several programs claim as few as 10 years for the measure life. Lifetimes assigned to linear replacement lamps are similar to those for linear fixtures. Screw base lamps have the lowest assumed measure lifetime since they tend to have shorter rated lifetimes compared to commercial fixtures, they can be easily removed by a customer, and may be subject to federal standards that would limit the energy savings and/or useful life that a utility can claim.

It is particularly noteworthy that all control measures are assigned shorter measure lifetimes than their fixture counterparts. In all cases reviewed, EE programs treat the control products as an independent measure for the purpose of energy savings and cost-effectiveness calculations. Historically, the reasons for a shorter lighting control lifetime were justified since controls were an add-on measure that in many cases failed (or were disabled) long before the lighting with which they were associated. Poor sensor coverage or placement, unpredictable operation, and incompatibility with fluorescent lighting were common issues.

Networked lighting controls greatly improve upon the earlier generation of controls, and when coupled with LED technology they provide superior performance. Many networked lighting control products are embedded directly within LED fixtures.

There is little reason to maintain the assumption that control measures will have a shorter useful lifetime than the associated LED equipment, but EE programs continue to do so. As a result, it is more difficult for lighting controls to pass a cost-effectiveness test, and the measure may be perceived as a drag on any portfolio that considers lifetime savings or benefits.

Control Savings Factor
Lighting control measures are assigned an energy savings factor (SF), as a percentage of full load hours, to calculate savings within a TRM. The savings factors identified through the TRM research are shown in Figure 4.

Among the programs that include a networked lighting control measure, all reference the DLC networked lighting controls specification and/or use the 47% savings estimate identified by DLC research completed in 2017. It is this higher savings value of 47% that is the basis for the unrealized savings potential.

Lifetime Savings Potential
Most utility EE programs measure and report energy savings in terms of annual (first-year) totals (Figure 5). These are the savings that a measure can be expected to deliver in its first full year of implementation. It is also common practice to reference cumulative annual savings, which is simply the sum of the annual savings over a certain time period such as a three-year plan. Less often, EE programs will measure and report lifetime savings. Lifetime savings more adequately represents the energy and economic potential of a measure, since most measures last far longer than one year.

The lifetime savings analysis leveraged the work already completed for the DLC analysis in 2018—estimating remaining C&I lighting energy savings potential from LED and networked lighting controls—with revisions for an additional year of adoption and the inclusion of measure lifetimes. The resulting lifetime savings potential, summed over the 2020 – 2035 analysis period, is shown in Figure 6.

The lifetime savings potential is an order of magnitude larger than the typical tracking and reporting convention of annual (first-year) savings, since it accounts for the savings over the entire measure life.

The lifetime savings potential by product category is shown in Figure 7. Indoor LED products represent the most significant reservoir of potential savings (43%), followed by outdoor LED (32%) and networked lighting controls (25%). Among specific product types, linear lamps and fixtures far and away offer the greatest lifetime savings potential.

Lifetime Savings Estimate & Adjusted NLC Measure Life
The lifetime savings estimates presented in Figure 7 are based on the measure lifetimes of each component, with separate values applied for the lighting equipment and networked lighting controls as identified in the TRM research.

However, as previously discussed, networked lighting controls and lighting lamps/fixtures increasingly operate as a system. LEDs and NLCs are dependent on each other to achieve the full savings potential, and in some cases are inseparable.

If the assumed measure lifetime for networked lighting controls were adjusted to align it to the lighting equipment with which it is associated, as shown in Table 2, the lifetime savings potential increases by 22%. This adjusted savings value may represent a more realistic estimate of LED and NLC measures operating as a system. Figure 8 compares the 2020 – 2035 cumulative savings potential among annual savings, lifetime savings, and adjusted lifetime savings using the NLC measure life.

With an adjusted measure life, the cumulative lifetime savings potential of networked lighting controls (1,077 TWh, 29% of total potential) nearly equals that of outdoor LED products (1,126 TWh, 30% of total potential). Despite the similar savings potential, an important distinction between the two measures must be considered: the adoption of networked lighting controls is just beginning, while outdoor LED lighting is at or near an apex of adoption and will start to decline in coming years. This fact is critically important for utilities to understand so that programs can be appropriately designed to focus on areas of growth.

Peak Demand Savings
Electricity is measured in terms of consumption (energy) and demand (power). Electricity consumption represents the power used over time, measured in kilowatt-hours (kWh); reductions in electricity consumption through energy efficiency are also measured and reported on in kWh. Electricity demand represents the instantaneous power required to meet the electrical loads of the utility, measured in kilowatts (kW). Peak demand represents the highest electric power demand over a time period (month, year, summer, winter, etc.). An illustration of consumption, demand, and peak demand is shown in Figure 9.

Why Peak Demand Matters
Peak demand determines the maximum power plant capacity necessary to serve a utility’s service territory and is therefore a critical factor in reducing the environmental and economic impacts of energy. Energy produced and purchased at the time of system peak is typically the most expensive energy a utility will face, due to supply constraints, and those costs are ultimately passed on to customers. Furthermore, the additional energy required to meet demand during peak periods often comes from the least clean power sources, such as oil and gas “peaker” power plants. Therefore, measures that reduce peak demand can have profoundly positive economic and environmental benefits.

Peak Demand Reduction Through Energy Efficiency
Measures that reduce energy through efficiency can also deliver peak demand savings, but not always. Since peak demand occurs during specific timeframes and seasons, the overlap of an energy efficiency measure with that timeframe matters. For example, LED street lights save energy during the night, and summer peak demand typically occurs during the afternoon, so the energy savings from LED street lighting is unlikely to have any impact on summer peak demand. Off-peak savings are still important and can provide economic and environmental benefits, but not to the same degree as on-peak savings.

How much a measure overlaps with peak demand is called coincidence. EE programs assign all measures a coincidence factor (CF), often for both winter and summer seasons; as an example, Table 3 shows the CFs used in the Massachusetts TRM. These coincidence factors, when combined with a measure’s actual (or estimated) total demand savings, are used to estimate the impact that a measure has on peak demand for the associated season.

Peak Demand Analysis
Using the average coincidence factors identified in the TRM research, summer peak demand savings potential was estimated for commercial lighting measures. These results are shown in Figure 10, with light blue representing full demand savings and dark blue representing peak demand savings potential. In the context of summer peak, indoor LED lighting and networked lighting controls are far and away the most important commercial lighting measures going forward for EE programs, and the best way to achieve both measures is to promote LED + NLC as a system. A program that relies on separate measures is bound to strand savings potential when LED is installed absent controls.

By 2035, the cumulative summer peak demand savings from C&I lighting totals 37,111 MW. Putting this summer peak savings potential in context, the installation of indoor LED and networked lighting control measures between 2020 and 2035 could displace seventy-four 500-megawatt power plants, or 5% of the generating capacity of the entire fleet of U.S fossil fuel power plants, as of 2017 (Figure 11).

The research project highlighted a concern that EE programs may be using overly conservative assumptions, especially for lighting controls. We cannot expect to accelerate the adoption of networked lighting controls if utilities can’t account for the savings properly and if the measure isn’t reflected in TRM documents. Treating LED and NLC as a system can improve cost effectiveness, since the NLC lifetime savings increase by 22%, and can limit the risk of stranding savings when LED is installed without controls. Additionally, combining LED and NLC enables integration with other building systems (e.g., HVAC), which can deliver even greater savings.

Based on the insights identified during this research project, the following actions are recommended to maximize the adoption (and lifetime as well as peak savings potential) of commercial LED and networked lighting controls:

  • The assumed measure lifetime for networked lighting control measures should be consistent with the lifetime of indoor LED fixtures.
  • A measure characterization for networked lighting controls is needed within all TRMs.
  • A system characterization for LED lighting systems and networked lighting controls within TRMs would minimize cost effectiveness challenges; maximize annual, lifetime and peak savings; limit stranded savings; and enable integration with other building systems.
  • EE programs should evaluate program design opportunities and incentive strategies that promote LED lighting and networked lighting controls as a system. Not only will this place program design in alignment with current practices while maximizing savings, but it establishes a foundation for more advanced system-level interests such as grid-interactive efficient buildings (GEB). •

*“Energy Savings Potential of DLC Commercial Lighting and Networked Lighting Controls,” available at https://www.designlights.org/resources/energy-savings-potential-of-dlc-commercial-lighting-and-networked-lighting-controls/
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† While lamps can achieve long life comparable to a fixture, the ENERGY STAR qualification requirement for most incentives programs requires a minimum of 15,000 hours for LED lamps compared to the DLC requirement of 50,000 hours for LED fixtures. https://www.energystar.gov/sites/default/files/ENERGY%20STAR%20Lamps%20V2.1%20Final%20Specification.pdf. https://www.designlights.org/solid-state-lighting/qualification-requirements/
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‡“Energy Savings from Networked Lighting Control (NLC) Systems,” available at https://www.designlights.org/lighting-controls/reports-tools-resources/nlc-energy-savings-report/
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About the Author
Dan Mellinger, P.E., LC,
is a senior consultant at Energy Futures Group, Hinesburg, Vt.