NEMA LSD 79-2018 Predicted Energy Savings from Lighting Systems.pdf

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1、NEMA Standards PublicationNational Electrical Manufacturers AssociationNEMA LSD 79-2018Predicted Energy Savings from Lighting SystemsA NEMA Lighting Systems Division Document LSD 79-2018 Predicted Energy Savings from Lighting Systems Prepared by: NEMA Lighting Controls Section National Electrical Ma

2、nufacturers Association 1300 North 17thStreet, Suite 900 Rosslyn, Virginia 22209 Approved: February 1, 2018 www.nema.org The requirements or guidelines presented in this document, a NEMA Lighting Systems Division white paper, are considered technically sound at the time they are approved for publica

3、tion. They are not a substitute for a product sellers or users own judgment with respect to the particular product discussed, and NEMA does not undertake to guarantee the performance of any individual manufacturers products by virtue of this document or guide. Thus, NEMA expressly disclaims any resp

4、onsibility for damages arising from the use, application, or reliance by others on the information contained in these white papers, standards, or guidelines. The opinions expressed in this statement represent the consensus views of the member companies of the Lighting Systems Division of the Nationa

5、l Electrical Manufacturers Association. The members of the Lighting Systems Division manufacture traditional technology lamps and ballasts, light-emitting diodes (LEDs and OLEDs), LED lamps and modules, LED drivers and power supplies, luminaires, lighting controls, and management systems. NEMA LSD 7

6、9-2018 Page 2 2018 National Electrical Manufacturers Association CONTENTS 1 Scope 3 2 Purpose 3 3 Energy Savings Calculations . 3 3.1 Energy Consumption 3 3.2 Savings with Respect to Baseline . 6 3.3 Integration with Other Systems (HVAC, Shades) 7 3.4 Local Instantaneous Calculations . 7 3.5 Allocat

7、ions of Savings by Strategy 11 4 Payback Factors 12 5 Other Important Metrics . 12 Figures Figure 1: Different Power Reductions for Several Controls Strategies 5 Figure 2: Power Reduction using Multiple Controls Strategies . 5 Figure 3: Simple Energy Consumption Calculation . 5 Figure 4: Legend 6 Fi

8、gure 5: Energy Savings with Respect to Baseline . 6 Figure 6: Energy Savings Including HVAC System 7 Figure 7: Operating Cost for a Residential Lighting System . 9 Figure 8: Variability with Respect to Baseline Case 10 Figure 9: Variability of Operating Costs with LED lamps on Combination Dimmer and

9、 Occupant Sensor 11 NEMA LSD 79-2018 Page 3 2018 National Electrical Manufacturers Association 1 Scope The scope of this paper includes a framework used to gauge the effectiveness of different lighting control methods. This paper is indifferent to the manufacturer of a controls system and provides a

10、 modular approach to measuring the potential savings realized from various lighting systems. 2 Purpose To justify their investments, utilities must have a way to capture the certain savings associated with incentive programs for lighting systems. Energy efficiency programs offer rebates and other fi

11、nancial incentives in return for residential and commercial building owners installing energy-efficient lighting systems. For this whitepaper, we define a lighting system as a combination of controls, sensors, lamps and/or luminaires. When used effectively, these incentives offset the building owner

12、s capital cost to install products and systems, which greatly reduce a buildings total energy consumption. As an investment option for utilities, these programs offer a compelling return by maximizing the power generation capacity of existing power plants already in service. While the potential to s

13、ave energy short term is very clear, a method is necessary to estimate the long-term average savings that can be captured based on the specific efficiency measures selected by a building owner. This paper describes the complexity of this determination and suggests a potential path forward. To be suc

14、cessful utilities must have a method of capturing the portion of those savings that are certain to be achieved. We identify these certain savings by first selecting the proper assumptions up front which will then be used to estimate the potential energy savings associated with a retrofit or new cons

15、truction project. These potential savings are then further refined based on the specific efficiency measures chosen for the project, which in turn determines the portion of savings that are certain to occur. Note: The terms “Lamp” and “Luminaire” are used interchangeably throughout this white paper.

16、 3 Energy Savings Calculations 3.1 Energy Consumption The start of any calculation of energy savings is energy consumption. Energy savings of a particular scenario is simply the difference of energy consumption of a baseline and the energy consumption of the particular scenario. As the typical units

17、 of energy consumption (kilowatt-hours) imply, energy consumption can be thought of as the average power consumption (kilowatts) multiplied by the interval of time (hours). More precisely, the energy consumption over a time interval is the integral of power over the time interval: Here E(t2,t1) is t

18、he energy consumed between time t1and t2, and P(t) is the instantaneous power consumed at every instant of time between t1and t2. The reason we take the integral of power instead using some value of power measured at one time is that the power can change over time, especially if the time interval is

19、 longer than a few minutes. For lighting systems in buildings, the power consumed at any instant in time is less than or equal to the maximum power the lighting system could draw (for example, when all the lights are on at their brightest setting). Consider a simple system that has only a switch to

20、control the light level. Of course, the lighting system consumes almost zero power when the switch is in the “off” position. The power consumed by Equation 1 NEMA LSD 79-2018 Page 4 2018 National Electrical Manufacturers Association most lighting systems in “standby mode” (e.g., for sensors, digital

21、 communication) is much less than the maximum power consumption. So we can think of the switch mathematically as a factor that takes on the value zero when it is in the “off” position and unity when it is the “on” position. Mathematically, the power consumed is the product of the maximum power possi

22、bly consumed and the switch factor. If the maximum power is constant over the interval of time considered, it can be factored out the integral. A switch is just one type of control. Some systems employ a combination of several types of controls (for example time clock schedulers, occupant sensing, h

23、igh-end trim, daylighting, etc.). Just as we did for the switch, we can think of the effect of each control scheme alone as modulating the maximum power consumption at any instant in time. The effect of using multiple control strategies is simply the minimum value of each of the individual control f

24、actors: Note: that we can calculate the effect of lighting controls on the energy consumption without knowing the maximum power consumed from the lighting system. Figure 1shows an example of a system using multiple lighting controls strategies used over the course of a day. The area under the consum

25、ption line (bold black line) is proportional to the energy consumption over a day. Equation 2 Equation 3 NEMA LSD 79-2018 Page 5 2018 National Electrical Manufacturers Association Figure 1: Different Power Reductions for Several Controls Strategies With knowledge of the lighting control modulation v

26、ersus time for each of the different lighting control strategies, we can calculate what the energy consumption would be for each combination of lighting control strategies. Figure 2 shows an example: Figure 2: Power Reduction using Multiple Controls Strategies Schematically, we can describe the ener

27、gy consumption of lighting controls as shown in Figure 3. It shows that the lighting energy consumption depends on (arrows) the maximum possible lighting energy consumption and the inputs from the lighting controls. Simplifying the picture somewhat, the lighting maximum energy consumption, in turn,

28、depends on the number of lamps and the lamp types. The lighting control inputs depend on the choices of lighting control strategies chosen, with the associated equipment, the maximum and target illuminance levels, and sensor inputs. Figure 3: Simple Energy Consumption Calculation -6.0012.0018.0024.0

29、024/7 operation 0. ManualBaseline1. Time clock 2. Timeclock +Occ Sensing3. Timeclock +Occ Sensing +HE trim +DaylightingEquivalentFullPower hours/day(LightingEnergyConsumption)Lighting ControlInputsIlluminanceTargetMax IlluminanceLighting MaxEnergyConsumptionNumber of LampsLamp TypesSensor InputsStra

30、tegies ChosenManual SwitchingTime ClockOccupant SensingHigh End TrimPersonal DimmingAutomated ShadesHVAC IntegrationNEMA LSD 79-2018 Page 6 2018 National Electrical Manufacturers Association Figure 4 shows a legend of the symbols used to represent goals (pink hexagons), decisions (blue boxes), or da

31、ta (yellow oval). Figure 4: Legend 3.2 Savings with Respect to Baseline For us to report the energy savings from lighting controls, we must specify what baseline we are considering. The energy savings of a particular scenario is simply the difference between the energy consumption of the baseline sc

32、enario and the energy consumption of the particular scenario. This whitepaper demonstrates how the energy consumption can be calculated for any scenario. Once one of those scenarios is designated as the “baseline,” then energy savings with respect to the baseline can be calculated. This is shown sch

33、ematically in Figure 5. Figure 5: Energy Savings with respect to Baseline Key to determining the actual lighting energy savings contributed by controls is establishing a baseline or control by which to measure. In short, the energy consumption in absence of additional control methods. While there ar

34、e several alternative approaches to this, one possible baseline is the predicted operation with manual switching. This replicates the anticipated periods of lighting use by manual activation by space occupants, without the benefit of any automatic control. This further isolates the contribution of s

35、pecific control schemes and establishes a least common denominator for all applications. This can be expressed as lighting being turned on, as an example, for 80% of the operational period of a space or facility. This approach is proposed over a baseline on uncontrolled lighting, by virtue of this n

36、ot being a common or code permissible condition for virtually all commercial spaces. Very few applications merit or can be installed without some form of local switching. Further, the baseline measurement is critical to be expressed as a percentage of energy saved and/or demand reduction versus mone

37、tary units. There is a rapid rate of change in the increase in light source efficiency that has not been experienced before, and we can anticipate significant advances yet to come. To express the savings in monetary units would disregard the actual incremental energy savings with controls regardless

38、 of fixture type or light source efficiency. It is a highly subjective matter to deem the savings achieved with efficient light sources alone as “good enough,” and through further advances in the efficiency of that same light source, this could be a very near-sighted determination. DecisionOption 1O

39、ption 2Goal to Maxim ize(Goal to Minimize)ProbabilityNodeLighting ControlInputsIlluminanceTargetMax IlluminanceLighting MaxEnergyConsumptionNumber of LampsLamp TypesSensor InputsStrategies ChosenManual SwitchingTime ClockOccupant SensingHigh End TrimPersonal DimmingAutomated ShadesHVAC IntegrationLi

40、ghtingEnergyConsumptionScenario 1Lighting Energy ConsumptionBaselineEnergy Savings between baselineand Scenario 1NEMA LSD 79-2018 Page 7 2018 National Electrical Manufacturers Association 3.3 Integration with Other Systems (HVAC, Shades) Just as we showed a schematic for energy consumption for a lig

41、hting system alone, we could also draw a similar schematic for the energy consumption of the HVAC system alone. If a centralized system coordinates the control of the lighting and HVAC systems, then the combined energy consumption would be calculated as shown by the schematic in Figure 6. Figure 6:

42、Energy Savings including HVAC System 3.4 Local Instantaneous Calculations While the mathematics of Equation 2 and Equation 3 are not difficult in principle, we run into challenges if we apply the methodology to larger spaces or longer intervals of time. For example, a single room can be either occup

43、ied or unoccupied, and so the energy consumption calculation is straightforward. However, consider applying the energy consumption calculation to two rooms: we can have one room occupied and the other room unoccupied. In this case, what value should we use for the occupancy control signal? One tempt

44、ing way around this difficulty is to calculate an average value of occupancy. Consider, for example, if we know the occupancy signals for two rooms, Cocc,a(t) and Cocc,b(t), we might be tempted to calculate the average occupancy as follows: Even for a system consisting of only two rooms with only oc

45、cupant sensing controls, we start to see challenges with this approach. The equations above are in fact not correct because the occupancy must be weighted by the maximum power of the individual rooms. (Lighting + HVACEnergy Consumption)Lighting ControlInputsHVACControlInputsIlluminanceTargetMax Illu

46、minanceLighting MaxEnergyConsumptionNumber of LampsLamp TypesSensor InputsStrategies ChosenManual SwitchingTime ClockOccupant SensingHigh End TrimPersonal DimmingAutomated ShadesHVAC IntegrationLightingEnergyConsumptionHVACEnergyConsumptionHVAC MaxEnergyConsumptionEquation 4 NEMA LSD 79-2018 Page 8

47、2018 National Electrical Manufacturers Association While the Equation 5 for the average occupancy is correct, it is no longer so simple as to be attractive to use. Nevertheless, if we include more rooms into our calculation of the average, then using the average occupancy in calculations in calculat

48、ions of energy savings of other areas (e.g., all office buildings) is more likely to be correct (on average). However, the approach of using the average occupancy does obscure the range of possible energy saving from different rooms. We might be tempted to extend this approach to daylighting as well

49、. But the approach gets more complicated for systems with multiple control strategies since the control signals are likely to be correlated. We would expect there to be a consistent relationship between the occupancy control signal and the daylighting control signal since for example, office rooms are often occupied at night when there is no contribution from daylighting. The challenges apply even if we consider savings scenarios involving a single circuit of light. For a residential example, suppose we want to compare the savings of a circuit of LED lamps with a c