RTF Lighting Standard Protocol

1. RTF Lighting Standard Protocol Review of Hours of Operations, Controls Savings, and Variation

2. Hours • Context: SR relies on interview used for hours with default as backup. How do our proposed defaults look? • Review measured hours versus default • Caveats • All logged data by some method from studies meant to ascertain hours • Unknown protocols for annualization • Unknown site sampling procedures & duration • Know little about building/occupant charateristics • Litlle know about sample selection • It would take substantial time mine for those unknowns

3. Hours of Operations Datasets Used • CPUC & Itron. (2010). Small Commercial Contract Group Direct Impact Evaluation Report CALMAC Study ID: CPU0019.01. Retrieved from http://www.calmac.org/abstract.asp?id=2739 • CPUC Database for Energy Efficient Resources (DEER). (2010). Summary of 2008 DEER Measure Energy Analysis Revisions Version 2008.2.05 – 09-11 Planning/Reporting Version, Comparison of 2005 and 2008 EFLH for Lighting. Retrieved from http://www.deeresources.com/deer0911planning/downloads/DEER2008UPDATE-EnergyAnalysisMethodsChangeSummaryV9.pdf • New York State. (2012). New York State Technical Resource Manual. Retrieved from http://www.aging.ny.gov/livableny/ResourceManual/Index.cfm • Bonneville Power Administration. (2011). BPA C&I Lighting Calculator. Retrieved from http://www.bpa.gov/energy/n/projects/lighting

4. Default from Calculator Total = 27 default options Reviewed = 14 Reviews were completed on datasets that had over 4 quality data points. Descriptive statistics were completed on all analyzed default inputs. Data was cleaned by eliminating statistical outliers. See workbook for full statistical analysis. (tab: Stats Review of Hours)

5. College or University

6. Hospital

7. Lodging

8. Manufacturing

9. Office <20,000 sf

10. Office >100,000 sf

11. Other Health, Nursing, Medical Clinic

12. Restaurant

13. Retail Boutique <5,000 sf

14. Retail Supermarket

15. Retail Big Box >50,000 sf One-Story

16. Retail Anchor Store >50,000 sf Multistory

17. School K-12

18. Warehouse

19. Some Conclusions • Significant range for hours within some building use types highlights the importance of the interview part of SRM • Use of default carries more uncertainty in some use types than others • Default hours for some building use types should be revised • Test of simplest reliable needs to include how often default is used • What is correlation between logged hours and reported business hours?

20. Hours of Operations Conclusion • Hours of Operations varies across building types and within building types. It depends on the building, occupants, type of work, and location within the building (e.g.: office vs. break room vs. computer room vs…..) • Because of large variation within building types it will be difficult to use defaults and estimate accurate operating hours • Even within the same utility, different programs report different operating hours for the same building type. • A regional primary study would most likely return the same uncertainty and not be worth the $$.

21. Control savings as a % Issues: • Most analysis, case studies focus on full lighting retrofits not just control upgrades • There are large variations in control only reported data • Type of lights, control settings, and operating hours all effect results • Location of controls effects performance 3 studies are presented to show the variability

22. LBNL Meta-Analysis from Lighting Controls • Focus on commercial buildings by building type • 240 savings estimates from 88 papers and case studies • Control types evaluated = Occupancy, Day lighting, Personal tuning, Institutional Tuning, and multiple types • Report website: http://efficiency.lbl.gov/drupal.files/ees/Lighting%20Controls%20in%20Commercial%20Buildings_LBNL-5095-E.pdf

23. LBNL Meta-Analysis Conclusions • Table 7 page 15 • These are the data points used in the calculator • These points are the average of all studies analyzed • These numbers include studies that are calculations and actual installation

24. LBNL Meta-Analysis Conclusions • Large Standard deviations indicated (+ - 20%) uncertainty and varying results • Actual installations are not broken up by building type

25. Rensselaer Polytechnic Institute review of Occupancy Sensors • Evaluation of Documented and undocumented studies by building location type • Evaluation identifies ranges and average savings • Most data evaluated reported prior to 2001

26. Rensselaer Polytechnic Institute review of Occupancy Sensors Findings

27. M & V of Day lighting Photocontrols • 5 Buildings evaluated (office, school, manufacturing, medical, warehouse) • Looked at the direction of Office Spaces • All locations based in Idaho • Report website: http://www.idlboise.com/pdf/papers/20100111_Final_Photo%20Controls.pdf

28. M & V of Day lighting Photocontrols Findings • Results from monitoring period during regular operation hours • Direction of Offices has large significant impact on savings • Variations in site savings provides uncertainty • Numbers and savings % are different from the LBNL study

29. Controls Savings Conclusions • Documented variations are large • Occupancy variations, directional variations, and space type variations, add to uncertainty • Small samples of installations do not accurately represent the population of installations • Most calculations overestimate actual savings