2. Lean Energy Analysis 2

3. Effective Energy Management
Develop baseline
Utility analysis
Plant energy balance
Lean energy analysis (LEA)
Take action
Identify and quantify energy saving opportunities
Prioritize energy saving opportunities
Implement energy saving opportunities
Measure and benchmark to sustain efforts
Develop metrics for system energy efficiency
Measure energy efficiency improvement with sliding NAC
Compare energy efficiency between facilities with NAC

4. ‘Lean Energy Analysis’
Quantifying relationship between energy and:
Production
Weather
using statistical models
Deriving actionable information from models

5. Source Data 5

6. Actual Temperature Data 6

7. Time Trends: Electricity and Outdoor Temperature7

8. Time Trends: Electricity and Production8

9. Electricity vs Toa: 3PC
R2 = CV-RMSE = 6.4% 9

10. Electricity vs Production: 2P
R2 = CV-RMSE = 9.2% 10

11. Electricity vs Toa: 3PC-MVR
R2 = CV-RMSE = 5.1% 11

12. Elec = Ind + Wea-dep + Prod-dep
E (kWh/dy) =
41,589 (kWh/dy)
(kWh/dy-F) x [Toa (F) – (F)]+
(kWh/dy-unit) x P (units)
Independent = 41,589 (kWh/dy)
Wea-dep = (kWh/dy-F) x [Toa (F) – (F)]+
Prod-dep = (kWh/dy-unit) x P (units) 12

13. Disaggregate Electricity Use
Weather
= 10%
Production = 39%
Independent = 51%
Temperature 13

14. Time Trends: Fuel Use and Outdoor Temperature14

15. Time Trends: Fuel Use and Production15

16. Fuel Use vs Toa: 3PH
R2 = CV-RMSE = 7.5% 16

17. Fuel Use vs Toa: 3PH-MVR
R2 = CV-RMSE = 5.1% 17

18. Fuel Use = Ind + Wea-dep + Prod-dep
Fuel Use (mcf/dy) =
59.58 (mcf/dy)
(mcf/dy-F) x [62.06 (F) - Toa (F)]+
(mcf/dy-unit) x P (units)
Independent = (mcf/dy)
Wea-dep = (mcf/dy-F) x [62.06 (F) - Toa (F)]+
Prod-dep = (mcf/dy-unit) x P (units) 18

19. Disaggregate Fuel Use Fuel Weather = 28% Production = 58%
Independent = 14%
Temperature 19

20. ‘Lean Energy Analysis’
Called “lean energy” analysis because of its synergy with the principles of “lean manufacturing”.
In lean manufacturing, “any activity that does not add value to the product is waste”.
Similarly, “any energy that does not add value to a product or the facility is also waste”. 20

21. Quantified “Leaness” of Electricity Use
“Independent” is energy not added to product.
Perfectly “lean” when Ind = 0
Weather
= 10%
Production = 39%
Independent = 51%
Temperature 21

22. Quantified “Leaness” of Fuel Use
“Independent” is energy not added to product.
Perfectly “lean” when Ind = 0
Weather = 28%
Production = 58%
Independent = 14%
Temperature 22

23. How ‘Lean’ is Your Electricity Use?23

24. How ‘Lean’ is Your Fuel Use?24

25. Average LEA Scores (%P+%W) 28 Manufacturing Facilities
39%
58%

26. Using ‘Lean Energy Analysis’ To Discover Savings Opportunities
LEA Indicators of Savings Opportunities
High “Independent” indicates waste
Departure from expected shape
High scatter indicates poor control 26

27. Low Electricity LEA (1%) Identifies Equipment Turn-off Opportunities
Company thought presses stamp 95% of time
Data show presses stamp 50% of time; use 66% of peak power when idle
Turning off presses saves 40% and dramatically increases plant LEA

28. Low Fuel LEA Identifies Insulation Opportunities

29. Departure From Expected Shape Identifies Malfunctioning Economizers
Functional economizer
Economizer w/ broken gears
Electricity use should flatten below 50 F

30. High Data Scatter Identifies Control Opportunities
Observation: heating energy varies by 3x at same temp
Discovery: didn’t close shipping doors 30

31. High Heating Slope Identifies Excess Ventilation
Turn off excess exhaust air fans reduces vent by 13,000 cfm
Lowers heating slope, balance temperature, and fuel use

32. Lean Energy Analysis Called “Lean Energy Analysis”
because of synergy with “Lean Manufacturing”.
In lean manufacturing, “any activity that does not add value to the product is waste”.
Similarly, “any energy that does not add value to a product or the facility is also waste”. 32

33. Lean Energy Analysis Quick but accurate disaggregation of energy use:
Quantifies non-value added energy
Helps identify savings opportunities
Provides an accurate baseline for measuring the effectiveness of energy management efforts over time. 33

34. Thank You!

35. Using LEA Models for Measurement and Benchmarking
Sustaining energy efficiency efforts requires that effectiveness of past efforts be accurately evaluated.
Verify the performance of past energy-efficiency efforts
Inform the selection of future energy-efficiency initiatives
Help develop energy-efficiency targets
Measurement
Use LEA model to measure savings
Benchmarking
Use LEA model to compare facilities benchmarking

36. Measure Weather-Normalized and Production-Normalized Energy Savings
Pre-retrofit
Post-retrofit

37. Track Weather-Normalized and Production-Normalized Energy Use (NAC)
Solid Line: NAC
Annual Consumption increased 17%.
NAC increased 6%
Plant energy efficiency decreased 6%.
Dashed Line: Actual Consumption

38. Track Weather-Normalized and Production-Normalized Energy Intensity (NEI)
Intensity decreased 5.4%.

39. Benchmarking Comparing energy performance across multiple sites
Benchmark best/worst NAC and change in NAC
Benchmark best/worst coefficients and change in coefficients

40. The Big Picture: Electricity NAC and DNAC for 14 Facilities

41. More Detail: Ei and DEi
Best candidates for lighting retrofits
DEi Ei

42. More Detail: Tb and DTb
DTB
Best candidates for controls retrofits TB

43. More Detail: CS and DCS
Best candidates for HVAC retrofits
DCS CS

44. Large Independent Fuel Use Identifies Insulation Opportunities
50% of fuel use by holding furnaces
Insulate furnaces and switch to coreless furnaces 44

45. Departure From Expected Shape Identifies Malfunctioning Economizers
Air conditioning electricity use should flatten below 50 F
Audit found malfunctioning economizers 45

46. High Heating Slope Identifies Ventilation Opportunities
Night heating with make-up air unit rather than unit heater

47. High Data Scatter Identifies Control Opportunities
Heating energy varies by 3X at same temp!

48. Lean Energy Analysis Quick, accurate disaggregation of energy use:
Quantifies non-value added energy
Helps identify savings opportunities
Provides an accurate baseline for measuring the effectiveness of energy management efforts over time. 48