1. Effective Energy Management

2.  Develop baseline –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 and EI –Compare energy efficiency between facilities with NAC and EI

3. Energy Use Baseline –Plant energy balance Map energy use throughout the plant –Statistical analysis (Lean Energy Analysis) Understand drivers of energy use

4. Estimate Equipment Electricity and Fuel Use 1) Estimate energy use from: rated power frac loaded operating hours 2) Calibrate sum against measured total energy use

5. Electricity And Fuel Energy Balances

6. Map Energy From Supply to Conversion To Process

7. Plant Energy Balances  Use plant energy balances to: –Identify biggest energy users –Prioritize action plans –Calibrate savings estimates

8. Lean Energy Analysis

9. Statistical ‘ Lean Energy Analysis ’  Quantifying relationship between: –Energy –Production –Weather by developing simple statistical models  Deriving actionable information from models

10. Source Data

11. Actual Temperature Data http://www.engr.udayton.edu/weather

12. Time Trends: Electricity and Outdoor Temperature

13. Time Trends: Electricity and Production

14. Electricity vs Toa: 3PC R 2 = 0.67 CV-RMSE = 6.4%

15. Electricity vs Production: 2P R 2 = 0.32 CV-RMSE = 9.2%

16. Electricity vs Toa: 3PC-MVR R2 = 0.82 CV-RMSE = 5.1%

17. Elec = Ind + Wea-dep + Prod-dep E (kWh/dy) = 41,589 (kWh/dy) + 361.159 (kWh/dy-F) x [Toa (F) – 30.7093 (F)] + + 2.4665 (kWh/dy-unit) x P (units) Independent = 41,589 (kWh/dy) Wea-dep = 361.16 (kWh/dy-F) x [Toa (F) – 30.71 (F)] + Prod-dep = 2.4665 (kWh/dy-unit) x P (units)

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

19. Time Trends: Fuel Use and Outdoor Temperature

20. Time Trends: Fuel Use and Production

21. Fuel Use vs Toa: 3PH R 2 = 0.92 CV-RMSE = 7.5%

22. Fuel Use vs Toa: 3PH-MVR R 2 = 0.97 CV-RMSE = 5.1%

23. Fuel Use = Ind + Wea-dep + Prod-dep Fuel Use (mcf/dy) = 59.58 (mcf/dy) + 9.372 (mcf/dy-F) x [62.06 (F) - Toa (F)] + + 0.0199 (mcf/dy-unit) x P (units) Independent = 59.58 (mcf/dy) Wea-dep = 9.372 (mcf/dy-F) x [62.06 (F) - Toa (F)] + Prod-dep = 0.0199 (mcf/dy-unit) x P (units)

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

25. ‘ 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”.

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

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

28. How ‘ Lean ’ is Your Electricity Use?

29. How ‘ Lean ’ is Your Fuel Use?

30. 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

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

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

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

34. 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

35. 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.

36. Take Action  Identify and quantify saving opportunities  Prioritize saving opportunities  Implement saving opportunities

37. Identify and Quantify Saving Opportunities  Identifying energy saving opportunities –Use “Integrated Systems + Principles Approach (ISPA)  Quantifying energy savings: may consider –Equipment vendors (compressed air, boiler, etc.) –Energy savings performance contractor (ESPC) –Independent energy audit

38. Prioritize Saving Opportunities  Multiple filters –Financial return on investment Rank versus other energy saving opportunities Rank versus other requests for capital Risk –Consistent with other priorities –Available and knowledgeable staff to manage project

39. Implement Savings Opportunities  Management commitment  Maintenance commitment  Operator commitment

40. 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

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

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

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

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

45. The Big Picture: Electricity NAC and  NAC for 14 Facilities  NAC NAC

46. More Detail: Ei and  Ei Best candidates for lighting retrofits  Ei Ei

47. More Detail: Tb and  Tb Best candidates for controls retrofits  TB TB

48. More Detail: CS and  CS Best candidates for HVAC retrofits  CS CS

49. Effective Energy Management: Summary  Develop baseline –Plant energy balance (breakdown) –Lean energy analysis (drivers)  Take action –Identify and quantify energy saving opportunities –Prioritize and implement energy saving opportunities –Implement energy saving opportunities  Measure and benchmark to sustain efforts –Use LEA models to measure energy efficiency improvement –Compare energy efficiency between facilities