Effective Energy Management

1. Effective Energy Management

2. Effective Energy Management • Develop baseline • Identify and quantify savings opportunities • Measure and benchmark to sustain efforts

3. 1. Energy Use Baseline Billing analysis How energy is priced Plant energy balance Where energy is used Lean energy analysis (LEA) What drives changes in energy use

4. Utility Bill Analysis • Analyze rate schedule • Verify billing amounts • Check for saving opportunities: • Primary/secondary • Power factor correction • Meter consolidation • Demand reduction potential • Benchmark costs

5. Plant Energy Balance • 1) Estimate energy use from: • rated power • frac loaded • operating hours • 2) Calibrate sum against measured total energy use

6. Energy Use Breakdowns by Equipment

7. Lean Energy Analysis • Understand what drives changes in Energy • Quantify “Waste” and “Lean” • Model: Energy = a + b Production + c Weather

8. Source Data

9. Actual Temperature Data http://academic.udayton.edu/kissock

10. Plot Fuel vs Toa

11. Model Fuel Use vs Toa: 3PH HS Find Tcp R2 = 0.92

12. Model Fuel Use vs Production: 2P R2 = 0.02 Prod Slope Negative

13. Model Fuel Use vs Toa and Prod: 3PH-MVR R2 = 0.97 Prod Slope = Positive

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

15. Model Electricity vs Toa: 3PC R2 = 0.67

16. Model Electricity vs Production: 2P R2 = 0.32

17. Model Electricity vs Toa and Prod: 3PC-MVR R2 = 0.82

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

19. 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”.

20. Quantified “Leaness” of Fuel Use “Independent” is a metric of energy not added to product Fuel LEA = %Production + %Weather Fuel LEA = 86%

21. Quantified “Leaness” of Electricity Use “Independent” is a metric of energy not added to product Electricity LEA = %Production + %Weather = 49% Electricity LEA = 49%

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

23. Use 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

24. Low Electric LEA = 24%Indicates Operating Opportunities

25. Low Fuel LEA Identifies Insulation Opportunities

26. High Heating Slope Identifies Heating Efficiency / Insulation Opportunities

27. High Data ScatterIdentifies Control Opportunities Heating Energy Varies by 3X at Same Temp!

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

29. Lean Energy Analysis Quick but accurate disaggregation of energy use: Quantifies the energy not adding value to product or the facility Helps identify savings opportunities Provides an accurate baseline for measuring the effectiveness of energy management efforts over time.

30. 2. Identify and Quantify Saving Opportunities • Identifying energy savings • Use “Integrated Systems + Principles Approach (ISPA) • ISPA is effective and thorough • Quantifying energy savings • Requires competent engineering • May warrant energy audit • May consider energy savings performance contract (ESPC)

31. 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

32. Implement Savings Opportunities • Management commitment • Operator and maintenance education and buy in

33. 3. 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 • Extend LEA with sliding NAC and EI to measure energy efficiency improvement • Benchmarking • Compare NAC and EI for inter-facility benchmarking

34. Normalized Energy Intensity 1) Characterize performance with ‘Energy signature’ model 2) Remove noise with ‘Normalized annual consumption’ NAC 3) Track performance with ‘Sliding NAC’ analysis 4) Benchmark performance with ‘Multi-site sliding NAC’ analysis

35. Raw Energy and Production Data

36. Normalized Energy Intensity

37. Benchmark NEI vs. Multiple Facilities DNEI NEI

38. Case Study: Turn off Make-up Air Units During Non-Production Hours Heating Slope Decreases by 50% Baseline Post-retrofit

39. Sliding NEI Fuel NEI decreased by 23% Independent of weather/production changes

40. Summary: Effective Energy Management • 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