1. Using M&V Models to Understand Energy Through Lean Energy Analysis Kelly Kissock, Ph.D., P.E. Department of Mechanical and Aerospace Engineering University of Dayton 300 College Park, Dayton, Ohio 45469-0238 937-229-2852kkissock@udayton.edukkissock@udayton.edu http://academic.udayton.edu/kissock

2. Lean Energy Analysis  Uses M&V baseline model to understand what drives changes in energy  Baseline M&V model: Energy = a + b Production + c Weather

3. Source Data Average daily temperature data 1995-present for 316 sites at: http://academic.udayton.edu/kissock

4. Model Fuel Use vs Toa: 3PH R 2 = 0.92 HS Find Tcp

5. Model Fuel Use vs Production: 2P R 2 = 0.02 Prod Slope Negative

6. Model Fuel Use vs Toa and Prod: 3PH-MVR R 2 = 0.97 Prod Slope = Positive

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

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

9. 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”.

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

11. 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

12. Low Fuel LEA Identifies Insulation Opportunities

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

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

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

16. 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.