Lean Energy Analysis 2

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

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

Source Data 5

Actual Temperature Data http://academic.udayton.edu/kissock/http/Weather/default.htm 6

Time Trends: Electricity and Outdoor Temperature 7

Time Trends: Electricity and Production 8

Electricity vs Toa: 3PC R2 = 0.67 CV-RMSE = 6.4% 9

Electricity vs Production: 2P R2 = 0.32 CV-RMSE = 9.2% 10

Electricity vs Toa: 3PC-MVR R2 = 0.82 CV-RMSE = 5.1% 11

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) 12

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

Time Trends: Fuel Use and Outdoor Temperature 14

Time Trends: Fuel Use and Production 15

Fuel Use vs Toa: 3PH R2 = 0.92 CV-RMSE = 7.5% 16

Fuel Use vs Toa: 3PH-MVR R2 = 0.97 CV-RMSE = 5.1% 17

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) 18

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

‘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

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

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

How ‘Lean’ is Your Electricity Use? 23

How ‘Lean’ is Your Fuel Use? 24

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

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

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

Low Fuel LEA Identifies Insulation Opportunities

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

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

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

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

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

Thank You!

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

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

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

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

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

The Big Picture: Electricity NAC and DNAC for 14 Facilities

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

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

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

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

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

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

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

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