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Using M&V Models to Understand Energy Through
Lean Energy Analysis
Kelly Kissock, Ph.D., P.E.
Department of Mechanical and Aerospace EngineeringUniversity of Dayton300 College Park,
Dayton, Ohio 45469-0238937-229-2852 [email protected]
http://academic.udayton.edu/kissock
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
Source Data
Date Elec (kWh/dy) Nat Gas (mcf/dy) Prod (units/dy) Toa (F)1/31/2002 76,127 590 13,065 34.72/28/2002 80,564 581 13,557 34.73/31/2002 77,362 542 12,401 39.44/30/2002 81,712 418 14,086 53.55/31/2002 80,059 348 14,181 58.66/30/2002 90,094 298 13,439 72.57/31/2002 86,361 287 10,551 77.48/31/2002 89,326 341 14,239 75.89/30/2002 95,441 348 13,830 69.710/31/2002 82,779 434 12,693 51.511/30/2002 77,639 535 12,977 39.612/31/2002 61,288 518 9,982 30.7
Average daily temperature data 1995-present for 316 sites at: http://academic.udayton.edu/kissock
Model Fuel Use vs Toa: 3PH
R2 = 0.92
HS
Find
Tcp
Model Fuel Use vs Production: 2P
R2 = 0.02 Prod Slope Negative
Model Fuel Use vs Toa and Prod: 3PH-MVR
R2 = 0.97 Prod Slope = Positive
Disaggregate Fuel Use
Weather = 28%
Production = 58%
Independent = 14%
Temperature
Fuel
Disaggregate Electricity Use
Weather = 10%
Production = 39%
Independent = 51%
Temperature
Electricity
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”.
Average LEA Scores (%P+%W)28 Manufacturing Facilities
39%
58%
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 idleTurning off presses saves 40% and dramatically increases plant LEA
Low Fuel LEA Identifies Insulation Opportunities
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!
Departure From Expected Shape Identifies Malfunctioning Economizers
Electricity use should flatten below 50 F
Functional economizer
Economizer w/ broken gears
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.
