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Effective Energy Management
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
Energy Use Baseline
– Plant energy balance• Map energy use throughout the plant
– Statistical analysis (Lean Energy Analysis)• Understand drivers of energy use
Estimate Equipment Electricity and Fuel Use
Equipment Rated Power Frac Loaded Oper Hours Elec Use(hr/yr) (kWh/yr)
AC #1 50 hp 90% 5,000 187,500Lights 10 kW 100% 6,000 60,000… … … … …Other 10,000
Utility Bill Total = 257,500
Equipment Rated Input Frac Loaded Oper Hours Gas Use(Btu/hr) (hr/yr) (MBtu/yr)
Boiler 1 1,000,000 70% 5,000 3,500Make Up #1 500,000 100% 2,000 1,000… … … … …Other 500
Utility Bill Total = 5,000
1) Estimate energy use from:
• rated power• frac loaded• operating hours
2) Calibrate sum against measured total energy use
Electricity And Fuel Energy Balances
0% 12% 24% 36% 48% 60%
Vacuum Pumps
Process Blowers/Fans
Lighting
Dust Collectors
Sanders
Other Process Motors
Air Compressors
Process Heating
Other
20%
18%
17%
12%
12%
8%
6%
5%
2%
Estimated Electrical Use Breakdown
0% 10% 20% 30% 40% 50% 60%
Other Fuel Using Equipment
Gas Fired Heater
Endo Generators
Sterlco Water Heater
Potable Water Heater
51%
13%
12%
11%
1%
Estimated Natural Gas Use Breakdown
Map Energy From Supply to Conversion To Process
Plant Energy Balances
Use plant energy balances to:– Identify biggest energy users– Prioritize action plans– Calibrate savings estimates
Lean Energy Analysis
Production39%
Independent51%
Weather10%
Statistical ‘Lean Energy Analysis’
Quantifying relationship between:– Energy– Production– Weather
by developing simple statistical models
Deriving actionable information from models
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
Actual Temperature Data
http://www.engr.udayton.edu/weather
Time Trends: Electricity and Outdoor Temperature
Time Trends: Electricity and Production
Electricity vs Toa: 3PC
R2 = 0.67 CV-RMSE = 6.4%
Electricity vs Production: 2P
R2 = 0.32 CV-RMSE = 9.2%
Electricity vs Toa: 3PC-MVR
R2 = 0.82 CV-RMSE = 5.1%
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)
Disaggregate Electricity Use
Weather= 10%
Production = 39%
Independent = 51%
Temperature
Electricity
Time Trends: Fuel Use and Outdoor Temperature
Time Trends: Fuel Use and Production
Fuel Use vs Toa: 3PH
R2 = 0.92 CV-RMSE = 7.5%
Fuel Use vs Toa: 3PH-MVR
R2 = 0.97 CV-RMSE = 5.1%
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)
Disaggregate Fuel Use
Weather = 28%
Production = 58%
Independent = 14%
Temperature
Fuel
‘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”.
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
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
How ‘Lean’ is Your Electricity Use?
R2 of Regression Model
0.00
0.20
0.40
0.60
0.80
1.00
0 5 10 15 20 25 30 35 40 45 50
Mean R2 Value Sorted R2 Value
Fraction Independent Electricity
0.00
0.20
0.40
0.60
0.80
1.00
0 5 10 15 20 25 30 35 40 45 50
Mean FI Elec Sorted FI Elec
Fraction Production-Dependend Electricity
0.00
0.20
0.40
0.60
0.80
1.00
0 5 10 15 20 25 30 35 40 45 50
Mean FPD NG Sorted FPD NG
Weather-Dependent Electricity Per ft2
0
10
20
30
40
50
0 5 10 15 20 25 30 35 40 45 50
Mean WD Elec (kWh/yr-ft2) Sorted WD Elec (kWh/yr-ft2)
R2 of Regression Model
0.00
0.20
0.40
0.60
0.80
1.00
1.20
0 5 10 15 20 25 30 35 40
Sorted R2 Values Mean R2 Value
Fraction Independent Fuel
0.00
0.20
0.40
0.60
0.80
1.00
0 5 10 15 20 25 30 35 40
Sorted FI NG Mean FI NG
Fraction Production-Depend Fuel
0.00
0.20
0.40
0.60
0.80
1.00
0 5 10 15 20 25 30 35 40
Sorted FPD of NG Usage Mean FPD NG
How ‘Lean’ is Your Fuel Use?
Weather-Dependent Fuel Per ft2
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0 5 10 15 20 25 30 35 40
Sorted WD NG (mmBtu/yr-ft2) Mean WD NG (mmBtu/yr-ft2)
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
Large Independent Fuel Use Identifies Insulation Opportunities
• 50% of fuel use by holding furnaces• Insulate furnaces and switch to coreless furnaces
Departure From Expected Shape Identifies Malfunctioning Economizers
Air conditioning electricity use should flatten below 50 F Audit found malfunctioning economizers
High Data Scatter Identifies Control Opportunities
•Observation: heating energy varies by 3x at same temp•Discovery: didn’t close shipping doors
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
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.
Take Action
Identify and quantify saving opportunities Prioritize saving opportunities Implement saving opportunities
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
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
Implement Savings Opportunities
Management commitment Maintenance commitment Operator commitment
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
Savings
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
Track Weather-Normalized and Production-Normalized Energy Intensity (NEI)
Normalized Energy 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 NAC for 14 Facilities
Smallest Energy Users
Biggest Energy Decrease
Biggest Energy Increase
Biggest Energy Users
NAC
NAC
More Detail: Ei and Ei
Best candidates for lighting retrofits
Smallest Eind Users
Biggest Eind Users
Biggest Eind Decrease
Biggest Eind Increase
Ei
Ei
More Detail: Tb and Tb
Best candidates for controls retrofits
Biggest Tb Increase
Biggest Tb
Biggest Tb Decrease
Smallest Tb
TB
TB
More Detail: CS and CS
Best candidates for HVAC retrofits
Biggest Slop Increase
Biggest Slope
Biggest Slope Decrease
Smallest Slope
CS
CS
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