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