Benchmarking Sectors and Certifying Industrial Plants. Presented by: Gale Boyd PhD, Duke University & ENERGY STAR Benchmark Developer

Transcription

1 Benchmarking Sectors and Certifying Industrial Plants Presented by: Gale Boyd PhD, Duke University & ENERGY STAR Benchmark Developer

2 Information is a Common Barrier to Efficiency Is 10 MPG for a 2-door economy car high or low? Is 10 MMBtu per vehicle for a plant that makes the 2-door economy car high or low? Answer: Common Knowledge Answer:?

3 Estimating the Energy Efficiency Gap Engineering models can estimate best practice, while statistical models are typically average practice. Measures of energy intensity based on averages are of limited use in managing energy use or goal setting. Averages can only tell us if we are above (or below) but not by how much. A more useful measure represents where a company or plant lies within a distribution of peer performance. Is my performance close (or far) from the industry best practice?

4 Plants Within Industries are Not All the Same

5 Energy Star Energy Performance Indicator (EPI) The EPI is a statistical model of plant energy use Since plants are not all the same a statistical model is used to make an apples to apples comparison. Statistical models can - Relate energy use to production activities Primary business of a manufacturing plant Incorporate the specific type or mixture of products Include external factors that influence energy use Variation in materials arising from upstream integration (make vs buy) Capacity and utilization Heating and cooling loads driven by geographic location

6 What are the Basic Inputs to an EPI? Plant level total primary energy (TPE) Total BTU s (GJ) of fuels kwh of electricity purchased from the grid is converted to BTUs (GJ) at average power plant thermal efficiency Production activities are captured by: Production - Level and Mix Levels may be flows of common inputs, products shipped, labor hours, or a combination. Mix are typically shares of different products with dollars or physical units as the denominator Capacity and utilization when data are available May include industry specific factors Input mix Upstream integration Climate (e.g. HDD and CDD)

7 Example of an EPI Input Screen Nitrogenous Fertilizer Plant Energy Performance Indicator Draft Version 1.1, Release XX/XX/2018 Plant Characteristics Current Plant Reference Plant Enter Name Enter Name NAICS Code: Year: ZIP or Postal Code: Choose US or International Units: US Units Location: Durham, NC Production of Final Ammonia: 150,000 short tons 0 30-Year HDD (deg F): 3,457 Sold Product Urea: 200,000 short tons 0 30-Year CDD (deg F): 1,417 Ammonium Nitrate: 120,000 short tons 150,000 UAN: 500,000 short tons 250,000 MAP: 0 short tons 0 DAP: 0 short tons 0 Notes Other Production Other Product Value Share: 5% % ($/TVS) 25% Details Ammonia Producer: yes yes/no no Urea Producer: yes yes/no no Ammonium Nitrate Producer: yes yes/no yes Phosphates Producer: no yes/no no Production Worker Hours: person hours 100 Energy Consumption Select Units Enter Name Annual Purchases & Transfers 600,000 1,300,000 Electricity Onsite Renewables Gas** Distillate Oil Residual Oil Coal Other 2016 Annual Cost ($)* Enter cost Enter cost Enter Name Annual Purchases & Transfers 70,000 20, Annual Cost ($)* Enter cost Enter cost * Entering cost data is optional and does not impact the computation of the Energy Performance Score. **Do not include natural gas purchased as a feedstock; only include natural gas used for heat and power.

8 Example of an EPI Results Screen Results Display energy results in: US Units Energy Performance Score (EPS) Source Energy (MMBtu) Site Energy (MMBtu) Annual Energy Cost ($/year) Total Production (short tons of N)* Your Current Plant Enter Name ,800 Your Reference Plant Enter Name Average Plant Enter Name ,456,447 $0 Efficient Plant Enter Name ,793, ,958 10,375,841 7,835,307 3,347,200 $0 258,840 $0 3,365,282 $0 126, , , Energy Cost/Total Production ($/short tons of N)* Energy Intensity (Source MMBtu/short tons of N)* $ $0.00 *Production units in the Results section match those selected in the above Plant Characteristics section $ $ Enter Name (2016) Enter Name (2015) 100% 100% EPS = 76 90% EPS = 46 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% Source Energy (Million Btu) 0% Source Energy (Million Btu)

9 A Variety of Data are used in EPI Industry Studies Focus industries Product mix Units Inputs Size or capacity Climate Other Cement 3 Product Types Tons - Capacity & # of Kilns Person hours Corn Refining 5 Product Types Bushels Corn Capacity Feed moisture Dairy - Fluid Milk * 6 Product Types Gallons Whole milk - CDD Person hours Dairy - Ice cream * 4 Product Types Gallons 2 types - CDD Person hours Ethyl Alcohol ** Single Gallons Food - Juice 8 Product Types Gallons 2 types Food - Frozen Fried Potatoes Single Pounds Warehouse (frozen) Food - Tomato products ** 2 Product Type 2 types - - Person hours Baking - Cookies & Crackers 3 Product Types Pounds Baking - Bread & rolls 5 Product Types lbs Raw dough - HDD, CDD Freezers Glass Flat Single Pounds Sand Glass Container Single - Price Pounds Sand, Cullet Iron and Steel - Integrated 4 Stages *** Tons - Furnace capacity - Iron and Steel Minimills * Single - Price Tons Scrap Furnace capacity - Metal casting - Iron 4 Product Types - Price Tons - - HDD Person hours Metal casting - Investment steel * Single $ Value Person hours Metal casting - Other steel * 3 Product Types $ Value Metal casting aluminum 3 Product Types - Price Tons - - HDD - Motor Vehicle - Assembly Vehicle Size Number of Vehicles - Production Capacity HDD, CDD Air Tempering Nitrogen Fertilizers 5 Product Types Tons of N - Capacity - Person hours Vehicle Powertrains - Motors 5 component types # of engines - Facility size (ft2) HDD, CDD Vehicle Powertrains - Transmissions Single # of transmissions - Facility size (ft2) HDD, CDD Pharmaceuticals 3 Activity Types **** Share of Floor Space - Facility size (ft2) HDD, CDD Operation hours Printing - Lithograph ** 6 Product Types $ Value 6 types - HDD, CDD - Pulp Mills 3 Product Types Tons 2 types - - Water treatment Water treatment, Paper & Board Integrated Mills 3 Product Types Tons 3 types - - Bleaching chemicals Ready Mix Concrete ** 2 Activities Tons, Miles

10 A Variety of Methods & Results Embody the EPI Focus industries Statistical Model Year # of plants Data source Returns to Scale 75 to 50 th Cement log normal (heteroscedastic OLS) Industry VSR 0.92 LR -6.1% Corn Refining half normal frontier Industry VSR Constant LR -14.5% Dairy - Fluid Milk * log normal OLS CM % Dairy - Ice cream * log normal OLS CM % Ethyl Alcohol ** log normal OLS CM Food - Juice log normal OLS CM % Food - Frozen Fried Potatoes log normal OLS CM % Food - Tomato products ** log normal OLS CM % Baking - Cookies & Crackers log normal OLS CM % Baking - Bread & rolls log normal OLS with Kernel Industry % Glass Flat log half normal frontier CM, MECS Variable -16.3% Glass Container log normal OLS CM, MECS % Iron and Steel - Integrated log exponential frontier Industry 0.72 SR 0.99 LR -4.5% Iron and Steel Minimills * log normal OLS CM, MECS VSR Constant LR -12.1% Metal casting - Iron log normal OLS CM, MECS % Metal casting - Investment steel * log half normal frontier CM % Metal casting - Other steel * log normal OLS CM Variable -25.8% Metal casting aluminum log normal OLS CM, MECS % Motor Vehicle - Assembly Gamma frontier Industry VSR Constant LR -21.4% Nitrogen Fertilizers* log normal OLS NR CM Constant LR Vehicle Powertrains - Motors log normal OLS with Kernel Industry Constant LR Vehicle Powertrains - Transmissions log normal OLS with Kernel Industry Constant LR Pharmaceuticals log half normal frontier Industry VSR 0.98 LR -30.1% Printing - Lithograph ** log half normal frontier CM % Pulp Mills log normal OLS CM, MECS % Paper & Board Integrated Mills log normal OLS CM, MECS % Ready Mix Concrete * log normal OLS Industry 0.83 SR 0.89 LR -35.5%

11 Performance & EPI Changes Over Time Total reduction Average annual change 13.0% 1.2% Energy Performance Score Distribution of U.S. Cement Manufacturing Plant Efficiency Distribution of U.S. Cement Manufacturing Plant Efficiency Million Btu Source Energy per ton of Clinker

12 Performance & EPI Changes Over Time Total reduction Average annual change 12.0% 2.3% Energy Performance Score Distribution of U.S. Auto Assembly Energy Efficiency Distribution of U.S. Auto Assembly Energy Efficiency MMBtu per Vehicle

13 The ENERGY STAR Score One simple number understood by ALL stakeholders.

14 Industrial Focus Sectors Fertilizer Breakfast Cereal Cement Concrete Commercial Baking Cookies & Crackers Breads & Baked Goods Corn Refining Dairy Processing Fluid dairies Ice Cream Fruit & Vegetable Processing Juice Potato Products Tomato Products Glass Fiberglass Flat glass Container glass Motor Vehicles Assembly Plants Engine Plants Transmission Metal Casting Ferrous Aluminum Petrochemical Manufacturing Petroleum Refining Pharmaceuticals Printing Pulp & Paper Integrated Mills Pulp Mills Recycled Mills Steel Primary Steel Mini Mills

15 Recognition Materials From EPA: Letter to CEO from EPA Certificate ENERGY STAR decal Electronic templates for banners, flags, posters Profile on ENERGY STAR Certified Building & Plant Registry Press release materials For purchase on the ENERGY STAR on-line store: Plaques Flags Decals

16 ENERGY STAR certification for industrial plants

17 Certified Plants Save Energy & Money Total number of ENERGY STAR certified plants (since 2006) 190 Cumulative Energy Savings (BTUs source) Equal to the annual energy use of: GHG Savings (MT CO2e) Cumulative Cost Savings 796 trillion Over 4 million households 52 million $5.3 billion Equivalent to the annual wages of ### manufacturing workers 114, Certified plants Certified plants energy savings (BTU source) 64 trillion Equal to the annual energy use of: 358,000 households 2017 Certified plants GHG Savings (MT CO2e) 4 million 2017 Certified plant cost savings $ 338 million Equivalent to the annual wages of ### manufacturing workers 7316

18 NRCAN Wants New Pins in the Map

19 Questions? Gale A. Boyd, PhD Associate Research Professor, Duke University Social Science Research Institute / Department of Economics Director, Triangle Federal Statistical Research Data Center Office Mobile gale.boyd@duke.edu