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Where Green Really Matters

Where Green Really Matters. Diego Klabjan & Yue Geng Industrial Engineering and Management Sciences Northwestern University. Extraterrestrial. Back to Earth. Customers NSF Pat Haggerty and Renee Crain Division of Arctic Sciences Funding through NSF grant General Motors

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Where Green Really Matters

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  1. Where Green Really Matters Diego Klabjan & Yue Geng Industrial Engineering and Management Sciences Northwestern University

  2. Extraterrestrial

  3. Back to Earth • Customers • NSF • Pat Haggerty and Renee Crain • Division of Arctic Sciences • Funding through NSF grant • General Motors • Jorge Arinez – R&D • Stephane Biller – R&D • Financial support

  4. Greenland: Summit • Major research site in the heart of Greenland • NSF approves and funds research projects • Logistics service provider • Logistics • Operations of the site • Challenge • Remote location, limited access • GM provides Chevy Volt

  5. Scope • Assess long term economical viability of Summit • Supporting transportation logistics needs • Operational considerations at Summit • Energy requirements • Environmental impact • Emissions from transportation • Renewable on-site generation

  6. Objectives • A tool to analyze scenarios • Cost • Emissions • Other KPIs • Given a possible scenario • Determine by means of optimization logistics requirements and expenses • Trade-off between cost and emissions

  7. Execution • Input • Demand through project requirements • Available transportation options • Cost parameters • Optimization models • Output • Overall logistics and operational cost • Carbon footprint

  8. Time (Days/Weeks) LC-130 from Scotia on day 8 arrive Kanger on day 9 Inventory left from previous day Vessel from VA Beach on day 2 arriving to Kanger on day 32 Time window for shipment A at origin Shipment A Location in the US 1 2 3 4 5 6 7 8 31 32 … … 1 2 3 4 5 6 7 8 31 32 … … Kanger 1 2 3 4 5 6 7 8 31 32 … … Summit … Time window for shipment A at destination Locations Aggregate by week Shipment A

  9. Model • Standard time based model • Main emission source • Fuel consumption at Summit • Heating, electricity, equipment, heavy machinery • Keeping track of fuel consumption at Summit • Challenge: Researchers and equipment consume electricity

  10. Bi-level Goal Programming • Phase 1 • Minimize cost • Phase 2 • Minimize emissions • Cost ≤ (1+f)∙ optimal cost from Phase 1 • Control tractability by aggregation • During season aggregate by week • Off-season by month

  11. Baseline • PRIMARY NODES • Kangerlussuaq • Summit Station • Thule Air Base • Remote Sites… Year 2008 calibration: CO2 Emission = 1,862 tons 47 vehicles Number of flights to Thule: very few Field Number of flights to Thule: 2 Basler Number of flights from Thule to Summit: 1 LC130 Number of vessels to Thule: 1 PacerGoose Number of flights from Kanger to Summit: 17 LC130 Number of vessels to Thule: 1 PacerGoose Number of flights from Kanger to Summit: 19LC130 Field Flights to remote locations: Kanger to Ilulissat 4 TwinO Kanger to Raven 3 TwinO Thule to Swiss Camp 1 T/O Number of vessels to Kanger: 2 Eimskip Number of vessels to Kanger: 2 Eimskip Number of flights to Kanger: 9 Basler and 5 C17 Number of flights to Kanger: 20 LC130 and 1 C5 Optimize Cost $900,000 CO2 Emission = 1, 701 tons 42 vehicles

  12. Fuel Implication at Summit

  13. Let’s Get Dirty with Renewables • Fuel consumption for electricity main source of emissions • Reduce also fuel delivery • Consider renewable sources • Wind turbines • PV panels • No sun in winter

  14. Renewable Portfolio • Given electricity demand • Find the right mix of renewable sources • Why not the lowest cost source?

  15. Model • Demand at hourly rate • How much of each renewable source to install? • Given • Output profile of each source • Installation cost (NPV) • O&M cost

  16. Here Comes GM • Manufacturing plants • Have been and will be using renewable resources • Only if positive NPV • Federal and state incentives • Investment and production tax credit • RECs • New option of power from grid

  17. Model Enhancement • Power purchase contract decisions • Power from spot market • At what year to switch from leasing to buying • Start accumulating RECs

  18. Enhancements • Constraints for each hour, month, and year • Incorporate risk • REC prices correlated to spot prices • Spot prices related to power purchase agreement • RECs and power purchase prices dependent

  19. Demand Profile

  20. GM Plant

  21. Should GM Invest?

  22. Holy Grail YIKES: Let’s stick with what-if!

  23. Almost as North as Summit

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