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Where Green Really Matters

Where Green Really Matters. Diego Klabjan & Yue Geng Industrial Engineering and Management Sciences Northwestern University. Agenda. Project overview Model Energy and emission aspects Current r esults Future actions. Project Overview. Scope Features Objectives. Scope.

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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. Agenda • Project overview • Model • Energy and emission aspects • Current results • Future actions

  3. Project Overview Scope Features Objectives

  4. 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

  5. The Greenland Physics Problem • THE KEY RESOURCE QUESTIONS • How much does it cost? • How much will the cost escalate? • How can we use less of it? • PRIMARY NODES • Kangerlussuaq • Summit Station • Thule Air Base • Remote Sites… Field • KEY METRICS • Pounds of cargo moved (O-D) • Number of Pax moved (O-D) • Hourly airlift costs • Ship costs per pound • Volume of fuel consumed for flights and infrastructure • Annual researcher days supported • Energy consumption at Summit • ON-ISLAND MODES • Military airlift (LC-130) • Commercial air (Twin Otter, Helos, ?) • Oversnow Traverse Field

  6. Features • Highly seasonal demand • Long planning period – over 5 years or more • Different modes of transportation are available • Emission should be controlled • Different emission factors for different modes of transportation • Transportation of fuel • Renewable on-site generation

  7. Travel on Greenland

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

  9. Model Network flow model Calibration

  10. Network flow model • Standard time based model • Keeping track of fuel consumption at Summit • Base fuel consumption plus fuel consumed by people

  11. 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

  12. Constraints • Flow balance for each commodity at each node • Consumable commodity • Non-consumable commodity • Capacity is not exceeded for each arc and each transportation mode • Inventory capacity is not exceeded at specific nodes • Certain matchup of commodity and transportation mode is forbidden

  13. Energy and Emission Aspect Background on transportation emission Features Methods

  14. Methods – Bi-level Goal Programming • Phase 1 • Minimize cost • Constraints are imposed on the constructed network • Phase 2 • Minimize emissions • Constraints are imposed on the constructed network • Cost ≤ (1+f)∙ optimal cost from Phase 1 • Control tractability by aggregation • During season aggregate by week • Off-season by month

  15. Size of the Model • Before aggregation of demand, thousands of commodities • After aggregation of demand • Around 150 commodities • Over 3, 000 arcs • Over 30, 000 variables • Over 10, 000 constraints

  16. Preliminary Results – Install renewables (f = 0.05)

  17. Current Results – Install renewables tons

  18. Future Actions • Calibrate the model based on data from more years • Develop decomposition algorithms to handle the long planning horizon • Handling possible future scenarios • Develop the decision support tool with the above ingredients

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