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Fleet Renewal with Electrical Vehicles at La Poste

Fleet Renewal with Electrical Vehicles at La Poste. Ata Oğuzcan Tekin Gökhun Çamurdan Kerem Sinan Tuncel. Background Information. La Poste is big French Postal Operator (PO) Fleet Renewal Process is very important for PO’s Vehicle Fleet is one of the important asset of PO’s

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Fleet Renewal with Electrical Vehicles at La Poste

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  1. FleetRenewalwithElectricalVehicles at La Poste Ata Oğuzcan Tekin Gökhun Çamurdan Kerem Sinan Tuncel

  2. Background Information • La Poste is big French Postal Operator (PO) • Fleet Renewal Process is very important for PO’s • Vehicle Fleet is one of the important asset of PO’s • Renewal projects have huge stake in budget • Electric Vehicles (EV) are serious competitors for Internal Combustion Vehicles (ICV) • EV’s has low carbon footprints. • France produce their 80% of energy from nuclear energy plants.

  3. Challenges in Project • Uncertanities in Energy prices (Battery and Fuel Prices) • Infrastructure and Support Services of New Technologies • Brand Reputation Effects of Green Investments • Uncertanity about Learning Effects

  4. Trade- Offs Between ICV and EV • EV’s operating cost are less than ICV’s but acquiring cost of EV’s are much higher than ICV’s • Operating costs are decided by trends in fuel, battery and electricity prices. • We consider 2 main decision options; • 1) Static Policy (15 year horizon) • 2) Dynamic Policy (decision made by quarterly basis)

  5. Searching for Solution • There are multiple uncertanities in model • La Poste given decision in quarterly basis, thus criteria based on discrite time- approach will be better fit for this case • Rare research about this issue • Because both EV’s and ICV’s has uncertanities

  6. Decision Model for Fleet Renewal • Life Time Cost= Maintenance + Operating Costs • Operating Cost for ICV = Fuel (Diesel ) Cost • Maintenance cost comes from past data • For EV’s, there are less data • Experts says that electricity cost have little effect on operating costs • EV’s maintance cost are 30% less than ICV’s • Batteries are very important in decision model • Batteries life time is change between 8-10 years • For commercial use 6 year of life time

  7. Characterizition of Uncertain Fuel Prices and Battery Prices • Diesel Prices has very strong correlation with crude oil prices. • 1998-2008 correlation between to aspects are 0,986 • Experts are expected that crude oil prices will increase • EV battery prices will be decreased by 65% in 2020 • Correlation between electricity prices and crude oil is very low.

  8. Formulating The Decision Model • Discrete – time, stochastic dynamic programming • Battery and Fuel is uncertain • Objective is to minimize TCO: Total Cost of Ownership

  9. Assumptions • Demand for delivery is fixed at 2010 levels • EV and ICV vehicles have the same capacity • Acquisition decisions are made in quarterly basis • Leasing contracts last 6 years • Number of vehicles to be purchased is determined by acquisition history and demand that are materialized until the decision making time

  10. Assumptions • Fixed cost at the first period it switches to EV to represent the anticipated cost of driver training and other one-time switching costs

  11. Optimal Portfolio of Vehicles • It is optimal to acquire only one type of vehicle type each period because; • No limits for the acquisition of EV • No quantity discount available • Cost seperability

  12. Optimal Portfolio of Vehicles • Since aquisition portfolio depends on the evolution of dynamic programming state variables, alternative scenerios will yield different optimal paths.

  13. Optimal Acquisition Policy • Optimal policy is a dynamic policy in which the optimal vehicle type is determined based on the last realizations of uncertainities in each period • Lower Bound: Expected value of perfect information • Upper Bound: Static Policy outcome

  14. Optimal Timing of EV Acquisition

  15. Impact of DeterministicDrift

  16. GovernmentSubsidy

  17. TheSensitivityto Model Risk

  18. Impact of a FixedCost

  19. Limitations of The Model • Limited range of EV batteries (lessthan 150 km) • Per vehicledistribution of La Poste’scurrentfleet = 50 to 250 km

  20. Benefits • Fastandreliablecomputationandsimulation. • Corresponding model has beeninstrumental in acquisitionstrategy. • Since 2011 thecompanyacquired 250 electricvehicles. (planned: 40000)

  21. LessonsLearned • Risksassociatedwiththedesicionprocess can be modeledtestedandcontrolled. • OR methodsallowedthedefinitionandtesting of relevantdecisionstrategies. • Outcomes of OR methodsshould be understandablebythemanagement.

  22. THANKS FOR LISTENING…

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