Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations

Frank Schneider (), Ulrich W. Thonemann () and Diego Klabjan ()
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Frank Schneider: Supply Chain Management and Management Science, University of Cologne, 50931 Cologne, Germany
Ulrich W. Thonemann: Supply Chain Management and Management Science, University of Cologne, 50931 Cologne, Germany
Diego Klabjan: Industrial Engineering and Management Science, Northwestern University, Evanston, Illinois 60208

Transportation Science, 2018, vol. 52, issue 5, 1211-1234

Abstract: An operator of a network of battery swap stations for electric vehicles must make a long-term investment decision on the number of batteries and charging bays in the system and periodic short-term decisions on when and how many batteries to recharge. Both decisions must be made concurrently, because there exists a trade-off between the long-term investment in batteries and charging bays, and short-term expenses for operating the system. Costs for electric energy as well as demand rates for batteries are stochastic: We consider an infinite time horizon for operation of the system. We derive an optimization problem, which cannot be solved optimally in a reasonable time for real world instances. By optimally solving various small problem instances, we show the mechanics of the model and the influence of its parameters on the optimal cost. We then develop a near-optimal solution heuristic based on Monte Carlo sampling following the ideas of approximate dynamic programming for the infinite horizon dynamic program. We show that operating battery swap stations in a network where lateral transshipments are allowed can substantially decrease expected operating costs.

Keywords: battery swapping; approximate dynamic programming; lateral transshipments; stochastic optimization; electric vehicles (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (20)

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