An operator of a network of battery swap stations for electric vehicles must make a long-terminvestment 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 aswell 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.
- Approximate dynamic programming
- Battery swapping
- Electric vehicles
- Lateral transshipments
- Stochastic optimization
ASJC Scopus subject areas
- Civil and Structural Engineering