Optimal Operation of Battery Swapping Stations for Electric Vehicles with Grid Energy Services: A Battery Resource Allocation Approach

A battery swapping station exchanges a depleted electric-vehicle pack for a charged one in minutes, and its shelf of batteries doubles as a grid-connected store that arbitrages a time-of-use tariff. Running both businesses together is a scheduling problem: when to charge each pack, when to discharge, and which pack to hand over. This paper states it as battery resource allocation (BatRes). In general the model is a mixed-integer nonlinear program (MINLP), because the request-to-battery assignment is binary and a no-simultaneous-charge-and-discharge condition is nonlinear. Under a first-come-first-served rule the assignment is fixed, and because losses are charged on both power directions the nonlinear condition never binds, so the solved model is a linear program. Two cases run under the industrial tariff of Pakistan: a three-request case, and a reproducible synthetic full day of thirty requests across eight batteries. Net profit ranges from PKR 939.2 to PKR 994.7 across the six arrival orders, and the swap business lifts profit to about four times the grid-only level. Against an aggregate-inventory baseline that ignores the returned charge, requirement matching adds 11.7% in the small case and 35.8% over the full day. Sensitivity sweeps over swap price, tariff, inventory, efficiency, and depth of discharge map the result.