LAUSR

Battery swapping stations (BSSs) have a potential of becoming a part of the electric vehicle charging infrastructure mix. A number of aggregated BSSs have a significant capacity and can act as strategic players in electricity market. This paper formulates a discrete cluster model for optimal operation of aggregated BSSs that take part in the day-ahead energy and reserve capacity markets and have sufficient combined capacity to affect market prices. In the presented bilevel structure the upper-level problem optimally defines charging and discharging schedules, as well as reserve capacity, of the aggregated BSSs, while the lower-level problem clears the market and provides locational marginal prices for each BSS, as well as the reserve capacity prices. This problem is converted into a single-level equivalent using the Karush-Kuhn-Tucker optimality conditions. The presented case study reveals that BSSs can collect significant revenues when providing reserve capacity. The main benefit of the proposed cluster model is computational tractability and solution accuracy, which depends on the resolution of the clusters.