Routing and Scheduling of Mobile EV Chargers for Vehicle to Vehicle (V2V) Energy Transfer

Ameliorating the range anxiety to propel the disparaged electric vehicle (EV) market necessitates an adequate charging infrastructure. But, the high initial installation cost, requirement of suitable places and the anticipated immense load on the grid during peak time hinder to elongate the charging station network, especially in urban areas. As a consequence, the bidirectional energy transferring capability between vehicle to vehicle (V2V) may act as an auxiliary solution to charge an EV at any place and at any time without leaning on a permanent charging infrastructure. Here in this work, we assume a company having a number of V2V enabled charging trucks equipped with a larger battery and a fast charger to charge a number of EVs at some particular parking lots. The company intends to maximize the served number EVs, when an EV should be considered as served if it would be fully charged during its declared charging window. All the charging requests are assumed to be received before the time horizon and we also consider that all trucks should return to the depot after serving EVs. We formulate an integer linear program (ILP) to maximize the number of served EVs by determining the optimal trajectory of each truck. The problem is formally proved as NP-hard and due to its larger computational time, we also propose three different heuristic algorithms: 1) Strictest Window Shortest Path First (SWSPF), 2) Smallest Demand Shortest Path First (SDSPF) and 3) Earliest Arrival Shortest Path First (EASPF). The performance of these three algorithms are examined in detail and finally, SDSPF shows the better performance and its performance is closer to the optimal solution.