Abstract
Electric taxis (ETs) are the primary public charging station (PCS) users. The inappropriate deployment may lead to inefficient use of PCSs and lengthy queueing of ETs. The fluctuating charging demand of ETs makes it challenging for public charging stations’ location and size decisions. To deal with this problem, this paper develops a new mathematical programming model for locating and sizing public charging stations by considering spatial-temporal ET charging demand. This model considers ET’s actions in detail, including searching for PCSs, queuing, and losing without being served in each period. The objective is to minimize the total cost, including ETs’ transportation cost of driving to PCSs, waiting cost for charging, loss penalty due to limited capacity, and weighted construction expenditure. The decisions are the locations of PCSs, the number of charging piles, and the number of parking spaces. The existing PCSs are considered. Numerical experiments validate the performance of the proposed model. The numerical experiment results show the effectiveness of the proposed model and the significance of taking the spatial-temporal distribution of charging demand into account.
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