Location Planning of PEV Fast Charging Station: An Integrated Approach Under Traffic and Power Grid Requirements

Abstract

Plug-in Electric Vehicles (PEV) are characterized as a type of unconventional electric load, and their Fast Charging Stations (FCS) are capital-intensive transportation service infrastructure. Therefore, FCS location planning must consider the requirements of electricity and transportation infrastructures simultaneously. This paper, for the first time, proposes a graph-computing based integrated location planning model, which maximizes PEV charging convenience while ensuring the power grid's reliability. In addition, the proposed model captures the long-term costs of critical grid assets induced by uncertainty and impulsiveness of charging demand. Finally, the model can be easily scaled to various coupling configurations and temporal resolutions through a graph-based scheme. The proposed model is cast as a multi-objective mixed-integer problem and is solved by the cross-entropy (CE) optimization algorithm, in which the computational efficiency is significantly improved with graph parallel computing techniques. The proposed planning model and graph implementation method are validated on a synthetic power-transportation coupled network.