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.

中文翻译：

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PEV快速充电站选址规划：交通和电网要求下的综合方法

插电式电动汽车 (PEV) 是一种非常规电力负载，其快速充电站 (FCS) 是资本密集型的​​交通服务基础设施。因此，FCS 选址规划必须同时考虑电力和交通基础设施的要求。本文首次提出了一种基于图计算的综合位置规划模型，在保证电网可靠性的同时，最大限度地提高了电动汽车充电的便利性。此外，所提出的模型捕获了由充电需求的不确定性和冲动性引起的关键电网资产的长期成本。最后，该模型可以通过基于图形的方案轻松扩展到各种耦合配置和时间分辨率。所提出的模型被视为一个多目标混合整数问题，并通过交叉熵（CE）优化算法解决，其中图并行计算技术显着提高了计算效率。所提出的规划模型和图实现方法在综合电力-运输耦合网络上得到验证。