The concept of smart city strives for greener technology to reduce carbon emission to ameliorate the global warming. Following this footprint, the transportation sector is experiencing a paradigm shift and the transition to electric vehicles (EVs) has prodigious plausibility in reducing carbon emission. However, the anticipated EV penetration is hindered by several challenges, among them are their shorter driving range, slower charging rate and the lack of ubiquitous availability of charging locations, which collectively contribute to range anxieties for EVs' drivers. Meanwhile, the expected immense EV load onto the power distribution network may degrade the voltage stability. To reduce the range anxiety, we present a two-stage solution to provision and dimension a DC fast charging station (CS) network for the anticipated energy demand and that minimizes the deployment cost while ensuring a certain quality of experience for charging e.g., acceptable waiting time and shorter travel distance to charge. This solution also maintains the voltage stability by considering the distribution grid capacity, determining transformers’ rating to support peak demand of EV charging and adding a minimum number of voltage regulators based on the impact over the power distribution network. We propose, evaluate and compare two CS network expansion models to determine a cost-effective and adaptive CSs provisioning solution that can efficiently expand the CS network to accommodate future EV charging and conventional load demands. We also propose two heuristic methods and compare our solution with them. Finally, a custom built Python-based discrete event simulator is developed to test our outcomes.

中文翻译：

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电动汽车快速充电基础设施的按需供应

智慧城市的概念力求采用更环保的技术来减少碳排放，以缓解全球变暖。遵循这一足迹，交通运输部门正在经历范式转变，向电动汽车 (EV) 的过渡在减少碳排放方面具有极大的合理性。然而，电动汽车的预期普及受到若干挑战的阻碍，其中包括行驶里程较短、充电速度较慢以及充电地点缺乏普遍性，这些共同导致电动汽车驾驶员对里程焦虑。同时，配电网络上预期的巨大电动汽车负载可能会降低电压稳定性。为了减少里程焦虑，我们提出了一个两阶段解决方案来为预期的能源需求提供和规划直流快速充电站 (CS) 网络，并最大限度地降低部署成本，同时确保一定的充电体验质量，例如可接受的等待时间和较短的行驶距离收费。该解决方案还通过考虑配电网容量、确定变压器的额定值以支持电动汽车充电的峰值需求以及根据对配电网络的影响添加最少数量的稳压器来保持电压稳定性。我们提出、评估和比较两种 CS 网络扩展模型，以确定一种经济高效且自适应的 CS 配置解决方案，该解决方案可以有效地扩展 CS 网络以适应未来的电动汽车充电和传统负载需求。我们还提出了两种启发式方法，并将我们的解决方案与它们进行比较。最后，开发了一个定制的基于 Python 的离散事件模拟器来测试我们的结果。