Scaling Up Battery Swapping Services in Cities

Wei Qi, Yuli Zhang, Ningwei Zhang
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引用次数: 3

Abstract

Battery swapping for electric vehicle refueling is reviving and thriving. Despite a captivating sustainable future where swapping batteries will be as convenient as refueling gas today, tensions are mounting in practice (beyond the traditional “range anxiety” issue): On one hand, it is desirable to maximize battery proximity and availability to customers. On the other hand, it is undesirable to incur too many batteries which are environmentally detrimental. Additionally, power grids for battery charging are not accessible everywhere. To reconcile these tensions, some cities are embracing an emerging infrastructure network: Decentralized swapping stations replenish charged batteries from centralized charging stations. In this paper, we model this new urban infrastructure network. This task is complicated by non-Poisson swaps (observed from real data), and by the intertwined stochastic operations of swapping, charging, stocking and circulating batteries among swapping and charging stations. We show that these complexities can be captured by analytical models. We next propose a new location-inventory model for citywide deployment of hub charging stations, which jointly determines the location, allocation and reorder quantity decisions with a non-convex non-concave objective function. We solve this problem exactly and efficiently by exploiting the hidden submodularity and combining constraint-generation and parameter-search techniques. Even for solving convexified problems, our algorithm brings a speedup of at least three orders of magnitude relative to Gurobi solver. The major insight is twofold: Centralizing battery charging may harm cost-efficiency and battery asset-lightness; however, this finding is reversed if foreseeing that decentralized charging will have limited access to grids permitting fast charging. We also identify planning and operational flexibilities brought by centralized charging. In a broader sense, this work deepens our understanding about how mobility and energy are coupled in future smart cities.
扩大城市电池交换服务
为电动汽车加油而更换电池正在复苏并蓬勃发展。尽管在未来,更换电池将像今天加油一样方便,但在实践中,紧张局势正在加剧(超越了传统的“里程焦虑”问题):一方面,希望最大限度地接近客户的电池和可用性。另一方面,使用太多对环境有害的电池是不可取的。此外,用于电池充电的电网并非随处可见。为了缓解这些紧张局势,一些城市正在采用一种新兴的基础设施网络:分散的交换站从集中的充电站补充充电电池。本文对这种新型城市基础设施网络进行了建模。非泊松交换(从真实数据中观察到),以及在交换站和充电站之间交换、充电、储存和循环电池等交织在一起的随机操作,使这项任务变得复杂。我们展示了这些复杂性可以通过分析模型来捕获。在此基础上,基于非凸非凹目标函数,提出了枢纽充电站在城市范围内部署的位置-库存模型,该模型共同确定了枢纽充电站的位置、配置和再订货数量决策。我们利用隐子模块性,结合约束生成和参数搜索技术,准确有效地解决了这一问题。即使对于求解凸性问题,我们的算法也带来了相对于Gurobi求解器至少三个数量级的加速。主要观点有两个方面:集中充电可能会损害成本效益和电池资产轻量化;然而,如果预见到分散充电将限制允许快速充电的电网的接入,这一发现就会被逆转。我们还确定了集中收费带来的规划和运营灵活性。从更广泛的意义上说,这项工作加深了我们对未来智慧城市中交通和能源如何结合的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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