论文标题

部分可观测时空混沌系统的无模型预测

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

论文作者

Ju, Yi, Zeng, Teng, Allybokus, Zaid, Moura, Scott

论文摘要

为插电式电动汽车用户充电基础设施可用性是一个主要问题。如今,有限的公共充电器通常被已经充满电的车辆所占据。这种现象被称为逾期储备,阻碍了其他车辆的可访问性。在本文中,我们分析了一项充电设施创新,以应对逾期的挑战,利用Robo-Chargers的想法 - 自动充电器,可以在充电站旋转并主动插入或拔下插件电动汽车。我们为结合了固定吸气器和机器人的车站的操作模型形式化。可以通过识别车辆授权任务,充电动力和客户等待行为的组合性质来解决最佳调度。然后,随着操作模型的嵌套,我们开发了一个计划模型,以指导两种类型的充电器的经济投资,以便将总拥有成本最小化。在计划阶段,它进一步考虑了收费需求差异和服务能力要求。在本文中,我们提供系统的技术 - 经济方法来评估如果引入机器人召唤者是否是有益的,那么考虑到特定的应用程序方案。基于现实世界数据的全面敏感性分析突出了机器人吸引者的优势,尤其是在逾期固定的情况下。验证还表明,在合理的模型不匹配,不确定性和干扰下,操作模型的障碍和计划结果的鲁棒性和计划结果的鲁棒性。

Charging infrastructure availability is a major concern for plug-in electric vehicle users. Nowadays, the limited public chargers are commonly occupied by vehicles which have already been fully charged. Such phenomenon, known as overstay, hinders other vehicles' accessibility to charging resources. In this paper, we analyze a charging facility innovation to tackle the challenge of overstay, leveraging the idea of Robo-chargers - automated chargers that can rotate in a charging station and proactively plug or unplug plug-in electric vehicles. We formalize an operation model for stations incorporating Fixed-chargers and Robo-chargers. Optimal scheduling can be solved with the recognition of the combinatorial nature of vehicle-charger assignments, charging dynamics, and customer waiting behaviors. Then, with operation model nested, we develop a planning model to guide economical investment on both types of chargers so that the total cost of ownership is minimized. In the planning phase, it further considers charging demand variances and service capacity requirements. In this paper, we provide systematic techno-economical methods to evaluate if introducing Robo-chargers is beneficial given a specific application scenario. Comprehensive sensitivity analysis based on real-world data highlights the advantages of Robo-chargers, especially in a scenario where overstay is severe. Validations also suggest the tractability of operation model and robustness of planning results for real-time application under reasonable model mismatches, uncertainties and disturbances.

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