Evaluating the network stability using probabilistic modelling of the future e-mobility ecosystem in urban areas

使用城市地区未来电动交通生态系统的概率模型评估网络稳定性

• 批准号: 2690222
• 金额: --
• 依托单位: Northumbria University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2690222
• 关键词: Evaluating; network; stability; using; probabilistic

Environmental concerns about greenhouse gas emission from transportation sector along with advancements in battery technologies has led to massive private and public investment into electrification of the sector (buses, vehicles, scooters, bikes). In this paradigm shift, managing e-mobility ecosystem and overcoming range anxiety are known as the key factors to unlock widespread adoption of the technologies. In this project, we intend to develop a stochastic optimal strategy for charging infrastructure design within distribution networks in urban areas to support future e-mobility ecosystem in both vehicle-to-grid and grid-to-vehicle operation. Several sources of uncertainties, including local traffic pattern, drivers' behaviour and renewable energy resources, will be considered in the proposed planning tool through stochastic modelling. A physical model of the transportation system (including roads, popular stopping points, parking lots, on-street parking) will be mapped over local low- and medium-voltage power network to account for network capacity availability and constraints. The outcome of the tool will be the optimal location of the future e-parking lots and on-street charging points, the size and types of the chargers at each location as well as the future network expansion to fulfil the e-mobility ecosystem requirements.

环境对运输部门的温室气体排放以及电池技术的进步引起了人们的关注，这导致了对该行业电气化的大量私人和公共投资（公交车，车辆，车辆，踏板车，自行车）。在这种范式的转变中，管理电子动力生态系统和克服范围焦虑症被称为解锁广泛采用技术的关键因素。在这个项目中，我们打算制定一种随机最佳策略，以在城市地区的分销网络中为基础设施设计充电，以支持车辆到网格和车辆到车辆操作中的未来电子动力生态系统。通过随机建模在拟议的计划工具中，将考虑几种不确定性的来源，包括当地交通模式，驱动程序的行为和可再生能源。运输系统的物理模型（包括道路，流行的停车点，停车场，路边停车）将在当地的低压和中型电压网络上绘制，以说明网络容量的可用性和约束。该工具的结果将是未来电子设备批次的最佳位置和街道充电点，每个位置的充电器的大小和类型以及未来的网络扩展，以满足E-Mobility生态系统要求。