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.

沿着电池技术的进步，对交通运输部门温室气体排放的环境担忧导致私人和公共部门对该部门的电气化（公共汽车，汽车，踏板车，自行车）进行了大量投资。在这种模式转变中，管理电动汽车生态系统和克服里程焦虑被认为是解锁广泛采用这些技术的关键因素。在这个项目中，我们打算为城市地区配电网络内的充电基础设施设计开发一个随机优化策略，以支持未来的电动汽车生态系统在车辆到电网和电网到车辆的操作。建议的规划工具会透过随机模式，考虑若干不明朗因素，包括当地交通模式、驾驶者行为及可再生能源。交通系统的物理模型（包括道路、热门停车点、停车场、路边停车场）将映射到当地的低压和中压电力网络，以说明网络容量的可用性和限制。该工具的结果将是未来电子停车场和路边充电点的最佳位置、每个位置充电器的大小和类型以及未来满足电动汽车生态系统要求的网络扩展。