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

对交通部门温室气体排放的环境担忧，以及电池技术的进步，导致大量私人和公共投资进入该部门的电气化（公共汽车、汽车、摩托车、自行车）。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推动电动汽车技术广泛采用的关键因素。在这个项目中，我们打算为城市地区配电网络中的充电基础设施设计开发一种随机优化策略，以支持未来的电动交通生态系统，包括车辆到电网和电网到车辆的运行。提出的规划工具将通过随机建模考虑几个不确定因素，包括当地交通模式、司机行为和可再生能源。运输系统的物理模型（包括道路、受欢迎的停车点、停车场、路边停车场）将被映射到当地的低压和中压电网，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街道充电点的最佳位置，每个位置的充电器的大小和类型，以及未来网络扩展以满足电动交通生态系统的要求。

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.