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

对运输部门温室气体排放的环境担忧，以及电池技术的进步，导致了对该部门(公共汽车、车辆、踏板车、自行车)电气化的大量私人和公共投资。在这种范式转变中，管理电子移动生态系统和克服里程焦虑被认为是释放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最优策略，以支持未来车辆到电网和电网到车辆运营的电子移动生态系统。拟议的规划工具将通过随机建模来考虑几个不确定因素，包括当地交通模式、司机的行为和可再生能源。交通系统的物理模型(包括道路、热门停靠点、停车场、路边停车)将在当地的中低压电网上绘制，以考虑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站的最佳位置、每个位置的充电器的大小和类型以及未来为满足电子移动生态系统要求而进行的网络扩展。

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.