论文标题
ACN-SIM：用于数据驱动的电动汽车充电研究的开源模拟器
ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research
论文作者
论文摘要
ACN-SIM是一个数据驱动的开源模拟环境，旨在加速智能电动汽车（EV）充电领域的研究。它满足了这个社区的需求，以实现广泛可用的现实模拟环境，研究人员可以在其中评估算法和测试假设。 ACN-SIM提供了一个模块化，可扩展的体系结构，该体系结构建模了真实充电系统的复杂性，包括电池充电行为和不平衡的三相基础架构。它还与更广泛的研究工具生态系统集成在一起。其中包括ACN-DATA，即EV充电会话的开放数据集，该数据集提供了现实的仿真场景和ACN-Live，这是用于现场测试充电算法的框架。它还与Matpower，Pandapower和Opendss等网格模拟器以及Openai Gym进行了集成，用于培训强化学习剂。
ACN-Sim is a data-driven, open-source simulation environment designed to accelerate research in the field of smart electric vehicle (EV) charging. It fills the need in this community for a widely available, realistic simulation environment in which researchers can evaluate algorithms and test assumptions. ACN-Sim provides a modular, extensible architecture, which models the complexity of real charging systems, including battery charging behavior and unbalanced three-phase infrastructure. It also integrates with a broader ecosystem of research tools. These include ACN-Data, an open dataset of EV charging sessions, which provides realistic simulation scenarios and ACN-Live, a framework for field-testing charging algorithms. It also integrates with grid simulators like MATPOWER, PandaPower and OpenDSS, and OpenAI Gym for training reinforcement learning agents.
