STTR Phase I: Intelligent Planning and Control Software for EV Charging Infrastructure

STTR第一阶段：电动汽车充电基础设施智能规划和控制软件

• 批准号: 1746858
• 负责人: Narayanan Sankar
• 金额: $ 22.45万
• 依托单位: Microgrid Labs Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1746858&HistoricalAwards=false
• 关键词: STTR; Phase; Intelligent; Planning; Control

The broader impact/commercial potential of this project is to develop smart software to plan and control Electric Vehicle (EV) charging infrastructure in commercial facilities, such as workplaces, hotels, car rental centers, parking garages, etc. The EV planning software finds the optimal design balancing design tradeoffs such as EV customer satisfaction, grid stability limits and financial constraints. This software will help facility operators to optimize their EV charging infrastructure by minimizing their operating costs and maximizing their revenue by utilizing intelligent scheduling and pricing strategies. The software leverages the latest developments in stochastic optimization for designing an optimal configuration of EV infrastructure that is robust to variations in mobility behavior of the users. This will enable public utilities to save billions of dollars by deferring expensive upgrades to their existing infrastructure. It will also empower small consulting businesses, facility managers and electrical contractors to design and build EV infrastructure without any specialized knowledge of optimization or modeling.This Small Business Technology Transfer (STTR) Phase I project addresses the problem of planning and controlling EV charging infrastructure to meet the rapidly growing energy demands of EV owners. EVs are expected to comprise 30% of all cars globally by 2030. This forecasted increase over the next 10 years is of major concern for utilities, and commercial real estate owners. Given the long commute distances, driving habits, time taken to charge using home-based chargers and range anxiety, there is a need for charging locations at workplaces, hotels, and car rental centers. Chargers at these locations will generally be medium power Level 2 chargers, which are 5 to 10 times the size of typical home chargers. Simultaneous uncontrolled charging of several EVs at these locations will easily overload the local electrical infrastructure. The software mitigates this problem by designing an optimal EV infrastructure together with optimally sized onsite generation and storage. The controlling solution ensures that the grid impacts are minimized by scheduling the installed EV chargers together with onsite generation and storage with optimal set points in real time.

该项目更广泛的影响/商业潜力是开发智能软件，以规划和控制商业设施中的电动汽车（EV）充电基础设施，如工作场所，酒店，汽车租赁中心，停车场等。EV规划软件可以找到最佳设计平衡设计权衡，如EV客户满意度，电网稳定性限制和财务约束。该软件将帮助设施运营商优化其电动汽车充电基础设施，通过利用智能调度和定价策略最大限度地降低运营成本并最大限度地提高收入。该软件利用随机优化的最新发展来设计对用户移动行为变化具有鲁棒性的EV基础设施的最佳配置。这将使公用事业公司能够通过推迟对现有基础设施进行昂贵的升级来节省数十亿美元。它还将使小型咨询企业、设施管理人员和电气承包商能够在没有任何优化或建模专业知识的情况下设计和建造电动汽车基础设施。这个小型企业技术转让（STTR）第一阶段项目解决了规划和控制电动汽车充电基础设施的问题，以满足电动汽车所有者快速增长的能源需求。预计到2030年，电动汽车将占全球所有汽车的30%。未来10年的预测增长是公用事业和商业真实的房地产业主的主要关注点。考虑到通勤距离长、驾驶习惯、使用家用充电器充电所需的时间和里程焦虑，需要在工作场所、酒店和汽车租赁中心设置充电地点。这些地方的充电器通常是中等功率的2级充电器，是典型家用充电器的5到10倍。在这些地点同时对几辆电动汽车进行不受控制的充电，很容易使当地的电力基础设施过载。该软件通过设计最佳的电动汽车基础设施以及最佳规模的现场发电和存储来缓解这一问题。控制解决方案通过真实的实时调度安装的EV充电器以及现场发电和存储的最佳设定点，确保电网影响最小化。