PFI:AIR - TT: Optimal adaptive charging system

这个PFI：空气技术翻译项目为自适应电动汽车(EV)充电网络开发软件，并将其过渡到市场。我们正处于未来几十年能源系统向更可持续形式的历史性转变的风口浪尖。我们交通系统的电气化将是一个重要的组成部分，因为今天，车辆消耗了超过四分之一的能源，排放了超过四分之一的与能源相关的二氧化碳(CO2)。电气化不仅将大大减少二氧化碳排放，电动汽车也可以成为关键资源，帮助将风能和太阳能等可再生能源整合到我们的电网中。大规模采用电动汽车的关键因素之一是智能充电网络的可用性。该项目将设计一套新颖而复杂的算法，优化电动汽车充电器网络，在软件中实施，并在加州理工学院的一个车库进行试点，研究人员已经在那里安装了可编程电动汽车充电器网络。它将作为一个原型，验证下一代自适应充电网络(ACN)的技术和商业潜力。与电动汽车充电行业的最先进水平相比，ACN将实现智能充电器的大规模部署，并以所需基础设施成本的一小部分提供相同的充电能力。该项目解决了以下技术差距，将其从研究发现转化为商业应用。在美国顶级电动汽车城市的许多工作场所，充电器相对于电动汽车来说严重短缺，例如，每2-5辆电动汽车就有一个充电器。未来，这一比例应该更接近1：1。然而，大规模充电设施的瓶颈不是电力或充电器的成本，而是配电系统容量的有限，以及市中心的房地产。当前市场上领先的充电器在每次插入电动汽车时都会以最高价格充电。如果不对配电系统进行昂贵得令人望而却步的升级，它们就不可能大规模部署。该项目将开发的技术将对自适应充电器网络的充电过程进行优化调度，以在不超过配电系统容量的情况下在最后期限内满足所有电动汽车的能源需求，否则将在竞争对手的电动汽车之间优化和公平地分配可用容量。因此，ACN最大限度地利用充电生态系统中最昂贵的资源，以低得多的基础设施成本提供目标充电能力，创造出令人信服的价值主张。该项目将应用优化理论、控制和动力系统以及算法设计的工具。重点是开发优化软件，该软件将在项目结束时准备商业化。该项目将涉及本科生和研究生。除了研究和软件开发，项目参与者还将获得创业和技术转让机会。

This PFI: AIR Technology Translation project develops software for adaptive electric vehicle (EV) charging networks and transitions it to the marketplace. We are at the cusp of a historic transformation of our energy system into a more sustainable form in the coming decades. Electrification of our transportation system will be an important component because, today, vehicles consume more than a quarter of our energy and emit more than a quarter of our energy-related carbon dioxide (CO2). Electrification will not only greatly reduce CO2 emission, but EVs can also be critical resources to help integrate renewable sources, such as wind and solar power, into our electric grid. One of the key enablers to mass EV adoption is the availability of smart charging networks. This project will design a set of novel and sophisticated algorithms that optimize a network of EV chargers, implement them in software, and pilot them in a Caltech garage where the researchers have already installed a network of programmable EV chargers. It will serve as a prototype that validates the technology and business potential of next-generation adaptive charging network (ACN). Compared with state of the art in the EV charging industry, ACN will enable massive deployment of smart chargers and provide the same charging capacity at a fraction of required infrastructure costs.This project addresses the following technology gaps as it translates from research discovery toward commercial application. At many workplaces in top EV cities in the US, there is a severe shortage of chargers relative to EVs, e.g., there is a charger for every 2-5 EVs. In the future, this ratio should be closer to 1:1. The bottleneck to a large-scale charging facility is, however, not the cost of electricity or chargers, but the limited capacity of electricity distribution system, as well as, in city centers, the real estate. The leading chargers in the current marketplace charge at their peak rates whenever EVs are plugged in. They cannot be deployed at scale without a prohibitively expensive upgrade of the electricity distribution system. The technologies to be developed in this project will optimally schedule the charging process of a network of adaptive chargers to satisfy energy requirements of all EVs within their deadlines without exceeding the capacity of the electricity distribution system whenever possible, and optimally and fairly allocate the available capacity among competing EVs otherwise. The ACN therefore maximally utilizes the most expensive resources in a charging ecosystem to provide a target charging capacity at a much lower infrastructure cost, creating a compelling value proposition.The project will apply tools from optimization theory, control and dynamical systems, and algorithm design. The focus is to develop optimization software that will be ready for commercialization at the end of the project. The project will involve undergraduate and graduate students. In addition to research and software development, the project participants will be exposed to entrepreneurship and technology transfer.