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

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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.