CPS- Synergy- Collaborative Research- Architectural and Algorithmic Solutions for Large Scale PEV Integration into Power Grids

This project designs algorithms for the integration of plug-in hybrid electric vehicles (PEVs) into the power grid. Specifically, the project will formulate and solve optimization problems critical to various entities in the PEV ecosystem -- PEV owners, commercial charging station owners, aggregators, and distribution companies -- at the distribution / retail level. Charging at both commercial charging stations and at residences will be considered, for both the case when PEVs only function as loads, and the case when they can also function as sources, equipped with vehicle-to-home (V2H) or vehicle-to-grid (V2G) energy reinjection capability. The focus of the project is on distributed decision making by various individual players to achieve analytical system-level performance guarantees. Four problems are presented as research highlights. Two problems consider residential charging while two others consider charging at commercial stations. In the first problem, PEVs are used to provide demand response flexibility to the grid. We consider the problem of designing a contract to solve the problem of phantom demand response, in which the PEV owner may present a false baseline to the aggregator to gain more reward for the same real demand reduction. In the second problem, PEVs are allowed to inject energy into the grid. We set up a repeated market in which the decisions of the PEV owners are coupled due to the storage in the PEV battery. We identify the optimal bidding strategy for the owners. The third problem considers optimal driving patterns to minimize battery consumption in a PEV. A detailed powertrain, wind, and battery model is used to optimize the driving pattern and the route. The fourth problem considers dynamic pricing and energy management policy for PEV charging stations with renewable energy integration and energy storage. A multi-objective program is set up and stochastic dynamic programming is used to solve the problem.