Sequential Energy Scheduling Approach to Support Decentralized Smart Charging of Electric Vehicles

This paper presents a sequential energy scheduling approach to support decentralized smart charging of Electric Vehicles (EVs) in distribution networks. Both utility and EV owner-side objective functions, constraints, and preferences are considered within a decentralized, multi-agent, smart charging scenario. In the proposed methodology, the distribution Locational Marginal Prices (LMPs) are exploited to effectively introduce grid-level constraint information into the smart charging process. The proposal comprises two main modules: i) a decentralized smart charging module, cast as a quadratic optimization program, and ii) a sequential energy scheduling module to optimally schedule Distributed Energy Resources (DERs) for a day of operation. The paper showcases an effective way to exchange information between the utility and EV owners to create an environment in which the objective function, constraints, and preferences of every agent are fulfilled. The methodology is demonstrated on the IEEE-123 distribution test feeder including 60, 75, and 95 EVs.