Optimal decentralized charging control algorithm for electrified vehicles connected to smart grid

Electrified vehicles (EV) and renewable power sources are two important technologies for sustainable ground transportation. If left unmitigated, the additional electric load could over-burden the electric grid. Meanwhile, a challenge for integrating renewable power sources into the grid lies in the fact their intermittency requires more regulation services which makes them expensive to deploy. Fortunately, EVs are controllable loads and the charging process can be interrupted. This flexibility makes it possible to manipulate EV charging to reduce the additional electric load and accommodate the intermittency of renewable power sources. To illustrate this potential, a two-level optimal charging algorithm is designed, which achieves both load shifting and frequency regulation. Load shifting can be realized through coordination of power generation and vehicle charging while reducing power generation cost and carbon dioxide emissions. To ensure practicality, a decentralized charging algorithm for load shifting is formulated by emulating the charging pattern identified through linear programming optimization solutions. The frequency regulation is also designed based on frequency droop that can be implemented in a decentralized way. The two control objectives can be integrated because they are functionally separated by time scale. Simulation results are presented to demonstrate the performance of the proposed decentralized algorithm.

► An implementable charging algorithm is developed for vehicles connected to a grid.
► The algorithm requires minimum exchange of information about the vehicles.
► The algorithm minimizes generation cost and CO2 emission.
► The algorithm works in a decentralized way but achieves near optimal performance.
► The algorithm provides regulation services without affecting charging completion.