Distributed charging management of multi-class electric vehicles with different charging priorities

This study proposes distributed energy management approach for charging multi-class electric vehicles (EVs) in community microgrids. The energy management problem is implemented in real-time and represented by a non-cooperative Stackelberg game for the power distribution inside the microgrid. In this game, a battery energy storage system is chosen as a leader and the EVs are designated as followers. The charging power distribution among EVs is tackled in the two cases of 'plenty of power' and 'lack of power'. The challenging case of 'lack of power' occurs when the total charging power is insufficient to meet the need of each EV, such as when weather conditions are unfavourable. A priority factor is included in the EV utility functions to address charging priorities of different classes of EVs in practical scenarios. A consensus-based distributed algorithm is developed later to iteratively reach the Nash equilibrium, i.e. final charging power distribution, among EVs with different charging priorities. Both simulation and experimental results show that the charging power is properly distributed when the predefined charging priorities are followed, particularly in the case of a 'lack of power'.