Distributed plug-in electric vehicles charging strategy considering driver behaviours and load constraints

This paper proposes a distributed charging strategy that considers load constraints and driver behaviours for plug-in electric vehicles (PEVs) in a smart charging station (SCS). Due to the fast-growing load demand of PEVs and infrastructure investments for load capacity, the PEV energy demands to be subjected to some constraints, such as overload limit and power limit, beyond which failures may occur. The concept of time anxiety is introduced to reduce the impact of uncertain events by adjusting the charging strategy, affecting the charging patterns and aborting PEV charging. This paper constructs a charging problem based on noncooperative game theory, where each PEV aims at minimizing the cost of charging while satisfying several constraints. Then, a distributed algorithm is developed to search for generalized Nash equilibria of the game. Simulations and results are introduced to verify the effectiveness of the proposed charging strategy.

Automated summary

This paper proposes a distributed charging strategy that considers load constraints and driver behaviours for plug-in electric vehicles (PEVs) in a smart charging station (SCS). The concept of time anxiety is introduced to reduce the impact of uncertain events by adjusting the charging strategy, affecting the charging patterns and aborting PEV charging. A distributed algorithm is developed to search for generalized Nash equilibria of the game. Simulations and results are introduced to verify the effectiveness of the proposed charging strategy.