Abstract:In the peak regulation of microgrid (MG) with Electric Vehicle (EV), the implementation of time-of-use price or real-time price policy guiding EV to participate in peak regulation of MG will lead to the problems of EV over-response or response exhaustion. For this reason, a game optimization scheduling strategy for MG with EVs was proposed under the incentive mechanism of Ladder electricity price and carbon quota. A master-slave game optimization scheduling model is developed with MG as the leader and EVs as the follower. Considering the complete consumption of new energy power generation, with the minimum operation cost and minimum mean load square error as the objectives, Ladder electricity price is formulated based on equivalent net load levels and is cooperated with carbon quotas, guiding EVs to charge and discharge responding to the surplus and deficiency of new energy power generation; Electric vehicle users respond to microgrid incentive policy to optimize EV charging and discharging behavior to minimize its cost. Particle swarm optimization method is used to solve the Nash equilibrium point of the game optimization model, and the MG optimal Ladder price and EV scheduling strategy are obtained. Finally, simulation examples was carried out to verify the correctness and effectiveness of the proposed method.