In order to solve the problem of new peak-valley load difference caused by the electric vehicle response when only the time-of-use price is implemented

based on the master-slave game theory of dynamic non-cooperative game

an optimal scheduling strategy for micro-grids containing electric vehicles is proposed based on the double incentive and cooperative game of electricity price and carbon quota. The model considers the complete consumption of new energy generation

and it formulates dual incentive policies for time-of-use prices and carbon quotas through equivalent load curves

with the micro-grid as the main body

and the minimum operating cost and mean square deviation of load as the main optimization goals. The owner side of the vehicle is the slave and the lowest cost of the vehicle is the related goal. The particle swarm optimization is adopted and the decoupling characteristic of the model is used to solve the Nash equilibrium point of it so as to get the collection of the optimal time-of-use price and the charging and discharging scheme of the electric vehicle. Through a comparative example

various typical scenarios before and after optimization are analyzed in detail

and the effects of peak-cutting and valley-filling and overall scheduling benefit of the proposed model are verified. The multiple policies collaborative incentive strategy in this paper can provide a reference for the relevant engineering practice of power system demand side response.