Study On Coordinated Charging Of Electric Vehicle Based On Game Model

The intensification of the energy crisis has made people aware of the need to use clean energy instead of traditional fossil energy.Electric energy substitution has become essentially to achieve human sustainable development.Many country has issued policies to promote the production of electric vehicles,so that the traditional fuel vehicles,which are the main consumer goods of fossil energy,are gradually replaced by electric vehicles,and electric vehicles are bound to become the main mode of travel in the future.Large-scale and stochastic electric vehicle loads will inevitably lead to worse load curve when connected to the grid.How to arrange the charging of electric vehicles in a coordinated manner has become the research focus of researchers.In this thesis,a coordinated charging strategy for electric vehicles based on game theory is proposed.Firstly,on the premise of real data,this thesis analyses the travel rules and daily mileage of a large number of electric vehicles,gets the probability distribution curve by fitting Gauss distribution,and classifies the travel rules of electric vehicles by using hierarchical clustering algorithm in big data technology,which makes the load modeling of electric vehicles more specific and detailed.On the premise of hypothesizing the simulation test of electric vehicle charging,the Monte Carlo method is used to simulate the load of electric vehicle and analyze the effect of disordered charging on the peak-valley difference of load.Then,this thesis studies the development and related principles of game theory,the composition of standard Nash game and the concept of equilibrium solution,and the application of game theory in the field of power system.Because the grid has innate pricing advantages,this thesis constructs a master-slave game model with the grid as the game subject and the electric vehicle as the game subordinate.In the game subordinate,the electric vehicle is regarded as the game participant with complete rationality,using price factors to play with other electric vehicles to make its charging price better.In this thesis,considering the constraints and actual conditions,the generalized Nash game is used to model the charging behavior of the electric vehicle,and the generalized Nash game model is transformed into a function optimization problem.The existence and uniqueness of the solution of the charging model of the electric vehicle are proved.In this thesis,the physical meaning and mathematical interpretation of particle swarm optimization are studied,and the model established in this thesis is solved by using it.At the same time,the constraint mechanism is added to the particle swarm optimization algorithm,which avoids the repeated generation of stochastic solutions conforming to the constraints.By using the optimization characteristics of the algorithm itself,the particle can find the optimal solution satisfying the constraints,and finally the number of iterations of the particle swarm optimization algorithm is reduced.In this thesis,the model is modeled and solved by MATLAB.Finally,simulation experiments are designed to simulate the impact of disorderly charging and orderly charging on power grid load under different permeability.Finally,it is proved that the model established in this thesis has played an optimized role in load curve and reduced peak-valley difference.Finally,the thesis introduces the infrastructure construction of the ordered charging project,and verifies the feasibility of the proposed ordered charging strategy through the experimental data in the background.