Research On Layered Reactive Power Scheduling Strategy Of Charging Station Based On V2G Technology

Reactive power compensation is one of the most effective measures to improve power quality and economic operation efficiency of power grid.As the share of new energy vehicles increases year by year,THE V2 G technology of EV can replace the traditional reactive power compensation equipment.Based on the basic idea of V2 G technology,this thesis proposes a V2 G reactive power scheduling strategy based on the combination of non-dominated sorting genetic algorithm and local optimization algorithm of global objective,and verifies the effectiveness of the scheduling strategy for the charging station system in Matlab.The main contents of this thesis are:First of all,this thesis mainly introduces the V2 G technical theory and the current situation and development trend of scheduling charging algorithm,and summarizes the advantages and disadvantages of existing technologies and the limitations of scheduling charging algorithm.The reactive capacity of charging pile is modeled,and the structure,distributed control strategy and circuit parameters of bidirectional converter are analyzed.The running state of the battery under five working conditions is simulated and verified by Simulink simulation,which lays a foundation for the subsequent reactive power optimization using V2 G technology.Secondly,the functional characteristics of the root charging station operator create a hierarchical charging station scheduling architecture,and the superstructure is an orderly charging strategy of ev based on non-dominated sorting genetic algorithm.The lower architecture is a V2 G reactive power optimization strategy based on orderly charging strategy and global objective minimization.Combined with the constraints of hierarchical architecture analysis;A mathematical model for reactive power optimization of charging stations was established,which took load mean square deviation,charging cost and voltage offset rate as the objective function.It was determined that the standard deviation of the user’s starting charge was the optimization variable in the upper architecture,and the active charging and reactive power compensation ratio of charging piles were the optimization variables in the lower architecture.The realization flow of reactive power optimization is developed based on the model.Finally,in order to verify the effectiveness of the V2 G reactive power optimization strategy in this thesis,an IEEE100 node multiplexing charging station system is constructed.Combined with the charging behavior of ev users in the charging station,the distribution of grid base load and the charging power demand,the electrical parameters of each node were calculated within the allowable error range through the calculation method of forward and back power flow.Finally,Matlab was used to verify the effectiveness and feasibility of the proposed strategy.The simulation results show that the charging station system can effectively maintain the smooth operation of the power grid,improve the economy,and reduce the voltage offset rate and network loss after selecting the charging scheme of the proposed strategy.