Research On The Access Control Of Large-Scale Charging Load In Distribution Network With Constant Capacity

With the transformation of the national energy structure and the continuous promotion of carbon peaking and carbon neutrality goals,the disorderly grid connection of large-scale new energy vehicles will cause problems such as the degradation of power quality of the distribution network system,the increase of system network loss,and the severe overload of the distribution network under the green and low-carbon background.The behavior optimization model of large-scale new energy vehicles can not only improve the acceptance capacity of the stock distribution network,but also promote the consumption of new energy,and help the realization of the "double carbon" goal.This paper focuses on the access control of large-scale charging load in the stock distribution network and researches the load characteristics and simulation modeling analysis of electric vehicles,the gridconnected power control of charging piles in the stock distribution network,and the orderly charging control in the charging area of the distribution network,respectively.(1)A multi-level user senseless coordination control strategy for electric vehicles is proposed.A distribution network charging pile simulation model with a multi-port power router as the core is established,and a multi-level user senseless charging pile coordination control strategy is proposed to control the power flow between different ports in real time and realize the coordination of multiple sources and loads.(2)A model for grid-connected power control of distribution network charging piles considering the characteristics of regional clusters is proposed:large-scale charging load;uncertainty in both space and time;control of charging load accession;distribution network operation optimization.The load characteristics of electric vehicles under spatial and temporal uncertainties are analyzed;an electric vehicle simulation model based on the load characteristics is established,and the fitted curves between grid-connected power and harmonic components are obtained;The clustering characteristics of electric vehicles under different types of charging piles are analyzed,and a model of regional clustering characteristics of electric vehicles is established based on the analysis results;a model of grid-connected power control of electric vehicle distribution network charging piles considering regional clustering characteristics is established to realize orderly charging of electric vehicles by controlling the grid-connected power of electric vehicles in different clusters;A senseless control strategy for users considering the characteristics of regional clusters is proposed,which solves the problem of dispatching electric vehicles across time scales with emergency use by users based on effectively reducing the charging cost of distribution network charging posts.(3)An orderly charging control model for distribution network charging area considering source-load bilateral uncertainty is proposed:A distribution network operation scenario generation model based on Latin hypercube sampling is established,and ten typical distribution network operation scenarios with their probability distributions are obtained by generating a large number of distribution network operation scenarios to simulate the uncertainty of source-load bilaterals;To realize the orderly control of grid-connected power and grid-connected location of scaled EVs,a two-layer EV charging control model in the distribution network charging area considering the distribution network operation scenario is established:the lower layer EV grid-connected power control model based on constrained unit commitment optimizes the distribution network operation cost Considering the cluster characteristics of different regions and the uncertainty of the source-load bilaterals,orderly controls the grid-connected charging and discharging power of scaled EVs;the EV gridconnected upper location control model based on optimal tide optimizes the distribution network operation loss,and orderly controls the charging nodes of large-scale electric vehicles.