Research On Impact Of Electric Vehicle Scale Access On Transformer And Control Method

As the world's environmental problems and energy shortage become increasingly serious,electric vehicles,as a new alternative transportation technology,have been widely used.Compared with the traditional internal combustion engine,electric vehicles have various advantages,such as lower maintenance cost and less emissions.However,due to the uncertain characteristics of EV charging,such as volatility,indirectness and randomness,new challenges have been put forward to the existing power system,which will have a non-negligible impact on the power grid and cause certain loss of transformer life.Therefore,it is necessary to analyze the advantages and disadvantages of the continuous development of electric vehicles,so as to enhance their strengths and offset their weaknesses and reduce their impact on the power grid.This paper mainly studies the impact of large-scale electric vehicles connected to the power grid on the transformer aging life loss,and proposes an EV charging scheduling optimization method considering energy arbitrage,the lowest cost of distribution network and the reduction of transformer life loss.The main work and results are as follows:1.Aiming at the calculation of EV charging load,this paper establishes an EV charging load model by analyzing the influencing factors of users' travel habits,charging behavior habits,charging power selection,EV type and other factors that cause deviation in EV charging load calculation.Combined with monte Carlo stochastic simulation method,the random charging load of EV under different infiltration is calculated by MATLAB simulation,which lays a foundation for evaluating the influence of different charging loads on transformer aging.2.In view of the electric car disordered charge influence on power transformer,this paper put forward by the IEC heat transformer model and the life loss,from under the permeability of electric vehicles and charging load under different environment to assess the life of the transformer loss is analyzed,additional,we also analyzed the transformer in electric vehicle charging failure rate,it can be seen that the electric car will lead to large-scale charging transformer temperature rising fast and even may be overloaded,had a huge impact on life lost,and transformer in the overload operation failure rate continues to rise,left a hidden danger for the safe operation.3.In order to mitigate the impact of unordered charging of EVs on transformers,this paper proposes an EV charging scheduling optimization method that considers energy arbitrage,minimizes the cost of distribution network and reduces the transformer life loss.The optimization strategy focuses on reducing the loss of energy arbitrage gains for EVs owners and introducing penalty costs,as well as assessing peak demand,power loss and transformer aging.This optimization strategy USES genetic algorithm to optimize each parameter.The case proves that the charging mode of EV optimized by this optimization strategy has the lowest peak demand cost,power loss cost and transformer life loss cost.