Research On Power Boosting And Operation Strategy Of Charging Pile Based On Distributed Mobile Energy Storage

In recent years,the user group of electric vehicles(EV)has become larger and larger.As a supporting charging infrastructure,the rapid recharging ability of EV charging piles and how to establish an effective operating mechanism according to this ability have gradually become the focus of the industry.From the perspective of grid security,high-power charging,especially large-scale high-power charging,is very easy to cause high peak load and load spikes.From the perspective of grid economy,the cost of expansion and transformation of the distribution network is high and the capacity utilization rate is low.Charging piles have a single operational business model with very few means to make profits.As a kind of energy buffer device,distributed mobile energy storage has been effectively applied for boosting the power capacity of charging piles,and it has enriched the operation modalities of charging piles.Therefore,the research on power boosting of charging piles based on distributed mobile energy storage has become the focus of this paper.First,for the high-power fast recharging scenario of electric vehicles under the condition of limited distribution network capacity,a charging pile power enhancement system based on two-way energy buffer is designed;energy information technology and energy storage battery dynamic reconfiguration technology are used to solve the energy management problem of charging and discharging of battery modules with differing characteristics.The differentiated charging and discharging performance of different energy storage batteries are used to improve the grid capacity.t A fast recharging mode of “energy following the user” is proposed to realize the temporal and spatial scheduling and control of energy storage battery modules to boost charging pile power.New energy operation mechanism is designed to manage multiple charging pile interfaces.Secondly,statistical modeling is used to fit the charging behavior of users who choose the fast charging mode.A daily load model is established based on data mining.Based on the daily load model and the output of distributed power sources,a scheduling model for distributed mobile energy storage is proposed.Optimal dispatching strategy is developed using rolling optimization and feedback correction based on model predictive control.The deviation of actual value from planned value caused by large day-ahead forecast errors is reduced.Based on this,the charging and discharging control strategy are improved,and optimal scheduling for distributed mobile energy storage is realized.The effectiveness of the proposed strategy is validated through comparison of the new model predictive control based scheduling strategy with the existing methods.Finally,starting from the two aspects of the approved cost and the optimal electricity pricing,the operation income of the energy operation mechanism developed in this thesis is calculated.In terms of approved costs,an optimized configuration plan for energy storage capacity based on energy consumption frequency model is proposed to obtain energy storage operating costs and dispatch costs.This helps completing the cost verification of distributed mobile energy storage.In determining the optimal electricity price,the impact of real-time scheduling of mobile energy storage on operating income is considered.An electricity pricing strategy is proposed based on the two dimensions of time and space.Electricity price elasticity matrix and genetic algorithm are used to compute the optimal time-of-use electricity price and its profit value under different scenarios.Compared with the operating income of fixed energy storage,the advantages of operating distributed mobile energy storage is demonstrated.