Research On Power Dispatch Management Of Energy Storage Charging Station For Large-scale Electric Vehicles

With the widespread adoption and application of electric vehicles(EVs),their uncoordinated charging activities pose serious challenges to the stability and operational efficiency of the power grid.To mitigate the impact of EV charging activities on the grid,coordinated optimization control strategies using energy storage systems have become a key solution.The charging station equipped with energy storage units,by integrating various power dispatch participants and formulating coordinated dispatch strategies,can achieve multi-element synergistic optimization.However,existing studies mainly focus on optimizing either the grid-side benefits or the user-side costs,struggling to balance the interests of multiple parties simultaneously.Moreover,the charging behaviors of numerous power dispatch participants are difficult to model and describe,with their high dimensionality and coupling characteristics leading to challenges in solving the control problems.Mean Field Game(MFG)theory offers a new perspective and tool for modeling and controlling large-scale systems and group behaviors,by studying the interactive behaviors and strategy choices among participants through dynamic game models.Therefore,this paper constructs an interactive energy system model centered on the electric grid,energy storage devices,and EVs under the framework of MFG theory.It focuses on the power dispatch management issue of energy storage the charging station to address the charging of a large number of EVs,aiming at coordinating and optimizing energy distribution strategies,providing new ideas and approaches for the optimization and adjustment of interactive energy systems.The specific research contents are as follows:Firstly,to explore the positive role of energy storage devices in interactive energy systems,an optimization problem aimed at minimizing the power dispatch cost of the charging station is proposed.Based on the MFG theory framework and considering the battery degradation cost of energy storage devices,power dispatch expenses,and EV charging demand,the Hamilton-Jacobi-Bellman equation solving method is used to formulate the optimal power dispatch strategy for energy storage devices.With the introduction of the mean field term,the optimal pricing strategy for the charging station under mean field equilibrium conditions is further obtained.In addition,the optimization problem is transformed into an equivalent set of forward-backward stochastic differential equations,with a corresponding iterative algorithm proposed to solve this set of equations.The formulation and implementation of dispatch strategies not only play a role in the power dispatch process of energy storage devices but also achieve efficient allocation of power resources.Secondly,to avoid the adverse fluctuations in the grid caused by uncoordinated charging of a large number of EVs,a charging control problem for heterogeneous EV groups is proposed.Within the MFG theory framework,a charging model considering the heterogeneity of EVs is constructed,aimed at balancing the power load of the grid and meeting the charging control needs of EVs.Through the use of mathematical tools such as variational analysis,the optimal power dispatch strategy for EV charging is obtained.Additionally,under the condition of supply-demand balance,the optimal pricing strategy for power transactions between the charging station and the EV group is formulated,and an iterative algorithm to solve the charging control problem is proposed.Effective power dispatch strategies promote orderly charging of EVs,balancing the grid load while enhancing the economic benefits for EVs.Then,to achieve joint optimization of the interests of both power dispatch participants,a charging station power dispatch problem based on principal-secondary participants is proposed.Taking into account the interests of both the charging station and EVs,and formulating optimal dispatch strategies for energy storage devices and optimal charging strategies for EVs,the goal is to minimize both the charging station dispatch cost and the EV charging cost.As these two optimization problems constitute a coupled control problem,the interaction between energy storage devices and EVs is modeled as a finite-time dynamic game process.A Nash certainty equivalence for the related optimization problems is further established,transforming the complex dynamic optimization problem into a more solvable form,and a solving algorithm for the Nash certainty equivalence set of equations is designed.This method not only simplifies the problem-solving process but also ensures that the formulation of dispatch strategies takes into account the economic interests of the charging station and the costeffectiveness of EVs.Finally,for the optimal economic objective of power dispatch for the EV aggregator,a two-layer optimal power dispatch problem is proposed.In the two-layer control framework,the lower-layer control is based on cooperative game theory,aiming to discuss the EV charging control strategies under the condition of social optimality.By applying the deterministic approximation method to solve the computational challenges caused by high dimensionality and coupled information in centralized control issues,the decentralized charging control strategies for EVs are designed to promote the common interest of the entire EV group.In the upper-layer control,based on the EV power demand statisticized by the lower layer,considering time-of-use electricity prices and other constraints,a power dispatch strategy between the charging station and the grid is formulated to minimize the energy dispatch cost of the charging station.Through the implementation of the two-layer control scheme,the minimization of the operating costs of the EV aggregator,is achieved.