| At present,energy is the key factor constraining the economic growth and acceleration of industrial structure transformation in our country.In order to achieve the long-term goals of energy diversification and low-carbon development,the research and development of renewable energy sources such as wind and solar power,as well as electric vehicles,are being vigorously promoted.However,the large-scale integration of electric vehicles into the grid poses serious challenges to the stability of the power grid.Meanwhile,the integration of renewable energy sources,due to their random and discontinuous nature,also poses challenges to the safe and stable operation of the power grid.Electric vehicles can utilize V2G(vehicle-to-grid)technology to provide ancillary services and reduce load fluctuations.Therefore,the planning and control of electric vehicle charging and discharging loads urgently need to be strengthened.This paper carries out research on the spatio-temporal interactive optimization dispatching of electric vehicle-integrated microgrid systems based on multi-level control,with the main research areas as follows:Firstly,a mathematical model is established for distributed generation units.In addition,to achieve the planning and control of electric vehicle charging and discharging loads,it is necessary to study the spatiotemporal characteristics of electric vehicles and investigate their charging patterns.To this end,this paper explores the corresponding travel patterns and establishes a mathematical model.Then,by simulating the charging behavior of electric vehicles under non-scheduled conditions,the study shows that there will still be a significant number of electric vehicles charging during the peak hours of electricity consumption at night,which undoubtedly further widens the gap between peak and valley loads.Under these circumstances,the safety and stability of the power grid cannot be guaranteed.Secondly,two coordination and scheduling strategies for electric vehicle clusters are established,one for optimizing electric vehicle user charging costs and the other for optimizing microgrid load fluctuations.By comparing them with non-scheduled charging behavior,it is found that these two scheduling strategies have their own advantages in reducing user charging expenses and smoothing peak and valley loads.However,these two strategies are not perfect.The former can significantly save user charging expenses but is ineffective in filling the valley.The latter is effective in filling the valley but leads to higher user charging expenses,which cannot fully stimulate the enthusiasm of users to participate in power system scheduling.Finally,considering the shortcomings of cluster scheduling strategies and the study of user participation in scheduling,a new energy microgrid multi-level vehicle-grid coordinated optimization strategy is proposed,taking into account user enthusiasm.The optimization process of the new energy microgrid is divided into the load layer,microgrid layer,and distribution network layer from a new perspective.The load layer considers electric vehicles as a means of controlling load and optimizes electricity consumption through time-of-use pricing while taking into account user enthusiasm.To maximize the fit with the clean energy output trend,the microgrid layer uses clean energy to support the optimized load at the upper layer and involves electric vehicles and energy storage in auxiliary regulation.The net load surplus is absorbed by the main grid and gas turbine in the distribution network layer,and the surplus clean energy is fed into the grid to obtain revenue,achieving a high degree of unity between economy and security.Simulation calculations are carried out using a regional power grid,and the optimization results of each layer are analyzed and compared with non-layered strategies.The results show that the proposed strategy can achieve win-win situations for multiple stakeholders,verifying the rationality and effectiveness of the proposed method. |
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