Collaborative Optimization Model For Electric Vehicle-Power Grid-Electric Source Considering The Spatial And Temporal Charging And Discharging Characteristics Of Electric Vehicle

To achieve the dual carbon goal,China proposes the conception of new power system with new energy as the mainstay.However,new energy,represented by wind and solar power,is significantly uncertain and anti-peak load in power generation.With the increasing installed capacity of new energy,how to ensure the safe and stable operation of the power system has become an urgent problem that needs to be solved.At the same time,to reduce carbon emissions from the transportation industry,China vigorously promotes the application of electric vehicles.As a highly flexible mobile charging load and energy storage unit,the promotion and application of electric vehicles have brought opportunities and challenges to constructing new power systems.When large-scale EVs disorderly charging,it may further increase the peak load of the power grid.But,when electric vehicles respond to the requirements of the power system by orderly charging or discharging,they can reduce the peak load,increase the valley load,and promote the consumption of new energy.Therefore,how to guide electric vehicles in orderly charging and discharging,alleviating the uncertainty of new energy power generation,and maintaining the stability of the load,has become the focus of the construction of new power systems at this stage.In view of this,this thesis research the collaborative management of electric vehiclepower grid-electric source under the spatial and temporal charging and discharging characteristics of electric vehicles.Firstly,the space-time charging characteristics of electric vehicles are analyzed based on charging data from charging stations.Secondly,based on the spatiotemporal charging characteristics,the time-sharing response potentiality of charging and discharging for electric vehicles in different areas is explored.Thirdly,according to the response potentiality of charging,the collaborative configuration plan for charging facilities and distribution networks is studied to support the implementation of charging response.Finally,taking the time-sharing response potentiality of charging and discharging,grid load,and new energy power generation characteristics into account,the collaborative operation management model for electric vehicles,power grid,and electric sources was constructed,and the charging and discharging behavior of electric vehicles was adjusted by real-time charging and discharging electricity prices in different areas.The main research contents of this thesis are as follows.(1)Research on the relevant theory to electric vehicle charging and discharging behavior management.Firstly,the basic theory of demand response is sorted out,and the potentiality for charging and discharging response of electric vehicles with different purposes is explored based on their travel and charging characteristics.Therefore,this thesis proposes to take electric private vehicles as the research object in the collaborative management of electric vehicles-power grid-electric sources.Secondly,the data analysis theory and method,the system simulation theory and method,and the system optimization and decision-making theory and methods are analyzed,laying the theoretical and methodological foundation for the research on the spatiotemporal characteristics of electric vehicle charging,the response potentiality of electric vehicle charging and discharging,the coordinated configuration of charging facilities and distribution networks,and the coordinated operation management of electric vehicle-power grid-electric source.(2)Based on transaction data from charging stations,the space-time charging characteristics analysis model for electric vehicle users is constructed.Firstly,select indicators that reflect the spatiotemporal characteristics of user charging,such as charging time,charging location,and charging power.Secondly,according to the classification of urban functional areas,clarify the classification standards for charging stations,and propose an automatic classification method for charging stations with the help of geographic information.Thirdly,with the help of data analysis methods and data processing techniques,the spatiotemporal characteristics analysis model for electric vehicle users is constructed to analyze the charging duration,charging capacity,and charging time of electric vehicles in different functional areas.Finally,based on actual transaction data from charging stations,the spatiotemporal distribution of electric vehicle user charging is clarified.The results show that the charging capacity of electric vehicles decreases from high to low in residential areas,commercial areas,and work areas,and the distribution of charging time significantly varies in different functional areas,which proves that managing the charging and discharging behavior of electric vehicles according to functional areas is scientific and reasonable.(3)Considering the charging spatiotemporal characteristics of electric vehicles,the agent-based simulation model for the response potentiality of electric vehicles charging and discharging in different functional areas is constructed.Firstly,based on the state of charge for electric vehicles,the measurement method for the capacity,work and power in charging and discharging is proposed.Secondly,considering the impact of parking time,state of charge,and charging and discharging electricity price on the charging and discharging response willingness,the evaluation model for the response willingness of electric vehicle users in charging and discharging is established based on fuzzy reasoning approach.Thirdly,combined with the decision-making process of electric vehicle charging and discharging response,the agent-based simulation method is applied in the potentiality response measurement of electric vehicle charging and discharging in different functional areas.Finally,based on the charging characteristics and living habits of residents,the simulation parameters for different functional areas are designed,and the potentiality of electric vehicle charging and discharging response in a variety of charging scenarios are measured,which provides the foundation for the collaborative configuration of charging stations and distribution networks and the collaborative operation optimization of electric vehicle-power grid-electric source.The research results show that the distribution of electric vehicles charging and discharging response potentiality in different functional areas exhibits significant differences,and the distribution in similar functional areas exhibits certain similar characteristics.(4)The collaborative optimization model of charging station and distribution network configuration for multiple functional areas are built,considering the electric vehicles charging response potentiality.And to determine the collaborative configuration scheme under the uncertainty of charging response potentiality,the multi-scenario example is analyzed.Due to the fact that electric vehicle discharging is still in the exploratory stage,the research focuses on the construction of facilities supporting charging response.Firstly,taking the charging response potentiality of different functional areas obtained from the simulation model into account,the lower charging station site selection and capacity determination model was constructed with the goal of optimizing the construction and operation costs of charging stations,the driving costs from electric vehicles to charging stations,and the charging waiting costs.Secondly,under the constraints of the location and capacity of the charging station,the upper distribution network transformation model is constructed with the goal of optimizing the cost of line transformation and the cost of transformer expansion,determining the nodes where the charging station connects to the distribution network and achieving collaborative configuration between the charging station and the distribution network.Finally,the parameters of charging station and distribution network configuration examples are designed according to the time-sharing charging response potentiality and the charging characteristics of electric vehicles in different areas,and the improved particle swarm optimization algorithm is used to calculate the optimization results.The results show that there is similarity in the collaborative configuration plans under different charging response potentiality.To satisfy the variable charging response potentiality,the construction plan that covers the most optional charging station location nodes be selected.(5)Using real-time charging and discharging electricity prices in different functional areas as means for regulating the charging and discharging behavior of electric vehicles,the collaborative operation optimization model for electric vehicles,power grids,and new energy has been established.Firstly,considering the battery cost,the number of battery charging and discharging cycles,and the vehicle mileage,the discharge electricity price boundary of electric vehicles is measured.Secondly,the pricing model for charging and discharging electricity prices of electric vehicles is constructed based on the theory of price elasticity.Thirdly,with the goal of optimizing the load variance,wind and solar energy consumption,and the charging and discharging benefits of electric vehicles in different functional areas,the collaborative operation optimization model for electric vehicles,power grids,and new energy are constructed,under the constraints of the charging and discharging response potentiality of electric vehicle in different functional areas with low and high electricity prices.And the charging and discharging power and the real-time charging and discharging electricity prices for electric vehicles in different functional areas in collaborative operation are researched.Finally,based on the multi-Agent Deep Deterministic Policy Gradient algorithm,the cooperative operation optimization model for electric vehicles,power grids,and new energy is solved,and a case study with multiple charging and discharging response potentiality scenarios are given.The results show that the optimal charging and discharging time and price of electric vehicles in functional areas have both regularity and differences in coordinated operating of electric vehicle-power gridelectric source.To sum up,through a series of researches on the simulation of charging and discharging response potentiality,the collaborative optimization of charging station and distribution network configuration,and the collaborative operation optimization of electric vehicle-power grid-electric source,this thesis has formed a management system for collaborative optimization of electric vehicle-power grid-electric source that fully considering the spatiotemporal characteristics of electric vehicle charging and discharging.The research of this thesis enriches the relevant research theory of collaborative optimization of electric vehicle-power grid-electric source,and conductive to the sustainable development of China’s transportation and power industries,which has certain theoretical and practical value.