Station area status determination method and electric vehicle hierarchical control method based on distribution network

Abstract

Embodiments of the present application provide a method for determining the status of a station area and a method for hierarchical regulation and control of electric vehicles based on a distribution network, which relate to the technical field of charging control. Among them, the method includes: obtaining the charging demand of a load and the historical charging data of the load; determining the value of each influencing factor based on the charging period, historical charging data, and charging amount demand, determining the coefficient of the value of the influencing factor based on the location information of the station area, and determining multiple load rate thresholds based on the influencing factor and the corresponding coefficient; determining the load status of the station area according to the relationship between the current load rate of the station area and the multiple load rate thresholds; generating service capacity information for the station area to respond to the charging demand based on the load status. At the same time, a method for hierarchical regulation and control of electric vehicles based on a distribution network is also provided. The embodiments of the present application are applied to the optimal scheduling of a charging station area to ensure the normal load of the station area.

Description

Technical Field

[0001] The present application relates to the technical field of charging control, and specifically relates to a method for determining a station area state, a method for hierarchical regulation and control of electric vehicles based on a distribution network, a system for hierarchical regulation and control of electric vehicles based on a distribution network, an electronic device, and a corresponding storage medium. Background Art

[0002] In recent years, the sales proportion of new energy vehicles has continued to increase, forming a structural growth trend in the domestic automobile market. New energy vehicles still have very broad development and application scenarios and will also be accepted and used by more consumers. The adaptability assessment of the distribution network to the large-scale access of electric vehicles and the guidance of the charging and discharging of electric vehicles are important factors to be considered in the future operation and planning of the distribution network. The large-scale access of electric vehicles to the distribution network will increase the difficulty of operation and control of the distribution network and reduce the economy of the distribution network. To meet the charging needs of a large number of electric vehicle owners and maintain the safety and stability of the operation of the distribution network, relevant policies and plans need to be formulated to guide the orderly charging and discharging of electric vehicles. An effective orderly charging and discharging guidance strategy can not only balance the interests of all parties, but also help improve the utilization rate of charging facilities and the flexibility of the distribution network. The fast charging load of electric vehicles usually adopts a high-power fast charging method, and the charging time and space are extremely uncertain, resulting in a large charging power, strong intermittency and volatility of the charging load during the peak power consumption period of some public charging stations. If these fast charging loads are not intervened, it will cause a decline in the power quality of the distribution network, overload of electrical equipment, and voltage over-limit at some nodes.

[0003] When an electric vehicle aggregator conducts centralized management and control of an electric vehicle cluster, it generally defaults that all electric vehicle clusters within the research area participate in the optimal scheduling, without considering the impact of the travel behavior, charging behavior, and user preference behavior of electric vehicles on the willingness of users to participate in demand response. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method for determining a station area state and a method for hierarchical regulation and control of electric vehicles based on a distribution network. With the goal of improving user satisfaction, comprehensively considering the location of charging stations, user travel characteristics, charging date, time, and user historical charging information, by optimizing the scheduling of electric vehicles with adjustable characteristics from the charging station area and the distribution network substation side, to at least solve some of the problems in the background art.

[0005] To achieve the above object, a method for determining the status of a station area is provided in the present application. The method includes: obtaining the charging demand of the load and the historical charging data of the load; determining the value of each influencing factor based on the charging period, historical charging data, and charging amount demand, determining the coefficient of the value of the influencing factor based on the location information of the station area, and determining a plurality of load rate thresholds based on the influencing factor and the corresponding coefficient; determining the load status of the station area according to the relationship between the current load rate of the station area and the plurality of load rate thresholds; generating service capacity information for the station area to respond to the charging demand based on the load status.

[0006] Optionally, after obtaining the charging demand, the method further includes: calculating and determining whether the power flow of the line in the station area is in a convergent state; when the power flow is in a convergent state, continuing to execute the subsequent steps.

[0007] Optionally, determining the value of each influencing factor based on the charging period, historical charging data, and charging amount demand includes: mapping the date in the charging period to a value in a first numerical set; mapping the time in the charging period to a value in a second numerical set; mapping the historical charging method in the historical charging data during the same period to a boolean value; mapping the historical charging amount in the historical charging data during the same period to a value in a third numerical set; mapping the charging amount demand to a value in a fourth numerical set.

[0008] Optionally, the number of the load rate thresholds is determined according to the classification of the service capacity information.

[0009] Optionally, the service capacity information is classified as: meeting the fast charging demand, meeting the limited fast charging demand, or meeting the slow charging demand; correspondingly, the number of the load rate thresholds is three.

[0010] Optionally, determining the load status of the station area according to the relationship between the current load rate of the station area and the plurality of load rate thresholds includes: when the current load rate is less than the minimum value of the plurality of load rate thresholds, determining that the load status of the station area is a light load state; when the current load rate is greater than the maximum value of the plurality of load rate thresholds, determining that the load status of the station area is a critical fault state; when the current load rate is between the minimum value and the maximum value of the plurality of load rate thresholds, determining that the load status of the station area is an intermediate state; when there are other load rate thresholds after removing the minimum value and the maximum value from the plurality of load rate thresholds, further dividing the intermediate state based on the other load rate thresholds.

[0011] Optionally, the number of the load rate thresholds is three, and the intermediate state is divided into an overload state and a heavy load state based on one threshold after removing the minimum value and the maximum value; the load rate of the overload state is lower than that of the heavy load state.

[0012] Optionally, generating service capacity information for the station area to respond to the charging demand based on the load status includes: when the load status of the station area is a light load status, determining whether the station area meets the fast charging demand or the load status becomes an overloaded status after the load is connected in the fast charging mode according to the relationship between the availability rate of fast charging piles in the station area and the first availability rate threshold; when the load status of the station area is an overloaded status, determining whether the station area meets the restricted fast charging demand or the load status becomes a heavily loaded status after the load is connected in the slow charging mode according to the relationship between the availability rate of fast charging piles in the station area and the second availability rate threshold; when the load status of the station area is a heavily loaded status, determining whether the station area meets the slow charging demand or the station area is converted into a critical fault status according to the relationship between the availability rate of slow charging piles in the station area and the third availability rate threshold.

[0013] Optionally, determining whether the station area meets the fast charging demand or the load status becomes an overloaded status after the load is connected in the fast charging mode according to the relationship between the availability rate of fast charging piles in the station area and the first availability rate threshold includes: when the availability rate of fast charging piles is greater than the first availability rate threshold, determining that the station area meets the fast charging demand; when the availability rate of fast charging piles is not greater than the first availability rate threshold, calculating the overall availability rate of charging piles after the fast charging demand is connected based on the number of fast charging loads in the station area after the fast charging demand is connected and a first-level control function; the first-level control function is a piecewise function, which is divided into a linear function, an inverse proportional function, and a constant function based on the number of loads of the fast charging demand; determining whether the station area meets the fast charging demand or the load status is converted into an overloaded status according to the overall availability rate of charging piles in the station area after the fast charging demand is connected.

[0014] Optionally, determining whether the station area meets the restricted fast charging demand or the load status becomes a heavily loaded status after the load is connected in the fast charging mode according to the relationship between the availability rate of fast charging piles in the station area and the second availability rate threshold includes: when the availability rate of fast charging piles is greater than the second availability rate threshold, determining that the station area meets the restricted fast charging demand; when the availability rate of fast charging piles is not greater than the second availability rate threshold, calculating the overall availability rate of charging piles after the slow charging demand is connected based on the number of charging loads in the station area after the slow charging demand is connected and a second-level control function; the second-level control function is a piecewise function, which is divided into a linear function, an inverse proportional function, and a constant function based on the number of loads of the slow charging demand; determining whether the station area provides restricted fast charging service or the load status is converted into a heavily loaded status according to the overall availability rate of charging piles in the station area after the slow charging demand is connected.

[0015] Optionally, when the load status of the station area is a critical fault status, new charging demands are prohibited from entering and a self-regulation control strategy is executed; the termination condition for executing the self-regulation control strategy is that the load status of the station area is not a critical fault status or the execution duration reaches a preset duration.

[0016] Optionally, when the self-regulating control strategy is executed for a preset duration but the load status of the station area is still in a critical fault state, a request is sent to the distribution network side to adjust the load of this station area.

[0017] Optionally, the distribution network side is further configured to: determine whether the power flow in the background area converges after adjustment, and provide the sharing of service capacity information for each station area under this substation area.

[0018] In this application, a hierarchical control method for electric vehicles based on the distribution network is also provided. The method includes: in response to the charging demand of an electric vehicle, sending the charging demand and the historical charging data of the electric vehicle to alternative station areas, and each alternative station area determines service capacity information based on the foregoing station area status determination method; pushing the alternative station areas and the service capacity information of the alternative station areas to the electric vehicle.

[0019] Optionally, the charging demand of the electric vehicle comes from a charging pile; the charging pile is configured to: make a preliminary prediction of the user's charging behavior in combination with the user's historical charging data, and generate the charging demand based on the prediction result.

[0020] Optionally, the alternative station areas are determined through the following steps: obtaining the location information of the electric vehicle; taking at least one substation area whose coverage includes the location information as an alternative substation area; selecting at least one station area from all the station areas under the alternative substation area as an alternative station area.

[0021] In this application, a hierarchical control system for electric vehicles based on the distribution network is also provided. The system includes: a charging pile side, which is used to generate the charging demand of the electric vehicle based on the upcoming charging behavior and charging historical data; a charging station side, which is used to determine the service capacity information of this station area by using the foregoing station area status determination method; a distribution network side, which is used to obtain the service capacity information of each station area within this substation area and generate the service capacity information of this substation area; the service capacity information of the station area or substation area is pushed to the electric vehicle for the electric vehicle to select a station area based on the service capacity information.

[0022] In this application, an electronic device is also provided, including: at least one processor; a memory connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the at least one processor realizes the foregoing station area status determination method or the hierarchical control method for electric vehicles based on the distribution network by executing the instructions stored in the memory.

[0023] In this application, a machine-readable storage medium is also provided. Instructions are stored on the machine-readable storage medium, and when the instructions are executed by a processor, the processor is configured to execute and implement the foregoing station area status determination method or the hierarchical control method for electric vehicles based on the distribution network.

[0024] In this application, a computer program product is also provided, including a computer program which, when executed by a processor, implements the foregoing method for determining the station area state or the method for hierarchical regulation and control of electric vehicles based on the distribution network.

[0025] The above technical solution has the following beneficial effects:

[0026] (1) An access control threshold function covering various factors such as date, time, vehicle historical simultaneous charging, vehicle historical simultaneous charging amount, remaining power, etc. is designed. By determining the limit values of charging electric vehicles in the charging station at different times and different dates through various factors, the line load in the station area is ensured to be within the normal range.

[0027] (2) By comprehensively considering various influencing factors such as the location of the charging station, user travel characteristics, charging date, time, and user historical charging information, and through optimizing the scheduling of electric vehicles with adjustable characteristics from the charging station area and the distribution network substation side, fully considering the charging station load situation of user needs, a reasonable charging scheduling scheme is designed.

[0028] Other features and advantages of the embodiments of this application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings are used to provide a further understanding of the embodiments of this application, and constitute a part of the specification. Together with the following specific implementation, they are used to explain the embodiments of this application, but do not constitute a limitation to the embodiments of this application. In the drawings:

[0030] Figure 1 Schematically shows a step diagram of the method for determining the station area state according to the embodiment of this application;

[0031] Figure 2 Schematically shows a diagram of the primary control function according to the embodiment of this application;

[0032] Figure 3 Schematically shows a diagram of the secondary control function according to the embodiment of this application;

[0033] Figure 4 Schematically shows a process diagram on the side of the electric vehicle and the charging pile according to the embodiment of this application;

[0034] Figure 5 Schematically shows a process diagram on the side of the charging station according to the embodiment of this application;

[0035] Figure 6 Schematically shows a process diagram on the side of the distribution network according to the embodiment of this application;

[0036] Figure 7 Schematically shows the internal structure diagram of an electronic device according to an embodiment of the present application. Specific embodiments

[0037] The following will describe in detail the specific embodiments of the embodiments of the present application in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application.

[0038] Figure 1 Schematically shows the step diagram of a method for determining the station area state according to an embodiment of the present application. As Figure 1 shown, a method for determining the station area state includes:

[0039] S01. Obtain the charging demand of the load and the historical charging data of the load;

[0040] S02. Determine the value of each influencing factor based on the charging period, historical charging data, and charging amount demand, determine the coefficient of the value of the influencing factor based on the location information of the station area, and determine multiple load rate thresholds based on the influencing factor and the corresponding coefficient;

[0041] S03. Determine the load state of the station area according to the relationship between the current load rate of the station area and the multiple load rate thresholds;

[0042] S04. Generate service capacity information for the station area to respond to the charging demand based on the load state.

[0043] Through the above embodiments, multiple factors are comprehensively considered to determine the load rate threshold. By flexibly adjusting the load rate threshold, the determination of the load state of the station area is made more accurate, and thus more precise load regulation is achieved. This embodiment avoids the problem of inaccurate load regulation caused by a fixed load rate threshold.

[0044] In some alternative embodiments, the historical charging data can be obtained in the following manner. First, on the premise of the user's voluntary permission, user information is collected for the electric vehicle to be charged. The data collected on charging behavior includes: battery capacity, historical charging records, charging location records, historical power consumption records, charging rate preferences, habitual charging time, and charging duration, and a user charging behavior matrix is formed and uploaded to the charging pile side.

[0045] The charging pile with computing and analysis capabilities cleans, preprocesses, and fuses the data uploaded by electric vehicles. Through algorithm analysis of user travel information, it models the user travel behavior and classifies the vehicle types. The charging pile combines the analysis results of user behavior characteristics to simply predict the user's electricity consumption demand and uploads information such as the user's charging demand, including fast and slow charging demand and charging volume demand.

[0046] The fast and slow charging demands can be judged in the following ways: The charging management platform in this station area analyzes the information uploaded by the charging pile to determine whether the electric vehicle joining this charging station reports a fast charging demand for this charging. If there is no reported fast charging demand, regular charging is directly carried out; according to the user travel mode combined with the charging station location information and time information, the corresponding charging method can be automatically selected. For example, for taxis with a high demand for fast charging, family cars and official cars located in the service area of the charging station are defaulted to fast charging.

[0047] In some alternative implementation manners of the present application, after obtaining the charging demand, the method further includes: calculating and judging whether the power flow of the line in the station area is in a converged state; when the power flow is in a converged state, continue to execute the subsequent steps. Power flow calculation is the basis of power system steady-state calculation, and its solution has very important significance. This implementation manner judges the convergence of the power flow before calculating the load state, which is beneficial to determining the stable state of the station area and improving the accuracy of the station area load calculation.

[0048] In some embodiments of the present application, determining the value of each influencing factor based on the charging period, historical charging data, and charging amount requirement includes: mapping the date in the charging period to a value in the first numerical set; the station area can automatically synchronize time and save and record date information such as whether it is a holiday, a weekend, or a working day, while retaining the time information; mapping the holiday date information to the first numerical set a = [1, 2, 3, 4, 5, 6, 7, 8, 9]. For example, days with relatively large traffic volumes such as the day before a legal holiday, the holiday itself, and the last day of the holiday can be set to three levels of [7, 8, 9] according to historical data. Mapping the time in the charging period to a value in the second numerical set; for different times of the day, map the charging time to the second numerical set b = [1, 2, 3, 4, 5, 6, 7, 8, 9] according to the locations of different charging stations; for example, map the time from 20:00 at night to 5:00 in the morning in a residential area or community to three levels of b = [7, 8, 9]; map the time from 5:00 in the morning to 20:00 at night on highways, roads, etc. to three levels of b = [7, 8, 9]; particularly, according to the national highway holiday travel policy in China, after 0:00 on the first day of a legal holiday and before 24:00 on the last day of the holiday, the number of vehicles traveling on the highway may reach the maximum. The holiday date can be taken as 9; the time is set to 9. Mapping the historical charging method in the historical charging data to a Boolean value; for the vehicle's historical charging method in the same period, this value takes 0 or 1. When fast charging is required, it is set to 1, and for conventional slow charging, it is 0. Mapping the historical charging amount in the historical charging data to a value in the third numerical set; for the vehicle's historical charging amount in the same period, directly read the charging amount of this electric vehicle in the historical period and map it to the second numerical set c = [1, 2, 3, 4, 5, 6, 7, 8, 9], where 1 represents that the historical charging amount is below 10% and below 20% of the battery capacity, and 9 represents that the historical charging amount is above 90%. The larger the historical charging amount, the more power may be required at this moment. Mapping the charging amount requirement to a value in the fourth numerical set; the charging amount requirement can be represented by the remaining battery power, which is the actual remaining capacity of the vehicle's battery at this moment. The less the remaining capacity, the more power is needed. This fourth numerical set can adopt the aforementioned 9-level setting. This embodiment provides multiple influencing factors and their quantification processes, providing a data basis for the accuracy of threshold determination.

[0049] Determining the coefficient of the value of the influencing factor based on the location information of the station area includes the following steps: First, determine the area where the charging station is located, which is divided into the following categories: public charging stations in residential communities, public charging stations in work areas such as companies, office buildings, office blocks, and factories, public charging stations on roads such as highways and national roads, and public charging stations in highway service areas. Set the coefficients of each of the aforementioned influencing factors to α, β, γ, δ, η respectively, where α + β + γ + δ + η = 1. Then there are:

[0050] The threshold function Ω = (α × date + β × time + γ × vehicle's historical charging method during the same period + δ × vehicle's historical charging amount during the same period + η / remaining battery power) / 5.

[0051] Among them, the values of α, β, γ, δ, and η can be determined differentially according to different charging scenarios. For example: During weekdays: Public charging stations in residential communities: α < 0.2, β > 0.2, γ = δ = η = 0.2; Public charging stations in work areas such as companies, office buildings, office blocks, factories, etc.: α < 0.2, β < 0.2, γ = δ < 0.2, η > 0.2; Public charging stations on roads such as highways and national roads: α < 0.2, β < 0.2, γ = δ > 0.2, η > 0.2; Public charging stations in highway service areas: α < 0.2, β > 0.2, γ = δ < 0.2, η > 0.2.

[0052] During weekend breaks: Public charging stations in residential communities: α > 0.2, β > 0.2, γ = δ = 0.2, η = < 0.2; Public charging stations in work areas such as companies, office buildings, office blocks, factories, etc.: α > 0.2, β < 0.2, γ = δ < 0.2, η > 0.2; Public charging stations on roads such as highways and national roads: α > 0.2, β < 0.2, γ = δ > 0.2, η > 0.2; Public charging stations in highway service areas: α > 0.2, β > 0.2, γ = δ < 0.2, η > 0.2.

[0053] During legal holiday short breaks: Public charging stations in residential communities: α > 0.2, β > 0.2, γ = δ < 0.2, η < 0.2; Public charging stations in work areas such as companies, office buildings, office blocks, factories, etc.: α < 0.2, β < 0.2, γ = δ > 0.2, η > 0.2; Public charging stations on roads such as highways and national roads: α > 0.3, β > 0.2, 0.2 > γ = δ > 0.1, 0.3 > η > 0.2; Public charging stations in highway service areas: α > 0.3, β > 0.2, γ = δ < 0.1, 0.3 > η > 0.2.

[0054] It can be seen from this that for the selection of the aforementioned multiple load rate thresholds, it is necessary to make a selection in combination with aspects such as the charging station location, charging date, charging time, and vehicle charging demand. It is not a fixed value and needs to be determined in combination with the actual situation.

[0055] In some embodiments of the present application, the number of load rate thresholds is determined according to the classification of service capacity information. When the service capacity information is divided into multiple categories or multiple intervals, the corresponding load rate intervals also need to be adapted, and the number of corresponding load rate thresholds is also determined according to the divided load rate intervals.

[0056] In the previous embodiment, the service capacity information is classified according to the charging capacity that can be provided to the electric vehicle, so it can be classified as: meeting the fast charging demand, meeting the limited fast charging demand, or meeting the slow charging demand; correspondingly, meeting the limited fast charging demand includes: restricting users with fast charging demand or coordinately adopting the slow charging method, etc. Adding the above classifications to the situation where charging service cannot be provided due to excessive load, there are a total of 4 categories at this time, and the corresponding load rate intervals are also 4, so the number of load rate thresholds required is 3.

[0057] In some embodiments of the present application, according to the relationship between the current load rate of the station area and the multiple load rate thresholds, the load state of the station area is determined, including: when the current load rate is less than the minimum value of the multiple load rate thresholds, it is determined that the load state of the station area is a light load state; when the current load rate is greater than the maximum value of the multiple load rate thresholds, it is determined that the load state of the station area is a critical fault state; when the current load rate is between the minimum value and the maximum value of the multiple load rate thresholds, it is determined that the load state of the station area is an intermediate state; when there are other load rate thresholds after removing the minimum value and the maximum value from the multiple load rate thresholds, the intermediate state is further divided based on the other load rate thresholds. This embodiment shows the situation of at least two load rate thresholds. When there are two load rate thresholds, the load state of the station area is divided into a light load state, an intermediate state, and a critical fault state.

[0058] In some embodiments of the present application, the number of the load rate thresholds is three, and the intermediate state is divided into an overload state and a heavy load state based on one threshold after removing the minimum value and the maximum value; the load rate of the overload state is lower than that of the heavy load state. The number of the load rate thresholds in this embodiment is set corresponding to the service capacity information of meeting the fast charging demand, meeting the limited fast charging demand, or meeting the slow charging demand described above. Generally, the light load state corresponds to meeting the fast charging demand, the overload state corresponds to meeting the limited fast charging demand, the heavy load state corresponds to meeting the slow charging demand, and the critical fault state corresponds to being unable to charge. However, in actual scenarios, other factors also need to be comprehensively considered for more detailed evaluation. This embodiment designs a hierarchical control function and a control method for charging stations with different load conditions. When the charging station is in a high load situation, different regulation methods are designed according to the light load, overload, heavy load, and critical fault states, etc., to protect the charging station from entering a fault state.

[0059] In some embodiments of the present application, generating service capacity information for the station area to respond to the charging demand based on the load status includes: when the load status of the station area is in a light load state, that is, within the interval of the lowest load rate, determining whether the station area meets the fast charging demand or the load status becomes overloaded after the load is connected in a fast charging manner according to the relationship between the available rate of fast charging piles in the station area and the first available rate threshold; when the load status of the station area is in an overloaded state, determining whether the station area meets the restricted fast charging demand or the load status becomes heavily loaded after the load is connected in a slow charging manner according to the relationship between the available rate of fast charging piles in the station area and the second available rate threshold; when the load status of the station area is in a heavily loaded state, determining whether the station area meets the slow charging demand or the station area is converted into a critical fault state according to the relationship between the available rate of slow charging piles in the station area and the third available rate threshold.

[0060] In some embodiments of the present application, determining whether the station area meets the fast charging demand or the load status becomes overloaded after the load is connected in a fast charging manner according to the relationship between the available rate of fast charging piles in the station area and the first available rate threshold includes: when the available rate of fast charging piles is greater than the first available rate threshold, determining that the station area meets the fast charging demand; when the available rate of fast charging piles is not greater than the first available rate threshold, calculating the overall available rate of charging piles after the fast charging demand is connected based on the number of fast charging loads and the first-level control function after the fast charging demand is connected to the station area; the first-level control function is a piecewise function, which is divided into a linear function, an inverse proportional function, and a constant function based on the number of loads of the fast charging demand; determining whether the station area meets the fast charging demand or the load status is converted into an overloaded state according to the overall available rate of charging piles in the station area after the fast charging demand is connected.

[0061] For the above logic, the example is as follows: when the load status of the station area is in a light load state, calculate the percentage of charging piles available for fast charging in the station area, and determine whether it is lower than 33%. Here, 33% is only an example of the first available rate threshold, and the specific value can be adjusted. If it is not lower than 33%, the station area can meet the fast charging demand, and users can charge in the station area. This information can be prompted at the entrance or pushed to electric vehicle users. If it is lower than 33%, further judgment is required. At this time, if users with fast charging demands continue to be received, it may cause the line in the station area to change from the current light load state to an overloaded state, and the electric vehicles that can be added to the station area are controlled according to the first-level control function. Figure 2 Schematically shows a schematic diagram of the first-level control function according to an embodiment of the present application. As Figure 2 shown, the expression of the piecewise function is as follows:

[0062]

[0063] where k is the slope of the linear function, 0 < k < 1; a is the coefficient of the inverse proportional function, a > 0; Θ1 is the primary control function; is the access volume of fast-charging electric vehicles, and are the characteristic points on the abscissa respectively, and θ1 and θ2 are the characteristic points on the ordinate respectively. The above formula indicates that when the allowable access charging rate of the charging piles in the entire charging station area is lower than 65%, the charging station transitions from a lightly loaded state to an overloaded state, and the transition trend conforms to the function curve trend. When Θ1 = θ1, the charging station imposes stricter restrictions on the allowable access rate of the charging piles in the station, and its transition trend conforms to the function curve trend. When the allowable access charging rate of the charging piles in the system is lower than θ2, the station area enters the overloaded state, and the judgment logic in the overloaded state is used for further judgment.

[0064] In some embodiments of the present application, according to the relationship between the available rate of the fast-charging piles in the station area and the second available rate threshold, it is determined that the station area meets the restricted fast-charging demand or the load state is overloaded after the load is connected in the fast-charging mode, including: when the available rate of the fast-charging piles is greater than the second available rate threshold, it is determined that the station area meets the restricted fast-charging demand; when the available rate of the fast-charging piles is not greater than the second available rate threshold, based on the number of charging loads after the slow-charging demand is connected to the station area and the secondary control function, calculate the overall available rate of the charging piles after the slow-charging demand is connected; the secondary control function is a piecewise function, which is divided into a linear function, an inverse proportional function, and a constant function based on the number of loads of the slow-charging demand; determine that the station area provides restricted fast-charging services or the load state is converted to the overloaded state according to the overall available rate of the charging piles in the station area after the slow-charging demand is connected.

[0065] For the above logic, the following is an example: when the load state of the station area is the overloaded state, calculate the percentage of the charging piles available for fast charging in the station area, and judge whether it is lower than 15%. Here, 15% is only an example of the second available rate threshold, and the specific value can be adjusted. If it is not lower than 15%, the station area can meet the restricted fast-charging demand, restrict users with fast-charging demands, and can coordinate to use the slow-charging method to reduce the proportion of fast-charging and discharging charging piles. This information can be prompted at the entrance of the station or pushed to electric vehicle users. If it is lower than 15%, further judgment is required. At this time, if users with fast-charging demands continue to be received, it may cause the line in the station area to enter the overloaded state from the current overloaded state, and use the secondary control function to limit the number of electric vehicles connected to the station area. Figure 3 Schematically shows a schematic diagram of the secondary control function according to an embodiment of the present application. As Figure 3 shown, the expression of this piecewise function is as follows:

[0066]

[0067] Where k is the slope of the linear function, 0 <k<1;b为反比例函数的系数,b> 0; Θ2 is the first-level control function; The number of fast-charging electric vehicles connected to the grid is to The above formula indicates that when the charging rate of charging piles in the entire charging station area is lower than 35%, the station area transitions from overload state to heavy load state, and the transition trend conforms to Function curve trend, when θ2=θ3, the charging station imposes stricter restrictions on the access rate of charging piles within the station, and its transition trend conforms to Function curve trend: when the charging rate allowed by the charging piles in the system is lower than θ4, the station area enters the overload state.

[0068] The above implementation method limits the number of electric vehicles connected to the charging station under different loads, thereby preventing the charging station from entering a fault state.

[0069] In some embodiments of the present application, when the load status of the station area is a critical fault state, new charging demands are prohibited from entering and a self-regulating control strategy is executed; the execution termination condition of the self-regulating control strategy is: the load status of the station area is not a critical fault state or the execution duration reaches a preset duration. When the station area is in a critical fault state, new charging demands are prohibited from entering, and the park self-regulation is performed, that is, a three-level regulation strategy. The time limit of the three-level regulation is monitored, and the relationship between the station area self-regulation time and the preset duration is monitored. The preset duration is also related to the station area location, charging period and time, and the preset duration range can be limited to 1-20 minutes. When the self-regulation time is less than the preset duration, the station area completes the station area self-regulation and outputs the service capacity information of the station area, which may include information on available charging piles. When the self-regulation time exceeds the preset duration, the distribution network side is requested to adjust the load of the station area and mobilize the distributed energy closest to the station area to replenish the power of the station area.

[0070] In some embodiments of the present application, the distribution network side is further configured to: determine whether the power flow in the background area converges, and provide the sharing of service capacity information in each station area under this station area. The distribution network side performs four-level regulation and control, and this regulation and control is auxiliary regulation and control. The intelligent terminal of the station area on the distribution network side adjusts the critical fault station area according to information such as time, charging demand of charging piles, and actual charging efficiency. At the same time, the position of the charging station area closest to the critical fault area and the number of available charging piles are transmitted, and the power consumption load information and the regulation and control strategies of the power grid and distributed resources for this period are uploaded to the master station to update the regulation and control strategy of this station area. The distribution network side also determines whether the power flow in the background area converges. If it converges, the positions of available charging stations and the number of available charging piles in this station area are provided and sent to the charging stations in the overloaded state and the heavily loaded state. If it does not converge, the load rate in the station area is calculated. When the load is low, for example, lower than 90%, the positions of available charging stations and the number of available charging piles in this station area are provided and sent to the charging stations in the overloaded state and the heavily loaded state; when the load is high, for example, higher than 90%, the distribution transformer area dispatches distributed resources to adjust the critical fault station area, assists in completing the self-regulation in the station area, updates the power regulation strategy in the station area, and generates a historical information database of power resource scheduling for this period. This embodiment comprehensively considers user characteristics, charging date and time and other characteristics, dynamically plans the access standards for charging stations at different positions in different periods, and protects the charging stations.

[0071] The present application also provides a method for hierarchical regulation and control of electric vehicles based on the distribution network. The method includes: in response to the charging demand of the electric vehicle, sending the charging demand and the historical charging data of the electric vehicle to the alternative station areas, and each alternative station area determines the service capacity information based on the foregoing method for determining the station area state; pushing the alternative station areas and the service capacity information of the alternative station areas to the electric vehicle. This embodiment can run on the background or the charging station side. After receiving the charging demand of the electric vehicle, the charging station side determines the service capacity information of several alternative station areas according to the foregoing method for determining the station area state, and then pushes the alternative station areas and the service capacity information of the alternative station areas to the electric vehicle. The electric vehicle completes charging in this station area or finds a suitable nearest station area according to the actual demand and the prompt of the charging station. In this embodiment, the charging station can directly indicate whether there are available charging piles in this station, the number of fast charging piles that can be used. If it cannot receive new charging demands, the nearest available charging station will be displayed in this station area for the user to choose, reducing the user's waiting time and improving the user's satisfaction. For the station areas that cannot charge, the vehicle owner can be prompted to charge at the nearest station area.

[0072] In some embodiments of the present application, the charging demand of the electric vehicle comes from a charging pile; the charging pile is configured to make a preliminary prediction of the user's charging behavior based on the user's historical charging data, and generate the charging demand based on the prediction result. This embodiment further limits the role and function of the charging pile. The charging pile first collects user information of the electric vehicle that needs to be charged. The collected data includes: battery capacity, historical charging records, charging location records, historical power consumption records, charging rate preferences, customary charging time and charging duration to form a user charging behavior matrix and upload it to the charging pile side. The charging pile with computing and analysis capabilities cleans the data uploaded by the electric vehicle, pre-processes the data, and fuses the data. It uses algorithms to analyze user travel information, model the user's travel behavior, and classify the vehicle type. The charging pile combines the results of the user behavior characteristic analysis to make a simple prediction of the user's electricity demand and uploads information such as the user's charging demand, fast or slow charging demand, and charging volume demand. The charging pile uploads user demand and prediction results to the charging station to which it belongs. The charging station records the real-time data of all types of charging electric vehicles and charging piles in the station area, and uploads it to the distribution network control center of the substation where the station area is located; and determines the location information, charging date, and charging time of the charging pile.

[0073] In some embodiments of the present application, the candidate station area is determined by the following steps: obtaining the location information of the electric vehicle; selecting at least one station area whose coverage area includes the location information as the candidate station area; and selecting at least one station area from all stations under the candidate station area as the candidate station area. When determining the candidate station area, the selection can be made based on the location information. When the electric vehicle needs to charge, a closer station area is preferred. This embodiment selects based on the coverage area of the station area, avoiding the range limitations of station area-based selection.

[0074] Based on the same inventive concept, the present application also provides a distribution network-based electric vehicle hierarchical control system, which includes: a charging pile side, the charging station side is used to generate the charging demand of the electric vehicle based on the charging behavior to be generated and the charging history data; a charging station side, the charging station side is used to use the aforementioned station area status determination method to determine the service capability information of the station area; a distribution network side, the distribution network side is used to obtain the service capability information of each station area within the station area and generate the service capability information of the station area; the service capability information of the station area or station area is pushed to the electric vehicle so that the electric vehicle can select the station area based on the service capability information.

[0075] Figures 4 to 6 The following diagrams illustrate the interaction flow charts when the charging pile side, charging station side and distribution network side execute the aforementioned distribution network-based electric vehicle hierarchical control method. Figures 4 to 6As shown, the electric vehicle hierarchical control method based on the distribution network implemented by the system mainly includes the following steps in one embodiment:

[0076] Step 1: First, user information is collected from electric vehicles that require charging. This data includes battery capacity, historical charging history, charging location records, historical power consumption records, charging rate preferences, customary charging times, and charging durations. This data is then compiled into a user charging behavior matrix and uploaded to the charging station. Charging stations with computing and analytical capabilities then clean, preprocess, and fuse the data uploaded by the electric vehicles. Using algorithms, they analyze user travel information, model user travel behavior, and classify vehicle types.

[0077] Step 2: The charging pile makes a simple prediction of the user's electricity demand based on the analysis results of the user's behavior characteristics, and uploads information such as the user's charging demand, fast charging demand, and charging amount demand.

[0078] Step 3: The charging pile uploads user demand and prediction results to the charging station to which it belongs. The charging station records the real-time data of all types of charging electric vehicles and charging piles in the station area, and uploads it to the distribution network control center of the substation where the station area is located; and determines the location information, charging date, and charging time of the charging pile.

[0079] Step 4: The charging management platform of this station area analyzes the information uploaded by the charging piles to analyze whether the electric vehicles joining this charging station have reported the need for fast charging for this charging. If no fast charging demand is reported, conventional charging will be directly carried out. The corresponding charging method can be automatically selected according to the user's travel mode combined with the charging station location information and time information. For example, for taxis with higher demand for fast charging, family cars and official cars with charging stations located in service areas will be fast charged by default. Otherwise, go to step 5.

[0080] Step 5: Calculate whether the line flow in the station area has converged, and determine whether the flow in the station area has converged; if the flow converges, proceed to step 6, otherwise proceed to step 19.

[0081] Step 6: Calculate the availability of charging piles and line load rate within the station area;

[0082] Step 7: Determine the load factor of the lines in the station area. If the load factor is less than threshold 1, the station area is lightly loaded and available, and the process proceeds to step 8. If threshold 1 is less than load factor and less than threshold 2, the process proceeds to step 12. If threshold 2 is less than load factor and less than threshold 3, the process proceeds to step 17; otherwise, the process proceeds to step 19. The determination of thresholds 1, 2, and 3 can be found in the previous implementation and will not be repeated here.

[0083] Step 8: When the station area is available, calculate the percentage of charging piles in the station area available for fast charging. If it is less than 33%, go to Step 10; otherwise, go to Step 9.

[0084] Step 9: The station area can prompt at the entrance that the fast charging demand can be met in this station area and users can charge in this station area.

[0085] Step 10: When the number of charging piles available for fast charging in the station area is less than 35%, if new users with fast charging demand are continuously received, it may cause the lines in the station area to enter an overloaded state. After controlling the electric vehicles that can enter the station area according to the first-level control function, go to Step 11. The first-level control function is as described throughout the text and will not be repeated here.

[0086] Step 11: Judge the result of the above first-level control function. If it is less than 35%, go to Step 12; otherwise, go to Step 9.

[0087] Step 12: The station area enters an overloaded state. It can prompt that the station area is available but the charging and discharging power and efficiency of the charging piles in the charging station area need to be restricted. Combining with the reported remaining battery power information of users, reduce fast charging, and then go to Step 13.

[0088] Step 13: Calculate the percentage of available fast charging piles in this station area. If it is less than 15%, go to Step 15; otherwise, go to Step 14.

[0089] Step 14: Restrict users with fast charging demand. Coordinate to use slow charging methods and reduce the proportion of fast charging and discharging charging piles.

[0090] Step 15: If the station area continues to receive users with fast charging demand, it will cause the lines in the station area to enter a heavy load state. The station area enters a transition state. Use the second-level control function Θ2 to limit the number of electric vehicles accessing this station area and then go to Step 16. The second-level control function is as described throughout the text and will not be repeated here.

[0091] Step 16: Judge the result of the above control function. If Θ2 is less than 15%, go to Step 17; otherwise, go to Step 14.

[0092] Step 17: The lines enter a heavy load state. Prompt that the station area is available, but only open to users with slow charging demand and do not perform fast charging, and then go to Step 18.

[0093] Step 18: Calculate the percentage of available slow charging piles in this station area. When it is less than 10%, go to Step 19, prompt that only users with slow charging demand can be received in this station area, and provide the location of the nearest fast charging station and the number of available fast charging piles.

[0094] Step 19: This station is in a critical fault state. New charging demands are prohibited from entering, and self-regulation of the park is carried out, that is, the three-level control strategy.

[0095] Step 20: Determine the regulation time limit of the three-level control strategy. When the self-regulation time of the station area exceeds a certain time limit (this time is still related to the location of the station area, the charging period, and the time, and the time range can be limited to (1 - 20 min)), go to Step 23; otherwise, go to Step 21.

[0096] Step 21: Complete the self-regulation within the station area and go to Step 22.

[0097] Step 22: Output the available charging pile information of this station area and go to Step 30.

[0098] Step 23: Request the distribution network to adjust the load of this station area, mobilize the distributed energy closest to this station area to supply power to this station area, and transfer to Step 24.

[0099] Step 24: Perform four-level regulation (auxiliary regulation). The intelligent terminal of the distribution network side adjusts the critical fault station area according to information such as time, charging pile charging demand, and actual charging efficiency; at the same time, upload the position of the charging station area closest to the critical fault area and the number of available charging piles, and upload the power load information and the regulation strategies of the power grid and distributed resources for this period to the main station to update the regulation strategy of this area. Then go to Step 25.

[0100] Step 25: Judge whether the power flow in the area converges after adjustment. If it does, go to Step 26; otherwise, go to Step 27.

[0101] Step 26: Calculate the load rate in the area. If it is higher than 90%, go to Step 27; otherwise, go to Step 28.

[0102] Step 27: Provide the location of available charging stations and the number of available charging piles in this area and send them to the overloaded and heavily loaded charging stations. Go to Step 29.

[0103] Step 28: The distribution substation schedules distributed resources to adjust the critical fault station area, assist in completing the self-regulation within the station area, update the power regulation strategy of the area within the substation, and generate a historical information database for power resource scheduling for this period. Go to Step 22.

[0104] Step 29: Output the available charging stations, the number of available charging piles, and the status information of this distribution substation and go to Step 30.

[0105] Step 30: The electric vehicle completes charging in this station area or finds a suitable and closest station area according to the actual demand and the prompt of the charging station.

[0106] Through the above embodiments, considering the charging station location, user travel characteristics, charging date, time, and user's historical charging information comprehensively, and optimizing the scheduling of electric vehicles with adjustable characteristics from the charging station area and the distribution network substation side, the charging demand of the charging station and the load situation are fully considered, and a reasonable charging scheduling scheme is designed.

[0107] In some embodiments of the present application, an electronic device is further provided, including: at least one processor; a memory connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the at least one processor executes the foregoing method for determining the station area state or the method for hierarchical regulation and control of electric vehicles based on the distribution network. Its internal structure diagram can be as Figure 7 shown. Figure 7 Schematically shows the internal structure diagram of the electronic device according to the embodiments of the present application. The electronic device includes a processor A01, a network interface A02, a memory (not shown in the figure), and a database (not shown in the figure) connected through a system bus. Among them, the processor A01 of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The network interface A02 of the electronic device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, it is used to implement a method for determining the station area state or a method for hierarchical regulation and control of electric vehicles based on the distribution network.

[0108] Those skilled in the art can understand that Figure 7 the structure shown in

[0109] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the electronic device to which the solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0110] In an embodiment provided by the present application, a machine-readable storage medium is provided. Instructions are stored on the machine-readable storage medium, and when the instructions are executed by a processor, the processor is configured to execute the foregoing method for determining the station area state or the method for hierarchical regulation and control of electric vehicles based on the distribution network.

[0111] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0112] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0113] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0115] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0116] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0117] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0118] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0119] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for determining the status of a station area, characterized in that The method includes: Obtaining the charging demand of the load and the historical charging data of the load; Determining the value of each influencing factor based on the charging period, historical charging data, and charging quantity demand, where the influencing factors include: the date and time in the charging period, the historical charging method and charging quantity in the historical charging data during the same period, and the charging quantity demand; Determining the coefficient of the value of the influencing factor based on the charging date and the location information of the station area, and determining multiple load rate thresholds based on the influencing factor and the corresponding coefficient; Determining the load state of the station area according to the relationship between the current load rate of the station area and the multiple load rate thresholds; Generating service ability information for the station area to respond to the charging demand based on the load state, where the service ability information is classified as: meeting the fast charging demand, meeting the limited fast charging demand, or meeting the slow charging demand.

2. The method according to claim 1, characterized in that, After obtaining the charging demand, the method further includes: Calculating and determining whether the power flow of the line in the station area is in a converged state; When the power flow is in a converged state, continuing to execute the subsequent steps.

3. The method according to claim 1, wherein Determining the value of each influencing factor based on the charging period, historical charging data, and charging quantity demand, including: Mapping the date in the charging period to a value in the first numerical set; Mapping the time in the charging period to a value in the second numerical set; Mapping the historical charging method during the same period in the historical charging data to a Boolean value; Mapping the historical charging quantity during the same period in the historical charging data to a value in the third numerical set; Mapping the charging quantity demand to a value in the fourth numerical set.

4. The method according to claim 1, wherein The number of the load rate thresholds is determined according to the classification of the service ability information.

5. The method according to claim 4, wherein The number of the load rate thresholds is three.

6. The method according to claim 4, wherein Determining the load state of the station area according to the relationship between the current load rate of the station area and the multiple load rate thresholds, including: When the current load rate is less than the minimum value of the multiple load rate thresholds, determining that the load state of the station area is a light load state; When the current load rate is greater than the maximum value of the multiple load rate thresholds, determining that the load state of the station area is a critical failure state; When the current load rate is between the minimum value and the maximum value of the multiple load rate thresholds, determining that the load state of the station area is an intermediate state; When there are other load rate thresholds after removing the minimum value and the maximum value from the multiple load rate thresholds, further dividing the intermediate state based on the other load rate thresholds.

7. The method according to claim 6, wherein The number of the load rate thresholds is three, and the intermediate state is divided into an overload state and a heavy load state based on one threshold after removing the minimum value and the maximum value; the load rate of the overload state is lower than that of the heavy load state.

8. The method according to claim 7, wherein Generating service ability information for the station area to respond to the charging demand based on the load state, including: When the load state of the station area is a light load state, determining that the station area meets the fast charging demand or the load state becomes an overload state after the load is connected in a fast charging manner according to the relationship between the available rate of the fast charging piles in the station area and the first available rate threshold; When the load status of the station area is in an overloaded state, according to the relationship between the available rate of fast charging piles in the station area and the second available rate threshold, it is determined that the station area meets the restricted fast charging demand or the load status becomes a heavy load state after the load is connected in the slow charging mode; When the load status of the station area is in a heavy load state, according to the relationship between the available rate of slow charging piles in the station area and the third available rate threshold, it is determined that the station area meets the slow charging demand or the station area is converted into a critical fault state.

9. The method according to claim 8, wherein Determining that the station area meets the fast charging demand or the load status becomes an overloaded state after the load is connected in the fast charging mode according to the relationship between the available rate of fast charging piles in the station area and the first available rate threshold includes: When the available rate of fast charging piles is greater than the first available rate threshold, it is determined that the station area meets the fast charging demand; When the available rate of fast charging piles is not greater than the first available rate threshold, based on the number of fast charging loads after the fast charging demand is connected to the station area and the first-level control function, calculate the overall available rate of charging piles after the fast charging demand is connected; the first-level control function is a piecewise function, which is divided into a linear function, an inverse proportional function and a constant function based on the number of loads of the fast charging demand; Determine whether the station area meets the fast charging demand or the load status is converted into an overloaded state according to the overall available rate of charging piles in the station area after the fast charging demand is connected.

10. The method according to claim 8, wherein Determining that the station area meets the restricted fast charging demand or the load status becomes a heavy load state after the load is connected in the fast charging mode according to the relationship between the available rate of fast charging piles in the station area and the second available rate threshold includes: When the available rate of fast charging piles is greater than the second available rate threshold, it is determined that the station area meets the restricted fast charging demand; When the available rate of fast charging piles is not greater than the second available rate threshold, based on the number of charging loads after the slow charging demand is connected to the station area and the second-level control function, calculate the overall available rate of charging piles after the slow charging demand is connected; the second-level control function is a piecewise function, which is divided into a linear function, an inverse proportional function and a constant function based on the number of loads of the slow charging demand; Determine whether the station area provides restricted fast charging services or the load status is converted into a heavy load state according to the overall available rate of charging piles in the station area after the slow charging demand is connected.

11. The method according to claim 6 or 7, characterized in that, When the load status of the station area is in a critical fault state, new charging demands are prohibited from entering and a self-regulation control strategy is executed; The execution termination condition of the self-regulation control strategy is: the load status of the station area is not in a critical fault state or the execution duration reaches a preset duration.

12. The method according to claim 11, wherein When the execution duration of the self-regulation control strategy reaches the preset duration but the load status of the station area is still in a critical fault state, request the distribution network side to adjust the load of this station area.

13. The method according to claim 12, characterized in that, The distribution network side is also configured to: Judge whether the power flow in the adjusted backstage area converges, and provide the sharing of service capacity information in each station area under this substation area.

14. A hierarchical control method for electric vehicles based on a distribution network, characterized in that, The method includes: In response to the charging demand of an electric vehicle, send the charging demand and the historical charging data of the electric vehicle to alternative station areas, and each alternative station area determines service capacity information based on the station area status determination method described in any one of claims 1 to 13; Push the alternative station areas and the service capacity information of the alternative station areas to the electric vehicle.

15. The method according to claim 14, wherein The charging demand of the electric vehicle comes from a charging pile; The charging pile is configured to: preliminarily predict the charging behavior of a user in combination with the user's historical charging data, and generate the charging demand based on the prediction result.

16. The method according to claim 14, wherein The alternative station area is determined through the following steps: Obtain the location information of the electric vehicle; Use at least one distribution transformer area with a coverage range including the location information as an alternative distribution transformer area; Select at least one station area from all the station areas under the alternative distribution transformer area as the alternative station area.

17. An electric vehicle hierarchical control system based on a distribution network, characterized in that, The system includes: On the charging pile side, the charging pile side is used to generate the charging demand of the electric vehicle based on the upcoming charging behavior and charging historical data; On the charging station side, the charging station side is used to determine the service capacity information of the station area by using the station area state determination method described in any one of claims 1 to 13; On the distribution network side, the distribution network side is used to obtain the service capacity information of each station area in the distribution transformer area and generate the service capacity information of the distribution transformer area; The service capacity information of the station area or the distribution transformer area is pushed to the electric vehicle for the electric vehicle to select the station area based on the service capacity information.

18. An electronic device, characterized in that, It includes: At least one processor; A memory connected to the at least one processor; Wherein, the memory stores instructions executable by the at least one processor, and the at least one processor realizes the station area state determination method described in any one of claims 1 to 13 or the hierarchical regulation method for electric vehicles based on the distribution network described in any one of claims 14 to 16 by executing the instructions stored in the memory.

19. A computer-readable storage medium having computer programs / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, the station area state determination method described in any one of claims 1 to 13 or the hierarchical regulation method for electric vehicles based on the distribution network described in any one of claims 14 to 16 is realized.

20. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, the method described in any one of claims 1 to 16 is realized.

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