An orderly charging method and system for electric vehicles based on intelligent fusion terminal in the substation

Abstract

The present invention discloses an orderly charging method and system for electric vehicles based on an intelligent fusion terminal in an electric vehicle substation, and belongs to the technical field of electric vehicle charging and discharging. The method of the present invention comprises: obtaining basic information of the charging piles in the substation, determining the daily load forecast results of the charging piles in the substation according to the basic information, and inputting the daily load forecast results and electricity price information into the intelligent fusion terminal in the substation; judging whether the charging piles in the substation can meet the charging demand according to the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information; determining the charging plan, and charging the newly connected electric vehicle with the newly formulated charging plan. The present invention can effectively improve the real-time and interconnectivity of charging facility data information, improve the compatibility of distribution automation terminals and electric vehicle charging facilities, and make the collected data sufficient to support the participation of electric vehicle charging facilities in interaction.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging and discharging, and more specifically, to an electric vehicle orderly charging method and system based on an intelligent fusion terminal in an area. Background Art

[0002] The development and use of electric vehicles can accelerate the replacement of fossil fuels and reduce automobile exhaust emissions, thus helping to ensure energy security, promote emission reduction and prevent air pollution. At present, the real-time and interoperability of charging facility data information are poor: the distribution automation terminal is poorly compatible with electric vehicle charging facilities, and the collected data is insufficient to support the participation of electric vehicle charging facilities in interaction. The large-scale development of new energy has led to a reduction in the frequency regulation and backup resources of traditional power grids. The large-scale receiving power grid faces prominent system security issues. It is urgent to promote the transformation of the traditional "source follows load" dispatching mode to the "load real-time regulation" mode to effectively improve the safety and stability level of the power grid and the lean level of regulation. The development and use of electric vehicles can accelerate the replacement of fossil fuels and reduce automobile exhaust emissions, thus helping to ensure energy security, promote emission reduction and prevent air pollution. It is urgent to solve the problem of giving full play to the automaticity of electric vehicle loads and coordinating dispatching to achieve real-time dispatching.

[0003] At present, charging piles in residential areas are difficult to accept the orderly charging regulation of the operating platform. According to statistics, the number of private electric vehicles accounts for a large proportion, of which 80% of the charging of private electric vehicles is completed in residential areas. Moreover, most of the charging piles in residential areas are currently non-communication and non-regulated piles, and cannot be connected to the platform operation. In order to give full play to the characteristics of the huge total amount of electric vehicles connected to the distribution network in residential areas and flexible regulation, the application research of electric vehicles participating in the regulation of distribution networks for residential areas should be carried out. At the same time, since orderly charging in residential areas is currently the lowest cost and most economical way to transform the power grid, the market demand for 20kW inertia orderly charging piles and 7kW inertia orderly charging piles will increase year by year in recent years, which is an important part of the customer-side flexible resources participating in the power grid auxiliary service market. Summary of the invention

[0004] In view of the above problems, the present invention provides an orderly charging method for electric vehicles based on a smart fusion terminal in a substation, comprising:

[0005] Obtain the basic information of the charging piles in the substation area, determine the daily load forecast results of the charging piles in the substation area based on the basic information, and input the daily load forecast results and electricity price information into the substation area intelligent fusion terminal;

[0006] The load information and user demand information of the charging piles in the substation are updated in real time through the intelligent fusion terminal in the substation. When the charging piles in the substation receive new electric vehicle access information, if the user chooses to charge in the grid dispatching mode, the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information are used to determine whether the charging piles in the substation can meet the charging demand.

[0007] If the conditions are met, when a new electric vehicle is connected to the charging pile in the substation before the new time node, determine whether the charging plan of the connected electric vehicle has been modified and whether the real-time load information is too different from the daily load forecast result. If not, charge the newly connected electric vehicle with the historical charging plan; if so, obtain the basic information of the newly connected electric vehicle, determine the charging plan based on the basic information and electricity price information, and charge the newly connected electric vehicle with the newly formulated charging plan.

[0008] Optional: basic information of charging piles in the substation, including: daily load curve, electricity price information, basic information of electric vehicles and charging facility information.

[0009] Optionally, a newly connected electric vehicle can also choose to charge in the charging mode based on the battery SOC information.

[0010] Optional, basic information of the electric vehicle, including: connection time, end time, battery SOC when connected, battery SOC when leaving, and rated charging power.

[0011] Optionally, the charging scheme meets the requirements of the load upper limit constraint of the charging piles in the substation, user demand, peak shaving and valley filling, and grid stability.

[0012] The present invention also proposes an orderly charging system for electric vehicles based on an intelligent fusion terminal in a substation area, comprising:

[0013] The intelligent fusion terminal unit in the substation obtains the basic information of the charging piles in the substation and determines the daily load forecast results of the charging piles in the substation based on the basic information;

[0014] The load information and user demand information of the charging piles in the substation are updated in real time through the intelligent fusion terminal in the substation. When the charging piles in the substation receive new electric vehicle access information, if the user chooses to charge in the grid dispatching mode, the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information are used to determine whether the charging piles in the substation can meet the charging demand.

[0015] If satisfied, when a new electric vehicle is connected to the charging pile in the substation before the new time node, determine whether the connected electric vehicle has modified the charging plan and whether the real-time load information is too far away from the daily load forecast result. If not, charge the newly connected electric vehicle with the historical charging plan; if so, obtain the basic information of the newly connected electric vehicle, determine the charging plan based on the basic information and electricity price information, and charge the newly connected electric vehicle with the newly formulated charging plan;

[0016] The data interaction unit is used for data interaction between the intelligent fusion terminal unit in the substation and the charging piles in the substation.

[0017] Optional: basic information of charging piles in the substation, including: daily load curve, electricity price information, basic information of electric vehicles and charging facility information.

[0018] Optionally, a newly connected electric vehicle can also choose to charge in the charging mode based on the battery SOC information.

[0019] Optional, basic information of the electric vehicle, including: connection time, end time, battery SOC when connected, battery SOC when leaving, and rated charging power.

[0020] Optionally, the charging scheme meets the requirements of the load upper limit constraint of the charging piles in the substation, user demand, peak shaving and valley filling, and grid stability.

[0021] The present invention can effectively improve the real-time and interconnectivity of charging facility data information, improve the compatibility of distribution automation terminals and electric vehicle charging facilities, and make the collected data sufficient to support the participation of electric vehicle charging facilities in interaction.

[0022] The orderly charging method in the present invention combines real-time load information to complete the formulation of the charging plan, more accurately captures the peak and valley information of the load, and further ensures the stable operation of the power grid; at the same time, it provides real-time feedback to users, fully considers the needs of users, saves charging costs for users, and realizes the transparency of charging behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the method of the present invention;

[0024] Figure 2 This is a system architecture diagram of the charging facility Internet of Things controller of the present invention;

[0025] Figure 3 This is a diagram of the edge computing control architecture of the present invention;

[0026] Figure 4 This is a diagram of the real-time charging and discharging control architecture of the distribution network based on distributed edge computing of the present invention;

[0027] Figure 5 The load curve diagrams of two orderly charging schemes when the actual load of the power grid of the present invention is the same as the predicted load;

[0028] Figure 6 The load curve diagrams of two orderly charging schemes when the actual load of the power grid of the present invention is different from the predicted load;

[0029] Figure 7 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0030] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0031] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0032] The present invention will be further described below in conjunction with embodiments and drawings:

[0033] The present invention provides an orderly charging method for electric vehicles based on an intelligent fusion terminal in a substation area, such as Figure 1 As shown, including:

[0034] Obtain and enter the basic information of the system, enter the daily load forecast results and electricity price information.

[0035] Update load information and user demand information in real time, receive new electric vehicle access information, and update the battery SOC information of electric vehicles. The real-time battery SOC status can be fed back to the user through the communication module.

[0036] Make a preliminary judgment on whether the user's charging needs can be met. If not, remind the user and provide feedback on the maximum charging value and corresponding charging plan.

[0037] Whether there are new electric vehicles connected before the new time node, if there are new electric vehicles connected, obtain the information of the electric vehicles, which includes the connection time, end time, battery SOC when connected, battery SOC when leaving and rated charging power; whether there are connected users who modify the charging plan, if so, obtain the modification information and modify the previous information; whether the real-time load information is too different from the predicted load, if so, revise the load curve. If there are no changes, the established plan will be adopted at the new time node.

[0038] The charging plan is determined based on the information obtained to meet the load upper limit constraints, user needs, peak shaving and valley filling, and grid stability.

[0039] At the new time point, the system operates according to the determined charging plan, updates the charging status and charge information of the electric vehicle battery, and provides users with real-time charging information and charging completion settlement reminders.

[0040] like Figure 2 As shown, the charging facility IoT controller is externalized to the charging pile as a general control module. The charging facility IoT controller module is connected to the charging pile mainboard downward to collect information from the charging pile mainboard and control it. It is connected to the terminal upward to be managed and controlled by the terminal. The charging facility IoT controller can be connected to the terminal without going through a smart meter. The charging facility IoT controller interacts with the intelligent fusion terminal in the substation area to enable the intelligent fusion terminal to play the role of an energy conversion hub and energy management basic platform for the substation area distribution network. To realize the above collection and control functions, it is necessary to upgrade the control program of the charging pile mainboard and add orderly charging and power market data collection and control to the terminal communication protocol.

[0041] The IoT controller of the charging facility needs to be connected to the distribution IoT energy manager of the substation through power carrier communication, and connected to the management platform through the distribution IoT energy manager of the power distribution. The charging facility uses the intelligent control panel as the core component, communicates with the vehicle BMS and controls and distributes power to the charging pile power module, uploads data to the management platform through the distribution IoT energy manager of the substation, and accepts the control of the management platform and the IoT energy manager at the same time, to achieve intelligent and orderly charging and remote management.

[0042] The IoT controller for electric vehicle charging facilities compatible with the intelligent fusion terminal of the substation adopts power carrier communication, processes the data signal in the form of digital signals, and modulates it to a certain carrier frequency (the dedicated frequency band for low-voltage power line carrier communication in China is 3-500kHz), and transmits it using existing power lines. Compared with traditional modulation technology, power carrier technology has the following advantages: strong anti-noise and anti-interference capabilities, reliable and stable communication; adaptive ability to changes in power line channels, and successful communication is possible when individual subcarriers are interfered; high data rate, usually more than tens of kbps.

[0043] After the charging facility IoT controller interacts with the substation intelligent fusion terminal, the substation intelligent fusion terminal in the present invention will mainly use edge computing technology to process and analyze the data.

[0044] like Figure 3 As shown in the figure, edge computing refers to the use of an open platform that integrates network, computing, storage, and application core capabilities to provide the nearest service on the side close to the object or data source. Its application is initiated on the edge side, resulting in faster network service response, meeting the basic needs of the industry in real-time business, application intelligence, security and privacy protection, etc. Edge computing is between the physical entity and the industrial connection, or on top of the physical entity. Cloud computing can still access historical data of edge computing. For the Internet of Things, breakthroughs in edge computing technology mean that many controls will be implemented through local devices without being handed over to the cloud, and the processing process will be completed at the local edge computing layer. This will undoubtedly greatly improve processing efficiency and reduce the load on the cloud. Because it is closer to users, it can also provide users with faster responses and solve their needs at the edge.

[0045] The real-time charging and discharging control architecture of the distribution network based on distributed edge computing is as follows: Figure 4 As shown. First is the user side, which consists of charging piles, plug-and-play modules and user electricity meters. The user side is responsible for sending charging pile information and user meter information to the substation side. Secondly, the substation side is composed of edge computing modules, communication modules, and intelligent sensor modules. The substation side first receives the charging pile information and user meter information from the user side, and then the edge computing module performs calculations and processing before sending the energy storage information, charging pile information, and distribution transformer information to the master station side. Finally, the master station side is composed of a cloud master station, a distribution automation master station, and a user procurement system. The master station side analyzes the energy storage information, charging pile information, and distribution transformer information received from the substation side, and provides optimization strategies and suggestions for the Internet of Vehicles platform and charging pile users.

[0046] Taking into account the user's travel habits, the Monte Carlo method is used to generate the number of electric vehicles, the start time of electric vehicle charging, the end time of electric vehicle charging and the starting SOC of electric vehicles. By default, the electric vehicle is fully charged at the end of the user's setting.

[0047] Among them, the number of electric vehicles follows a normal distribution with a mean of 80 and a standard deviation of 5; the charging start time follows a normal distribution with a mean of 19:00 and a standard deviation of 2; the charging end time follows a normal distribution with a mean of 7:30 and a standard deviation of 1; the starting SOC of electric vehicles follows a normal distribution with a mean of 0.5 and a standard deviation of 0.2, and the value range is 0 to 1.

[0048] To prevent frequent switching of electric vehicles on and off for battery use from causing problems for grid stability and to ensure the continuity of charging, there is a 15-minute difference between each two time nodes. The same electric vehicle has only two states: charging and not charging between the two time nodes until charging is completed.

[0049] After determining the access parameters of the new electric vehicle, first determine the number of charging time periods required by the electric vehicle:

[0050]

[0051] Where m is the number of time periods required for an electric vehicle to be fully charged, B is the battery capacity of the electric vehicle, and S c is the initial state of charge of the electric vehicle, η is the charging efficiency, t is the time interval between each charging, 15 minutes, and p is the rated charging power of the electric vehicle.

[0052] Then, determine the total number of charging time periods for the electric vehicle:

[0053]

[0054] Where n is the total number of charging time periods for electric vehicles, t b and t f are the start and end time of electric vehicle charging. By comparing n and m, we can preliminarily judge whether the user's needs can be met. When m is greater than n, we reset the value of m by setting m=n. And prompt the user with the maximum chargeable amount. After the above processing, we can get m≤n.

[0055] After determining the charging demand of the electric vehicle at the current node, obtain the charging time period t of the electric vehicle. f ~t b The load information of n time nodes within is stored in the matrix P:

[0056] P=(P1 P2 … P n )

[0057] Pi It is not the load value predicted at the corresponding time point, but the result of the superposition of the basic load value predicted at that time point and the load of the electric vehicles with a determined charging plan at that time point.

[0058] The scheme that does not consider real-time load and user interaction completely formulates the charging strategy based on the given predicted load curve. The m charging time periods required by the electric vehicle can be directly allocated to the time periods corresponding to the n time nodes in P according to the charging strategy with the smallest load fluctuation. Therefore, its optimization objective function is expressed as follows:

[0059]

[0060]

[0061] In the formula, To determine the average load at n time points after the charging plan, K i is the switch status of the charging pile at the corresponding time point, charging corresponds to a value of 1, and shutting down corresponds to a value of 0, and K i Satisfy the following formula, which is also the constraint condition of the optimization function.

[0062]

[0063] After determining the charging plan, the determined P i =P i +K i The p0 value is updated to the load of the corresponding time in the matrix P, and waits for a new charging request.

[0064] Considering the user demand and real-time load change, the load information of the most recent time node, i.e., P1, should be corrected according to the real-time load information obtained, and P2~P n The value of is consistent with the predicted value. The information of the rechargeable nodes in the matrix P is corrected according to the user's real-time load demand, which includes the time information and load information of the node. And according to the corrected matrix P, the same control strategy with minimum load fluctuation is used to determine the charging time.

[0065] The scheme without real-time load and user interaction completely formulates the charging strategy based on the given predicted load curve, and allocates the charging time required for each electric vehicle to the time period with less load within their respective charging time range. Taking into account the real-time load factors and the impact of users modifying the charging plan midway, the load information and the charging information of the electric vehicle will be updated before each new time node, and the charging strategy will be formulated based on the new data. Several constraints should be met in formulating the charging plan: charging time constraint; user demand constraint; transformer capacity limit, that is, the sum of all loads should not exceed the capacity of the community transformer; priority is given to charging at the time point with the lowest load.

[0066] In this embodiment, when the actual load of the power grid is different from the predicted load, the load curves of the two orderly charging schemes are as follows: Figure 5 and Figure 6 It can be seen that when the actual load curve deviates from the predicted load curve, the scheme designed entirely based on the predicted curve will have a large deviation with the deviation of the actual load curve, while the scheme adjusted according to real-time load information can still achieve the goal of peak shaving and valley filling to ensure the stability of the power grid.

[0067] Therefore, through this embodiment, it can be found that relying on the intelligent fusion terminal in the substation area to obtain information on the grid side, user side and charging piles in real time, and real-time optimization based on edge computing technology can meet user needs while better ensuring the stability of the power grid and promoting orderly charging of electric vehicles.

[0068] The present invention also proposes an orderly charging system 200 for electric vehicles based on a smart fusion terminal in a substation area. Figure 7 As shown, including:

[0069] The intelligent fusion terminal unit 201 of the substation obtains the basic information of the charging piles in the substation, and determines the daily load prediction result of the charging piles in the substation according to the basic information;

[0070] The load information and user demand information of the charging piles in the substation are updated in real time through the intelligent fusion terminal in the substation. When the charging piles in the substation receive new electric vehicle access information, if the user chooses to charge in the grid dispatching mode, the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information are used to determine whether the charging piles in the substation can meet the charging demand.

[0071] If satisfied, when a new electric vehicle is connected to the charging pile in the substation before the new time node, determine whether the connected electric vehicle has modified the charging plan and whether the real-time load information is too far away from the daily load forecast result. If not, charge the newly connected electric vehicle with the historical charging plan; if so, obtain the basic information of the newly connected electric vehicle, determine the charging plan based on the basic information and electricity price information, and charge the newly connected electric vehicle with the newly formulated charging plan;

[0072] The data interaction unit 202 is used for data interaction between the intelligent fusion terminal unit in the substation area and the charging piles in the substation area.

[0073] Among them, the basic information of charging piles in the substation includes: daily load curve, electricity price information, basic information of electric vehicles and charging facility information.

[0074] Among them, newly connected electric vehicles can also choose to charge in charging mode based on the battery's SOC information.

[0075] Among them, the basic information of the electric vehicle includes: connection time, end time, battery SOC when connected, battery SOC when leaving and rated charging power.

[0076] Among them, the charging plan meets the requirements of the load upper limit constraints of the charging piles in the substation, user demand, peak shaving and valley filling, and grid stability.

[0077] The present invention can effectively improve the real-time and interconnectivity of charging facility data information, improve the compatibility of distribution automation terminals and electric vehicle charging facilities, and make the collected data sufficient to support the participation of electric vehicle charging facilities in interaction.

[0078] The orderly charging method in the present invention combines real-time load information to complete the formulation of the charging plan, more accurately captures the peak and valley information of the load, and further ensures the stable operation of the power grid; at the same time, it provides real-time feedback to users, fully considers the needs of users, saves charging costs for users, and realizes the transparency of charging behavior.

[0079] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0080] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0083] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0084] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for orderly charging of electric vehicles based on a smart fusion terminal in a substation, the method comprising: Obtain the basic information of the charging piles in the substation area, determine the daily load forecast results of the charging piles in the substation area based on the basic information, and input the daily load forecast results and electricity price information into the substation area intelligent fusion terminal; The intelligent fusion terminal of the substation updates the load information and user demand information of the substation charging pile in real time, and determines the number of charging time periods required by the electric vehicle after the substation charging pile receives new electric vehicle access information: Where m is the number of time periods required for an electric vehicle to be fully charged, B is the battery capacity of the electric vehicle, and S c is the initial state of charge of the electric vehicle, η is the charging efficiency, t is the time interval between each charge of 15 minutes, and p is the rated charging power of the electric vehicle; Then, determine the total number of charging time periods for the electric vehicle: Where n is the total number of charging time periods for electric vehicles, t b and t f They are the start and end time of electric vehicle charging. By comparing n and m, it is preliminarily determined whether the user's needs can be met. When m is greater than n, m=n is set to reset the value of m and the user is prompted with the maximum chargeable amount. After the above processing, m≤n is obtained. After determining the charging demand of the electric vehicle at the current node, obtain the charging time period t of the electric vehicle. f ~t b The load information of n time nodes within is stored in the matrix P: P=(P1 P2 … P i … P n ) P i It is not the load value predicted at the corresponding time point, but the result of superimposing the basic load value predicted at that time point and the load of the electric vehicles with confirmed charging plans at that time point; The scheme that does not consider real-time load and user interaction completely formulates the charging strategy based on the given predicted load curve, and directly allocates the m charging time periods required by the electric vehicle to the time periods corresponding to the n time nodes in P according to the charging strategy with the smallest load fluctuation. Therefore, its optimization objective function is expressed as follows: In the formula, To determine the average load at n time points after the charging plan, K i is the switch status of the charging pile at the corresponding time point, charging corresponds to a value of 1, and shutting down corresponds to a value of 0, and K i Satisfy the following formula, which is also the constraint condition of the optimization function; After determining the charging plan, the determined P i =P i +K i The p0 value is updated to the load of the corresponding time in the matrix P, and waits for new charging requests; If the user chooses to charge in the grid dispatching mode, the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information will be used to determine whether the charging piles in the substation area can meet the charging demand; If the conditions are met, when a new electric vehicle is connected to the charging pile in the substation before the new time node, determine whether the charging plan of the connected electric vehicle has been modified and whether the real-time load information is too different from the daily load forecast result. If not, charge the newly connected electric vehicle with the historical charging plan; if so, obtain the basic information of the newly connected electric vehicle, determine the charging plan based on the basic information and electricity price information, and charge the newly connected electric vehicle with the newly formulated charging plan.

2. According to the method of claim 1, the basic information of the charging pile in the station area includes: Daily load curve, electricity price information, basic information of electric vehicles and charging facility information.

3. According to the method of claim 1, the newly connected electric vehicle selects the charging mode for charging according to the SOC information of the battery.

4. According to the method of claim 1, the basic information of the electric vehicle includes: Connection time, end time, battery SOC when connected, battery SOC when leaving, and rated charging power.

5. The method according to claim 1, wherein the charging scheme meets the requirements of the load upper limit constraint of the charging piles in the substation, user demand, peak shaving and valley filling, and grid stability.

6. An orderly charging system for electric vehicles based on a smart fusion terminal in a substation, the system comprising: The intelligent fusion terminal unit in the substation obtains the basic information of the charging piles in the substation and determines the daily load forecast results of the charging piles in the substation based on the basic information; The intelligent fusion terminal of the substation updates the load information and user demand information of the substation charging pile in real time, and determines the number of charging time periods required by the electric vehicle after the substation charging pile receives new electric vehicle access information: Where m is the number of time periods required for an electric vehicle to be fully charged, B is the battery capacity of the electric vehicle, and S c is the initial state of charge of the electric vehicle, η is the charging efficiency, t is the time interval between each charge of 15 minutes, and p is the rated charging power of the electric vehicle; Then, determine the total number of charging time periods for the electric vehicle: Where n is the total number of charging time periods for electric vehicles, t b and t f They are the start and end time of electric vehicle charging. By comparing n and m, it is preliminarily determined whether the user's needs can be met. When m is greater than n, m=n is set to reset the value of m and the user is prompted with the maximum chargeable amount. After the above processing, m≤n is obtained. After determining the charging demand of the electric vehicle at the current node, obtain the charging time period t of the electric vehicle. f ~t b The load information of n time nodes within is stored in the matrix P: P=(P1 P2 … P i … P n ) P i It is not the load value predicted at the corresponding time point, but the result of superimposing the basic load value predicted at that time point and the load of the electric vehicles with confirmed charging plans at that time point; The scheme that does not consider real-time load and user interaction completely formulates the charging strategy based on the given predicted load curve, and directly allocates the m charging time periods required by the electric vehicle to the time periods corresponding to the n time nodes in P according to the charging strategy with the smallest load fluctuation; therefore, its optimization objective function is expressed as follows: In the formula, To determine the average load at n time points after the charging plan, K i is the switch status of the charging pile at the corresponding time point, charging corresponds to a value of 1, and shutting down corresponds to a value of 0, and K i Satisfy the following formula, which is also the constraint condition of the optimization function; After determining the charging plan, the determined P i =P i +K i The p0 value is updated to the load of the corresponding time in the matrix P, and waits for new charging requests; If the user chooses to charge in the grid dispatching mode, the SOC information of the newly connected electric vehicle battery, the daily load forecast results, the real-time updated load information and the user demand information will be used to determine whether the charging piles in the substation area can meet the charging demand; If satisfied, when a new electric vehicle is connected to the charging pile in the substation before the new time node, determine whether the connected electric vehicle has modified the charging plan and whether the real-time load information is too far away from the daily load forecast result. If not, charge the newly connected electric vehicle with the historical charging plan; if so, obtain the basic information of the newly connected electric vehicle, determine the charging plan based on the basic information and electricity price information, and charge the newly connected electric vehicle with the newly formulated charging plan; The data interaction unit is used for data interaction between the intelligent fusion terminal unit in the substation and the charging piles in the substation.

7. According to the system of claim 6, the basic information of the charging piles in the area includes: Daily load curve, electricity price information, basic information of electric vehicles and charging facility information.

8. The system according to claim 6, wherein the newly connected electric vehicle selects the charging mode for charging according to the SOC information of the battery.

9. The system according to claim 6, wherein the basic information of the electric vehicle comprises: Connection time, end time, battery SOC when connected, battery SOC when leaving, and rated charging power.

10. The system according to claim 6, wherein the charging scheme meets the requirements of the load upper limit constraint of the charging piles in the substation, user demand, peak shaving and valley filling, and grid stability.

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