Virtual power plant data processing method and system based on energy storage cabinet

Abstract

This invention discloses a virtual power plant data processing method and system based on energy storage cabinets. If a heavy-duty truck charging pile is detected as connected to a heavy-duty truck, the target heavy-duty truck charging pile obtains charging and discharging task information and sends it to an edge server. If the edge server determines that it corresponds to a discharging task type, it obtains the current target discharging time period and the current amount of electricity to be discharged, retrieves the daily grid-connected price curve of the energy storage cabinet from the virtual power plant server, and determines the current V2G revenue information. The target heavy-duty truck charging pile executes the discharging task according to the confirmation instruction of the current V2G revenue information. This invention enables the edge server to determine the specific task type of the heavy-duty truck's charging and discharging task information, and when it determines that it is a discharging task type, it communicates and interacts with the virtual power plant server to quickly determine the current V2G revenue information. After the user confirms the execution of the discharging task, it intelligently controls the reverse charging process of the heavy-duty truck's charging battery module to the energy storage cabinet.

Description

Technical Field

[0001] This invention relates to the field of virtual power plant technology, and in particular to a virtual power plant data processing method and system based on energy storage cabinets. Background Technology

[0002] Currently, heavy-duty truck charging stations (heavy-duty trucks are typically deployed in locations with heavy-duty truck transportation needs, such as ports, mining areas, and industrial parks) are generally equipped with charging piles and energy storage cabinets. These cabinets supply power to the charging piles to charge the trucks. Simultaneously, the charging piles can also be directly powered by the grid to charge the trucks. However, the energy storage cabinets, as energy storage devices in heavy-duty truck charging stations, are generally used for charging the trucks connected to the charging piles and cannot interact with the virtual power plant server to intelligently control the reverse charging of the energy storage cabinet by the truck's battery module. Summary of the Invention

[0003] This invention provides a virtual power plant data processing method and system based on an energy storage cabinet, aiming to solve the problem that in the prior art, energy storage cabinets, as energy storage devices in heavy-duty truck charging stations, are generally used to charge heavy-duty trucks connected to the charging piles, and cannot interact with the virtual power plant server to intelligently control the reverse charging of the energy storage cabinet by the charging battery modules of the heavy-duty trucks.

[0004] In a first aspect, embodiments of the present invention provide a virtual power plant data processing method based on an energy storage cabinet, applied to a virtual power plant data processing system based on an energy storage cabinet. The virtual power plant data processing system includes several heavy-duty truck charging station subsystems and a virtual power plant server. Each of the heavy-duty truck charging station subsystems includes several heavy-duty truck charging piles, several energy storage cabinets, and an edge server. The several heavy-duty truck charging piles are connected to the several energy storage cabinets, and both the several heavy-duty truck charging piles and the several energy storage cabinets are communicatively connected to the edge server. The edge server is communicatively connected to the virtual power plant server. The method includes:

[0005] For each of the several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the heavy-duty truck charging station subsystem is detected to have been successfully connected to the charging port of the heavy-duty truck, then the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server.

[0006] If the edge server determines that the charging and discharging task information corresponds to the discharging task type, it obtains the current target time period and the current amount of electricity to be discharged from the charging and discharging task information, and obtains the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0007] The edge server determines the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and sends it to the receiving end connected to the current target heavy truck charging pile.

[0008] If the current target heavy-duty truck charging pile detects a confirmation instruction for the current V2G revenue information, it will charge several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information until the current discharge capacity is discharged within the current discharge target time period.

[0009] Secondly, embodiments of the present invention also provide a virtual power plant data processing system based on an energy storage cabinet, which includes several heavy-duty truck charging station subsystems and a virtual power plant server. Each of the several heavy-duty truck charging station subsystems includes several heavy-duty truck charging piles, several energy storage cabinets, and an edge server. The several heavy-duty truck charging piles are connected to the several energy storage cabinets, and the connections of the several heavy-duty truck charging piles and the several energy storage cabinets are all communicatively connected to the edge server. The edge server is communicatively connected to the virtual power plant server.

[0010] For each of the several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the heavy-duty truck charging station subsystem is detected to have been successfully connected to the charging port of the heavy-duty truck, then the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server.

[0011] The edge server is used to obtain the current target discharge time period and the current amount of electricity to be discharged from the charge and discharge task information if it is determined that the charge and discharge task information corresponds to the discharge task type, and to obtain the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0012] The edge server is also used to determine the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and send it to the current target heavy truck charging pile.

[0013] The current target heavy-duty truck charging pile is used to charge several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information if a confirmation instruction for the current V2G revenue information is detected, until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period.

[0014] This invention provides a virtual power plant data processing method and system based on energy storage cabinets. The method includes: for each of several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the subsystem is detected to have successfully connected to the charging port of a heavy-duty truck, the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server; if the edge server determines that the charging and discharging task information corresponds to the discharging task type, it obtains the current target discharging time period and the current amount of electricity to be discharged from the charging and discharging task information, and obtains the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server; the edge server determines the current V2G revenue information based on the current target discharging time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet for the day, and sends it to the receiving end connected to the current target heavy-duty truck charging pile; if the current target heavy-duty truck charging pile detects a confirmation instruction for the current V2G revenue information, it charges several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information until the discharge operation of the current amount of electricity to be discharged is completed within the current target discharging time period. The embodiments of the present invention can determine the specific task type of the charging and discharging task information of the heavy truck by the edge server, and when it is determined to be a discharging task type, communicate and interact with the virtual power plant server to quickly determine the current V2G revenue information. After the user confirms the execution of the discharging task, the reverse charging process of the heavy truck's charging battery module to the energy storage cabinet is intelligently controlled. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of a scenario for a virtual power plant data processing method based on an energy storage cabinet, according to an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of the structure of the energy storage cabinet in the scenario illustration of the virtual power plant data processing method based on the energy storage cabinet according to an embodiment of the present invention;

[0018] Figure 3 This is a flowchart illustrating the data processing method for a virtual power plant based on an energy storage cabinet provided in an embodiment of the present invention.

[0019] Figure 4 This is a schematic diagram of the first sub-process of the virtual power plant data processing method based on energy storage cabinet provided in an embodiment of the present invention;

[0020] Figure 5This is another flowchart illustrating the virtual power plant data processing method based on energy storage cabinets provided in this embodiment of the invention.

[0021] Figure 6 This is a schematic diagram of the second sub-process of the virtual power plant data processing method based on energy storage cabinet provided in the embodiments of the present invention;

[0022] Figure 7 This is a schematic diagram of the third sub-process of the virtual power plant data processing method based on energy storage cabinet provided in the embodiments of the present invention;

[0023] Figure 8 This is a schematic block diagram of a virtual power plant data processing system based on an energy storage cabinet, provided as an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0026] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0027] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0028] Please also refer to Figures 1-3 ,in Figure 1 This is a schematic diagram of a scenario for the virtual power plant data processing method based on an energy storage cabinet according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the energy storage cabinet in the scenario illustration of the virtual power plant data processing method based on the energy storage cabinet according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating the virtual power plant data processing method based on an energy storage cabinet provided in an embodiment of the present invention. Figure 1 and Figure 2 As shown in the figure, the virtual power plant data processing method based on energy storage cabinet provided in this embodiment of the invention is applied to a virtual power plant data processing system based on energy storage cabinet. The virtual power plant data processing system based on energy storage cabinet includes several heavy-duty truck charging station subsystems 100 and a virtual power plant server 200. Each heavy-duty truck charging station subsystem 110 in the several heavy-duty truck charging station subsystems 100 includes several heavy-duty truck charging piles 111, several energy storage cabinets 112 and an edge server 113. The several heavy-duty truck charging piles 111 are connected to the several energy storage cabinets 112, and the several heavy-duty truck charging piles 111 and the several energy storage cabinets 112 are all connected to the edge server 113 for communication. The edge server 113 is connected to the virtual power plant server 200 for communication. Specifically, the energy storage cabinet 112 can be a modular energy storage box, for example, it supports three-phase four-wire AC access, has a capacity of 261 kWh (or other capacities, which can be determined according to actual design requirements), uses liquid cooling and has an operating temperature of -20℃ to 50℃.

[0029] like Figure 3 As shown, the method includes the following steps S110-S140.

[0030] S110. For each of the several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the heavy-duty truck charging station subsystem is detected to have been successfully connected to the charging port of the heavy-duty truck, then the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server.

[0031] In this embodiment, if a heavy-duty truck driver drives his heavy-duty truck into a heavy-duty truck charging station based on his actual usage needs (such as needing to fully charge the truck's battery module in time for upcoming trips, or not needing to use the truck in the near future and only needing to leave a portion of the battery charge to be fully charged before the next time he needs to use it), he can select one of the idle heavy-duty truck charging piles and connect his charging gun to the truck's charging port. He can then set the charging and discharging task information for the heavy-duty truck on the touch screen of the heavy-duty truck charging pile. In order to obtain the user's usage needs more quickly and accurately, the charging and discharging task information can be sent to the edge server included in the heavy-duty truck charging station subsystem to which the heavy-duty truck charging pile belongs for corresponding rapid data processing.

[0032] S120. If the edge server determines that the charging and discharging task information corresponds to the discharging task type, it obtains the current target time period and the current amount of electricity to be discharged from the charging and discharging task information, and obtains the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0033] In this embodiment, if the edge server determines that the charging / discharging task information corresponds to a discharging task type, it means that the user has selected the V2G technology (V2G stands for Vehicle-to-Grid, a two-way interactive technology that allows electric vehicles or heavy trucks to both charge and send power back to the grid) supported by the heavy truck charging station to send power back to the grid. Of course, when sending power back to the grid through the heavy truck charging station, the energy storage cabinet in the heavy truck charging station needs to store the electricity first, and the electricity can be sent back to the grid during peak electricity price periods. To more intelligently send the electricity from the energy storage cabinet in the heavy truck charging station back to the grid, the edge server can first obtain the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0034] S130, The edge server determines the current V2G revenue information based on the current discharge target time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and sends it to the receiving end connected to the current target heavy truck charging pile.

[0035] In this embodiment, the edge server extracts the current target discharge time period and the current amount of electricity to be discharged from the charging and discharging task information, and calculates the current V2G revenue information by combining it with the grid-connected price curve of the energy storage cabinet obtained from the virtual power plant server. Specifically, the edge server can verify the current amount of electricity to be discharged by comparing it with the current remaining capacity of the heavy truck's charging battery module. Only when the ratio of the current remaining capacity minus the current amount of electricity to be discharged, divided by the full capacity of the heavy truck's charging battery module, is greater than a first ratio threshold, can the current amount of electricity to be discharged in the charging and discharging task information be considered to have passed the discharge task verification. This ensures that the heavy truck has sufficient reserve power to ensure that it can be driven a certain distance to a heavy truck charging station for charging on the next trip.

[0036] After obtaining the current V2G revenue information related to the charging / discharging task from the edge server, it can be sent to the receiving end used by the heavy truck driver, such as a smartphone. After the heavy truck driver connects the charging gun of the target heavy truck charging station to the truck, the receiving end can scan the QR code currently displayed on the touch screen of the target heavy truck charging station to establish a communication connection. The current V2G revenue information determined by the edge server is not sent directly to the target heavy truck charging station, but rather to the receiving end to which the target heavy truck charging station is connected, to avoid the current V2G revenue information being stored and displayed at the target heavy truck charging station, effectively improving the security of privacy data.

[0037] In one embodiment, such as Figure 4 As shown, step S130 includes:

[0038] S131. Determine the current candidate grid connection price curve from the grid connection price curve of the energy storage cabinet on the same day according to the current target discharge time period;

[0039] S132. Determine the current V2G revenue information based on the current amount of electricity to be discharged and the current candidate grid connection price curve.

[0040] In this embodiment, when determining the current V2G revenue information in the edge server based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on that day, the current candidate grid-connected price curve can first be determined based on the current target discharge time period in the grid-connected price curve of the energy storage cabinet on that day (in the grid-connected price curve of the energy storage cabinet on that day, the horizontal axis is time and the vertical axis is the real-time grid-connected price of the energy storage cabinet). That is, the corresponding horizontal axis value range in the grid-connected price curve of the energy storage cabinet on that day is selected by the current target discharge time period. Then, the current V2G revenue information is determined based on the current amount of electricity to be discharged and the current candidate grid-connected price curve, and the calculation process is similar to the integral operation in mathematical operations. The current V2G revenue information obtained in the edge server can be directly sent to the receiving end for heavy truck drivers to view intuitively.

[0041] In one embodiment, such as Figure 4 As shown, after step S132, the following steps are also included:

[0042] S133. Obtain the heavy truck identity identifier corresponding to the charging and discharging task information, and send the heavy truck identity identifier and the current V2G revenue information to the virtual power plant server, so that the virtual power plant server adds the digital signature corresponding to the heavy truck identity identifier to the current V2G revenue information and sends it back to the edge server.

[0043] In this embodiment, to enhance the data security and reliability of the current V2G revenue information, the heavy-duty truck identification (such as the truck's chassis number) can be extracted from the charging and discharging task information. Then, the heavy-duty truck identification and the current V2G revenue information are sent to the virtual power plant server. After the virtual power plant server obtains the digital signature corresponding to the heavy-duty truck identification, it adds it to the current V2G revenue information to update it. Subsequently, the virtual power plant server sends the updated current V2G revenue information back to the edge server. This process of adding a digital signature to the current V2G revenue information improves its data security and reliability.

[0044] S140. If the current target heavy truck charging pile detects a confirmation instruction for the current V2G revenue information, it charges several energy storage cabinets connected to the current target heavy truck charging pile according to the charging and discharging task information until the current discharge capacity is discharged within the current discharge target time period.

[0045] In this embodiment, after the heavy-duty truck driver views the current V2G revenue information through their receiver, if they click "Confirm to Start Charging / Discharging Task" on the user interface, a confirmation command is generated and sent to the edge server. The edge server then forwards the confirmation command for the current V2G revenue information to the target heavy-duty truck charging station. Once the target heavy-duty truck charging station detects the confirmation command for the current V2G revenue information, it can execute the charging / discharging task corresponding to the charging / discharging task information. The charging / discharging task information is used to charge several energy storage cabinets connected to the target heavy-duty truck charging station until the current discharge capacity is discharged within the target discharge time period.

[0046] In one embodiment, step S140 includes:

[0047] Based on the current discharge target time period and the current amount of electricity to be discharged corresponding to the charging and discharging task information, the power of the charging battery module of the heavy truck is controlled to charge several energy storage cabinets connected to the current target heavy truck charging pile until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period.

[0048] In this embodiment, when controlling the charging battery module of the heavy truck to charge several energy storage cabinets connected to the current target heavy truck charging pile according to the current discharge target time period and the current amount of electricity to be discharged, the energy storage cabinets that are currently idle can be sorted in order from the lowest remaining energy to the highest remaining energy. Then, it is calculated whether the sum of the remaining energy of the top N energy storage cabinets is exactly greater than the current amount of electricity to be discharged (the sum of the remaining energy of the top N-1 energy storage cabinets is less than the current amount of electricity to be discharged). The discharge capacity is calculated by adding the remaining capacity of the first Nth energy storage cabinet to the current discharge capacity. When this first exceeds the current discharge capacity, it is considered whether the sum of the remaining capacity of the first N energy storage cabinets is exactly greater than the current discharge capacity (where N is a positive integer). When it is determined that the sum of the remaining capacity of the first N energy storage cabinets is greater than the current discharge capacity for the first time, the corresponding energy storage cabinet is selected as the energy storage cabinet to be charged. The charging order of the charging battery modules of the heavy truck in these energy storage cabinets to be charged is also in the order from the 1st to the Nth position. This arrangement can effectively reduce the total number of times the charging object is switched.

[0049] Among them, the rechargeable battery module of the heavy truck is discharged within the current discharge target time period. During high current discharge, there is a serious concentration polarization phenomenon. According to the internal equivalent circuit model of the rechargeable battery module (such as the second-order RC model), the edge server can issue a discharge sequence with a preset pulse interval and use the pulsed intermittent discharge method to eliminate the concentration polarization.

[0050] In one embodiment, such as Figure 5 As shown, after step S110, the following is also included:

[0051] S150. If the edge server determines that the charging and discharging task information corresponds to a charging task type, it obtains the current charging task and the charging task priority identifier from the charging and discharging task information; wherein, the charging task priority identifier is an efficient charging identifier or a low-cost charging identifier.

[0052] S160. The edge server determines the current energy storage cabinet charging task sequence corresponding to the current charging task based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy truck charging station subsystem, and the preset charging task allocation strategy.

[0053] S170. The edge server controls the corresponding energy storage cabinets in several energy storage cabinets in the heavy truck charging station subsystem to perform charging operations on the heavy truck according to the current energy storage cabinet charging task sequence, until the current charging task is completed.

[0054] In this embodiment, if the edge server determines that the charging / discharging task information corresponds to a charging task type, it indicates that the heavy-duty truck's battery module has a charging requirement. At this point, it can specifically obtain the current charging task and charging task priority identifier from the charging / discharging task information. The charging task priority identifier is either a high-efficiency charging identifier or a low-price charging identifier. The current charging task is a charging task such as charging for a set duration, charging for a set amount, or fully charging the battery. Through the current charging task and charging task priority identifier, the edge server can more intelligently and reasonably determine the charging task for the heavy-duty truck's battery module.

[0055] In the edge server, specifically, based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy-duty truck charging station subsystem, and a preset charging task allocation strategy, a current energy storage cabinet charging task sequence corresponding to the current charging task is determined. The current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each corresponding to an energy storage cabinet ID and a charging task power (representing the power output value required by the energy storage cabinet to execute this charging task).

[0056] Subsequently, based on the current energy storage cabinet charging task sequence, the edge server sequentially controls the corresponding energy storage cabinets in the heavy-duty truck charging station subsystem to perform charging operations on the heavy-duty truck according to the order of the energy storage cabinet charging tasks, until the current charging task is completed. By controlling the entire charging task through the current energy storage cabinet charging task sequence, the remaining power of each energy storage cabinet is fully considered, and the charging of each energy storage cabinet is more rationally scheduled while meeting the user's charging needs.

[0057] In one embodiment, as a first embodiment of step S160, such as Figure 6 As shown, step S160 includes:

[0058] S1611. If the charging task priority identifier is determined to be an efficient charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with fast charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the first energy storage cabinet.

[0059] S1612. Based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, select the corresponding number of first candidate energy storage cabinet remaining amounts from the descending sorting results of the remaining amounts of the first energy storage cabinet in descending order, and form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the energy storage cabinet charging task amount corresponding to the remaining amounts of each first candidate energy storage cabinet.

[0060] In this embodiment, as the first embodiment of step S160, if the charging task priority identifier is determined to be a high-efficiency charging identifier in the edge server, it means that the user needs to complete the charging task of the heavy truck's battery module in the shortest possible time. At this time, according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with fast charging identifiers in the heavy truck charging station subsystem is sorted in descending order to obtain the first energy storage cabinet remaining power descending order sorting result. Then, according to the charging task allocation strategy and the current power to be charged corresponding to the current charging task, the remaining power of the first energy storage cabinets is selected in descending order from the first energy storage cabinet remaining power descending order, so that the sum of the remaining power of these first candidate energy storage cabinets is exactly greater than the current power to be charged in the charging and discharging task information for the first time (that is, as long as the remaining power of any one of the first candidate energy storage cabinets is reduced, the sum of the remaining power of these first candidate energy storage cabinets will be less than the current power to be charged). After obtaining the energy storage cabinet ID number and charging task amount corresponding to the remaining power of the first number of candidate energy storage cabinets in descending order, a current energy storage cabinet charging task sequence can be formed. This current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each with its own energy storage cabinet ID number and charging task amount. This intelligent determination method of the current energy storage cabinet charging task sequence effectively reduces the total number of energy storage cabinet switching operations when charging the battery modules of heavy-duty trucks.

[0061] In one embodiment, as a second embodiment of step S160, such as Figure 7 As shown, step S160 includes:

[0062] S1621. If the charging task priority identifier is determined to be a low-price charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with ordinary power charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the second energy storage cabinet.

[0063] S1622. According to the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, select the corresponding number of second candidate energy storage cabinet remaining amounts from the descending sorting results of the remaining amounts of the second energy storage cabinet in descending order, and form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the energy storage cabinet charging task amount corresponding to the remaining amounts of each second candidate energy storage cabinet.

[0064] In this embodiment, as a second embodiment of step S160, if the charging task priority identifier is determined to be a low-price charging identifier in the edge server, it means that the user needs to complete the charging task of the heavy truck's battery module at the lowest charging cost. At this time, according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with the normal power charging identifier in the several energy storage cabinets of the heavy truck charging station subsystem is sorted in descending order to obtain the second energy storage cabinet remaining power descending order sorting result; wherein, the charging unit price of the energy storage cabinet with the normal power charging identifier is generally lower than the charging unit price of the energy storage cabinet with the fast charging identifier. Next, based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, a corresponding number of second candidate energy storage cabinets are selected from the descending sorted results of the remaining electricity of the second energy storage cabinets. This ensures that the sum of the remaining electricity of these second candidate energy storage cabinets is exactly greater than the current amount of electricity to be charged in the charging / discharging task information (i.e., reducing the remaining electricity of any one of the second candidate energy storage cabinets will result in the sum of their remaining electricity being less than the current amount of electricity to be charged). After obtaining the energy storage cabinet ID and charging task electricity corresponding to the remaining electricity of each of the selected second candidate energy storage cabinets in descending order, the current energy storage cabinet charging task sequence can be formed. This current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each with its own energy storage cabinet ID and charging task electricity. This intelligent determination method for the current energy storage cabinet charging task sequence effectively reduces the total number of energy storage cabinet switching operations when charging the battery modules of heavy trucks.

[0065] As can be seen, the implementation of this method can enable the edge server to determine the specific task type of the heavy truck's charging and discharging task information, and when it is determined to be a discharging task type, it can communicate and interact with the virtual power plant server to quickly determine the current V2G revenue information, and intelligently control the reverse charging process of the heavy truck's charging battery module to the energy storage cabinet after the user confirms the execution of the discharging task.

[0066] Figure 8 This is a schematic block diagram of a virtual power plant data processing system based on an energy storage cabinet, provided in an embodiment of the present invention. Figure 8As shown, corresponding to the above-described virtual power plant data processing method based on energy storage cabinets, the present invention also provides a virtual power plant data processing system 10 based on energy storage cabinets. This virtual power plant data processing system 10 includes several heavy-duty truck charging station subsystems 100 and a virtual power plant server 200. Each heavy-duty truck charging station subsystem 110 includes several heavy-duty truck charging piles 111, several energy storage cabinets 112, and an edge server 113. The heavy-duty truck charging piles 111 are connected to the several energy storage cabinets 112, and both the heavy-duty truck charging piles 111 and the several energy storage cabinets 112 are communicatively connected to the edge server 113. The edge server 113 is communicatively connected to the virtual power plant server 200. Specifically, the energy storage cabinet 112 can be a modular energy storage box, for example, it supports three-phase four-wire AC access, has a capacity of 261 kWh (or other capacities, which can be determined according to actual design requirements), uses liquid cooling and has an operating temperature of -20℃ to 50℃.

[0067] For each of the several heavy-duty truck charging station subsystems, the heavy-duty truck charging pile is used to detect that it has been successfully connected to the charging port of the heavy-duty truck. Then, the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server.

[0068] In this embodiment, if a heavy-duty truck driver drives his heavy-duty truck into a heavy-duty truck charging station based on his actual usage needs (such as needing to fully charge the truck's battery module in time for upcoming trips, or not needing to use the truck in the near future and only needing to leave a portion of the battery charge to be fully charged before the next time he needs to use it), he can select one of the idle heavy-duty truck charging piles and connect his charging gun to the truck's charging port. He can then set the charging and discharging task information for the heavy-duty truck on the touch screen of the heavy-duty truck charging pile. In order to obtain the user's usage needs more quickly and accurately, the charging and discharging task information can be sent to the edge server included in the heavy-duty truck charging station subsystem to which the heavy-duty truck charging pile belongs for corresponding rapid data processing.

[0069] The edge server 113 is used to obtain the current target discharge time period and the current amount of electricity to be discharged from the charge and discharge task information if it is determined that the charge and discharge task information corresponds to the discharge task type, and to obtain the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0070] In this embodiment, if the edge server determines that the charging / discharging task information corresponds to a discharging task type, it means that the user has selected the V2G technology (V2G stands for Vehicle-to-Grid, a two-way interactive technology that allows electric vehicles or heavy trucks to both charge and send power back to the grid) supported by the heavy truck charging station to send power back to the grid. Of course, when sending power back to the grid through the heavy truck charging station, the energy storage cabinet in the heavy truck charging station needs to store the electricity first, and the electricity can be sent back to the grid during peak electricity price periods. To more intelligently send the electricity from the energy storage cabinet in the heavy truck charging station back to the grid, the edge server can first obtain the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server.

[0071] The edge server 113 is also used to determine the current V2G revenue information based on the current discharge target time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and send it to the receiving end connected to the current target heavy truck charging pile.

[0072] In this embodiment, the edge server extracts the current target discharge time period and the current amount of electricity to be discharged from the charging and discharging task information, and calculates the current V2G revenue information by combining it with the grid-connected price curve of the energy storage cabinet obtained from the virtual power plant server. Specifically, the edge server can verify the current amount of electricity to be discharged by comparing it with the current remaining capacity of the heavy truck's charging battery module. Only when the ratio of the current remaining capacity minus the current amount of electricity to be discharged, divided by the full capacity of the heavy truck's charging battery module, is greater than a first ratio threshold, can the current amount of electricity to be discharged in the charging and discharging task information be considered to have passed the discharge task verification. This ensures that the heavy truck has sufficient reserve power to ensure that it can be driven a certain distance to a heavy truck charging station for charging on the next trip.

[0073] After obtaining the current V2G revenue information related to the charging / discharging task from the edge server, it can be sent to the receiving end used by the heavy truck driver, such as a smartphone. After the heavy truck driver connects the charging gun of the target heavy truck charging station to the truck, the receiving end can scan the QR code currently displayed on the touch screen of the target heavy truck charging station to establish a communication connection. The current V2G revenue information determined by the edge server is not sent directly to the target heavy truck charging station, but rather to the receiving end to which the target heavy truck charging station is connected, to avoid the current V2G revenue information being stored and displayed at the target heavy truck charging station, effectively improving the security of privacy data.

[0074] In one embodiment, the edge server 113 is specifically used for:

[0075] Based on the current target discharge time period, determine the current candidate grid connection price curve from the daily energy storage cabinet grid connection price curve;

[0076] The current V2G revenue information is determined based on the current amount of electricity to be discharged and the current candidate grid connection price curve.

[0077] In this embodiment, when determining the current V2G revenue information in the edge server based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on that day, the current candidate grid-connected price curve can first be determined based on the current target discharge time period in the grid-connected price curve of the energy storage cabinet on that day (in the grid-connected price curve of the energy storage cabinet on that day, the horizontal axis is time and the vertical axis is the real-time grid-connected price of the energy storage cabinet). That is, the corresponding horizontal axis value range in the grid-connected price curve of the energy storage cabinet on that day is selected by the current target discharge time period. Then, the current V2G revenue information is determined based on the current amount of electricity to be discharged and the current candidate grid-connected price curve, and the calculation process is similar to the integral operation in mathematical operations. The current V2G revenue information obtained in the edge server can be directly sent to the receiving end for heavy truck drivers to view intuitively.

[0078] In one embodiment, the edge server 113 is further specifically used for:

[0079] Obtain the heavy truck identity identifier corresponding to the charging and discharging task information, and send the heavy truck identity identifier and the current V2G revenue information to the virtual power plant server, so that the virtual power plant server adds the digital signature corresponding to the heavy truck identity identifier to the current V2G revenue information and sends it back to the edge server.

[0080] In this embodiment, to enhance the data security and reliability of the current V2G revenue information, the heavy-duty truck identification (such as the truck's chassis number) can be extracted from the charging and discharging task information. Then, the heavy-duty truck identification and the current V2G revenue information are sent to the virtual power plant server. After the virtual power plant server obtains the digital signature corresponding to the heavy-duty truck identification, it adds it to the current V2G revenue information to update it. Subsequently, the virtual power plant server sends the updated current V2G revenue information back to the edge server. This process of adding a digital signature to the current V2G revenue information improves its data security and reliability.

[0081] The current target heavy-duty truck charging pile is used to charge several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information if a confirmation instruction for the current V2G revenue information is detected, until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period.

[0082] In this embodiment, after the heavy-duty truck driver views the current V2G revenue information through their receiver, if they click "Confirm to Start Charging / Discharging Task" on the user interface, a confirmation command is generated and sent to the edge server. The edge server then forwards the confirmation command for the current V2G revenue information to the target heavy-duty truck charging station. Once the target heavy-duty truck charging station detects the confirmation command for the current V2G revenue information, it can execute the charging / discharging task corresponding to the charging / discharging task information. The charging / discharging task information is used to charge several energy storage cabinets connected to the target heavy-duty truck charging station until the current discharge capacity is discharged within the target discharge time period.

[0083] In one embodiment, the current target heavy-duty truck charging station is specifically used for:

[0084] Based on the current discharge target time period and the current amount of electricity to be discharged corresponding to the charging and discharging task information, the power of the charging battery module of the heavy truck is controlled to charge several energy storage cabinets connected to the current target heavy truck charging pile until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period.

[0085] In this embodiment, when controlling the charging battery module of the heavy truck to charge several energy storage cabinets connected to the current target heavy truck charging pile according to the current discharge target time period and the current amount of electricity to be discharged, the energy storage cabinets that are currently idle can be sorted in order from the lowest remaining energy to the highest remaining energy. Then, it is calculated whether the sum of the remaining energy of the top N energy storage cabinets is exactly greater than the current amount of electricity to be discharged (the sum of the remaining energy of the top N-1 energy storage cabinets is less than the current amount of electricity to be discharged). The discharge capacity is calculated by adding the remaining capacity of the first Nth energy storage cabinet to the current discharge capacity. When this first exceeds the current discharge capacity, it is considered whether the sum of the remaining capacity of the first N energy storage cabinets is exactly greater than the current discharge capacity (where N is a positive integer). When it is determined that the sum of the remaining capacity of the first N energy storage cabinets is greater than the current discharge capacity for the first time, the corresponding energy storage cabinet is selected as the energy storage cabinet to be charged. The charging order of the charging battery modules of the heavy truck in these energy storage cabinets to be charged is also in the order from the 1st to the Nth position. This arrangement can effectively reduce the total number of times the charging object is switched.

[0086] Among them, the rechargeable battery module of the heavy truck is discharged within the current discharge target time period. During high current discharge, there is a serious concentration polarization phenomenon. According to the internal equivalent circuit model of the rechargeable battery module (such as the second-order RC model), the edge server can issue a discharge sequence with a preset pulse interval and use the pulsed intermittent discharge method to eliminate the concentration polarization.

[0087] In one embodiment, the edge server 113 is further configured to:

[0088] If it is determined that the charging and discharging task information corresponds to a charging task type, then the current charging task and the charging task priority identifier in the charging and discharging task information are obtained; wherein, the charging task priority identifier is an efficient charging identifier or a low-cost charging identifier.

[0089] Based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy truck charging station subsystem, and the preset charging task allocation strategy, determine the current energy storage cabinet charging task sequence corresponding to the current charging task.

[0090] According to the current energy storage cabinet charging task sequence, the corresponding energy storage cabinet in the heavy truck charging station subsystem is controlled to perform charging operation on the heavy truck until the current charging task is completed.

[0091] In this embodiment, if the edge server determines that the charging / discharging task information corresponds to a charging task type, it indicates that the heavy-duty truck's battery module has a charging requirement. At this point, it can specifically obtain the current charging task and charging task priority identifier from the charging / discharging task information. The charging task priority identifier is either a high-efficiency charging identifier or a low-price charging identifier. The current charging task is a charging task such as charging for a set duration, charging for a set amount, or fully charging the battery. Through the current charging task and charging task priority identifier, the edge server can more intelligently and reasonably determine the charging task for the heavy-duty truck's battery module.

[0092] In the edge server, specifically, based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy-duty truck charging station subsystem, and a preset charging task allocation strategy, a current energy storage cabinet charging task sequence corresponding to the current charging task is determined. The current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each corresponding to an energy storage cabinet ID and a charging task power (representing the power output value required by the energy storage cabinet to execute this charging task).

[0093] Subsequently, based on the current energy storage cabinet charging task sequence, the edge server sequentially controls the corresponding energy storage cabinets in the heavy-duty truck charging station subsystem to perform charging operations on the heavy-duty truck according to the order of the energy storage cabinet charging tasks, until the current charging task is completed. By controlling the entire charging task through the current energy storage cabinet charging task sequence, the remaining power of each energy storage cabinet is fully considered, and the charging of each energy storage cabinet is more rationally scheduled while meeting the user's charging needs.

[0094] In one embodiment, as a first embodiment of edge server 113, edge server 113 is further specifically used for:

[0095] If the charging task priority identifier is determined to be an efficient charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with fast charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the first energy storage cabinet.

[0096] Based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, the remaining electricity of the first energy storage cabinet is selected in descending order from the results of the descending sorting of the remaining electricity of the first energy storage cabinet. The remaining electricity of each first candidate energy storage cabinet is used to form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the charging task electricity of the energy storage cabinet.

[0097] In this embodiment, as a first embodiment of the edge server 113, if the charging task priority identifier is determined to be a high-efficiency charging identifier in the edge server, it means that the user needs to complete the charging task of the heavy truck's battery module in the shortest possible time. At this time, according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with fast charging identifiers in several energy storage cabinets of the heavy truck charging station subsystem is sorted in descending order to obtain the first energy storage cabinet remaining power descending order sorting result. Then, according to the charging task allocation strategy and the current power to be charged corresponding to the current charging task, the remaining power of the first energy storage cabinets is selected in descending order from the first energy storage cabinet remaining power descending order, so that the sum of the remaining power of these first candidate energy storage cabinets is exactly greater than the current power to be charged in the charging and discharging task information for the first time (that is, as long as the remaining power of any one of the first candidate energy storage cabinets is reduced, the sum of the remaining power of these first candidate energy storage cabinets will be less than the current power to be charged). After obtaining the energy storage cabinet ID number and charging task amount corresponding to the remaining power of the first number of candidate energy storage cabinets in descending order, a current energy storage cabinet charging task sequence can be formed. This current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each with its own energy storage cabinet ID number and charging task amount. This intelligent determination method of the current energy storage cabinet charging task sequence effectively reduces the total number of energy storage cabinet switching operations when charging the battery modules of heavy-duty trucks.

[0098] In one embodiment, as a second embodiment of edge server 113, edge server 113 is further specifically used for:

[0099] If the charging task priority identifier is determined to be a low-price charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with ordinary power charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the second energy storage cabinet.

[0100] Based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, the remaining electricity of the second energy storage cabinet is selected in descending order from the results of the descending sorting of the remaining electricity of the second energy storage cabinet. The remaining electricity of each second candidate energy storage cabinet is used to form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the charging task electricity of the energy storage cabinet.

[0101] In this embodiment, as a second embodiment of the edge server 113, if the charging task priority identifier is determined to be a low-price charging identifier in the edge server, it means that the user needs to complete the charging task of the heavy truck's battery module at the lowest charging cost. At this time, according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with the normal power charging identifier in the several energy storage cabinets of the heavy truck charging station subsystem is sorted in descending order to obtain the second energy storage cabinet remaining power descending order sorting result; wherein, the charging unit price of the energy storage cabinet with the normal power charging identifier is generally lower than the charging unit price of the energy storage cabinet with the fast charging identifier. Next, based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, a corresponding number of second candidate energy storage cabinets are selected from the descending sorted results of the remaining electricity of the second energy storage cabinets. This ensures that the sum of the remaining electricity of these second candidate energy storage cabinets is exactly greater than the current amount of electricity to be charged in the charging / discharging task information (i.e., reducing the remaining electricity of any one of the second candidate energy storage cabinets will result in the sum of their remaining electricity being less than the current amount of electricity to be charged). After obtaining the energy storage cabinet ID and charging task electricity corresponding to the remaining electricity of each of the selected second candidate energy storage cabinets in descending order, the current energy storage cabinet charging task sequence can be formed. This current energy storage cabinet charging task sequence includes several energy storage cabinet charging tasks, each with its own energy storage cabinet ID and charging task electricity. This intelligent determination method for the current energy storage cabinet charging task sequence effectively reduces the total number of energy storage cabinet switching operations when charging the battery modules of heavy trucks.

[0102] As can be seen, the implementation of this system can enable the edge server to determine the specific task type of the heavy truck's charging and discharging task information, and when it is determined to be a discharging task type, it can communicate and interact with the virtual power plant server to quickly determine the current V2G revenue information. After the user confirms the execution of the discharging task, it can intelligently control the reverse charging process of the heavy truck's charging battery module to the energy storage cabinet.

[0103] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0104] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0105] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0106] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0107] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A virtual power plant data processing method based on energy storage cabinets, applied to a virtual power plant data processing system based on energy storage cabinets, characterized in that, The virtual power plant data processing system based on energy storage cabinets includes several heavy-duty truck charging station subsystems and a virtual power plant server. Each heavy-duty truck charging station subsystem includes several heavy-duty truck charging piles, several energy storage cabinets, and an edge server. The heavy-duty truck charging piles are connected to the energy storage cabinets, and both the heavy-duty truck charging piles and the energy storage cabinets are communicatively connected to the edge server. The edge server is communicatively connected to the virtual power plant server. The method includes: For each of the several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the heavy-duty truck charging station subsystem is detected to have been successfully connected to the charging port of the heavy-duty truck, then the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server. If the edge server determines that the charging and discharging task information corresponds to the discharging task type, it obtains the current target time period and the current amount of electricity to be discharged from the charging and discharging task information, and obtains the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server. The edge server determines the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and sends it to the receiving end connected to the current target heavy truck charging pile. If the current target heavy truck charging pile detects a confirmation instruction for the current V2G revenue information, it will charge several energy storage cabinets connected to the current target heavy truck charging pile according to the charging and discharging task information until the current discharge capacity is discharged within the current discharge target time period. The step of charging several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information until the current discharge target time period is completed includes: Based on the current discharge target time period and the current amount of electricity to be discharged corresponding to the charging and discharging task information, the power of the charging battery module of the heavy truck is controlled to charge several energy storage cabinets connected to the current target heavy truck charging pile until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period; wherein, the energy storage cabinets that are currently idle are first sorted in order from the lowest remaining energy to the highest remaining energy. When it is determined that the sum of the remaining energy of the first N energy storage cabinets is greater than the current amount of electricity to be discharged for the first time, the corresponding energy storage cabinet is selected as the energy storage cabinet to be charged, and the charging order of the charging battery module of the heavy truck in the energy storage cabinet to be charged is also in the sorting order from the 1st to the Nth position; N is a positive integer.

2. The method according to claim 1, characterized in that, The step of determining the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet for the day includes: Based on the current target discharge time period, determine the current candidate grid connection price curve from the daily energy storage cabinet grid connection price curve; The current V2G revenue information is determined based on the current amount of electricity to be discharged and the current candidate grid connection price curve.

3. The method according to claim 2, characterized in that, After determining the current V2G revenue information based on the current amount of electricity to be discharged and the current candidate grid connection price curve, the method further includes: Obtain the heavy truck identity identifier corresponding to the charging and discharging task information, and send the heavy truck identity identifier and the current V2G revenue information to the virtual power plant server, so that the virtual power plant server adds the digital signature corresponding to the heavy truck identity identifier to the current V2G revenue information and sends it back to the edge server.

4. The method according to claim 1, characterized in that, In each of the plurality of heavy-duty truck charging station subsystems, after the step of detecting that a heavy-duty truck charging pile in the subsystem has been successfully connected to the charging port of a heavy-duty truck, obtaining the charging and discharging task information corresponding to the heavy-duty truck as the current target heavy-duty truck charging pile, and sending the charging and discharging task information to the corresponding edge server, the method further includes: If the edge server determines that the charging and discharging task information corresponds to a charging task type, it obtains the current charging task and the charging task priority identifier from the charging and discharging task information; wherein, the charging task priority identifier is an efficient charging identifier or a low-cost charging identifier. The edge server determines the current energy storage cabinet charging task sequence corresponding to the current charging task based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy truck charging station subsystem, and the preset charging task allocation strategy. The edge server controls the corresponding energy storage cabinets in several energy storage cabinets in the heavy truck charging station subsystem to perform charging operations on the heavy truck according to the current energy storage cabinet charging task sequence, until the current charging task is completed.

5. The method according to claim 4, characterized in that, The step of determining the current energy storage cabinet charging task sequence corresponding to the current charging task based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy truck charging station subsystem, and a preset charging task allocation strategy includes: If the charging task priority identifier is determined to be an efficient charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with fast charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the first energy storage cabinet. Based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, the remaining electricity of the first energy storage cabinet is selected in descending order from the results of the descending sorting of the remaining electricity of the first energy storage cabinet. The remaining electricity of each first candidate energy storage cabinet is used to form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the charging task electricity of the energy storage cabinet.

6. The method according to claim 4, characterized in that, The step of determining the current energy storage cabinet charging task sequence corresponding to the current charging task based on the current charging task, the charging task priority identifier, the current remaining power of each energy storage cabinet in the heavy truck charging station subsystem, and a preset charging task allocation strategy includes: If the charging task priority identifier is determined to be a low-price charging identifier, then according to the charging task allocation strategy, the current remaining power of the energy storage cabinets with ordinary power charging identifiers in the heavy truck charging station subsystem are sorted in descending order to obtain the descending order of the remaining power of the second energy storage cabinet. Based on the charging task allocation strategy and the current amount of electricity to be charged corresponding to the current charging task, the remaining electricity of the second energy storage cabinet is selected in descending order from the results of the descending sorting of the remaining electricity of the second energy storage cabinet. The remaining electricity of each second candidate energy storage cabinet is used to form the current energy storage cabinet charging task sequence with the energy storage cabinet ID number and the charging task electricity of the energy storage cabinet.

7. A virtual power plant data processing system based on an energy storage cabinet, characterized in that, The system includes several heavy-duty truck charging station subsystems and a virtual power plant server. Each heavy-duty truck charging station subsystem includes several heavy-duty truck charging piles, several energy storage cabinets, and an edge server. The heavy-duty truck charging piles are connected to the energy storage cabinets, and the heavy-duty truck charging piles and the energy storage cabinets are all connected to the edge server. The edge server is connected to the virtual power plant server. For each of the several heavy-duty truck charging station subsystems, if a heavy-duty truck charging pile in the heavy-duty truck charging station subsystem is detected to have been successfully connected to the charging port of the heavy-duty truck, then the heavy-duty truck charging pile is used as the current target heavy-duty truck charging pile to obtain the charging and discharging task information of the heavy-duty truck and send it to the corresponding edge server. The edge server is used to obtain the current target discharge time period and the current amount of electricity to be discharged from the charge and discharge task information if it is determined that the charge and discharge task information corresponds to the discharge task type, and to obtain the grid-connected price curve of the energy storage cabinet for the day from the virtual power plant server. The edge server is also used to determine the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet on the same day, and send it to the current target heavy truck charging pile. The current target heavy truck charging pile is used to charge several energy storage cabinets connected to the current target heavy truck charging pile according to the charging and discharging task information if a confirmation instruction for the current V2G revenue information is detected, until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period. The step of charging several energy storage cabinets connected to the current target heavy-duty truck charging pile according to the charging and discharging task information until the current discharge target time period is completed includes: Based on the current discharge target time period and the current amount of electricity to be discharged corresponding to the charging and discharging task information, the power of the charging battery module of the heavy truck is controlled to charge several energy storage cabinets connected to the current target heavy truck charging pile until the discharge operation of the current amount of electricity to be discharged is completed within the current discharge target time period; wherein, the energy storage cabinets that are currently idle are first sorted in order from the lowest remaining energy to the highest remaining energy. When it is determined that the sum of the remaining energy of the first N energy storage cabinets is greater than the current amount of electricity to be discharged for the first time, the corresponding energy storage cabinet is selected as the energy storage cabinet to be charged, and the charging order of the charging battery module of the heavy truck in the energy storage cabinet to be charged is also in the sorting order from the 1st to the Nth position; N is a positive integer.

8. The virtual power plant data processing system based on energy storage cabinet according to claim 7, characterized in that, The step of determining the current V2G revenue information based on the current target discharge time period, the current amount of electricity to be discharged, and the grid-connected price curve of the energy storage cabinet for the day includes: Based on the current target discharge time period, determine the current candidate grid connection price curve from the daily energy storage cabinet grid connection price curve; The current V2G revenue information is determined based on the current amount of electricity to be discharged and the current candidate grid connection price curve.

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