Charging pile cooperation method and device, electronic equipment and computer readable storage medium

Abstract

The invention provides a charging pile cooperation method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: determining an optimal power transfer path under the condition that the fault of at least one charging pile exceeds a fault allowed range; distributing the load of the fault charging pile to the healthy charging pile according to the optimal power transfer path; determining a power parameter transmitted to the power grid according to the power measured value; wherein the power parameter is configured to suppress voltage fluctuation of the power grid. According to the embodiment of the invention, under the condition that the fault charging pile exists, the load of the fault charging pile is distributed to the healthy charging pile according to the determined optimal power transfer path, so that dynamic regulation and control of energy can be realized through the healthy charging pile, and the overall energy efficiency loss is reduced. Besides, under the condition that the load is redistributed, the power parameter transmitted to the power grid is determined according to the power measured value, so that the voltage fluctuation of the power grid is inhibited, and the stability and the safety of the system can be further improved.

Description

Technical Field

[0001] The present application relates to the field of charging, and more specifically, to a charging pile collaboration method, device, electronic device, and computer-readable storage medium. Background Art

[0002] With the rapid adoption of electric vehicles, the scale of charging infrastructure, particularly centralized public charging stations (equipped with multiple charging piles), continues to expand. While these multiple charging pile scenarios meet user charging needs, they also present increasingly complex energy management challenges. Currently, mainstream technical solutions focus on localized control of individual charging piles, such as implementing basic charging start and stop functions, status monitoring, billing, and simple power limiting. However, when faced with charging stations consisting of dozens or even hundreds of charging piles, existing technical solutions suffer from significant "fragmentation" and "localization" deficiencies in energy regulation. Summary of the Invention

[0003] In view of this, the purpose of the embodiments of the present application is to provide a charging pile collaboration method, device, electronic device and computer-readable storage medium, which can reduce the overall energy efficiency loss while achieving dynamic regulation of the overall energy of the system.

[0004] In a first aspect, an embodiment of the present application provides a charging pile coordination method, which is applied to a multi-charging pile system. The method includes: determining an optimal power transfer path when the fault of at least one charging pile exceeds the allowable fault range; distributing the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path; determining the power parameters transmitted to the power grid based on the actual power measured value; wherein the power parameters are configured to suppress voltage fluctuations of the power grid.

[0005] In this implementation, if a faulty charging station exists, the load is distributed to healthy charging stations based on the determined optimal power transfer path. This allows for dynamic regulation of the system's overall energy while reducing overall energy efficiency losses. Furthermore, when load redistribution occurs, the power parameters transmitted to the grid are determined based on measured power values, thereby suppressing grid voltage fluctuations and further improving system stability and security.

[0006] In one embodiment, when the fault of at least one charging pile exceeds the allowable fault range, determining the optimal power transfer path includes: constructing constraint conditions based on the healthy charging pile and the grid voltage constraint; establishing an objective function based on the constraint conditions; and determining the optimal power transfer path by solving the objective function.

[0007] In the above implementation process, by constructing constraints and establishing an objective function based on the healthy charging pile and grid voltage constraints, and then determining the optimal power transfer path, the obtained optimal power transfer path can meet the healthy charging pile and grid voltage constraints, while improving the load distribution accuracy and the stability of the healthy charging pile and voltage.

[0008] In one embodiment, distributing the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path includes: sorting the healthy charging piles by allocation priority; dividing the healthy charging piles into multiple levels according to the allocation priority; and respectively allocating a corresponding proportion of the load to the healthy charging piles in each level.

[0009] In the above implementation process, when it is necessary to distribute the load of a faulty charging pile to a healthy charging pile, the healthy charging piles are prioritized and layered, so that non-layered healthy charging piles can be allocated a load with a corresponding proportion, thereby achieving energy balance between the healthy charging piles after load distribution and improving the stability of the healthy charging piles.

[0010] In one embodiment, after allocating a corresponding proportion of load to the healthy charging piles at each level, the method further includes: obtaining the real-time status of the healthy charging piles at set time intervals; when the load rate of any healthy charging pile exceeds the load range, reallocating the excess load in the healthy charging pile to other healthy charging piles.

[0011] In the above implementation process, after the load of the faulty charging pile is distributed to the healthy charging pile, the real-time status of the healthy charging pile is continued to be obtained, and when the load rate of any healthy charging pile exceeds the load range, the excess load in the healthy charging pile is reallocated to other healthy charging piles, so that the healthy charging pile can work within the load range as much as possible, thereby improving the safety and stability of the healthy charging pile.

[0012] In one embodiment, determining the power parameters transmitted to the power grid based on the measured power values ​​includes: obtaining the measured power values ​​of the power grid when the change of the electrical parameters in the power grid exceeds a threshold range; controlling the inverter to output corresponding electrical parameters based on the measured power values ​​and set droop characteristics; and determining the power parameters transmitted by the charging pile to the power grid based on the electrical parameters.

[0013] In the above implementation process, by controlling the inverter output corresponding electrical parameters according to the actual power measurement value and setting the droop characteristics, the voltage fluctuation of the power grid is suppressed, which can avoid the grid voltage fluctuation caused by load changes during load distribution, and improve the stability and safety of the grid voltage.

[0014] In one embodiment, the method further includes: calibrating the charging pile data of the detected charging pile; generating a fault strategy based on the charging pile data according to a set algorithm; determining a reward value corresponding to the fault strategy through a digital twin; wherein the digital twin includes a medium power distribution model of the charging pile, the power grid and the battery; and updating the fault strategy through fault data when the reward value does not converge.

[0015] In the above implementation process, by using digital twins to verify the fault strategy and updating the fault strategy when the reward value corresponding to the fault strategy has not converged, the fault strategy in the charging pile can be made as optimal as possible, thereby improving the accuracy of the fault strategy.

[0016] In one embodiment, the method further includes: when the bus load rate of the bus connected to the charging pile exceeds a load threshold, dividing the plurality of charging piles into a plurality of subnets; wherein the charging piles in each subnet preferentially transmit corresponding signals; adjusting the bus priority of each bus according to the real-time data priority of each charging pile; and controlling each bus to perform signal transmission according to the bus priority.

[0017] In the above implementation process, when the bus load exceeds the load threshold, the charging pile is divided into multiple subnets, and the bus priority of each bus is adjusted according to the real-time data priority of the charging pile, and the signal is transmitted according to the bus priority, so that data that needs to be transmitted urgently can be transmitted first, thereby improving the flexibility of data transmission.

[0018] In the second aspect, an embodiment of the present application also provides a charging pile collaborative device, which is applied to a multi-charging pile system, and the device includes: a first determination module, which is used to determine the optimal power transfer path when the fault of at least one charging pile exceeds the allowable fault range; a distribution module, which is used to distribute the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path; a second determination module, which is used to determine the power parameters transmitted to the power grid based on the actual power measured value; wherein, the power parameters are configured to suppress the voltage fluctuations of the power grid.

[0019] In a third aspect, an embodiment of the present application further provides an electronic device comprising: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of the method in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0020] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the charging pile collaboration method according to the above-mentioned first aspect or any possible implementation of the first aspect are executed.

[0021] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the following embodiments are given in conjunction with the accompanying drawings for detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and therefore should not be regarded as limiting the present application. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A schematic diagram of the operating environment of the charging pile collaboration method provided in an embodiment of the present application; Figure 2 A block diagram of an electronic device provided in an embodiment of the present application; Figure 3 A flowchart of the charging pile collaboration method provided in an embodiment of the present application; Figure 4 Schematic diagram of the functional modules of the charging pile collaboration device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings in the embodiments of the present application.

[0025] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0026] With the rapid development of the new energy vehicle industry, the number of new energy vehicles has continued to grow rapidly, directly driving the continuous expansion of charging pile construction. Multiple charging piles are now common in cities, highway service areas, large commercial complexes, and other areas, aiming to provide convenient and efficient charging services for new energy vehicle users.

[0027] However, after extensive research, the inventors of this application discovered a key issue in energy regulation during the actual operation of multiple charging piles: the lack of global energy regulation across multiple charging piles. Currently, most charging pile systems operate in a relatively independent mode of energy management, lacking effective information exchange and coordination mechanisms between charging piles. Each charging pile distributes and regulates energy solely based on the charging needs of its connected vehicles, making it difficult to comprehensively plan energy flows across the entire charging scenario.

[0028] In light of this, the present invention proposes a charging pile coordination method. In the presence of a faulty charging pile, the load of the faulty charging pile is distributed to healthy charging piles based on a determined optimal power transfer path. This allows for dynamic energy regulation using healthy charging piles, reducing overall energy efficiency losses. Furthermore, while redistributing the load, the power parameters transmitted to the power grid are determined based on the measured power values, thereby suppressing voltage fluctuations in the grid and further improving system stability and security.

[0029] To facilitate understanding of this embodiment, the operating environment of a charging pile collaboration method disclosed in the embodiment of this application is first introduced in detail.

[0030] like Figure 1 The figure shows a schematic diagram of the interaction between charging piles, power grid and battery in a multi-charging pile scenario provided by an embodiment of the present application. Multiple charging piles are connected to the power grid, and each charging pile can be used to connect to a battery to charge the corresponding battery.

[0031] The battery is the battery in the vehicle. The charging station draws electricity from the grid and charges the battery connected to it.

[0032] The charging piles, power grid and batteries here can also be connected through the network for data communication or interaction.

[0033] Optionally, electronic equipment is provided in one or more of the charging pile, the power grid and the battery for performing data processing and calculation.

[0034] To facilitate understanding of this embodiment, the electronic device that executes the charging pile collaboration method disclosed in the embodiment of this application is introduced in detail below.

[0035] like Figure 2 , which is a block diagram of an electronic device. The electronic device 100 may include a memory 111 and a processor 113. A person skilled in the art will understand that Figure 2 The structure shown is only for illustration and does not limit the structure of the electronic device 100. For example, the electronic device 100 may further include Figure 2More or fewer components than shown, or with Figure 2 Different configurations shown.

[0036] The memory 111 and processor 113 are electrically connected to each other, directly or indirectly, to enable data transmission or interaction. For example, these components may be electrically connected to each other via one or more communication buses or signal lines. The processor 113 is used to execute the executable modules stored in the memory.

[0037] The memory 111 may be, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc. The memory 111 is used to store programs, and the processor 113 executes the programs after receiving an execution instruction. The method executed by the electronic device 100 defined by the process disclosed in any embodiment of the present application may be applied to the processor 113 or implemented by the processor 113.

[0038] The processor 113 may be an integrated circuit chip with signal processing capabilities. The processor 113 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or any conventional processor.

[0039] The electronic device 100 in this embodiment can be used to execute each step in each method provided in the embodiments of this application. The following describes in detail the implementation process of the charging pile coordination method through several embodiments.

[0040] See also Figure 3 , is a flow chart of the charging pile coordination method provided by the embodiment of the present application. Figure 3 The specific process shown is explained in detail.

[0041] Step S201: When the fault of at least one charging pile exceeds the allowed fault range, determine the optimal power transfer path.

[0042] It should be understood that when a fault is detected in a charging pile, it can be further determined whether the load of the faulty charging pile needs to be distributed to other charging piles based on the fault scope.

[0043] The fault tolerance range here refers to the range within which a charging pile fault has little or no impact on the charging of the battery by the charging pile, or the range within which the impact is negligible. This fault tolerance range can be set based on the actual situation of the charging pile.

[0044] For example, if there are N charging piles, and the fault of the i-th charging pile exceeds the fault tolerance range (eg, output power Pi=0), the load of the i-th charging pile needs to be distributed to other healthy charging piles.

[0045] It is understandable that when it is determined that the load of the faulty charging pile needs to be distributed to the healthy charging pile, it is necessary to further determine the distribution strategy, and then distribute the load to the corresponding healthy charging pile according to the optimal power transfer path.

[0046] The goal of the above-mentioned optimal power transfer path is to find the optimal allocation vector while satisfying the constraints of the power grid and charging piles, so as to minimize the overall energy efficiency loss of the system.

[0047] Step S202: Distribute the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path.

[0048] The faulty charging pile here refers to a charging pile whose fault exceeds the allowable fault range, and the healthy charging pile refers to a charging pile without any fault.

[0049] Optionally, the load can be distributed to all healthy charging piles or to some healthy charging piles. The healthy charging piles used to distribute the load can be selected according to actual conditions.

[0050] Among them, when distributing the load, it can be distributed according to the priority of the healthy charging piles, or according to the charging status of the healthy charging piles, or according to the remaining capacity of the healthy charging piles. The distribution method of the healthy charging piles can be selected according to actual conditions.

[0051] Step S203: determining the power parameters transmitted to the power grid according to the measured power values.

[0052] The power parameters are configured to suppress voltage fluctuations in the power grid.

[0053] It should be understood that when the load of a faulty charging pile is redistributed, the voltage in the power grid may fluctuate due to the load redistribution, thereby affecting the stability of the system. Therefore, when the load of the faulty charging pile is redistributed, the power parameters transmitted by the charging pile to the power grid can be further determined based on the actual power measurement value, and the power parameters can be used to suppress the voltage fluctuation of the power grid.

[0054] The power parameter here can be active power or reactive power, and the power parameter can be selected according to actual conditions.

[0055] Reactive power can be used to offset reactive power demand from loads and increase grid voltage, while active power can be used to simulate the inertia response of synchronous generators and suppress frequency drops.

[0056] In this implementation, if a faulty charging station exists, the load is distributed to healthy charging stations based on the determined optimal power transfer path. This allows for dynamic energy regulation using healthy charging stations, reducing overall energy efficiency losses. Furthermore, when load redistribution occurs, the power parameters transmitted to the grid are determined based on measured power values, thereby suppressing grid voltage fluctuations and further improving system stability and security.

[0057] In one possible implementation, step S201 includes: constructing constraint conditions based on healthy charging piles and grid voltage constraints; establishing an objective function based on the constraint conditions; and determining an optimal power transfer path by solving the objective function.

[0058] The constraints here may include healthy charging pile capacity constraints, grid voltage constraints, power conservation constraints, etc.

[0059] In one embodiment, the healthy pile capacity constraint may be: ; in, For the The maximum allowable output power of a healthy charging pile, For the The capacity of a healthy charging station.

[0060] The grid voltage constraint can be: after the power parameters are injected, the grid voltage fluctuation range is controlled within ±2%.

[0061] The power conservation constraint can be: ; The above objective function can be: ; in, For the Rated power of healthy charging pile, For the The capacity of the healthy charging pile, For the The load of a faulty charging pile, The number of healthy charging stations to distribute the load.

[0062] The above objective function can be solved by combining quadratic programming with graph theory. That is, first construct a network topology of healthy charging piles, and then solve the optimal allocation through quadratic programming.

[0063] Building a healthy charging pile network topology graph can be achieved through the following steps: abstracting healthy charging piles into graph nodes, setting the edge weights to the communication delay between piles (which can be used to reflect the feasibility of power transfer), and removing edges with communication delays greater than a set time (for example, 50ms, edges with communication delays greater than the set time can be regarded as unreachable paths).

[0064] Solving the optimal allocation through quadratic programming can be achieved through the following steps: using setting tools (e.g., MATLAB Optimization Toolbox, embedded QP solver) to solve the objective function under the constraints, and then obtain the optimal transfer power of each healthy charging pile.

[0065] For example, if the original load of the fault charging point KW, healthy charging pile A (rated power 50KW, remaining capacity 40KW), healthy charging pile B (rated power 100KW, remaining capacity 80KW), then it is allocated according to the remaining flux ratio, =60×40+8040=20KW, =60×80+8040=40KW, satisfying KW, KW. Then, the square sum of the load is , the square sum of the load is the optimal solution.

[0066] In this implementation, if a faulty charging station exists, the load is distributed to healthy charging stations based on the determined optimal power transfer path. This allows for dynamic regulation of the system's overall energy while reducing overall energy efficiency losses. Furthermore, when load redistribution occurs, the power parameters transmitted to the grid are determined based on measured power values, thereby suppressing grid voltage fluctuations and further improving system stability and security.

[0067] In one possible implementation, the load of the faulty charging pile is distributed to the healthy charging piles according to the optimal power transfer path, including: sorting the healthy charging piles according to the allocation priority; dividing the healthy charging piles into multiple levels according to the allocation priority; and allocating a corresponding proportion of the load to the healthy charging piles in each level.

[0068] The allocation priority sorting here can be sorted according to the remaining capacity of the healthy charging pile, or according to the communication quality of the bus connected to the healthy charging pile, or according to the historical failure rate of the healthy charging pile, etc. The allocation priority sorting can be selected according to actual conditions.

[0069] For example, when the allocation priority is sorted according to the remaining capacity of healthy charging piles, it can be determined that the higher the remaining capacity of healthy charging piles, the higher the allocation priority. For another example, when the allocation priority is sorted according to the historical failure rate of healthy charging piles, it can be determined that the lower the historical failure rate of healthy charging piles, the higher the allocation priority. For another example, when the allocation priority is sorted according to the communication quality of the bus connected to the healthy charging piles, it can be determined that the lower the bit error rate of the bus, the higher the allocation priority.

[0070] In one embodiment, the remaining capacity ratio of the healthy charging pile can be expressed by the following formula: ; in, The remaining capacity ratio of the healthy charging pile, For the The maximum allowable output power of a healthy charging pile, is the new output power.

[0071] It is understood that the allocation priority ranking of healthy charging piles can also be determined by combining multiple factors. For example, the allocation priority ranking of healthy charging piles can be determined by combining the remaining capacity ratio of healthy charging piles, the historical failure rate of healthy charging piles, and the communication quality of the bus connected to the healthy charging piles.

[0072] Then, the allocation priority ranking of the healthy charging pile can be expressed by the following formula: ; in, Assign priority levels to healthy charging piles. is the weight coefficient of the remaining capacity of the healthy charging pile, is the weight coefficient of the historical failure rate of healthy charging piles, is the weight coefficient of the communication quality of the bus connected to the healthy charging pile, The remaining capacity ratio of the healthy charging pile, For the historical failure rate of healthy charging piles, The communication quality of the bus connected to the healthy charging pile.

[0073] It can be understood that after the healthy charging piles are sorted by allocation priority, the healthy charging piles can be further divided into multiple levels according to the allocation priority, and then the corresponding proportion of load can be allocated to the healthy charging piles at each level according to the level.

[0074] The hierarchy here may include: dedicated standby charging piles, high-priority healthy charging piles, low-priority healthy charging piles, etc. Dedicated standby charging piles can be the healthy charging piles with the highest allocation priority, high-priority healthy charging piles can be the healthy charging piles with a medium allocation priority, and low-priority healthy charging piles can be the healthy charging piles with the lowest allocation priority.

[0075] Optionally, the proportion of healthy charging piles in each level can be adjusted according to actual needs, and the number of healthy charging piles in each level can be adjusted.

[0076] For example, 10%-20% of healthy charging piles can be set as dedicated backup piles, 50% of healthy charging piles can be set as high-priority healthy piles, and the remaining healthy charging piles can be set as low-priority healthy piles. In the event of a serious fault at a faulty charging pile, the dedicated backup pile can be activated to achieve a rapid response. High-priority healthy piles can be used to bear 60%-80% of the transferred load, while the remaining load is evenly shared by low-priority healthy piles.

[0077] In the above implementation process, when it is necessary to distribute the load of a faulty charging pile to a healthy charging pile, the healthy charging piles are prioritized and layered, so that non-layered healthy charging piles can be allocated a load with a corresponding proportion, thereby achieving energy balance between the healthy charging piles after load distribution and improving the stability of the healthy charging piles.

[0078] In one possible implementation, after allocating a corresponding proportion of load to each level of healthy charging piles, the method further includes: obtaining the real-time status of the healthy charging piles at set time intervals; when the load rate of any healthy charging pile exceeds the load range, reallocating the excess load in the healthy charging pile to other healthy charging piles.

[0079] The time interval can be set according to actual conditions, for example, 50ms, 100ms, 1s, 2s, 0ms, etc.

[0080] It should be understood that during the entire process of charging pile coordination, the real-time status of the healthy charging pile can be obtained according to the set time interval, and whether the load of the healthy charging pile exceeds the load range can be determined based on the real-time status of the healthy charging pile, and the excess load in the healthy charging that exceeds the load range can be redistributed to other healthy charging piles.

[0081] The load range here can be set according to the actual type and application scenario of the healthy charging pile. For example, the load range can be 90% rated load, 95% rated load, 100% rated load, etc.

[0082] The real-time status of the healthy charging pile mentioned above may include the capacity of the healthy charging pile, the failure rate of the healthy charging pile, the communication quality of the healthy charging pile, etc. The real-time status of the healthy charging pile can be selected according to actual conditions.

[0083] In the above implementation process, after the load of the faulty charging pile is distributed to the healthy charging pile, the real-time status of the healthy charging pile is continued to be obtained, and when the load rate of any healthy charging pile exceeds the load range, the excess load in the healthy charging pile is reallocated to other healthy charging piles, so that the healthy charging pile can work within the load range as much as possible, thereby improving the safety and stability of the healthy charging pile.

[0084] In one possible implementation, step S203 includes: when the change of electrical parameters in the power grid exceeds a threshold range, obtaining the measured power value of the power grid; controlling the inverter to output corresponding electrical parameters based on the measured power value and the set droop characteristics; and determining the power parameters transmitted by the charging pile to the power grid based on the electrical parameters.

[0085] Among them, the droop characteristic refers to the natural droop relationship between the output power, voltage and frequency when the generator is operating in the power grid: that is, active power-frequency droop and reactive power-voltage droop.

[0086] Active power-frequency droop means that when the output active power increases, the generator speed decreases and the frequency decreases; Reactive power-voltage droop refers to the decrease in terminal voltage when the output reactive power increases.

[0087] The linear relationship of the droop characteristics here can be expressed as: ; in, is the rated frequency, is the rated voltage, is the real-time active power, is the real-time reactive power, is the active power-frequency droop coefficient, is the reactive-voltage droop coefficient.

[0088] It is understandable that in a scenario with multiple charging stations, the droop characteristics of the generator can be simulated by controlling the replication and frequency of the inverter output voltage. Specifically, this can include an active power-frequency control loop and a reactive power-voltage control loop.

[0089] The active-frequency control loop is used to simulate mechanical characteristics. By introducing virtual moment of inertia and damping coefficient, the virtual rotor motion equation can be constructed: ; in, is the virtual electrical angular velocity, is the virtual mechanical torque, is the virtual electromagnetic torque, Virtual moment of inertia, is the damping coefficient.

[0090] When performing droop control, the active power deviation can be converted into a frequency regulation signal, that is: ; in, is the virtual electrical angular velocity, is the active power-frequency droop coefficient, It is the active power instruction.

[0091] By converting the active power deviation into a frequency regulation signal, when the active power output of the charging pile increases, the virtual frequency decreases, and the grid frequency fluctuation is suppressed by adjusting the output voltage frequency.

[0092] The above reactive power-voltage control loop is used to simulate electromagnetic characteristics. By introducing virtual excitation inductance and excitation resistance, a virtual excitation equation is constructed: ; in, is the virtual excitation electromotive force, is the grid voltage, is the reactive current component, is the excitation resistance.

[0093] When performing droop control, the reactive power deviation can be converted into a voltage amplitude adjustment signal, that is: ; in, is the active power-frequency droop coefficient, is the real-time reactive power, is the rated voltage, Reactive power command.

[0094] By converting reactive power deviation into a voltage amplitude regulation signal, when the grid voltage fluctuates, the charging pile automatically adjusts the reactive power output to compensate for the grid amplitude deviation.

[0095] It can be understood that by obtaining the electrical parameters in the power grid, when the change of the electrical parameters in the power grid exceeds the threshold range, the actual power measurement value of the power grid can be further obtained, and the power parameters that the charging pile needs to transmit to the power grid can be determined based on the actual power measurement value, thereby suppressing the voltage fluctuation of the power grid.

[0096] The electrical parameters here may be voltage parameters, current parameters, power parameters, etc., and the electrical parameters can be selected according to actual conditions.

[0097] For example, if the threshold range is within 5%, then when it is detected that the grid voltage drops by more than 5% due to a sudden load change, such as when the voltage drops to , it can be determined that the change of electrical parameters in the power grid exceeds the threshold range.

[0098] When controlling the inverter output corresponding electrical parameters based on the measured power value and the set droop characteristics, and determining the power parameters transmitted from the charging pile to the grid based on the electrical parameters, there are two cases: Case 1: If the measured reactive power value is less than the reactive power command, the virtual excitation electromotive force is automatically increased based on the reactive power-voltage droop factor to increase the inverter output voltage amplitude. At this time, the charging pile transmits capacitive reactive power to the grid (equivalent to the synchronous generator overexcitation state), offsetting the load reactive power demand and raising the grid voltage to within a certain range of the rated voltage.

[0099] Case 2: If the measured active power value is less than the commanded active power, the virtual rotor speed decreases according to the active power-frequency droop factor, and the inverter output voltage and frequency decrease accordingly. The charging station adjusts its active power output (for example, reducing the charging power of non-critical stations) to simulate the generator's inertia response and suppress further frequency drops.

[0100] The above voltage fluctuation suppression method is only exemplary and can be adjusted according to actual conditions.

[0101] In one embodiment, when multiple charging pile clusters are connected in parallel, reactive power can be evenly distributed through droop coefficient consistency control. Each charging pile dynamically adjusts the droop coefficient according to its own capacity to avoid reactive power concentration at a certain node, thereby improving the overall voltage adjustment efficiency.

[0102] In the above implementation process, by controlling the inverter output corresponding electrical parameters according to the actual power measurement value and setting the droop characteristics, the voltage fluctuation of the power grid is suppressed, which can avoid the grid voltage fluctuation caused by load changes during load distribution, and improve the stability and safety of the grid voltage.

[0103] In one possible implementation, the method further includes: calibrating the charging pile data of the detected charging pile; generating a fault strategy based on the charging pile data of the set algorithm; determining a reward value corresponding to the fault strategy through a digital twin; and updating the fault strategy through fault data when the reward value has not converged.

[0104] Among them, the digital twin includes the medium-power distribution model of charging piles, power grids and batteries.

[0105] The charging pile data here can be obtained through the data interface. For example, an edge computing module can be deployed at each charging pile to obtain data such as the voltage, current, and temperature of the charging pile through the bus.

[0106] Optionally, the acquired charging pile data can be transmitted to a server.

[0107] The aforementioned failure strategy can be determined using the PPO algorithm. Through multiple simulations and training, the PPO algorithm can generate failure strategies for various failure scenarios. For example, in the case of a "multi-pile communication interruption," it automatically triggers a switch to the backup priority network.

[0108] In one embodiment, determining the fault strategy using the PPO algorithm may be achieved through the following process: For the state space: including charging pile data such as voltage, current, temperature, bus load rate, etc. of multiple charging piles; its additional global state is: grid voltage fluctuation, number and dimension of healthy charging piles; when performing normalization processing: use sliding window normalization with a window size of a set number of steps (for example, 100 steps) to ensure input stability.

[0109] Regarding the action space: Discrete action sets can include multiple actions such as "switching to a backup pile," "reducing power within a set range (e.g., reducing power by 5%)," "remote reset," "starting reactive power compensation," and "no operation." Continuous action parameters can include power allocation ratios and reactive power injection amounts.

[0110] Among them, the reward function can be implemented by the following formula: ; in, It is a negative indicator of the absolute value of the grid voltage deviation. It is a negative indicator of the absolute value of the frequency deviation. For system energy efficiency, is a negative indicator of fault handling delay, 、 、 and is the weight coefficient.

[0111] In one embodiment, , , 2, .

[0112] It should be understood that when creating the network architecture, a two-layer fully connected neural network can be used, with the number of neurons in the hidden layer of the neural network being 256 and the activation function being ReLU. Training parameters may include: batch size, optimizer, discount factor, entropy regularization coefficient, etc.

[0113] When training a model, you can use distributed training and use the Ray framework to start multiple simulation environment instances in parallel. This can improve the training speed and reduce the time required for model iteration.

[0114] Optionally, a high-precision clock chip can be built into the edge computing module of each charging pile to ensure that the timestamp error is less than a set error (e.g., 1ms).

[0115] In addition, a rendering pipeline can be set up on the charging pile side to customize the rendering process. Multiple charging pile embodiments can be divided into multiple rendering batches.

[0116] Among them, each charging pile contains status components, stores real-time data such as voltage and current, and these real-time data can be updated in real time.

[0117] It is understandable that the grid can also be equipped with the same computing module as the charging pile, and can also be used to generate corresponding fault strategies based on the charging pile data. Similarly, the battery used for charging can also be equipped with the same computing module as the charging pile, and can also be used to generate corresponding fault strategies based on the charging pile data.

[0118] The power grid, charging stations, and batteries can form a digital twin. The reward values ​​determined by each end of the digital twin can be used to determine whether the current fault strategy is the optimal one. If the fault strategy is not optimal, the fault strategy can be updated.

[0119] When determining the reward value, it can be achieved through real-time matching, priority scheduling, and parameter adaptation: Real-time matching: The edge computing module searches the policy library for matching based on the fault feature vector (such as "communication interruption + temperature > 85°C").

[0120] Priority scheduling: Using the "monotonic rate scheduling" algorithm, severe fault policies have higher priority than moderate faults, and the preemption threshold can be set to 0μs.

[0121] Parameter adaptation: Dynamically adjust strategy parameters based on the real-time capacity of the physical piles. For example, when the remaining capacity of the backup pile is insufficient, the "switch to the backup pile" action is automatically changed to "load sharing among multiple piles."

[0122] When verifying and iterating on a fault strategy, you can do so by following these steps: Closed-loop testing: The generated strategy is injected back into the digital twin for multiple validation cycles. Verification metrics may include: strategy execution success rate: ≥99% and expected effect consistency: ≥95%.

[0123] Online learning: When the deviation between the actual response of the physical pile and the expected strategy is greater than the preset deviation (e.g., 10%), transfer learning is automatically triggered to fine-tune the strategy network using the latest multiple fault data.

[0124] In the above implementation process, by using digital twins to verify the fault strategy and updating the fault strategy when the reward value corresponding to the fault strategy has not converged, the fault strategy in the charging pile can be made as optimal as possible, thereby improving the accuracy of the fault strategy.

[0125] In one possible implementation, the method further includes: when the bus load rate of the bus connected to the charging pile exceeds a load threshold, dividing the multiple charging piles into multiple subnets; adjusting the bus priority of each bus according to the real-time data priority of each charging pile; and controlling each bus to perform signal transmission according to the bus priority.

[0126] Among them, the charging piles in each subnet give priority to transmitting the corresponding signals.

[0127] The bus load rate here can be determined by monitoring. The load rate can be calculated by the following formula: Load rate = bus nominal rate × ×100%.

[0128] Optionally, when the load rate is greater than a set ratio (e.g., 80%) for multiple consecutive statistical periods (e.g., 50ms), a dynamic subnet division mechanism can be triggered to divide multiple charging piles into multiple subnets.

[0129] In one embodiment, because a bus load exceeding 80% is prone to frame collisions, resulting in critical data delays, the bus load can be set to ≤70%. Subnetting can split a single bus into multiple low-load subnets, thereby improving transmission reliability.

[0130] The subnets here can include production subnets and monitoring subnets.

[0131] Among them, the production subnet is used for real-time control instructions and emergency fault alarms.

[0132] Real-time control instructions may include: remote reset of faulty charging piles, power adjustment instructions, etc.

[0133] Emergency fault alarms may include: overvoltage alarm, overcurrent alarm, battery thermal runaway warning, etc.

[0134] In one embodiment, the priority guarantee mechanism of the production subnet may be: using fixed priority scheduling, allocating the lowest bus identity identifier to the control instruction, and determining priority occupation of the bus.

[0135] Among them, when the number of nodes in the subnet is ≤16, the bus arbitration length can be shortened and the delay can be further reduced (target ≤20ms).

[0136] The monitoring subnet can be used to carry data. The types of data carried can include: periodically reported data such as battery consistency, charging pile voltage, charging pile current, and temperature; and non-emergency diagnostic information such as historical fault logs and device parameter configuration.

[0137] In one embodiment, the data transmission strategy in the monitoring subnet may include: periodic scheduling with a longer transmission period to avoid frequent bus occupancy; data compression transmission (e.g., differential encoding) to reduce payload length (e.g., an average compression ratio of 1.5:1).

[0138] In the above implementation process, when the bus load exceeds the load threshold, the charging pile is divided into multiple subnets, and the bus priority of each bus is adjusted according to the real-time data priority of the charging pile, and the signal is transmitted according to the bus priority, so that data that needs to be transmitted urgently can be transmitted first, thereby improving the flexibility of data transmission.

[0139] Based on the same application concept, the embodiment of the present application also provides a charging pile cooperation device corresponding to the charging pile cooperation method. Since the principle of solving the problem by the device in the embodiment of the present application is similar to that of the aforementioned charging pile cooperation method embodiment, the implementation of the device in this embodiment can refer to the description in the embodiment of the above method, and the repeated parts will not be repeated.

[0140] See also Figure 4 , is a schematic diagram of the functional modules of the charging pile collaboration device provided in an embodiment of the present application. The modules in the charging pile collaboration device in this embodiment are used to execute the steps in the above method embodiment. The charging pile collaboration device includes a first determination module 301, an allocation module 302, and a second determination module 303.

[0141] The first determining module 301 is configured to determine an optimal power transfer path when a fault of at least one charging pile exceeds an allowable fault range.

[0142] The distribution module 302 is used to distribute the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path.

[0143] The second determining module 303 is configured to determine a power parameter to be transmitted to the power grid according to the measured power value; wherein the power parameter is configured to suppress voltage fluctuations of the power grid.

[0144] In a possible implementation, the first determination module 301 is further used to: construct constraint conditions based on the healthy charging pile and grid voltage constraints; establish an objective function based on the constraint conditions; and determine the optimal power transfer path by solving the objective function.

[0145] In a possible implementation, the first determination module 301 is specifically used to: sort the healthy charging piles by allocation priority; divide the healthy charging piles into multiple levels according to the allocation priority; and respectively allocate a corresponding proportion of load to the healthy charging piles in each level.

[0146] In one possible implementation, the charging pile collaborative device further includes a distribution module for obtaining the real-time status of the healthy charging pile at set time intervals; when the load rate of any of the healthy charging piles exceeds a load range, the excess load in the healthy charging pile is reallocated to other healthy charging piles.

[0147] In one possible implementation, the second determination module 303 is further used to: obtain the measured power value of the power grid when the change of the electrical parameters in the power grid exceeds a threshold range; control the inverter to output corresponding electrical parameters according to the measured power value and the set droop characteristics; and determine the power parameters transmitted by the charging pile to the power grid according to the electrical parameters.

[0148] In one possible implementation, the charging pile collaborative device further includes an update module for calibrating the charging pile data of the detected charging pile; generating a fault strategy based on the charging pile data according to a set algorithm; determining a reward value corresponding to the fault strategy through a digital twin; wherein the digital twin includes a medium power distribution model of the charging pile, the power grid, and the battery; and updating the fault strategy through fault data when the reward value does not converge.

[0149] In one possible embodiment, the charging pile collaborative device also includes a division module for dividing the plurality of charging piles into a plurality of subnets when the bus load rate of the bus connected to the charging piles exceeds a load threshold; wherein the charging piles in each subnet preferentially transmit corresponding signals; the bus priority of each bus is adjusted according to the real-time data priority of each charging pile; and each bus is controlled to perform signal transmission according to the bus priority.

[0150] In addition, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the charging pile collaboration method described in the above method embodiment are executed.

[0151] The computer program product of the charging pile collaboration method provided in the embodiment of the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the charging pile collaboration method described in the above method embodiment. For details, please refer to the above method embodiment and will not be repeated here.

[0152] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0153] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0154] If the functions are implemented in the form of software modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or the portion 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 for causing a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage media include various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks. It should be noted that, in this document, relational terms such as first and second, etc., are used solely to distinguish one entity or operation from another, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element. The foregoing description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included within the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined or explained in subsequent figures.

[0155] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A charging pile coordination method, characterized in that: Applied to a multi-charging pile system, the method includes: Determine an optimal power transfer path when the fault of at least one charging pile exceeds the fault tolerance range; Distributing the load of the faulty charging pile to the healthy charging piles according to the optimal power transfer path; A power parameter transmitted to the power grid is determined based on the actual power measurement value; wherein the power parameter is configured to suppress voltage fluctuations of the power grid.

2. The method according to claim 1, characterized in that The determining of the optimal power transfer path when the fault of at least one charging pile exceeds the allowable fault range includes: Constructing constraint conditions based on the healthy charging pile and grid voltage constraints; Establishing an objective function according to the constraints; The optimal power transfer path is determined by solving the objective function.

3. The method according to claim 2, characterized in that The distributing the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path includes: Prioritizing the allocation of the healthy charging piles; Dividing the healthy charging piles into multiple levels according to the allocation priority; A corresponding proportion of load is allocated to the healthy charging piles at each level.

4. The method according to claim 3, characterized in that After allocating a corresponding proportion of load to the healthy charging piles at each level, the method further includes: Obtain the real-time status of the healthy charging pile at set time intervals; When the load rate of any of the healthy charging piles exceeds the load range, the excess load in the healthy charging pile is redistributed to other healthy charging piles.

5. The method according to claim 1, wherein Determining the power parameters transmitted to the power grid according to the measured power values ​​includes: When a change in an electrical parameter in the power grid exceeds a threshold range, obtaining a measured power value of the power grid; Controlling the inverter to output corresponding electrical parameters according to the measured power value and the set droop characteristics; The power parameters transmitted by the charging pile to the power grid are determined according to the electrical parameters.

6. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Calibrate the charging pile data of the detected charging pile; Generate a fault strategy based on the charging pile data described in the set algorithm; Determining a reward value corresponding to the fault strategy through a digital twin; wherein the digital twin includes a medium power distribution model of the charging pile, the power grid, and the battery; In a case where the reward value does not converge, the fault policy is updated using fault data.

7. The method according to any one of claims 1 to 4, characterized in that The method further comprises: When the bus load rate of the bus connected to the charging pile exceeds a load threshold, the plurality of charging piles are divided into a plurality of subnets; wherein the charging piles in each subnet preferentially transmit corresponding signals; Adjusting the bus priority of each bus according to the real-time data priority of each charging pile; Each bus is controlled to perform signal transmission according to the bus priority.

8. A charging pile coordination device, characterized in that: Applied to a multi-charging pile system, the device includes: A first determination module is configured to determine an optimal power transfer path when a fault of at least one charging pile exceeds an allowable fault range; A distribution module, configured to distribute the load of the faulty charging pile to the healthy charging pile according to the optimal power transfer path; The second determination module is used to determine the power parameters transmitted to the power grid according to the actual power measurement value; wherein the power parameters are configured to suppress voltage fluctuations of the power grid.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps of any one of the methods according to claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method according to any one of claims 1 to 7.

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