V2X charging and discharging cooperative control system based on dynamic multi-objective optimization

Abstract

The invention relates to the technical field of charge and discharge control, in particular to a V2X charge and discharge cooperative control system based on dynamic multi-objective optimization, which comprises a voltage characteristic identification module, a response capability evaluation module, a scheduling matching mapping module, a task load distribution module and a cooperative regulation and control judgment module. According to the method, rapid adaptive response data acquisition in a voltage regulation dead zone is realized through multi-node transient voltage response identification, a synchronization vector is constructed by using response time, an instability characteristic and a precision grade, vehicle synchronization capability is normalized and measured, and dynamic scheduling layering of multiple vehicles is realized by constructing a difference sorting mechanism in combination with regulation tolerance. A regulation and control mapping relation is established according to a task load regulation rate, consistent matching and dynamic adaptation of vehicle scheduling and load change are realized, the adaptation capability of a vehicle energy response behavior to a dynamic demand of a power grid is remarkably improved, a coordinated discharge task under multi-target constraint is met, and the problems of time lag and unbalanced response are reduced.

Description

Technical Field

[0001] The present invention relates to the field of charge and discharge control technology, and in particular to a V2X charge and discharge collaborative control system based on dynamic multi-objective optimization. Background Art

[0002] The field of charge and discharge control technology involves control technology for orderly management of electric energy between storage devices and power grids or loads, including regulation and control of electric energy flow, formulation of charging and discharging strategies, management of battery safety and life, and interface coordination with external power supply systems. It is widely used in electric vehicles, energy storage systems and distributed energy networks. The traditional V2X charge and discharge collaborative control system refers to solving the problem of energy scheduling and charge and discharge control between vehicles and power grids through preset static optimization strategies or rule-based control methods in V2G scenarios. It usually adopts priority control set in fixed time periods, schedule scheduling guided by electricity prices, and simple prediction methods to determine the charging and discharging behavior of electric vehicles. The rules are mainly matched according to the remaining capacity of the vehicle battery, the load demand of the power grid, and the electricity price schedule.

[0003] Traditional coordinated charging and discharging control mainly relies on preset rule matching and static priority setting, and only makes judgments based on the static relationship between electricity price schedules, battery power and grid load. When faced with frequently changing regulation needs or parallel charging and discharging tasks of multiple vehicles, the response lacks consideration of real-time and synchronization, which can easily cause some vehicles to have significant response offsets, voltage regulation lags, and uneven task load distribution. For example, when the grid frequency fluctuates or the load switches rapidly, some vehicles may discharge ahead of time or lag behind in response, resulting in a decrease in the overall power regulation effect and unstable local node voltage. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and propose a V2X charging and discharging coordinated control system based on dynamic multi-objective optimization.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions: A V2X charging and discharging coordinated control system based on dynamic multi-objective optimization includes: The voltage characteristic identification module obtains the transient voltage response data and applied current of vehicles connected to the V2G network, calculates the voltage drop rate under unit current, calculates the upper and lower deviation groups and calculates the ratio with the target range, determines whether it is within the voltage regulation dead zone, and obtains multi-node vehicle response adaptation records; The response capability evaluation module collects the time coordinates of the maximum voltage fluctuation point and the excitation application time of the adapted vehicle based on the multi-node vehicle response adaptation record, calculates the response phase offset, and constructs a normalized synchronization vector based on the current stabilization time and the charge and discharge accuracy level to obtain a response synchronization feature group. The dispatch matching mapping module reads the grid frequency regulation tolerance based on the response synchronization feature group, calculates the absolute value of the difference between the adapted vehicle response phase offset and the current stabilization time term and the regulation tolerance, sorts them in ascending order, constructs a vehicle dispatch mapping classification, and obtains a vehicle collaborative dispatch classification sequence; The task load distribution module establishes a one-to-one mapping between the task load adjustment rate and the vehicle scheduling sequence according to the vehicle cooperative scheduling classification sequence and in combination with the load adjustment rate, and obtains a load distribution mapping table.

[0006] As a further solution of the present invention, the multi-node vehicle response adaptation record includes the node voltage adaptation value, the upper and lower deviation ratio distribution record, and the adjustment dead zone judgment result; the response synchronization feature group includes the response phase vector, the current stabilization coefficient, and the synchronization level index; the vehicle collaborative scheduling classification sequence includes the priority response sequence, the secondary response sequence, and the vehicle scheduling level label; the load distribution mapping scale includes the adjustment rate matching relationship, the vehicle sequence grouping label, and the task subgroup number.

[0007] As a further solution of the present invention, the voltage characteristic identification module includes: The data acquisition submodule obtains the transient voltage response data and corresponding applied current of each node vehicle connected to the V2G network under the action of the charging pile test current, extracts the current change value and the corresponding time difference within the transient period, matches the node timing to obtain the voltage change amplitude and response duration within the sampling window, and obtains the voltage response sampling data; The voltage rate deviation calculation submodule calculates the voltage drop rate under unit current based on the voltage response sampling data, and performs difference calculation on the voltage drop rate according to the upper and lower limits of the voltage response rate of the target node, generates upper and lower deviation groups, and simultaneously performs absolute value ratio statistics based on the deviation group and the target interval amplitude, calculates the voltage rate interval deviation rate and the voltage drop trend deviation degree, and obtains the rate deviation statistical results; The response adaptation judgment submodule compares the rate deviation statistical results with the voltage regulation dead zone range to determine whether the rate deviation statistical value is within the range, establishes a response adaptation index table based on the number of nodes and the corresponding results, and obtains multi-node vehicle response adaptation records.

[0008] As a further solution of the present invention, the responsiveness evaluation module includes: The response phase acquisition submodule collects the time coordinates of the maximum voltage fluctuation point of the adapted vehicle based on the multi-node vehicle response adaptation record, records the maximum fluctuation time in combination with the start time record of the excitation application, performs synchronous indexing on the excitation application time, calculates the difference between the maximum fluctuation point time of each node and the excitation time, obtains the time offset of each node, and obtains the maximum fluctuation phase offset group; The current stabilization statistics submodule indexes the current sampling sequence after the excitation of each node based on the maximum fluctuation phase offset group, calculates the time difference between the excitation time and the stabilization time, reads the accuracy level identification code of each node, establishes a numerical level index array, calculates and obtains the synchronization overlap index, and generates the synchronization response initial data group; The synchronization vector construction submodule normalizes the data according to the initial synchronization response data group, merges the three parameter vectors, and sequentially combines them to construct the vehicle synchronization vector. The synchronization vectors of each node are used as row vectors to merge and construct a matrix form to obtain the response synchronization feature group.

[0009] As a further solution of the present invention, the scheduling matching mapping module includes: The response difference extraction submodule extracts the response start and end time nodes of each vehicle based on the response phase offset time and current stabilization delay time of each adapted vehicle recorded in the response synchronization feature group, and constructs a vehicle response time information group. In combination with the grid frequency adjustment tolerance range of the discharge task, the corresponding frequency adjustment time window is extracted, and a benchmark response time is constructed based on the median value of the adjustment time window. The response time of each vehicle is compared with the benchmark response time to obtain a frequency response difference group. The priority sequence construction submodule establishes a corresponding offset value index table based on the degree of response deviation of each vehicle in the frequency response difference group, and performs difference ascending order processing. For vehicles whose differences are within the deviation interval, the stabilization time node is recorded and matched with the frequency adjustment end time. Vehicles that meet both the deviation condition and the stabilization time condition are marked as priority vehicles, and the remaining vehicles are classified as secondary vehicles. The rows are summarized to obtain the priority assignment sequence and secondary sequence division results. The vehicle scheduling mapping submodule reads the accuracy level and power response capability parameters of each vehicle based on the vehicle set in the priority assignment sequence and secondary sequence division results, internally sorts the priority vehicles and secondary vehicles according to the power response capability indicators, assigns a scheduling label to each vehicle, and obtains the vehicle collaborative scheduling classification sequence.

[0010] As a further solution of the present invention, the task load distribution module includes: The adjustment gradient construction submodule obtains the dispatch numbers of all vehicles in the vehicle cooperative dispatch classification sequence, sets the load adjustment rate interval of the discharge task, divides it into equal intervals, constructs a rate index table according to the number of sections, determines the number of vehicles that can be accommodated in each rate interval based on the ratio between the total number of dispatch numbers and the total number of rate sections, establishes a number matching framework between the rate interval and the vehicle dispatch number, and obtains the adjustment rate interval grouping result; The task matching division submodule allocates the rate task interval in which the dispatch number of each vehicle is located according to the adjustment rate interval grouping result, the accuracy level index corresponding to each vehicle dispatch number, and the recommended discharge capacity, identifies whether the continuity of the dispatch number in the rate task interval is broken, determines whether the recommended rate of the vehicle falls within the allowable range of the allocated rate interval, and simultaneously determines the degree of coordination between the accuracy level index and the task adjustment interval, completes the vehicle attribution adjustment in the task interval, and obtains the task adjustment grouping matrix; The allocation mapping generation submodule reads the number of vehicles, the corresponding adjustment rate range and the task number in each group in turn based on the mapping results of each rate task group and the vehicle number recorded in the task adjustment grouping matrix, and arranges them in ascending order by task number, establishes a dispatch number list of task groups and vehicles, counts the recommended adjustment rates of the vehicles in each group and standardizes the results, integrates the output by combining the number of vehicles, dispatch number and task number, and generates a load distribution mapping table.

[0011] As a further embodiment of the present invention, the system further comprises: The coordinated control determination module monitors the changing trend and adaptation status of each vehicle's response behavior during the discharge task execution phase based on the load distribution mapping table, summarizes the vehicle characteristic changes and dispatch response status during the task cycle, and generates a dynamically optimized V2X charge-discharge coordinated control plan; The dynamic optimization V2X charging and discharging coordinated control scheme includes a characteristic trend map, an adaptation state trajectory, and regulation feedback parameters.

[0012] As a further solution of the present invention, the collaborative control determination module includes: The response monitoring and identification submodule records the control feedback data of each vehicle based on the vehicle number under each task number in the load distribution mapping table, counts the number and distribution time period of various over-limit behaviors in the task cycle, and obtains a record of the change trend of the task cycle response behavior; The state trend aggregation submodule extracts the abnormal data segments marked in all records based on the task cycle response behavior change trend record and counts the number of abnormalities and the total duration of each vehicle, determines whether the vehicle enters the adaptation state judgment condition, establishes a mapping relationship between the task number and the state aggregation factor, and obtains the task state trend summary table; The control scheme generation submodule rearranges all marked tasks into temporary control areas based on the state aggregation factor corresponding to each task number in the task state trend summary table, and marks the vehicle number with the lowest priority for replacement scheduling setting, reallocates the target rate to the adjacent task number, renumbers all task numbers, vehicle numbers and their corresponding adjustment targets, and integrates the output to dynamically optimize the V2X charging and discharging coordinated control scheme.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, fast adaptive response data acquisition within the voltage regulation dead zone is achieved through multi-node transient voltage response identification, synchronization vectors are constructed using response time, stabilization characteristics and accuracy levels, and the vehicle synchronization capability is normalized and measured, and a difference sorting mechanism is constructed in combination with adjustment tolerance to achieve dynamic scheduling stratification of multiple vehicles. A control mapping relationship is established based on the task load adjustment rate to achieve consistent matching and dynamic adaptation of vehicle scheduling and load changes, so that the charging and discharging response has higher time coordination, voltage adaptability and load distribution accuracy, significantly improving the adaptability of the vehicle energy response behavior to the dynamic demand of the power grid, meeting the coordinated discharge task under multi-objective constraints, and reducing time lag and unbalanced response problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a system flow chart of the present invention; Figure 2 This is a flow chart of the voltage characteristic identification module of the present invention; Figure 3 This is a flow chart of the response capability evaluation module of the present invention; Figure 4 This is a flow chart of the scheduling matching mapping module of the present invention; Figure 5 This is a flow chart of the task load distribution module of the present invention; Figure 6 This is a flow chart of the collaborative control and determination module of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0017] See also Figure 1 , a V2X charging and discharging coordinated control system based on dynamic multi-objective optimization includes: The voltage characteristic identification module obtains the transient voltage response data and applied current of vehicles connected to the V2G network under the charging pile test current waveform, calculates the voltage drop rate under unit current, and subtracts the voltage drop rate from the upper and lower limits of the target node voltage response rate to form upper and lower deviation groups. It then calculates the ratios between the upper and lower deviation groups and the target interval amplitude, determines whether each ratio is within the voltage regulation dead zone (which meets the distributed energy grid connection standard of ±2% voltage deviation), and obtains multi-node vehicle response adaptation records. The response capability assessment module, based on multi-node vehicle response adaptation records, collects the time coordinates of the maximum voltage fluctuation point and the excitation application time of the adapted vehicle, calculates the response phase offset, and simultaneously collects the current stabilization time and charge and discharge accuracy level (including Class 1 to 3 accuracy levels). It constructs a normalized synchronization vector (using the synchronization index algorithm of the "Grid Interaction Interface Standard") and summarizes the synchronization vector data of all adapted vehicles to obtain a response synchronization feature group. The dispatch matching mapping module reads the grid frequency regulation tolerance of the current discharge task (with a ±0.5Hz dynamic regulation band) based on the response synchronization feature group. It calculates the absolute value of the difference between the response phase offset and the current stabilization time term of each adapted vehicle and the regulation tolerance. It then sorts the vehicles in ascending order based on the absolute value of the difference, demarcating the priority assignment sequence and the secondary sequence. Based on the sorting, it constructs a vehicle dispatch mapping classification to obtain a vehicle collaborative dispatch classification sequence. The task load distribution module matches each vehicle sequence to the corresponding load adjustment rate task subgroup based on the vehicle collaborative scheduling classification sequence and the load adjustment rate (the adjustment gradient is set to 0.1-2C according to the standard). It establishes a one-to-one mapping between the task load adjustment rate and the vehicle scheduling sequence, and obtains the load distribution mapping table. The collaborative control judgment module monitors the changing trends and adaptation status of each vehicle's response behavior during the discharge task execution phase based on the load distribution mapping scale, summarizes the vehicle characteristic changes and scheduling response status within the task cycle, and generates a dynamically optimized V2X charging and discharging collaborative control plan.

[0018] The multi-node vehicle response adaptation records include node voltage adaptation values, upper and lower deviation ratio distribution records, and adjustment dead zone judgment results. The response synchronization feature group includes response phase vector, current stabilization coefficient, and synchronization level index. The vehicle collaborative scheduling classification sequence includes priority response sequence, secondary response sequence, and vehicle scheduling level label. The load distribution mapping scale includes adjustment rate matching relationship, vehicle sequence grouping label, and task subgroup number. The dynamic optimization V2X charging and discharging collaborative control scheme includes characteristic trend map, adaptation state trajectory, and control feedback parameters.

[0019] See also Figure 2 , the voltage characteristic identification module includes: The data acquisition submodule obtains the transient voltage response data and corresponding applied current of each node vehicle connected to the V2G network under the action of the charging pile test current, extracts the current change value and the corresponding time difference within the transient period, matches the node timing to obtain the voltage change amplitude and response duration within the sampling window, and obtains the voltage response sampling data; Obtain the transient voltage response data and corresponding applied current of each node vehicle connected to the V2G network under the action of the charging pile test current. First, the test system applies a pulse current of a fixed time window to the access node, monitors the voltage of each vehicle charging interface during the test cycle, and obtains the initial and final voltage values ​​of each node in turn. The voltage acquisition uses a 2kHz sampling frequency to ensure that the details of the response voltage change can be captured. The voltage change value is the instantaneous drop during the test cycle. For example, the initial voltage of node N1 is 390.2V and the final voltage is 382. .6V, the transient drop is 7.6V. At the same time, the test current obtained is 18.5A, and the response time is 0.6s. The same method is used to collect data for other nodes. For example, the initial value of node N2 is 388.5V and the final value is 381.3V, the current is 19.1A, and the initial value of N3 is 391.1V and the final value is 383.9V, the current is 18.7A. After obtaining the voltage change and combining it with the current change value, the voltage drop rate parameter is established as an important input for the subsequent calculation of the rate deviation. The response time is uniformly set to 0.6s. The data is shown in Table 1: Table 1 Node voltage response sampling value table Sample No. Node number Initial voltage value (V) Final voltage value (V) Current change (A) Response time (s) Sample 1 N1 390.2 382.6 18.5 0.6 Sample 2 N2 388.5 381.3 19.1 0.6 Sample 3 N3 391.1 383.9 18.7 0.6 As shown in Table 1, the voltage drop amplitude of each node is basically between 6–8 V, the current amplitude is maintained in the range of 18–20 A, and the response time is consistent, providing reliable input for the subsequent unit current voltage rate calculation, and ultimately obtaining voltage response sampling data.

[0020] The voltage rate deviation calculation submodule calculates the voltage drop rate under unit current based on the voltage response sampling data, and calculates the difference between the voltage drop rate according to the upper and lower limits of the voltage response rate of the target node, generates upper and lower deviation groups, and simultaneously performs absolute value ratio statistics based on the deviation group and the target interval amplitude, using the formula: ; The voltage rate interval deviation rate and the voltage drop trend deviation degree are calculated and the rate deviation statistics are obtained, where: Represents the voltage drop rate per unit current, and are the lower and upper limits of the voltage response rate of the target node, is the transient voltage drop value of the i-th sampling vehicle, is the corresponding current applied value, n is the number of sample groups, and R is the rate interval deviation rate; Based on the voltage response sampling data, the voltage drop rate under unit current is calculated. First, the ratio of the transient voltage drop value of each node to the applied current amplitude is determined to obtain the voltage drop rate of the current vehicle under this test. , taking sample 1 as an example, the drop amplitude is 7.6V, corresponding to the current 18.5A, then The system presets the upper and lower limits of the target node's allowed rate as follows: 、 , which is used to make a ratio judgment on the degree of deviation in the future, and the rate deviation rate is constructed using the formula.

[0021] Bring in data: Sample 1: ; Sample 2: ; Sample 3: ; The sum of squares is calculated as: ; Square root , the numerator is calculated as: ; The denominator is: ; Finally, we get: ; The judgment threshold 1 used is set based on the system voltage rate response standard interval deviation tolerance. The specific setting method is: when the deviation rate R value is 1, it means that the total deviation of the voltage rate between the upper and lower limits under the unit current of the current node is exactly equal to half of the amplitude of the standard interval multiplied by the number of samples, that is, the upper and lower deviations are completely consistent with the tolerance amplitude. Therefore, R=1 can be regarded as the boundary of the voltage rate deviating from the upper tolerance limit. This value is limited by 、 The absolute value of the set difference and the multiplication relationship of the sample number n are established. R increases linearly with the number of sample nodes and decreases with the width of the upper and lower limits. Setting this value to 1 is equivalent to ensuring that the deviation value of a single node does not exceed the mean amplitude of the interval, ensuring that the voltage rate consistency is controlled within an acceptable range. Therefore, this threshold has technical traceability and engineering setting basis. A value greater than the judgment threshold of 1 indicates that the current vehicle node voltage rate deviates significantly from the standard upper and lower limits, ultimately generating rate deviation statistics.

[0022] The rate interval deviation rate is a dimensionless ratio used to quantify the degree of difference between the voltage response rate of the current vehicle node under unit current and the target interval set by the system. Its specific significance lies in simultaneously measuring the absolute deviation between the node rate value and the upper and lower limits of the target rate interval, as well as the average response fluctuation level of the entire node group in the test round, and normalizing the composite deviation with the preset standard interval amplitude to obtain the evaluation coefficient. The smaller the deviation rate, the closer the current node voltage response rate is to the standard interval, the more centralized the system response and the higher the coordination. Conversely, if the deviation rate is significantly greater than 1, it indicates that the node voltage response behavior is obviously out of the target interval limit, and there is a risk of response mismatch. Therefore, this indicator can provide a quantitative judgment basis for the node response performance within the target tolerance interval, and provide quantitative decision support for node grid adaptation and dynamic screening.

[0023] The formula is constructed based on the triple deviation analysis structure of the unit current voltage drop rate. First, and The two items are used to measure the absolute offset between the current node rate and the upper and lower boundaries of the preset response interval. The sum of these two items reflects the degree of concentrated deviation of the current vehicle response value from the target interval. Secondly, It expresses the square root of the sum of the rate values ​​of all sampling nodes, which is essentially the Euclidean norm of the unit current response rate, and is used to capture the average fluctuation intensity of the overall response of the system to avoid error amplification caused by relying solely on a single node judgment. The purpose of adding these terms in the numerator is to incorporate individual offsets and group fluctuations into the evaluation structure to enhance robustness. The denominator uses half the interval width multiplied by the number of samples to form an amplified value of the standard reference amplitude, and establishes a normalized reference benchmark proportional to the sample size to ensure that the calculated value is not unbalanced due to the number of nodes or interval settings, and can reflect the relative adaptability of the current node.

[0024] The response adaptation judgment submodule compares the rate deviation statistics with the voltage regulation dead zone range to determine whether the rate deviation statistics are within the range. It then establishes a response adaptation index table based on the number of nodes and the corresponding results to obtain multi-node vehicle response adaptation records. According to the rate deviation statistics, it is input into the response adaptation judgment logic, and the R value is compared with the set rate dead zone tolerance judgment threshold. The current standard stipulates that if the R value is less than 1, it is judged as adapted, and if it is greater than or equal to 1, it is judged as unfit. In the above calculation, R=5.19, so this node is judged as unfit. The rates of other sample nodes are: sample 2 is 0.377V / A, and sample 3 is 0.385V / A. After similar calculations, their R values ​​are 4.63 and 4.87 respectively, both greater than the threshold, and are judged as unfit. The judgment results of the three nodes are encoded as [0, 0, 0] in sequence and written into the node response record matrix. The corresponding index order is stored in the multi-node response dictionary table, which is used to retrieve the stable response differences of the analysis node in other environments, and finally obtain the multi-node vehicle response adaptation record.

[0025] See also Figure 3 , the responsiveness assessment module includes: The response phase acquisition submodule collects the time coordinates of the maximum voltage fluctuation point of the adapted vehicle, records the maximum fluctuation time in combination with the start time record of the excitation application, synchronizes the excitation application time, calculates the difference between the maximum fluctuation point time of each node and the excitation time, obtains the time offset of each node, and obtains the maximum fluctuation phase offset group; The time coordinates of the maximum voltage fluctuation point of each vehicle in all adapted vehicles are collected. First, the voltage time series data of each node is read, and the voltage change before and after each time point is scanned with a step length of 0.1s. If the voltage difference exceeds 5V within any continuous 0.3s, the moment is considered to be a significant voltage fluctuation point. In this way, the maximum voltage change moment of each vehicle node within 6s after excitation is determined, and this moment is recorded as the maximum fluctuation time point of the node. At the same time, the excitation application time of each vehicle is extracted and uniformly set to 1.0s. The phase offset time is obtained by subtracting the excitation time from the fluctuation time point. The fluctuation point of sample 1 is 4.2s, and the offset is 3.2s. The fluctuation point of sample 2 is 4.6s, and the offset is 3.6s. The fluctuation point of sample 3 is 4.4s, and the offset is 3.4s. All information is summarized in the following table: Table 2 Vehicle node fluctuation characteristics collection table Sample No. Vehicle number Maximum voltage fluctuation time (s) Excitation application time (s) Phase shift time (s) Sample 1 V1 4.2 1.0 3.2 Sample 2 V2 4.6 1.0 3.6 Sample 3 V3 4.4 1.0 3.4 As shown in Table 2, the difference between the maximum voltage fluctuation point and the excitation application time of all vehicle nodes is between 3.2 and 3.6 s, and the maximum fluctuation phase offset group is finally obtained.

[0026] The current stabilization statistics submodule indexes the current sampling sequence after the excitation of each node according to the maximum fluctuation phase offset group, calculates the time difference between the excitation time and the stabilization time, reads the accuracy level identification code of each node, and establishes a numerical level index array using the formula: ; The synchronization overlap index is obtained by operation, and the initial data set of synchronization response is generated, where: Indicates the maximum voltage fluctuation time point of the j-th adapted vehicle (unit: s), represents the starting time point of the current stabilization of the j-th vehicle (unit: s), Indicates the starting application time of the excitation current (unit: s), Indicates the synchronization adjustment factor corresponding to the j-th vehicle node according to the accuracy level (Class1–Class3) (Class1 takes 1, Class2 takes 2, Class3 takes 3, used to adjust the time offset contribution), Indicates the maximum value of the maximum voltage fluctuation time among all compatible vehicles (unit: s). It represents the minimum value of the current stabilization time among all the adapted vehicles (unit: s), m is the total number of adapted vehicles participating in the synchronization evaluation, and S is the response synchronization overlap index value, which is used to measure the level of multi-node response coordination; According to the maximum fluctuation phase offset group, the current time series of each node after excitation is collected. The absolute value of the current change is set to be less than 0.2A in three consecutive sampling points as the starting time of current stabilization. Through indexing, it is determined that the current of sample 1 reaches stability at 6.1s, sample 2 at 6.4s, and sample 3 at 6.0s. Subtracting them from the excitation time of 1.0s, the delay values ​​are 5.1s, 5.4s, and 5.0s, respectively. At the same time, the accuracy level of each node is read, and the corresponding synchronization factors are set to 1, 2, and 3 according to Class 1, Class 2, and Class 3, respectively. The results are summarized as follows: Table 3 Vehicle node stabilization and accuracy characteristics Sample No. Current stabilization time (s) Delay time (s) Accuracy grade <![CDATA[Dilution factor (g k )]]> Sample 1 6.1 5.1 Class1 1 Sample 2 6.4 5.4 Class2 2 Sample 3 6.0 5.0 Class3 3 As shown in Table 3, after establishing all participating items, substitute into the formula: ; The first difference is: ; The second precision dilution weight is: ; The denominator is calculated as: (Unreasonable, adjust the order); After adjustment: ; Final result: ; This value indicates that there is a significant degree of synchronization offset between the vehicle nodes during the response process, and ultimately generates an initial data set of synchronous responses.

[0027] The synchronization overlap index is a dimensionless evaluation value used to measure the relative consistency and degree of synchronization of multiple vehicle nodes in the process of responding to excitation. Its specific significance lies in taking the time difference between each node from the moment of excitation application to the maximum voltage fluctuation point and the current stabilization moment as the main response parameter, and introducing the adjustment factor set by the accuracy level. The total amount of overall response difference is calculated by weighted superposition. At the same time, it is normalized by combining the time bandwidth of the maximum fluctuation time and the minimum stabilization time between all nodes. This allows the index to reflect the average deviation trend of the response behavior of each node and the regulatory effect of different accuracy levels on the synchronization coordination capability. Finally, a numerical result with strong comparability and unified scale is used to express the comprehensive performance of response synchronization in the multi-node system.

[0028] The operational logic of the formula is constructed based on the cumulative time difference of response behavior and the intervention effect of accuracy level in synchronization assessment. First, The part is used to sum the absolute time difference of each vehicle node from the time point of maximum voltage fluctuation to the time point of current stabilization, reflecting the cumulative degree of phase offset of each node in the response process. The larger the value, the more concentrated the response deviation. The precision factor adjustment item is introduced in part, which multiplies the time delay by the weight factor determined by the precision level to form the offset contribution assessment guided by precision. The two parts together serve as the numerator, which represents the total amount of overall response difference after weighting the time offset and the precision factor. The denominator is The theoretical synchronization reference bandwidth, which is composed of the total number of participating nodes and the span of the maximum fluctuation time and the minimum stabilization time, is used as a normalization benchmark to adjust the scale of the numerator. This structure integrates the absolute time difference and the precision guidance term and normalizes them into a dimensionless indicator, thereby comprehensively reflecting the degree of multi-node response synchronization deviation.

[0029] The synchronization vector construction submodule normalizes the data based on the initial synchronization response data set, merges the three parameter vectors, and sequentially combines them to construct the vehicle synchronization vector. The synchronization vectors of each node are used as row vectors to construct a matrix form to obtain the response synchronization feature group. According to the phase offset time, current stabilization delay time and accuracy level factor recorded in the initial data set of synchronous response, three parameter normalization intervals are set, namely phase offset (0–5s), delay time (0–10s), and accuracy level (Class1=1 to Class3=3). The linear normalization conversion formula is used. Standardization is performed, where represents the normalized value, Represents the current value, represents the minimum value, Representing the maximum value, the phase offset of sample 1 is 3.2s, corresponding to the normalized value of 0.64, the delay time is 5.1s corresponding to 0.51, the accuracy level is 1 corresponding to 0, sample 2 is normalized to [0.72, 0.54, 0.5], and sample 3 is [0.68, 0.50, 1]. Finally, the normalized vectors are sorted by vehicle number and combined to construct the synchronization feature matrix as follows: Table 4 Vehicle synchronization normalized characteristic matrix Sample No. Phase offset normalized value Normalized delay time value Normalized value of accuracy level Sample 1 0.64 0.51 0.00 Sample 2 0.72 0.54 0.50 Sample 3 0.68 0.50 1.00 As shown in Table 4, the three-dimensional synchronization vector has completed the normalized coding combination, and finally obtained the response synchronization feature group.

[0030] See also Figure 4 , the scheduling matching mapping module includes: The response difference extraction submodule extracts the response start and end time nodes of each vehicle based on the response phase offset time and current stabilization delay time recorded in the response synchronization feature group, and constructs a vehicle response time information group. Combined with the grid frequency regulation tolerance range of the discharge task, it extracts the corresponding frequency regulation time window, constructs a benchmark response time based on the median value of the regulation time window, and compares the response time of each vehicle with the benchmark response time to obtain a frequency response difference group. Based on the response offset time and stabilization delay time data recorded in the response synchronization feature group, the voltage phase offset time and current stabilization time of each adapted vehicle are extracted in turn. By accumulating the two, the total response time of each vehicle is constructed. The response starting point is taken as the starting point of the voltage excitation time, and the end point is the current stabilization moment. Combined with the grid frequency regulation tolerance setting range of ±0.5Hz set in the scheduling period, the effective response time of frequency regulation is determined to be 7.5s by consulting the actual fluctuation time band in the frequency regulation cycle, and this value is set as the benchmark response time. Then, each vehicle The total response time is compared with the benchmark response time one by one, and the absolute differences are recorded in sequence to form a response difference array for a group of vehicles. For example, the response time of sample 1 is 7.0s, the difference is |7.0-7.5|=0.5s, the response time of sample 2 is 8.0s, the difference is |8.0-7.5|=0.5s, the response time of sample 3 is 7.5s, the difference is |7.5-7.5|=0s, and the response time of sample 4 is 7.0s, the difference is |7.0-7.5|=0.5s. All the original response data and response differences are shown in the following table: Table 5 Vehicle response time information table Sample No. Vehicle number Phase shift time (s) Return to stabilization delay time (s) Total response time (s) Benchmark response time (s) Response difference (s) Sample 1 V01 2.8 4.2 7.0 7.5 0.5 Sample 2 V02 3.4 4.6 8.0 7.5 0.5 Sample 3 V03 3.1 4.4 7.5 7.5 0.0 Sample 4 V04 2.9 4.1 7.0 7.5 0.5 As shown in Table 5, all vehicle nodes have obtained the absolute difference of the relative frequency adjustment reference time, and obtained the frequency response difference group.

[0031] The priority sequence construction submodule creates a corresponding offset value index table based on the degree of response deviation of each vehicle in the frequency response difference group, and sorts the differences in ascending order. For vehicles whose differences fall within the deviation interval, the stabilization time node is recorded and matched against the frequency adjustment end time. Vehicles that meet both the deviation and stabilization time conditions are marked as priority vehicles, and the remaining vehicles are classified as secondary vehicles. The rows are summarized to obtain the priority assignment sequence and secondary sequence division results. According to the difference value of each vehicle in the frequency response difference group, all the differences are processed in ascending order to determine whether the vehicle falls within the benchmark deviation range. 0 to 1s is set as the deviation allowable range, and the vehicles falling within this range are marked as preliminary priority candidate vehicles. Then, the current stabilization time nodes of the candidate vehicles are retrieved one by one, and compared with the end time of the grid frequency adjustment period. The end of the adjustment period is set to 9.0s. It is determined whether the stabilization time of the candidate vehicle is less than this moment. If the conditions are met, it is retained in the priority sequence, otherwise it is eliminated from the priority sequence. Sequence and transfer to the secondary vehicle queue. Taking sample data as an example, sample 1 has a stabilization time of 4.2s, which is less than 9.0s, and a response difference of 0.5s, which falls within the allowable range, and is classified as a priority vehicle. Sample 2 has a difference of 0.5s and a stabilization time of 4.6s, which still meets the conditions and is also classified as a priority vehicle. Sample 3 has a difference of 0s, which has the highest priority, and a stabilization time of 4.4s, which meets the conditions. Sample 4 has a difference of 0.5s and a stabilization time of 4.1s, which also meets the conditions. All four samples meet the two criteria, so all are included in the priority vehicle set. The data is summarized as follows: Table 6 Priority vehicle screening conditions Sample No. Vehicle number Response difference (s) Settling time (s) Is it within the tolerance range? Is it in the time window Sequence Category Sample 1 V01 0.5 4.2 yes yes priority Sample 2 V02 0.5 4.6 yes yes priority Sample 3 V03 0.0 4.4 yes yes priority Sample 4 V04 0.5 4.1 yes yes priority As shown in Table 6, all vehicles are marked as priority categories, and the priority assignment sequence and secondary sequence division results are obtained.

[0032] The vehicle scheduling mapping submodule reads the accuracy level and power response capability parameters of each vehicle based on the vehicle set in the priority assignment sequence and secondary sequence division results, internally sorts the priority vehicles and secondary vehicles based on the power response capability indicators, assigns a scheduling label to each vehicle, and obtains the vehicle collaborative scheduling classification sequence; Based on the results of the priority assignment sequence and the secondary sequence division, the accuracy level identifier corresponding to the vehicle number in the sequence and the maximum discharge power response value of each vehicle are read. The accuracy levels Class1, Class2, and Class3 are set to 3, 2, and 1 respectively. The power response capabilities are set to sample 1: 45kW, sample 2: 50kW, sample 3: 40kW, and sample 4: 42kW respectively. The power values ​​of the priority vehicles are sorted in descending order, and are sorted as sample 2, sample 1, sample 4, and sample 3 in sequence. The sorting results are re-numbered and labeled. Sample 2 is numbered P1, sample 1 is numbered P2, sample 4 is numbered P3, and sample 3 is numbered P4. The mapping labels of all vehicles are organized as follows: Table 7 Vehicle dispatch mapping sequence table Vehicle number Accuracy grade Discharge power (kW) Priority Category Dispatch Number V02 Class2 50 priority P1 V01 Class1 45 priority P2 V04 Class3 42 priority P3 V03 Class2 40 priority P4 As shown in Table 7, all vehicle scheduling mapping classification and numbering operations have been completed, generating a vehicle collaborative scheduling classification sequence.

[0033] See also Figure 5 , the task load distribution module includes: The adjustment gradient construction submodule obtains the dispatch numbers of all vehicles in the vehicle cooperative dispatch classification sequence, sets the load adjustment rate intervals for the discharge task, divides them into equal intervals, constructs a rate index table based on the number of segments, determines the number of vehicles that can be accommodated in each rate interval based on the ratio between the total number of dispatch numbers and the total number of rate segments, establishes a number matching framework between the rate intervals and the vehicle dispatch numbers, and obtains the adjustment rate interval grouping results; Obtain the dispatch numbers of all six adapted vehicles in the vehicle cooperative dispatch classification sequence, and based on the task discharge rate requirement, set the adjustment rate interval to 0.1C to 2.0C. Within this range, segment the rate gradient with an interval of 0.5C. Finally, divide the rate gradient into four sections: 0.1–0.5C, 0.6–1.0C, 1.1–1.5C, and 1.6–2.0C, numbered T01 to T04. Each section is configured with a limit on the number of vehicles that can be accommodated. Based on the total number of vehicles and the task granularity requirements, the capacity of each section is set to 2 vehicles, 2 vehicles, 1 vehicle, and 1 vehicle, respectively. Generate an adjustment gradient grouping table. The specific rate section ranges, numbers, and capacity configurations are shown in the following table: Table 8 Load Regulation Rate Grouping Table Task Group Number Task Number Adjustment rate range (C) Number of vehicles that can be allocated Task Group 1 T01 0.1–0.5 2 Task Group 2 T02 0.6–1.0 2 Task Group 3 T03 1.1–1.5 1 Task Group 4 T04 1.6–2.0 1 As shown in Table 8, a one-to-one correspondence has been established between the task numbers and the adjustment rate intervals, and the adjustment rate interval grouping results are obtained.

[0034] The task matching submodule allocates the rate task interval in which each vehicle's dispatch number is located based on the adjustment rate interval grouping results, the precision level index corresponding to each vehicle dispatch number, and the recommended discharge capacity. It then identifies whether the dispatch number continuity in the rate task interval is disrupted, determines whether the vehicle's recommended rate falls within the allowable range of the assigned rate interval, and simultaneously determines the degree of coordination between the precision level index and the task adjustment interval. It completes the vehicle attribution adjustment within the task interval and obtains the task adjustment grouping matrix. According to the regulation rate range and vehicle capacity limit defined in Table 8, the recommended discharge rate value and accuracy level of each vehicle are extracted from the vehicle dispatch sequence, and they are assigned to the matching regulation rate task group in turn. In the sample data, the recommended rate values ​​of vehicles P1 to P6 are set to 0.45C, 0.85C, 1.20C, 1.70C, 0.35C, and 0.90C respectively, and the accuracy levels are Class2, Class3, Class1, Class2, Class1, and Class2 respectively. The accuracy level values ​​are set to Class1=1, Class2=2, and Class3=3. In the corresponding judgment process, P1's rate of 0.45C is assigned to T01, which is within the interval range, and its accuracy level is 2, which also meets the requirements, and is marked as successfully grouped; then P2's rate of 0.85C is determined to fall into the T02 range, with an accuracy level of 3, which meets the conditions; P3's rate of 1.20C matches T03, with an accuracy level of 1, which meets the high-rate group conditions; P4's rate of 1.70C corresponds to T04, with an accuracy level of 2, allowing it to enter the high-rate task; P5's rate of 0.35C falls into T01, with an accuracy level of 1, which is a barrier-free match; P6's rate of 0.90C is assigned to T02 and is grouped together with P2, with an accuracy level of 2, which is still within the allowable range; the task numbers and grouping results of all vehicles are summarized in the following table: Table 9 Vehicle Adjustment Task Assignment Table Vehicle number Recommended rate (C) Accuracy grade Assign a task number Allocation rate range (C) P1 0.45 Class2 T01 0.1–0.5 P5 0.35 Class1 T01 0.1–0.5 P2 0.85 Class3 T02 0.6–1.0 P6 0.90 Class2 T02 0.6–1.0 P3 1.20 Class1 T03 1.1–1.5 P4 1.70 Class2 T04 1.6–2.0 As shown in Table 9, all vehicles have completed task assignment and obtained the task adjustment grouping matrix.

[0035] The allocation mapping generation submodule reads the number of vehicles, corresponding adjustment rate range, and task number in each group based on the mapping results of each rate task group and vehicle number recorded in the task adjustment group matrix, and arranges them in ascending order by task number. It then creates a dispatch number list of task groups and vehicles, collects statistics on the recommended adjustment rates of the vehicles in each group, and standardizes the results. It then integrates the output of the number of vehicles, dispatch number, and task number to generate a load allocation mapping table. According to the task allocation information of each vehicle in Table 9, the vehicle numbers and corresponding recommended speed values ​​contained in each task number are summarized. The average value of the vehicle speed value under each task number is calculated and rounded to 0.05C units. For example, task T01 contains vehicles P1 and P5, with speeds of 0.45C and 0.35C respectively, an average of 0.40C, rounded to 0.40C; T02 is 0.85C and 0.90C, an average of 0.875C, rounded to 0.90C; T03 and T04 are 1.20C and 1.70C respectively, no rounding is required, and the original values ​​are retained. The task numbers, vehicle lists, and average speeds are sorted as follows: Table 10 Task vehicle scheduling mapping table Task Number Assign vehicle number Recommended rate average (C) Standard rate value (C) T01 P1, P5 0.40 0.40 T02 P2, P6 0.88 0.90 T03 P3 1.20 1.20 T04 P4 1.70 1.70 As shown in Table 10, the vehicle dispatch numbers have been rearranged according to the task numbers and a standard rate mapping relationship has been formed to generate a load distribution mapping table.

[0036] See also Figure 6 , the collaborative control and judgment module includes: The response monitoring and identification submodule records the control feedback data of each vehicle based on the vehicle number under each task number in the load distribution mapping table, counts the number and distribution time period of various over-limit behaviors within the task cycle, and obtains the task cycle response behavior change trend record; The operation task data of each vehicle is collected and grouped according to the task number. The nodes with vehicle numbers P1 and P2 are classified into task number T1, and P3 is classified into task number T2. The operation status of each node in a complete sampling cycle is counted respectively, and the total number of samples is 100. The vehicle current, voltage and status response signals are collected at a fixed frequency during the sampling cycle. The number of sampling points that exceed the rated current limit in the current detection cycle is taken as the number of current limit violations, which is 5 times for P1, 2 times for P2, and 6 times for P3. Then, the number of times when the voltage fluctuation drops below the specified threshold is counted, which are 3 times, 1 time, and 5 times respectively. The node response timing and the setting are further judged. Is there a delay of more than 3s in the timing sequence? If so, it is recorded as a response delay event. Samples P1 and P3 appear 4 and 5 times respectively, and P2 has no delay. After integrating various abnormal events, determine whether it is in an adaptive state. If any one of the three items is 0 and the total is greater than 3, the adaptation state is set to 0, otherwise it is 1. On this basis, the total time covered by all abnormal events is counted. The abnormal duration of P1 is 4.2s, P2 is 1.0s, and P3 is 5.6s. The scheduling priority is set comprehensively according to the duration distribution and adaptation status. The more abnormalities, the lower the priority. Finally, the scheduling priority of sample P2 is 2, P1 is 3, and P3 is 1.

[0037] The state trend aggregation submodule extracts the abnormal data segments marked in all records based on the task cycle response behavior change trend record, and counts the number of abnormalities and the total duration of each vehicle, determines whether the vehicle has entered the adaptive state judgment condition, establishes the mapping relationship between the task number and the state aggregation factor, and obtains the task state trend summary table; Based on the statistical results of the aforementioned sampling periods, the task allocation adaptability of all vehicles is dynamically identified. First, all current, voltage, and response status sampling records of vehicle P1 within task T1 are read to identify the start and end time periods of continuous current deviation events. The voltage drop trend is further mapped to determine whether it occurs simultaneously with the current anomaly. The response delay signal is then extracted to determine whether it recurs within 3 seconds before and after the anomaly period. This forms a composite structural feature set of abnormal events. The time occupied by each of these feature sets is calculated and accumulated in seconds, and the total duration of the anomaly is recorded. A determination is also made as to whether there are any nodes with an adaptability status of 1. If so, the frequency of anomalies within its task period is extracted and compared with other nodes. If the total number of current and voltage anomalies is less than 20% of the average number of nodes in the task group, the node is identified as highly adaptable. Currently, P2 has an adaptability status of 1, with two current limit violations and one voltage fluctuation, both lower than the T1 group averages of four and two, respectively. Therefore, it is confirmed to be a node with good adaptability, and its corresponding scheduling priority is explicitly identified in the scheduling system.

[0038] The control scheme generation submodule rearranges all marked tasks into temporary control zones based on the state aggregation factors corresponding to each task number in the task state trend summary table. It then marks the vehicle number with the lowest priority for replacement scheduling, reallocates the target rate to adjacent task numbers, renumbers all task numbers, vehicle numbers, and their corresponding adjustment targets, and integrates and outputs a dynamically optimized V2X charging and discharging coordinated control scheme. Combined with the above vehicle abnormal status and scheduling priority data, the initial scheduling vector is constructed for the current batch task nodes. The nodes with an adaptation status of 1 are selected for priority sorting. The abnormal duration and the number of events are used as the basis for post-sorting. P2 with an adaptation status of 1 is placed at the top of the priority queue, and P1 and P3 with an adaptation status of 0 are placed in the second place. According to the abnormal duration, the sorting is refined. P1 is 4.2s and P3 is 5.6s. P1 has the second highest priority after P2, and P3 has the lowest priority. This forms the scheduling priority vector [P2, P1, P3]. This vector can be directly used for task push judgment in the next stage scheduling system, and the vehicle task scheduling order is solidified as the final decision output, as shown in Table 11.

[0039] Table 11 Vehicle task scheduling priority table Scheduling order Vehicle number Adaptation status Total abnormal duration (s) Scheduling priority No. 1 pick P2 1 1.0 2 No. 2 P1 0 4.2 3 No. 3 pick P3 0 5.6 1 As shown in Table 11, the scheduling order is based on the dual indicators of adaptation status and total abnormality duration, forming a clear response sorting output result.

[0040] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of protection of the technical solution of the present invention.

Claims

1. A V2X charging and discharging coordinated control system based on dynamic multi-objective optimization, characterized in that: The system comprises: The voltage characteristic identification module obtains the transient voltage response data and applied current of vehicles connected to the V2G network, calculates the voltage drop rate under unit current, calculates the upper and lower deviation groups and calculates the ratio with the target range, determines whether it is within the voltage regulation dead zone, and obtains multi-node vehicle response adaptation records; The response capability evaluation module collects the time coordinates of the maximum voltage fluctuation point and the excitation application time of the adapted vehicle based on the multi-node vehicle response adaptation record, calculates the response phase offset, and constructs a normalized synchronization vector based on the current stabilization time and the charge and discharge accuracy level to obtain a response synchronization feature group. The dispatch matching mapping module reads the grid frequency regulation tolerance based on the response synchronization feature group, calculates the absolute value of the difference between the adapted vehicle response phase offset and the current stabilization time term and the regulation tolerance, sorts them in ascending order, constructs a vehicle dispatch mapping classification, and obtains a vehicle collaborative dispatch classification sequence; The task load distribution module establishes a one-to-one mapping between the task load adjustment rate and the vehicle scheduling sequence according to the vehicle cooperative scheduling classification sequence and in combination with the load adjustment rate, and obtains a load distribution mapping table.

2. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1 is characterized in that: The multi-node vehicle response adaptation record includes the node voltage adaptation value, the upper and lower deviation ratio distribution record, and the adjustment dead zone judgment result. The response synchronization feature group includes the response phase vector, the current stabilization coefficient, and the synchronization level index. The vehicle collaborative scheduling classification sequence includes the priority response sequence, the secondary response sequence, and the vehicle scheduling level label. The load distribution mapping scale includes the adjustment rate matching relationship, the vehicle sequence grouping label, and the task subgroup number.

3. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1, characterized in that: The voltage characteristic identification module includes: The data acquisition submodule obtains the transient voltage response data and corresponding applied current of each node vehicle connected to the V2G network under the action of the charging pile test current, extracts the current change value and the corresponding time difference within the transient period, matches the node timing to obtain the voltage change amplitude and response duration within the sampling window, and obtains the voltage response sampling data; The voltage rate deviation calculation submodule calculates the voltage drop rate under unit current based on the voltage response sampling data, and performs difference calculation on the voltage drop rate according to the upper and lower limits of the voltage response rate of the target node, generates upper and lower deviation groups, and simultaneously performs absolute value ratio statistics based on the deviation group and the target interval amplitude, calculates the voltage rate interval deviation rate and the voltage drop trend deviation degree, and obtains the rate deviation statistical results; The response adaptation judgment submodule compares the rate deviation statistical results with the voltage regulation dead zone range to determine whether the rate deviation statistical value is within the range, establishes a response adaptation index table based on the number of nodes and the corresponding results, and obtains multi-node vehicle response adaptation records.

4. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1, characterized in that: The response capability assessment module includes: The response phase acquisition submodule collects the time coordinates of the maximum voltage fluctuation point of the adapted vehicle based on the multi-node vehicle response adaptation record, records the maximum fluctuation time in combination with the start time record of the excitation application, performs synchronous indexing on the excitation application time, calculates the difference between the maximum fluctuation point time of each node and the excitation time, obtains the time offset of each node, and obtains the maximum fluctuation phase offset group; The current stabilization statistics submodule indexes the current sampling sequence after the excitation of each node based on the maximum fluctuation phase offset group, calculates the time difference between the excitation time and the stabilization time, reads the accuracy level identification code of each node, establishes a numerical level index array, calculates and obtains the synchronization superposition index, and generates the synchronization response initial data group; The synchronization vector construction submodule normalizes the data according to the initial synchronization response data group, merges the three parameter vectors, and sequentially combines them to construct the vehicle synchronization vector. The synchronization vectors of each node are used as row vectors to merge and construct a matrix form to obtain the response synchronization feature group.

5. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1, characterized in that: The scheduling matching mapping module includes: The response difference extraction submodule extracts the response start and end time nodes of each vehicle based on the response phase offset time and current stabilization delay time of each adapted vehicle recorded in the response synchronization feature group, and constructs a vehicle response time information group. In combination with the grid frequency adjustment tolerance range of the discharge task, the corresponding frequency adjustment time window is extracted, and a benchmark response time is constructed based on the median value of the adjustment time window. The response time of each vehicle is compared with the benchmark response time to obtain a frequency response difference group. The priority sequence construction submodule establishes a corresponding offset value index table based on the degree of response deviation of each vehicle in the frequency response difference group, and performs difference ascending order processing. For vehicles whose differences are within the deviation interval, the stabilization time node is recorded and matched with the frequency adjustment end time. Vehicles that meet both the deviation condition and the stabilization time condition are marked as priority vehicles, and the remaining vehicles are classified as secondary vehicles. The rows are summarized to obtain the priority assignment sequence and secondary sequence division results. The vehicle scheduling mapping submodule reads the accuracy level and power response capability parameters of each vehicle based on the vehicle set in the priority assignment sequence and secondary sequence division results, internally sorts the priority vehicles and secondary vehicles according to the power response capability indicators, assigns a scheduling label to each vehicle, and obtains the vehicle collaborative scheduling classification sequence.

6. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1, characterized in that: The task load distribution module includes: The adjustment gradient construction submodule obtains the dispatch numbers of all vehicles in the vehicle cooperative dispatch classification sequence, sets the load adjustment rate interval of the discharge task, divides it into equal intervals, constructs a rate index table according to the number of sections, determines the number of vehicles that can be accommodated in each rate interval based on the ratio between the total number of dispatch numbers and the total number of rate sections, establishes a number matching framework between the rate interval and the vehicle dispatch number, and obtains the adjustment rate interval grouping result; The task matching division submodule allocates the rate task interval in which the dispatch number of each vehicle is located according to the adjustment rate interval grouping result, the accuracy level index corresponding to each vehicle dispatch number, and the recommended discharge capacity, identifies whether the continuity of the dispatch number in the rate task interval is broken, determines whether the recommended rate of the vehicle falls within the allowable range of the allocated rate interval, and simultaneously determines the degree of coordination between the accuracy level index and the task adjustment interval, completes the vehicle attribution adjustment in the task interval, and obtains the task adjustment grouping matrix; The allocation mapping generation submodule reads the number of vehicles, the corresponding adjustment rate range and the task number in each group in turn based on the mapping results of each rate task group and the vehicle number recorded in the task adjustment grouping matrix, and arranges them in ascending order by task number, establishes a dispatch number list of task groups and vehicles, counts the recommended adjustment rates of the vehicles in each group and standardizes the results, integrates the output by combining the number of vehicles, dispatch number and task number, and generates a load distribution mapping table.

7. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 1, characterized in that: The system further comprises: The coordinated control determination module monitors the changing trend and adaptation status of each vehicle's response behavior during the discharge task execution phase based on the load distribution mapping table, summarizes the vehicle characteristic changes and dispatch response status during the task cycle, and generates a dynamically optimized V2X charge-discharge coordinated control plan; The dynamic optimization V2X charging and discharging coordinated control scheme includes a characteristic trend map, an adaptation state trajectory, and regulation feedback parameters.

8. The V2X charge-discharge coordinated control system based on dynamic multi-objective optimization according to claim 7, characterized in that: The collaborative control determination module includes: The response monitoring and identification submodule records the control feedback data of each vehicle based on the vehicle number under each task number in the load distribution mapping table, counts the number and distribution time period of various over-limit behaviors in the task cycle, and obtains a record of the change trend of the task cycle response behavior; The state trend aggregation submodule extracts the abnormal data segments marked in all records based on the task cycle response behavior change trend record and counts the number of abnormalities and the total duration of each vehicle, determines whether the vehicle enters the adaptation state judgment condition, establishes a mapping relationship between the task number and the state aggregation factor, and obtains the task state trend summary table; The control scheme generation submodule rearranges all marked tasks into temporary control areas based on the state aggregation factor corresponding to each task number in the task state trend summary table, and marks the vehicle number with the lowest priority for replacement scheduling setting, reallocates the target rate to the adjacent task number, renumbers all task numbers, vehicle numbers and their corresponding adjustment targets, and integrates the output to dynamically optimize the V2X charging and discharging coordinated control scheme.

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