Vehicle network interaction control method and device

Abstract

The invention relates to a vehicle network interaction control method and device. The method is applied to a vehicle network interaction controller, and the vehicle network interaction controller communicates with a vehicle access point and a power grid side. The method comprises the steps that interaction data of a vehicle access point and a power grid side and operation state data of the power grid side are acquired; acquiring power demand information of a vehicle access point, first performance data of the vehicle access point, second performance data of the new energy vehicle and current load data of a power grid side under the condition that a power angle instability risk is detected to exist on the power grid side based on the interaction data and the operation state data; and according to the power demand information, the first performance data, the second performance data and the current load data, carrying out charging and discharging control on the vehicle access point. The method can improve the power angle stability of the power grid.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a vehicle-to-grid (V2G) interactive control method and device. Background Technology

[0002] With the rapid development of new energy technologies, new energy vehicles, as a clean and efficient mode of transportation, are receiving increasing attention.

[0003] Currently, vehicle charging points are typically directly connected to the power grid. However, when vehicles are connected to the grid on a large scale, it can significantly impact the power grid's stability, thereby affecting the safe and stable operation of the entire power system. Summary of the Invention

[0004] Therefore, it is necessary to provide a vehicle-grid interaction control method and device that can improve the power angle stability of the power grid, addressing the aforementioned technical problems.

[0005] In a first aspect, this application provides a vehicle-to-grid (V2G) interaction control method, applied to a V2G controller, which communicates with both the vehicle access point and the power grid side; the method includes:

[0006] Acquire interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side;

[0007] When a risk of power angle instability is detected on the grid side based on interactive data and operational status data, the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side are obtained.

[0008] Based on power demand information, first performance data, second performance data, and current load data, charge and discharge control is performed on the vehicle access point.

[0009] In one embodiment, before obtaining the power demand information of the vehicle access point and the current load data on the grid side, the method further includes:

[0010] Based on interactive data and operational status data, the current transient stability margin value on the power grid side is detected;

[0011] If the current transient stability margin is less than the preset transient stability margin target value, it is determined that there is a risk of power angle instability on the grid side.

[0012] In one embodiment, charging and discharging control of the vehicle access point is performed based on power demand information, first performance data, second performance data, and current load data, including:

[0013] Based on the current load data, detect the current static stability margin value on the grid side;

[0014] Based on the difference between the current transient stability margin value and the preset transient stability margin target value, and the current static stability margin value, the static stability margin target value on the grid side is detected.

[0015] Based on power demand information, first performance data, second performance data, and static stability margin target value, charge and discharge control is performed on the vehicle access point so that after charge and discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0016] In one embodiment, charging and discharging control is performed on the vehicle access point based on power demand information, first performance data, second performance data, and a static stability margin target value, so that after charging and discharging control, the current transient stability margin value on the grid side exceeds a preset transient stability margin target value, including:

[0017] Charge and discharge control steps: Based on power demand information, first performance data, second performance data, and static stability margin target value, charge and discharge control is performed on the vehicle access point;

[0018] Detect the current transient stability margin value of the grid side after charge and discharge control;

[0019] If the current transient stability margin value after charge / discharge control is less than the preset transient stability margin target value, increase the static stability margin target value and return to the charge / discharge control steps until the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0020] In one embodiment, the charging and discharging control of the vehicle access point based on power demand information, first performance data, second performance data, and current load data further includes:

[0021] Based on power demand information and second performance data, the charging priority of new energy vehicles is ranked.

[0022] Based on the charging priority, first performance data, second performance data, and current load data of each new energy vehicle, the charging and discharging control of the vehicle access point is performed.

[0023] In one embodiment, after acquiring the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side, the method further includes:

[0024] Based on interactive data and operational status data, and predicting that there is a risk of power angle instability on the grid side at a target future time, the power demand forecast curve, the first performance data of the vehicle access point, the second performance data of new energy vehicles, and the load forecast curve on the grid side are obtained.

[0025] The first adjustment period is located from the load forecast curve. The first adjustment period is before the target future time, and the load value of the first adjustment period is less than the preset load threshold.

[0026] Based on the power demand forecast curve, the first performance data, the second performance data, and the load forecast curve, detect the first power adjustment data corresponding to the first adjustment period and the second power adjustment data corresponding to the target future time.

[0027] When the real-time time is in the first adjustment period, the charging power of the vehicle access point is increased based on the first power adjustment data.

[0028] When the real-time time reaches the target future time, the charging power of the vehicle access point is reduced based on the second power adjustment data.

[0029] Secondly, this application also provides a vehicle-to-grid (V2G) interaction control device, applied to a V2G controller, which communicates with both the vehicle access point and the power grid side; the device includes:

[0030] The acquisition module is used to acquire interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side.

[0031] The detection module is used to obtain power demand information of the vehicle access point, first performance data of the vehicle access point, second performance data of the new energy vehicle, and current load data of the grid side when the risk of power angle instability is detected on the grid side based on interactive data and operating status data.

[0032] The charging and discharging control module is used to control the charging and discharging of the vehicle access point based on power demand information, first performance data, second performance data, and current load data.

[0033] Thirdly, this application also provides a computer device applied to a vehicle-to-grid (V2G) interactive controller, which communicates with both the vehicle access point and the power grid side. The computer device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0034] Acquire interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side;

[0035] When a risk of power angle instability is detected on the grid side based on interactive data and operational status data, the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side are obtained.

[0036] Based on power demand information, first performance data, second performance data, and current load data, charge and discharge control is performed on the vehicle access point.

[0037] Fourthly, this application also provides a computer-readable storage medium applied to a vehicle-to-grid (V2G) controller, which communicates with both the vehicle access point and the power grid side. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0038] Acquire interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side;

[0039] When a risk of power angle instability is detected on the grid side based on interactive data and operational status data, the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side are obtained.

[0040] Based on power demand information, first performance data, second performance data, and current load data, charge and discharge control is performed on the vehicle access point.

[0041] Fifthly, this application also provides a computer program product applied to a vehicle-to-grid (V2G) controller, which communicates with both the vehicle access point and the power grid side. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0042] Acquire interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side;

[0043] When a risk of power angle instability is detected on the grid side based on interactive data and operational status data, the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side are obtained.

[0044] Based on power demand information, first performance data, second performance data, and current load data, charge and discharge control is performed on the vehicle access point.

[0045] The aforementioned vehicle-to-grid (V2G) interaction control method and device first achieve data monitoring of both the V2G and V2G sides by acquiring interaction data between the vehicle access point and the grid side, as well as the grid side's operating status data. Then, based on the interaction data and operating status data, when a risk of power angle instability is detected on the grid side, the device acquires the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side. Based on the power demand information, the first performance data, the second performance data, and the current load data, the device performs charging and discharging control on the vehicle access point, achieving timely response to the risk of power angle instability in the V2G segment. In this way, the V2G interaction controller can prevent new energy vehicles from directly connecting to the grid. Through the data monitoring and real-time response mechanism of the V2G interaction controller, the energy interaction between new energy vehicles and the grid can be adjusted in real time, thereby enhancing the grid side's ability to cope with emergencies. When the grid load increases or a large number of new energy vehicles connect, it can detect this in a timely manner and adjust the grid energy configuration through charging and discharging control, thereby improving the grid side's power angle stability and ensuring the safe and stable operation of the power system. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a diagram illustrating the application environment of a vehicle-to-grid (V2G) interactive control method in one embodiment of this application.

[0048] Figure 2 This is a flowchart illustrating a vehicle-to-grid (V2G) interaction control method in one embodiment of this application.

[0049] Figure 3 This is a flowchart illustrating a vehicle-to-grid (V2G) interaction control method in another embodiment of this application.

[0050] Figure 4 This is a structural block diagram of a vehicle-to-grid (V2G) interactive control device in one embodiment of this application;

[0051] Figure 5 This is an internal structural diagram of a computer device in one embodiment of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0053] In one exemplary embodiment, a vehicle-to-everything (V2X) interactive control method is provided. This embodiment illustrates the application of this method to a terminal, where the terminal can be a V2X interactive controller, or various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices equipped with a V2X interactive controller. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted displays, etc. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. It is understood that this method can also be applied to a server, or to a system including both a terminal and a server, and implemented through the interaction between the terminal and the server.

[0054] A vehicle-to-grid (V2G) controller can refer to a control device used to coordinate and manage energy and information exchange between the new energy vehicle access point and the power grid. The V2G controller can communicate with at least the vehicle access point and the power grid. Through this communication, it can monitor, analyze, and regulate the charging and discharging behavior of the new energy vehicle access point in real time, optimize the power grid's operating status, and improve the stability, economy, and reliability of the power system.

[0055] In some feasible implementations, such as Figure 1 As shown, the vehicle-to-grid (V2G) controller includes a data acquisition and processing module, a main control unit, a communication feedback control module, and a storage module. New energy vehicles can connect to the power grid using charging and discharging equipment as their access point. Specifically:

[0056] The data acquisition and processing module comprises a data acquisition module and a data processing module. The data acquisition module uses onboard sensors and communication equipment to collect and monitor in real time the status of new energy vehicles connecting to the power grid at the vehicle access point, including key parameters such as voltage, current, and power factor at the vehicle access point. It also acquires real-time power grid operating status data through the power grid-side data interface. The data acquisition and processing module utilizes cloud computing and big data processing technologies to process and analyze the received vehicle and power grid data in real time, providing data support for subsequent control strategies. Based on data analysis and peak / valley electricity consumption times on the user side, it predicts power grid load changes and pre-determines corresponding control strategies.

[0057] The main control unit can employ high-performance processors and controllers. Based on the results of data acquisition and processing, it is responsible for executing the overall control logic and processing data; formulating corresponding control strategies to control the power exchange between the vehicle and the power grid, including adjusting charging and discharging power, thereby stabilizing the power grid's power angle stability.

[0058] The communication feedback control module can communicate with the power grid dispatch center in real time and receive instructions from the center. It can also interact with the onboard information system and upload real-time data from new energy vehicles.

[0059] The storage module can store information such as control policies, historical data, and operation logs.

[0060] In this embodiment, as Figure 2 As shown, the method includes the following steps S10-S30. Wherein:

[0061] Step S10: Obtain the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side.

[0062] Among them, vehicle access point can refer to the physical interface connecting new energy vehicles to the power grid, including charging piles, battery swapping stations, etc.

[0063] In some feasible implementations, the vehicle access point has bidirectional charging and discharging capabilities. That is, the new energy vehicle and the vehicle access point have the ability to flow energy in both directions, allowing the new energy vehicle to charge itself by drawing power from the grid and to discharge power back to the grid.

[0064] Interactive data refers to the electrical parameters and control signals exchanged between new energy vehicles and the power grid through the vehicle access point. This data reflects the energy exchange between the two systems. For example, during the charging process, the charging station can upload data such as voltage, current, and power factor to the power grid in real time.

[0065] Operational status data can refer to a set of data describing the current operating status of the power grid. This includes, but is not limited to, at least one of the following: power grid frequency, voltage level, load distribution, and power angle.

[0066] For example, the vehicle-to-grid (V2G) controller can establish communication connections with both the vehicle access point and the power grid to acquire relevant data. Specifically, it can collect interaction data between each vehicle access point and the power grid through at least one of the following: on-board sensors, sensors at the vehicle access point, and communication interfaces; simultaneously, it can obtain the power grid's operating status data from the power grid's data interface.

[0067] Step S20: If a risk of power angle instability is detected on the grid side based on interactive data and operating status data, obtain the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side.

[0068] Among these, power angle instability risk refers to the risk that excessive phase difference between generator units in the power grid due to various reasons may lead to system synchronization loss. For example, when a large number of new energy vehicles charge simultaneously, causing local overload of the power grid, power angle instability risk may occur.

[0069] Power demand information for vehicle access points refers to the power value and its temporal distribution required by the power grid to meet the charging or discharging needs of new energy vehicles during the current or future time period. Power demand information can be determined based on multi-source data such as real-time charging demand, reservation plans, and grid dispatch instructions. For example, the planned power demand information for a charging station during the future time period t1-t2 may include at least one of the following: the power required for new energy vehicles that start charging before t1 and whose charging time continues beyond t1 during the t1-t2 time period; or the power required for new energy vehicles that make reservations before t1 and are charging during the t1-t2 time period.

[0070] The first performance data can refer to the performance parameters of the vehicle access point itself, including at least one of the following: maximum allowable charging power, maximum allowable discharging power, and temperature limit.

[0071] The second performance data can refer to the performance parameters of the new energy vehicle itself, including at least one of the following: battery health status, current charge level, and maximum discharge power.

[0072] For example, after obtaining the interaction data and operating status data, the power angle instability risk on the grid side can be detected based on the interaction data and operating status data in the current and future period.

[0073] If a risk of power angle instability in the power grid is identified, further detailed information is needed to make corresponding adjustments. This involves acquiring power demand information from vehicle access points, primary performance data from these access points, secondary performance data from new energy vehicles, and current load data from the power grid. The primary performance data from the vehicle access points can be pre-stored in the memory of the vehicle-to-grid controller and can be retrieved directly from the memory. Power demand information from these access points can be obtained from the vehicle access points themselves or from users' charging reservation information. Secondary performance data from new energy vehicles can be determined based on vehicle information uploaded by users through the charging application during charging or scheduled charging. Current load data from the power grid can be obtained in real-time from the power grid.

[0074] If it is determined that there is no risk of power angle instability in the power grid, then there is no need to adjust the charging and discharging control strategy, and the risk of power angle instability in the power grid can be continuously monitored.

[0075] One method for detecting the existence of power angle instability risk on the grid side in the current and future periods based on interactive data and operational status data can be: inputting interactive data and operational status data into a pre-set power angle instability risk detection model, using the model to detect whether power angle instability risk currently exists on the grid side, and predicting whether power angle instability risk will exist on the grid side in the future period. The power angle instability risk detection model can be a pre-trained machine learning model or a logical reasoning model. For example, if a sudden change in vehicle power is detected based on interactive data, this can easily lead to grid power imbalance and cause power angle oscillations, thus indicating a power angle instability risk. Furthermore, based on the grid side's operational status data, power angle stability parameters such as power angle difference and power angle change rate can be directly calculated. If these parameters exceed the corresponding stability threshold, a power angle instability risk can be identified.

[0076] Step S30: Based on the power demand information, the first performance data, the second performance data, and the current load data, perform charging and discharging control on the vehicle access point.

[0077] Charge and discharge control refers to the process of adjusting the energy flow between new energy vehicles and the power grid based on specific algorithms and rules. Through charge and discharge control, grid stability can be optimized or specific needs can be met. For example, the charging power at the vehicle access point can be reduced during peak electricity consumption periods, and the charging rate at the vehicle access point can be increased during off-peak electricity consumption periods.

[0078] For example, after acquiring the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid, the vehicle-grid interaction controller can optimize the charging and discharging control strategy based on this data and information, aiming to make the transient stability margin value closest to the transient stability margin target value, or to make the static stability margin value closest to the static stability margin target value. Based on the optimized charging and discharging control strategy, the controller can execute the corresponding charging and discharging control operations. For instance, when the grid load is low, the vehicle can be charged first, and the charging power can be dynamically adjusted using an optimization algorithm to avoid overcharging. When the grid load is high, the vehicle's energy storage system can be called upon to discharge, and the discharge power can be dynamically adjusted to ensure stable grid operation. Furthermore, load balancing can be achieved based on the grid's voltage and frequency stability, as well as the vehicle's charging and discharging characteristics, reducing the impact on the grid system's power angle stability.

[0079] In some feasible implementations, the method for generating a charging and discharging control strategy based on the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side may include:

[0080] Based on the second performance data of the energy storage system of new energy vehicles, the maximum discharge power of the new energy vehicles is evaluated; constraints are set based on power demand information, the first performance data of the vehicle access point, and the second performance data of the energy storage system of the new energy vehicles; a stability objective function is set. Then, based on the maximum discharge power of each new energy vehicle, the constraints, and the stability objective function, a charging and discharging control strategy is generated.

[0081] For example, the energy storage system of a new energy vehicle can be its battery; the second performance data can include temperature, SOC (State of Charge, remaining charge), and state of health. Generally, the discharge capacity of a battery is limited at low temperatures, while at high temperatures, although the discharge capacity may be improved, it will affect battery life and safety. By installing a temperature sensor on the battery, the battery temperature can be measured in real time. A relationship model between temperature and discharge capacity can be established. For example, when the temperature is below a set minimum temperature threshold, the maximum discharge power can be positively correlated with the battery capacity, the current state of charge, and the battery's state of health. When the temperature is above a set maximum temperature threshold, to ensure battery safety, it is necessary to reduce the discharge power or take protective measures, such as pausing discharge.

[0082] Simultaneously, based on the battery type and the manufacturer's specified discharge rate limits, the maximum permissible discharge rate at different states of charge (SOC) is determined. For example, for lithium-ion batteries, a higher discharge rate is permissible at higher SOCs, while a lower discharge rate is required at lower SOCs to prevent over-discharge. Therefore, the maximum discharge power can be further adjusted by combining the maximum permissible discharge rate and battery capacity.

[0083] The constraints may include at least one of the following: grid demand constraints, vehicle energy storage system limitation constraints, and battery safety constraints. Among them, grid demand constraints include at least one of the following: power balance constraints, voltage and frequency constraints; vehicle energy storage system limitation constraints include at least one of the following: discharge power constraints, battery SOC constraints; and battery safety constraints include at least one of the following: current constraints and temperature constraints.

[0084] In this context, power balance constraint refers to the requirement that the discharge power at the vehicle's connection point should meet the power demand of the power grid. In practical applications, the power grid dispatch center sends discharge power demand instructions to the vehicle-grid interaction controller based on the grid load and the imbalance in power generation.

[0085] Voltage and frequency constraints refer to ensuring that the voltage and frequency of the power grid remain within permissible ranges during discharge. If changes in discharge power cause the grid voltage or frequency to exceed permissible ranges, it is necessary to adjust the discharge power or take other measures (such as reactive power compensation) to maintain the stable operation of the power grid.

[0086] Discharge power constraint refers to the fact that the discharge power cannot exceed the battery's maximum discharge power.

[0087] Battery SOC constraint refers to the lower limit of SOC set to prevent over-discharge of the battery. During discharge, the battery SOC should be ensured not to fall below the lower limit. When the battery SOC approaches this limit, the discharge power can be gradually reduced or the discharge can be stopped to protect the battery.

[0088] Current constraint refers to the requirement that the battery's discharge current cannot exceed its maximum permissible discharge current to prevent damage from overcurrent. The maximum discharge current can be determined based on the battery's performance parameters and thermal management requirements.

[0089] Temperature constraints refer to the requirement that the battery's operating temperature should remain within a safe range. If the battery temperature exceeds the allowable range, corresponding measures (such as adjusting the discharge power, activating the cooling system, etc.) need to be taken to reduce the temperature and ensure the battery's safe operation.

[0090] The stability objective function can characterize whether the transient stability margin value is closest to the preset transient stability margin target value, or the static stability margin value is closest to the preset static stability margin target value.

[0091] In the aforementioned vehicle-to-grid (V2G) interaction control method, data monitoring of both the V2G and V2G ends is achieved by first acquiring interaction data between the vehicle access point and the grid side, as well as the grid side's operational status data. Then, based on the interaction data and operational status data, when a risk of power angle instability is detected on the grid side, the system acquires the power demand information of the vehicle access point, the vehicle access point's first performance data, the new energy vehicle's second performance data, and the grid side's current load data. Based on these data, the system performs charging and discharging control on the vehicle access point, enabling timely response to the risk of power angle instability in the V2G segment. Thus, the V2G interaction controller avoids direct grid connection for new energy vehicles. Through its data monitoring and real-time response mechanism, the energy interaction between new energy vehicles and the grid can be adjusted in real time, enhancing the grid's ability to cope with emergencies. In cases of increased grid load or a large influx of new energy vehicles, the system can detect these changes promptly and adjust the grid's energy configuration through charging and discharging control, thereby improving the grid's power angle stability and ensuring the safe and stable operation of the power system.

[0092] In one exemplary embodiment, such as Figure 3As shown, before obtaining the power demand information of the vehicle access point and the current load data on the grid side, the vehicle-grid interaction control method further includes steps 302 to 304. Wherein:

[0093] Step 302: Based on the interaction data and operating status data, detect the current transient stability margin value on the power grid side.

[0094] The transient stability margin refers to the ability of a power system to recover to normal operation after experiencing a large disturbance. A higher transient stability margin indicates higher power angle stability on the grid side. It can be determined by analyzing the power angle curve after the disturbance. Large disturbances can include short-circuit faults, generator tripping, etc.

[0095] For example, after obtaining the interaction data between the vehicle access point and the power grid, as well as the operating status data of the power grid side, the vehicle-to-grid interaction controller can use this data to calculate the current transient stability margin value of the power grid side.

[0096] In some feasible implementations, the current transient stability margin value can be calculated using the following formula:

[0097]

[0098] in, The critical value for power angle stability is usually the maximum power angle before the system loses synchronism. It is determined by the grid topology and generator parameters, and can be predetermined through static stability analysis or historical fault data. This represents the actual maximum value of the power angle after the disturbance.

[0099] The actual maximum value of the power angle after disturbance can be determined by generating the power angle curve after disturbance through time-domain simulation or solving the generator rotor motion equation, and then determining the actual maximum value of the power angle after disturbance based on the power angle curve after disturbance.

[0100] Step 304: If the current transient stability margin value is less than the preset transient stability margin target value, it is determined that there is a risk of power angle instability on the grid side.

[0101] The preset transient stability margin target value can refer to the minimum allowable margin threshold set according to the power grid security requirements. When the transient stability margin value on the power grid side is higher than the preset transient stability margin target value, the power grid side may be unable to withstand sudden large disturbances, and the risk of power angle instability is high. Therefore, control measures need to be taken to improve the power angle stability of the power grid side and ensure that the power grid side always has the ability to withstand sudden large disturbances.

[0102] For example, after obtaining the current transient stability margin value on the grid side, the current transient stability margin value can be compared with a preset transient stability margin target value. If the current transient stability margin value is less than the transient stability margin target value, it can be determined that there is a risk of power angle instability on the grid side. If the current transient stability margin value is greater than or equal to the transient stability margin target value, it can be determined that there is no risk of power angle instability on the grid side at present.

[0103] In this embodiment, by monitoring and timely judging the transient stability margin value, instability problems of the power grid can be detected at an early stage, and effective control measures can be taken to prevent power angle instability and ensure the safe and stable operation of the power system.

[0104] In an exemplary embodiment, charging and discharging control of the vehicle access point is performed based on power demand information, first performance data, second performance data, and current load data, in steps S311 to S313. Wherein:

[0105] Step 311: Based on the current load data, detect the current static stability margin value on the grid side.

[0106] It should be noted that power angle instability typically occurs on the order of milliseconds to seconds, requiring ultra-high-speed response for direct control. Furthermore, the analysis and regulation of transient stability margin rely on nonlinear differential equations (such as rotor motion equations), which are complex to solve in real time and require high-performance computing resources. Therefore, the regulation of transient stability margin usually requires relatively complex technologies and equipment, such as fast-response energy storage systems or advanced control systems.

[0107] The static stability margin value refers to the ability of a power system to maintain synchronous operation under small disturbances. It can be determined by analyzing the difference between the maximum transmission power of the grid and the current operating power. For example, if the maximum transmission power of the grid is 100MW and the current operating power is 70MW, then its static stability margin value is 30%.

[0108] Static stability is fundamental to ensuring a system's ability to handle small disturbances during daily operation. Insufficient static stability means that even if the system's initial response is good after a large disturbance, it may fail to maintain long-term stability due to fundamental instability. Therefore, increasing the static stability margin enhances the system's overall robustness, providing a more solid foundation for handling larger-scale disturbances. Furthermore, there is a synergistic effect between static stability and transient stability. Compared to directly adjusting the transient stability margin, the control of the static stability margin can be achieved through conventional scheduling and management methods, requiring less technical expertise and equipment.

[0109] In some feasible implementations, the transient stability margin target value corresponding to the method of indirectly controlling transient stability by adjusting static stability can be higher than that corresponding to the method of directly controlling transient stability. Thus, by appropriately increasing the transient stability margin target value, a certain preventative effect can be achieved, resulting in a control effect comparable to or better than that of directly controlling transient stability.

[0110] For example, after obtaining the current load data, the current operating power of the grid side and the current discharge power of other terminals currently discharging to the grid side can be directly extracted from the current load data. The current discharge power can be added to the base value of the maximum transmission power of the grid side to obtain the current maximum transmission power of the grid side. For a specific grid structure, there is a theoretical maximum transmission power value, which can be obtained through power flow calculation, simulation analysis, and other methods. After obtaining it, it can be used as the base value of the maximum transmission power of the grid side. Furthermore, the current discharge power can be subtracted from the current maximum transmission power of the grid side, and the difference between the two can be divided by the current maximum transmission power of the grid side to obtain the static stability margin value.

[0111] Step 312: Based on the difference between the current transient stability margin value and the preset transient stability margin target value, and the current static stability margin value, detect the static stability margin target value on the grid side.

[0112] Among them, the static stability margin target value can refer to the minimum allowable static stability margin threshold set according to the actual needs of the power grid.

[0113] For example, a correlation between the change in transient stability margin and the change in static stability margin can be established in advance based on historical data or test results. Then, during actual control, the difference between the current transient stability margin value and the preset transient stability margin target value can be calculated first. Then, based on the correlation between the change in transient stability margin and the change in static stability margin, the difference between the current transient stability margin value and the preset transient stability margin target value can be converted into the difference between the current static stability margin value and the preset static stability margin target value. Finally, the difference between the current static stability margin value and the preset static stability margin target value can be added to the current static stability margin value to obtain the static stability margin target value on the grid side.

[0114] Step 313: Based on the power demand information, the first performance data, the second performance data, and the static stability margin target value, perform charge and discharge control on the vehicle access point so that after charge and discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0115] For example, after acquiring the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side, the vehicle-to-grid interaction controller can optimize the charging and discharging control strategy based on this data and information, with the goal of making the static stability margin value closest to the static stability margin target value. Based on the optimized charging and discharging control strategy, the controller then executes the corresponding charging and discharging control operations. Since the static stability margin target value is determined based on the transient stability margin target value and the transient stability margin value, the transient stability margin value can be controlled by adjusting the static stability margin value to be close to the static stability margin target value.

[0116] In this embodiment, by indirectly controlling the transient stability margin through the static stability margin, the control cost can be further reduced and the control efficiency can be improved while ensuring the stability of the power grid.

[0117] In one exemplary embodiment, such as Figure 3 As shown, based on power demand information, first performance data, second performance data, and a static stability margin target value, charge and discharge control is performed on the vehicle access point so that after charge and discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value, including steps 3131 to 3133. Wherein:

[0118] Step 3131, Charge and discharge control steps: Based on the power demand information, the first performance data, the second performance data, and the static stability margin target value, charge and discharge control is performed on the vehicle access point.

[0119] For example, after obtaining the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side, the vehicle-grid interaction controller can optimize the charging and discharging control strategy based on this data and information, with the goal of optimizing the static stability margin value to be closest to the static stability margin target value, and execute the corresponding charging and discharging control operation based on the optimized charging and discharging control strategy.

[0120] Step 3132: Detect the current transient stability margin value of the grid side after charge and discharge control.

[0121] For example, after executing the corresponding charge and discharge control operation according to the optimized charge and discharge control strategy, the optimized interaction data between the vehicle access point and the grid side, as well as the grid side's operating status data, can be obtained. The optimized current transient stability margin value of the grid side can be calculated using the optimized interaction data and operating status data.

[0122] Step 3133: If the current transient stability margin value after charge / discharge control is less than the preset transient stability margin target value, increase the static stability margin target value and return to the charge / discharge control steps until the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0123] For example, after obtaining the optimized current transient stability margin value, the optimized current transient stability margin value is compared with the preset transient stability margin target value. If the optimized current transient stability margin value is still less than the transient stability margin target value, it indicates that the optimization effect has not met expectations. The static stability margin target value can then be increased according to a preset increase range. A new charging and discharging control strategy is then formulated based on the increased static stability margin target value, and the corresponding charging and discharging control operations are executed based on the newly formulated charging and discharging control strategy until the optimized current transient stability margin value is greater than or equal to the transient stability margin target value. If the optimized current transient stability margin value is greater than or equal to the transient stability margin target value, it indicates that the optimization effect has met expectations, and the stability of the grid side can be continuously monitored.

[0124] The preset increase range can be determined based on actual conditions or test results. For example, the preset increase range can be an increase percentage. If the static stability margin target value is 50% and the increase percentage is 10%, then the static stability margin target value after the increase adjustment can be 55%. The preset increase range can also be a fixed value. If the static stability margin target value is 50% and the increase percentage is 10%, then the static stability margin target value after the increase adjustment can be 60%.

[0125] In this embodiment, by iteratively adjusting the target value of the static stability margin and continuously optimizing the charging and discharging control strategy, the transient stability of the power grid can be gradually improved. While ensuring the maintenance of power grid stability, the impact on user charging can be effectively reduced.

[0126] In one exemplary embodiment, such as Figure 3 As shown, based on power demand information, first performance data, second performance data, and current load data, charging and discharging control is performed on the vehicle access point, including steps 321 to 322. Wherein:

[0127] Step 302: Based on the power demand information and the second performance data, prioritize the charging of new energy vehicles.

[0128] Charging priority refers to the order in which charging resources are allocated to new energy vehicles that have already been connected or have been scheduled to be connected.

[0129] For example, charging priority can be ranked based on power demand information, secondary performance data of new energy vehicles, and preset ranking rules, to determine the charging priority of currently connected or scheduled-to-connect new energy vehicles. The charging power of the vehicle access point can be positively correlated with the charging priority ranking.

[0130] Power demand information can be used to assess the urgency of charging needs. For example, the closer a user expects to pick up their vehicle to the current time, the higher their charging demand and the higher their charging priority.

[0131] The second performance data of new energy vehicles can be used to assess the necessity of charging demand. For example, vehicles with lower remaining battery power should be given higher priority to ensure that users can use the vehicle in an emergency. However, as charging progresses and the remaining battery power increases, its charging priority can also be reduced. In this way, when the power supply is insufficient, vehicles with lower remaining current have higher priority and can be allocated resources first to ensure that vehicles with lower remaining current are charged with higher power. However, when their remaining current rises to a certain threshold, their priority decreases and their charging power can be reduced to allocate more power to other vehicles with higher priority.

[0132] In some feasible implementations, the urgency coefficient of each new energy vehicle can be detected based on power demand information, and the necessity coefficient of each new energy vehicle can be detected based on the second performance data of the new energy vehicles. Then, the urgency coefficient and the necessity coefficient are weighted and fused according to the first weight value corresponding to the urgency coefficient and the second weight value corresponding to the necessity coefficient to obtain a priority evaluation value. The new energy vehicles are then sorted in descending order of priority evaluation value. The first weight value is lower than the second weight value.

[0133] Step 304: Based on the charging priority, first performance data, second performance data and current load data of each new energy vehicle, perform charging and discharging control on the vehicle access point.

[0134] For example, the vehicle-to-grid interaction controller can optimize the charging and discharging control strategy based on charging priority ranking, first performance data, second performance data, and current load data, with the aim of optimizing the transient stability margin value to be closest to the transient stability margin target value, or with the aim of optimizing the static stability margin value to be closest to the static stability margin target value, and execute the corresponding charging and discharging control operation based on the optimized charging and discharging control strategy.

[0135] In this embodiment, by prioritizing the charging of new energy vehicles, the user's vehicle needs can be met as much as possible while maintaining the stability of the power grid.

[0136] In an exemplary embodiment, after acquiring the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side, the vehicle-to-grid interaction control method further includes:

[0137] Based on interactive data and operational status data, and predicting that there is a risk of power angle instability on the grid side at a target future time, the power demand forecast curve, the first performance data of the vehicle access point, the second performance data of new energy vehicles, and the load forecast curve on the grid side are obtained.

[0138] The first adjustment period is located from the load forecast curve. The first adjustment period is before the target future time, and the load value of the first adjustment period is less than the preset load threshold.

[0139] Based on the power demand forecast curve, the first performance data, the second performance data, and the load forecast curve, detect the first power adjustment data corresponding to the first adjustment period and the second power adjustment data corresponding to the target future time.

[0140] When the real-time time is in the first adjustment period, the charging power of the vehicle access point is increased based on the first power adjustment data.

[0141] When the real-time time reaches the target future time, the charging power of the vehicle access point is reduced based on the second power adjustment data.

[0142] The power demand forecast curve refers to the prediction of the charging or discharging demand of new energy vehicles over a future period. It can be generated based on historical data, user behavior patterns, and real-time monitoring data. Power demand forecast curves typically require a large amount of historical and user behavior data, and are predicted using model algorithms. This places high demands on data storage and computing power, and is usually generated in the cloud before being sent to the vehicle-to-grid (V2G) controller. In other words, the V2G controller can send real-time monitoring data and power demand forecast requests to the cloud. The cloud responds to these requests by predicting the charging and discharging demand over a future period based on the received real-time monitoring data, as well as the historical and user behavior data stored in the cloud, generating a power demand forecast curve, and then returning the generated curve to the V2G controller.

[0143] A load forecast curve refers to a trend of load changes over the next 24 hours generated using a predictive model based on historical load data and real-time load conditions. Load forecast curves typically require a large amount of historical data and are generated through model algorithms, placing high demands on data storage and computing power. They are usually generated in the cloud and then sent to the vehicle-to-grid (V2G) controller. In other words, the V2G controller can send real-time load data and load forecast requests to the cloud. The cloud responds to the load forecast request by predicting the load change trend over a future period based on the received real-time load data and historical load data stored in the cloud, generating a load forecast curve, and then returning the generated load forecast curve to the V2G controller.

[0144] The first adjustment period can refer to the period of low grid load before the target future time when there is a risk of power angle instability. If the risk of power angle instability is predicted at the target future time, the adjustment power can be increased in advance to reserve a buffer space before the peak load and reduce the risk of power angle instability.

[0145] Power regulation data can refer to either the adjusted power value or the target power value. The power regulation value characterizes the magnitude of power regulation. The target power value refers to the desired power value achieved through adjustment.

[0146] For example, after obtaining the interaction data and operating status data, it is possible to predict whether there is a risk of power angle instability on the power grid side in the future based on the interaction data and operating status data.

[0147] If a power angle instability risk is predicted for the power grid side within a certain period of time, the target future moment of the power angle instability risk is located. Through interaction with the cloud, power demand forecast curves and load forecast curves are obtained, along with first performance data for vehicle access points and second performance data for new energy vehicles. Then, based on a preset load threshold, a first adjustment period is determined from the load forecast curve, where the load value is less than the preset load threshold before the target future moment and the duration exceeds a preset adjustment duration. Next, based on the power demand forecast curve, the first performance data, the second performance data, and the load forecast curve, the charging and discharging power of the vehicle access points is planned for the first adjustment period and after the target future moment, determining the first power adjustment data for the first adjustment period and the second power adjustment data for the target future moment. Then, when the real-time is detected to be within the first adjustment period, the charging power of the vehicle access points is increased according to the first power adjustment data; when the real-time reaches the target future moment, the charging power of the vehicle access points is immediately decreased according to the second power adjustment data.

[0148] In this embodiment, by adjusting the charging power in advance during peak load periods, the risk of grid overload can be effectively avoided, thereby reducing the risk of grid instability at the target future time and improving the reliability and stability of the grid.

[0149] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0150] Based on the same inventive concept, this application also provides a vehicle-to-grid interaction control device for implementing the above-mentioned vehicle-to-grid interaction control method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more vehicle-to-grid interaction control device embodiments provided below can be found in the limitations of the vehicle-to-grid interaction control method described above, and will not be repeated here.

[0151] In one exemplary embodiment, such as Figure 4 As shown, a vehicle-to-grid (V2G) interactive control device is provided, comprising: an acquisition module 402, a detection module 404, and a charging / discharging control module 406, wherein:

[0152] The acquisition module 402 is used to acquire the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side;

[0153] The detection module 404 is used to obtain power demand information of the vehicle access point, first performance data of the vehicle access point, second performance data of the new energy vehicle, and current load data of the grid side when a risk of power angle instability is detected on the grid side based on interactive data and operating status data.

[0154] The charging and discharging control module 406 is used to control the charging and discharging of the vehicle access point based on power demand information, first performance data, second performance data and current load data.

[0155] In an exemplary embodiment, the vehicle-to-grid (V2G) interaction control device further includes a determination module, which, before acquiring the power demand information of the vehicle access point and the current load data on the grid side, is configured to:

[0156] Based on interactive data and operational status data, the current transient stability margin value on the power grid side is detected;

[0157] If the current transient stability margin is less than the preset transient stability margin target value, it is determined that there is a risk of power angle instability on the grid side.

[0158] In one exemplary embodiment, the charge / discharge control module 406 is further configured to:

[0159] Based on the current load data, detect the current static stability margin value on the grid side;

[0160] Based on the difference between the current transient stability margin value and the preset transient stability margin target value, and the current static stability margin value, the static stability margin target value on the grid side is detected.

[0161] Based on power demand information, first performance data, second performance data, and static stability margin target value, charge and discharge control is performed on the vehicle access point so that after charge and discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0162] In one exemplary embodiment, the charge / discharge control module 406 is further configured to:

[0163] Charge and discharge control steps: Based on power demand information, first performance data, second performance data, and static stability margin target value, charge and discharge control is performed on the vehicle access point;

[0164] Detect the current transient stability margin value of the grid side after charge and discharge control;

[0165] If the current transient stability margin value after charge / discharge control is less than the preset transient stability margin target value, increase the static stability margin target value and return to the charge / discharge control steps until the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

[0166] In one exemplary embodiment, the charge / discharge control module 406 is further configured to:

[0167] Based on power demand information and second performance data, the charging priority of new energy vehicles is ranked.

[0168] Based on the charging priority, first performance data, second performance data, and current load data of each new energy vehicle, the charging and discharging control of the vehicle access point is performed.

[0169] In one exemplary embodiment, the vehicle-to-grid (V2G) interaction control device further includes a power regulation module; after acquiring the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side, the power regulation module is used to:

[0170] Based on interactive data and operational status data, and predicting that there is a risk of power angle instability on the grid side at a target future time, the power demand forecast curve, the first performance data of the vehicle access point, the second performance data of new energy vehicles, and the load forecast curve on the grid side are obtained.

[0171] The first adjustment period is located from the load forecast curve. The first adjustment period is before the target future time, and the load value of the first adjustment period is less than the preset load threshold.

[0172] Based on the power demand forecast curve, the first performance data, the second performance data, and the load forecast curve, detect the first power adjustment data corresponding to the first adjustment period and the second power adjustment data corresponding to the target future time.

[0173] When the real-time time is in the first adjustment period, the charging power of the vehicle access point is increased based on the first power adjustment data.

[0174] When the real-time time reaches the target future time, the charging power of the vehicle access point is reduced based on the second power adjustment data.

[0175] Each module in the aforementioned vehicle-to-grid (V2G) interactive control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0176] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a vehicle-to-everything (V2X) interactive control method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0177] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0178] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0179] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0180] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0181] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0182] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0183] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0184] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A vehicle-to-grid (V2G) interactive control method, characterized in that, The method is applied to a vehicle-to-grid (V2G) interaction controller, which communicates with both the vehicle access point and the power grid side; the method includes: Acquire the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side; If, based on the interaction data and the operating status data, a risk of power angle instability is detected on the power grid side, the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the power grid side are obtained. Based on the power demand information, the first performance data, the second performance data, and the current load data, the vehicle access point is charged and discharged.

2. The method according to claim 1, characterized in that, Before acquiring the power demand information of the vehicle access point and the current load data of the power grid side, the method further includes: Based on the interaction data and the operating status data, the current transient stability margin value of the power grid side is detected; If the current transient stability margin value is less than the preset transient stability margin target value, it is determined that there is a risk of power angle instability on the power grid side.

3. The method according to claim 2, characterized in that, The step of controlling the charging and discharging of the vehicle access point based on the power demand information, the first performance data, the second performance data, and the current load data includes: Based on the current load data, detect the current static stability margin value on the grid side; Based on the difference between the current transient stability margin value and the preset transient stability margin target value, and the current static stability margin value, the static stability margin target value on the grid side is detected. Based on the power demand information, the first performance data, the second performance data, and the static stability margin target value, the vehicle access point is charged and discharged to ensure that, after the charge and discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

4. The method according to claim 3, characterized in that, The step of performing charge / discharge control on the vehicle access point based on the power demand information, the first performance data, the second performance data, and the static stability margin target value, so that after the charge / discharge control, the current transient stability margin value on the grid side exceeds the preset transient stability margin target value, includes: Charging and discharging control steps: Based on the power demand information, the first performance data, the second performance data, and the static stability margin target value, charge and discharge control is performed on the vehicle access point; The current transient stability margin value of the power grid side after charge and discharge control is detected; If the current transient stability margin value after charge / discharge control is less than the preset transient stability margin target value, the static stability margin target value is increased, and the charge / discharge control steps are returned to be executed until the current transient stability margin value on the grid side exceeds the preset transient stability margin target value.

5. The method according to claim 1, characterized in that, The step of controlling the charging and discharging of the vehicle access point based on the power demand information, the first performance data, the second performance data, and the current load data further includes: Based on the power demand information and the second performance data, the charging priority of new energy vehicles is ranked. Based on the charging priority of each new energy vehicle, the first performance data, the second performance data, and the current load data, the vehicle access point is charged and discharged.

6. The method according to any one of claims 1 to 5, characterized in that, After acquiring the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side, the method further includes: Based on the interaction data and the operating status data, if it is predicted that the power grid side has a risk of power angle instability at a target future time, the power demand prediction curve, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the load prediction curve of the power grid side are obtained. The first adjustment period is located from the load forecast curve. The first adjustment period is before the target future time, and the load value of the first adjustment period is less than a preset load threshold. Based on the power demand forecast curve, the first performance data, the second performance data, and the load forecast curve, detect the first power adjustment data corresponding to the first adjustment period and the second power adjustment data corresponding to the target future time. When the real-time period is within the first adjustment period, the charging power of the vehicle access point is increased based on the first power adjustment data. When the real-time time reaches the target future time, the charging power of the vehicle access point is reduced based on the second power adjustment data.

7. A vehicle-to-grid (V2G) interactive control device, characterized in that, An application is made in a vehicle-to-grid (V2G) interaction controller, which communicates with both the vehicle access point and the power grid side; the device includes: The acquisition module is used to acquire the interaction data between the vehicle access point and the power grid side, as well as the operating status data of the power grid side; The detection module is used to obtain the power demand information of the vehicle access point, the first performance data of the vehicle access point, the second performance data of the new energy vehicle, and the current load data of the grid side when the risk of power angle instability is detected on the grid side based on the interaction data and the operating status data. The charging and discharging control module is used to control the charging and discharging of the vehicle access point based on the power demand information, the first performance data, the second performance data, and the current load data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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