A method and system for dynamic control of safety margin in power grid operation and dispatching

Abstract

This invention discloses a method and system for dynamic control of safety margin in power grid operation scheduling, belonging to the field of power grid control, and particularly relating to power balance regulation. The method includes: continuously collecting real-time power data of a target power grid, and determining whether there is an operating point deviation based on the real-time power data; wherein the real-time power data includes active power, reactive power, and voltage amplitude; if an operating point deviation is determined, acquiring equipment switching records and load flow data of the target power grid to determine the safety boundary of the target power grid; evaluating the current safety margin of the target power grid based on the safety boundary; if the current safety margin does not meet preset conditions, generating power grid operation control commands based on pre-acquired power transmission distribution data to achieve safety margin regulation. This application can improve the stability of power grid operation through precise and efficient dynamic control of safety margin.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid control, and in particular to a safety margin dynamic regulation method and system for power grid operation scheduling. BACKGROUND

[0002] During the operation of the power grid, due to frequent scheduling operations such as load fluctuation and device switching, the system operating point is prone to deviation, resulting in dynamic reconstruction of the safety boundary, and the original safety margin evaluation benchmark is invalid. If dynamic regulation of the safety margin is not performed, the power grid may not be able to adapt to changes in the operating state in real time, increasing the risk of cross-limitation of the section, voltage instability, and the like, and therefore it is necessary to real-time adjust the safety boundary and the early warning threshold through dynamic regulation means to ensure the safety and stability of the power grid scheduling operation.

[0003] At present, the existing technology relies on a pre-set static safety boundary or an early warning mechanism based on a fixed threshold when regulating the safety margin, and the regulation strategy is difficult to adapt to the boundary reconstruction problem caused by the deviation of the operating point. This leads to a serious disconnection between the evaluation benchmark and the actual operating condition, and false positives or false negatives often occur; at the same time, due to the lack of accurate prediction of the trend of the operating state and the consideration of the sensitivity difference of the regulation device, the regulation instructions generated by the existing method are often insufficient in pertinence and unclear in priority, making the regulation process slow and inefficient, and difficult to support the fast and accurate scheduling control requirements of the power grid in a complex operating environment. SUMMARY

[0004] The present application provides a safety margin dynamic regulation method, device, equipment and medium for power grid operation scheduling, which can improve the stability of power grid operation through accurate and efficient safety margin dynamic regulation.

[0005] In a first aspect, the present application embodiment provides a safety margin dynamic regulation method for power grid operation scheduling, comprising:

[0006] Continuously collecting real-time power data of the target power grid, and determining whether there is an operating point deviation according to the real-time power data; wherein the real-time power data includes active power, reactive power and voltage amplitude;

[0007] If it is determined that there is an operating point deviation, the device switching record and load flow data of the target power grid are obtained, and the safety boundary of the target power grid is determined according to the device switching record and load flow data;

[0008] According to the safety boundary, a current safety margin of the target power grid is evaluated, and if the current safety margin does not meet a preset condition, a power transmission distribution data pre-acquired is used to generate a power grid operation control instruction to realize control of the safety margin through the power grid operation control instruction; wherein the power grid operation control instruction determines a control priority according to a sensitivity coefficient of each control device in the target power grid.

[0009] The embodiment of the present application continuously collects real-time power data of the target power grid to provide real-time and accurate basic information for subsequent judgment of whether the power grid operating point is deviated, ensures dynamic monitoring of the power grid operating state, avoids misjudgment or missed judgment of the abnormal state of the power grid due to data lag, and timely discovers the abnormal trend of the power grid operation by judging whether the operating point is deviated, provides a trigger condition for subsequent start of the safety boundary determination and safety margin control process, ensures that the control is started only when necessary, and avoids unnecessary intervention; the safety boundary of the target power grid is determined according to the device switching record and load flow direction data, the current safe operation "red line" of the power grid is determined, a standard and basis for subsequent evaluation of the safety margin are provided, the safety margin evaluation result is targeted and accurate; when the safety margin does not meet the preset condition, the power grid operation control instruction is generated according to the pre-acquired power transmission distribution data, the control instruction is targeted at the weak link of the power grid power transmission, accurate adjustment of the power grid operating state is realized, the safety margin is restored to a required level, wherein the control priority is determined according to the sensitivity coefficient, the device with the most significant improvement effect on the safety margin is preferentially selected for control, the control efficiency is improved, unnecessary device adjustment is reduced, the control cost and disturbance to the power grid operation are reduced, and the power grid is ensured to restore the safe and stable operating state in the shortest time. Compared with the prior art, the present application can improve the stability of the power grid operation through accurate and efficient dynamic control of the safety margin.

[0010] Further, the judgment of whether the operating point is deviated according to the real-time power data is specifically:

[0011] The active power sequence and the reactive power sequence are extracted from the real-time power data through a preset time window, and the active power deviation value and the reactive power deviation value of each sampling point are calculated according to the active power sequence, the reactive power sequence and the preset power reference data, to obtain the active power deviation sequence and the reactive power deviation sequence; wherein the power reference data includes the active power reference value and the reactive power reference value.

[0012] The voltage amplitude in the real-time power data is extracted, and the voltage change rate between each adjacent sampling point is calculated according to the voltage amplitude to obtain the voltage change rate sequence.

[0013] If there is a deviation value greater than the preset power deviation threshold in the active power deviation sequence or the reactive power deviation sequence, and there is a voltage change rate greater than the preset voltage change rate threshold in the voltage change rate sequence, it is determined that the target power grid has an operating point deviation.

[0014] The preset time window is used to extract the active power sequence and the reactive power sequence from the real-time power data, so as to provide a stable and reliable data basis for subsequent calculation of the power deviation value, and avoid misjudgment of the power change trend caused by a single instantaneous abnormal data. The active power deviation sequence and the reactive power deviation sequence are obtained based on the power reference data, so as to quantify the difference degree of the current active power and the reactive power from the normal standard value. The voltage change rate sequence is obtained by calculating the voltage change rate between each adjacent sampling point, so as to sensitively capture the rapid fluctuation of the voltage. The double-threshold judgment mechanism is used to avoid the limitation of single condition judgment, improve the accuracy and reliability of the operating point deviation judgment, and ensure that only when the power grid has a substantial and continuous abnormal operation trend, the operating point deviation is determined, so as to prevent the mis-triggering of the subsequent regulation process.

[0015] Further, the safety boundary of the target power grid is determined according to the device switching record and the load flow direction data, specifically:

[0016] The operation development of the target power grid is predicted according to the real-time power data, and an operation development prediction set is obtained.

[0017] The device switching record and the operation development prediction set are time-aligned through a preset time stamp, an extended trajectory data set is obtained, and a power flow distribution data is generated through a preset power flow tracking algorithm according to the extended trajectory data set and the load flow direction data.

[0018] The safety boundary of the target power grid is determined according to the power flow distribution data.

[0019] The embodiment of the present application can extend the analysis of the power grid state from "current" to "future" by predicting the operation development to obtain an operation development prediction set, avoid the limitation caused by determining the safety boundary only according to the current data, make the determination of the safety boundary more forward-looking and dynamically adaptive, obtain the expected operation trajectory of the power grid at different time points in the future under a specific device configuration by obtaining the extended trajectory data set, provide comprehensive and related input data for subsequent power flow distribution calculation, ensure that the power flow distribution calculation result can accurately reflect the influence of device switching on the future power grid operation, and generate the power flow distribution data to clearly master the change rule and key weak link of the future power grid power flow, provide direct power flow level basis for subsequent determination of the safety boundary, and determine the safety boundary of the target power grid according to the power flow distribution data, so that the safety boundary is more suitable for the actual operation condition of the power grid, and provide accurate and feasible standard for subsequent safety margin evaluation.

[0020] Further, the operation development of the target power grid is predicted according to the real-time power data to obtain an operation development prediction set, specifically:

[0021] A current operation point trajectory is generated according to the real-time power data.

[0022] A plurality of historical operation point trajectory segments are obtained from a preset database, and a distance value of the current operation point trajectory and each historical operation point trajectory segment is calculated in sequence by a preset dynamic time warping algorithm.

[0023] The historical operation point trajectory segments are filtered according to a preset distance threshold and the distance value to obtain a similar trajectory group.

[0024] The subsequent development paths of each historical operation point trajectory segment in the similar trajectory group are obtained from the database to obtain a prediction path group, and a weighted average of each subsequent development path in the prediction path group is obtained to obtain an operation development prediction set.

[0025] The embodiment of the present application generates a current operation point trajectory to provide a complete current state sample for subsequent comparison with historical operation trajectories, ensures that the comparison and analysis can be based on continuous state changes rather than instantaneous states, improves the accuracy of comparison, filters historical trajectories similar to the change rule of the current operation state from historical data to provide referenceable historical cases for predicting future operation development, obtains subsequent development paths to form a prediction path group, that is, collects the future development results of a plurality of "similar historical cases", and performs a weighted average on each subsequent development path to integrate the information of a plurality of historical cases, avoid the influence of the contingency of a single historical case on the prediction result, and obtain a more objective and accurate operation development prediction set.

[0026] Further, the safety boundary of the target power grid is determined according to the power flow distribution data, specifically:

[0027] According to the power flow distribution data, the active power value and the reactive power value of each key section of the target power grid are extracted to obtain a power combination point set, and the power value set is screened according to a preset voltage stability constraint and a thermal stability limit to obtain a safe power combination point set.

[0028] According to the safe power combination point set, a safety boundary contour line is generated, wherein the horizontal and vertical coordinate values of each point on the safety boundary contour line are safety boundary position coordinates.

[0029] The power combination point set is formed by combining the active power and the reactive power of each key section into a power combination point, and the complex power grid power flow distribution is simplified into a power state set of multiple key sections, which provides a clear and focused analysis object for subsequent screening of safe power states, avoids low efficiency caused by comprehensive analysis of all nodes and lines, and screens the power combination point set according to the preset voltage stability constraint and the thermal stability limit, so as to eliminate the power combination points whose active power exceeds the thermal stability limit or whose reactive power does not meet the voltage stability constraint, obtain the safe power combination point set, and provide safe state samples for subsequent generation of the safety boundary contour line. The safety boundary contour line is generated to quantify the position of the safety boundary, so that the power grid operator can clearly and intuitively determine whether the power state of the current key section is within the safe range, and provide an explicit and quantifiable boundary standard for subsequent safety margin evaluation.

[0030] Further, the current safety margin of the target power grid is evaluated according to the safety boundary, specifically:

[0031] The current active power and the current reactive power of the target power grid are obtained, and the active power and the reactive power are mapped to a current operating point.

[0032] The minimum Euclidean distance from the current operating point to the safety boundary contour line is calculated, and the minimum Euclidean distance is determined as the current safety margin.

[0033] If the current safety margin is less than a preset safety margin threshold, it is determined that the safety margin of the target power grid does not meet the preset condition.

[0034] The current active power and reactive power in the embodiment of the application are core parameters reflecting the current operation state of the power grid, especially the current active power and reactive power of the key section, which directly determines the current operation state of the key section. Mapping the two parameters to a current operating point (a point in a two-dimensional coordinate system with active power as the horizontal coordinate and reactive power as the vertical coordinate) can convert the abstract power grid operation state into an intuitive and locatable geometric point, providing a specific analysis object for subsequent calculation of the distance from the point to the safety boundary, enabling the evaluation of safety margin to be converted from an abstract concept to a quantifiable geometric calculation problem. By determining the minimum Euclidean distance as the current safety margin, the current safety level of the power grid can be quantified, avoiding the ambiguity of judging the safety state by qualitative description only, and providing a clear quantitative basis for subsequent judgment of whether regulation is needed.

[0035] Further, according to the pre-acquired power transmission distribution data, a power grid operation regulation instruction is generated to realize regulation of the safety margin through the power grid operation regulation instruction, specifically:

[0036] According to the power transmission distribution data, a key power transmission section set is obtained by identifying key power transmission sections that have an impact on the safety margin exceeding a preset impact threshold, and the power margin of each key power transmission section in the key power transmission section set is calculated in turn.

[0037] According to the rate margin and the safety boundary, the required active power adjustment amount and reactive power adjustment amount are calculated, and the power grid operation regulation instruction is generated according to the active power adjustment amount and the reactive power adjustment amount.

[0038] The embodiment of the application focuses on the key regulation by identifying and forming a key power transmission section set, avoids applying force evenly to all sections, improves the pertinence and efficiency of regulation, ensures that regulation resources are prioritized for improving the sections that have the greatest impact on the safety margin, and quantifies the safety state differences of each key section by calculating the power margin of the key power transmission section, providing specific data support for subsequent calculation of the required adjustment amount and avoiding blind adjustment. By calculating the power adjustment amount and the reactive power adjustment amount, the regulation instruction provides a specific "adjustment target", ensuring that the regulation instruction has a clear quantitative index and avoiding correct regulation direction but insufficient or excessive adjustment.

[0039] Further, according to the active power adjustment amount and the reactive power adjustment amount, a power grid operation regulation instruction is generated, specifically:

[0040] The sensitivity coefficients of each regulation device in the target power grid to the safety margin are calculated by a preset sensitivity analysis algorithm, wherein the regulation devices include generators, reactive power compensation devices and transformers.

[0041] According to the sensitivity coefficient, a regulation priority is determined, and a power grid operation regulation instruction is generated according to the regulation priority; wherein the power grid operation regulation instruction comprises at least one of adjusting generator active power, adjusting generator reactive power, switching in a capacitor bank or switching in a reactor.

[0042] The embodiment of the present application can clearly grasp the regulation efficiency of each device on the safety margin by calculating the sensitivity coefficient of each regulation device, and provides a quantitative basis for subsequent determination of the regulation priority, so as to avoid the selection of a device with low regulation efficiency, which leads to poor regulation effect and high cost; the priority is determined according to the sensitivity coefficient, that is, the device with a large sensitivity coefficient is preferentially selected for regulation, and such a device can achieve greater safety margin improvement with smaller adjustment amount, so that the power grid safety state can be improved in the shortest time and at the lowest cost.

[0043] Further, it further comprises:

[0044] The target power grid twin model is pre-constructed, the power grid operation regulation instruction is simulated to obtain a simulated power flow distribution, and the safety margin after regulation is predicted according to the simulated power flow distribution to obtain a predicted safety margin;

[0045] If the predicted safety margin still does not meet the preset condition, the regulation instruction is re-generated until the predicted safety margin meets the requirement, and the finally determined regulation instruction is issued to the target power grid to control the device to execute.

[0046] The power grid twin model is constructed based on digital twin technology, and is a digital model highly consistent with the physical structure and operation characteristics of the target power grid, which can accurately simulate the operation state change of the power grid under different operations, simulate the execution of the regulation instruction, and predict the change of the power flow distribution of the power grid after the execution of the regulation instruction without actually operating the physical device; the safety margin after regulation is predicted based on the simulated power flow distribution to determine whether the instruction meets the requirement; through a cyclic optimization mechanism, the instruction is re-generated until the predicted safety margin meets the requirement, to ensure the effectiveness of the instruction; finally, the final instruction is issued to control the device to execute, to complete the regulation closed loop.

[0047] In a second aspect, the embodiment of the present application provides a safety margin dynamic regulation system for power grid operation scheduling, comprising an operating point offset judgment module, a safety boundary determination module and a safety margin regulation module, wherein,

[0048] The operating point offset judgment module is used to continuously collect real-time power data of a target power grid, and to judge whether there is an operating point offset according to the real-time power data; wherein the real-time power data comprises active power, reactive power and voltage amplitude;

[0049] The safety boundary determination module is configured to, if it is determined that there is a running point deviation, acquire device switching record and load flow direction data of the target power grid, and determine the safety boundary of the target power grid according to the device switching record and the load flow direction data.

[0050] The safety margin regulation module is configured to, according to the safety boundary, evaluate the current safety margin of the target power grid, and if the current safety margin does not meet a preset condition, generate a power grid operation regulation instruction according to the pre-acquired power transmission distribution data, so as to realize regulation of the safety margin through the power grid operation regulation instruction; wherein the power grid operation regulation instruction determines a regulation priority according to a sensitivity coefficient of each regulation device in the target power grid to the safety margin.

[0051] The running point deviation judgment module of the embodiment of the present application continuously acquires real-time power data of the target power grid, provides real-time and accurate basic information for subsequent judgment of whether the power grid running point deviates, ensures dynamic monitoring of the power grid running state, avoids misjudgment or missed judgment of the abnormal state of the power grid due to data lag, and timely discovers the abnormal trend of the power grid running by judging whether there is a running point deviation, provides a triggering condition for subsequent starting of the safety boundary determination and safety margin regulation processes, ensures that regulation is started only when necessary, and avoids unnecessary intervention; the safety boundary determination module determines the safety boundary of the target power grid according to the device switching record and the load flow direction data, clearly defines the “red line” of the current safe operation of the power grid, provides a standard and basis for subsequent evaluation of the safety margin, and makes the safety margin evaluation result targeted and accurate; when the safety margin does not meet the preset condition, the safety margin regulation module generates a power grid operation regulation instruction according to the pre-acquired power transmission distribution data, ensures that the regulation instruction is targeted at weak links of power transmission of the power grid, realizes accurate adjustment of the power grid running state, and restores the safety margin to a level that meets the requirements, wherein the regulation priority is determined according to the sensitivity coefficient, the device that has the most significant improvement effect on the safety margin can be selected for regulation preferentially, the regulation efficiency is improved, unnecessary device adjustment is reduced, the regulation cost and disturbance to the power grid running are reduced, and the power grid is ensured to restore the safe and stable running state in the shortest time.

[0052] The above description is only a summary of the technical scheme of the embodiment of the present application, in order to more clearly understand the technical means of the embodiment of the present application, which can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation manner of the present application is described below. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 A safety margin dynamic regulation method for power grid operation scheduling provided by the embodiment of the present application is shown in the figure;

[0054] Figure 2 This is a structural diagram of a dynamic control system for safety margin in power grid operation scheduling, provided as an embodiment of the present invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Example 1:

[0057] like Figure 1 As shown in the figure, a collaborative control method for an energy storage system for power grid frequency regulation provided by an embodiment of the present invention includes the following steps:

[0058] S101, continuously collect real-time power data of the target power grid, and determine whether there is an operating point deviation based on the real-time power data; wherein, the real-time power data includes active power, reactive power and voltage amplitude;

[0059] In this embodiment, determining whether there is an operating point offset based on the real-time power data specifically involves: extracting active power and reactive power sequences from the real-time power data through a preset time window; calculating the active power deviation and reactive power deviation values ​​for each sampling point based on the active power sequence, reactive power sequence, and preset power reference data to obtain an active power deviation sequence and a reactive power deviation sequence; wherein the power reference data includes active power reference values ​​and reactive power reference values; extracting the voltage amplitude from the real-time power data; and calculating the voltage change rate between each adjacent sampling point based on the voltage amplitude to obtain a voltage change rate sequence; if there is a deviation value in the active power deviation sequence or reactive power deviation sequence that is greater than a preset power deviation threshold, and there is a voltage change rate in the voltage change rate sequence that is greater than a preset voltage change rate threshold, then it is determined that the target power grid has an operating point offset.

[0060] Preferably, the real-time power data needs to be pre-processed as follows: four types of electrical measurement data of active power, reactive power, voltage amplitude and phase angle difference are synchronously collected from the mutual inductor and measurement terminal of the key section of the power grid, the four types of electrical measurement data are time-aligned according to the sampling time stamp, and the aligned electrical measurement data is stored in a buffer for temporary storage; when the number of data points accumulated in the buffer reaches a preset processing batch size, the data is subjected to outlier detection and filtering processing, the active power and the reactive power are converted into a per-unit form, the voltage amplitude is normalized to a rated voltage reference, and the phase angle difference data is converted into a radian system, and a filtered standardized power operation data set is obtained through data format unification and time stamp indexing.

[0061] In a specific embodiment, the active power and reactive power data sequences in a continuous sampling period are extracted from the standardized power operation data set, a two-dimensional power space is established with the power values under the reference working condition as the coordinate origin, and the power data points at each sampling time are connected in time sequence to form a moving trajectory of operating points; according to the coordinate values of each sampling point on the moving trajectory of operating points, the difference between the active power at the current time and the active power under the reference working condition is calculated to obtain the active power deviation, the difference between the reactive power at the current time and the reactive power under the reference working condition is calculated to obtain the reactive power deviation, and the voltage amplitude sequence at the corresponding time is extracted from the data set, and the voltage change rate value is obtained by dividing the difference between the voltage amplitudes at adjacent times by the sampling time interval; the active power deviation and the reactive power deviation are compared with the preset power offset critical value respectively, if the absolute value of any deviation exceeds the corresponding critical value, an offset identification signal is generated and the out-of-limit time is recorded, and an operating point offset alarm process is activated, the alarm process includes sending an offset alarm information to a monitoring terminal; according to the out-of-limit time, the dispatching operation log is queried, the dispatching operation records within a preset time length before and after the out-of-limit time are extracted, if the time difference between the execution time of the operation record and the out-of-limit time is less than a preset threshold, the offset event is associated with the corresponding dispatching operation, the offset trigger source is confirmed, and the trajectory offset identification is completed.

[0062] In a specific embodiment, the establishment process of the two-dimensional power space is to map the operating state of the power system into a plane coordinate system with active power as the horizontal axis and reactive power as the vertical axis.

[0063] It should be noted that the calculation of the power deviation uses the direct difference method, i.e. the power measurement value at the current time is subtracted by the corresponding power value under the reference working condition.

[0064] For example, if the active power in the reference operating condition is 1000 MW and the measured value at the current time is 1150 MW, the active power deviation is 150 MW. This deviation intuitively reflects the degree of deviation of the system operating point from the steady state, and the greater the deviation, the more severe the change in the system state. The calculation method of the reactive power deviation is the same, and the two deviations together determine the position of the operating point in the two-dimensional power space.

[0065] Preferably, the calculation process of the voltage rate of change involves differential processing of the voltage amplitude time series.

[0066] In a specific embodiment, first, the continuous voltage amplitude sequence is extracted from the standardized power operation data set, and then the voltage difference between adjacent sampling times is calculated, which is divided by the sampling time interval to obtain the instantaneous voltage rate of change.

[0067] For example, if the sampling interval is 0.1 seconds, the voltage amplitude at the previous time is 230 kV, and the current time is 229.5 kV, the voltage rate of change is -5 kV per second. This indicator reflects the dynamic characteristics of voltage stability, and a large change rate often indicates that the system may lose voltage stability.

[0068] Preferably, the activation process of the alarm flow includes the coordinated action of multiple links. When the offset condition is met, the system first generates an offset event record locally, which includes the time stamp, the section identification, the real-time values of each electrical parameter, and the deviation. Subsequently, the alarm information is pushed to the monitoring terminal of the provincial or regional dispatching center through the dispatching data network, and at the same time, the audible and visual alarms are triggered to remind the dispatcher. The priority of the alarm information is dynamically adjusted according to the offset amplitude, and the larger the offset, the higher the priority, to ensure that serious offset events are handled in a timely manner.

[0069] S102, if it is determined that there is an operating point offset, obtaining device switching record and load flow direction data of the target power grid, and determining the safety boundary of the target power grid according to the device switching record and the load flow direction data;

[0070] In this embodiment, the safety boundary of the target power grid is determined according to the device switching record and the load flow direction data, specifically: predicting the operation development of the target power grid according to the real-time power data to obtain an operation development prediction set; aligning the device switching record and the operation development prediction set in time through a preset time stamp to obtain an extended trajectory data set, and generating power flow distribution data according to the extended trajectory data set and the load flow direction data through a preset power flow tracking algorithm; and determining the safety boundary of the target power grid according to the power flow distribution data.

[0071] In the embodiment, the operation development of the target power grid is predicted according to the real-time power data, and a set of operation development prediction is obtained. Specifically, a current operation point trajectory is generated according to the real-time power data; a plurality of historical operation point trajectory segments are obtained from a preset database, and distance values of the current operation point trajectory and each historical operation point trajectory segment are calculated in sequence by using a preset dynamic time warping algorithm; the historical operation point trajectory segments are filtered according to a preset distance threshold and the distance values, and a similar trajectory group is obtained; subsequent development paths of the historical operation point trajectory segments in the similar trajectory group are obtained from the database, a prediction path group is obtained, and a set of operation development prediction is obtained by performing weighted average on each subsequent development path in the prediction path group.

[0072] In a specific embodiment, the device switching record and real-time load flow data in the latest period are obtained from the dispatch automation database, the device switching record includes circuit breaker state displacement information and operation time stamp, and the load flow data includes node injection power value and branch power flow direction identification. The active power, the reactive power and the voltage amplitude in the current operation state are subtracted from the normal working condition reference value to obtain a deviation sequence and connect to form a current operation point offset trajectory. The current operation point offset trajectory is sampled at a fixed time interval to obtain a trajectory feature point sequence, and trajectory segments with the same sampling interval are extracted from historical data. The distance values of the current trajectory feature point sequence and the historical trajectory segments are calculated by using a dynamic time warping algorithm, and the historical trajectories with distance values less than a preset threshold are selected as a similar trajectory group. According to the subsequent development paths of each trajectory in the similar trajectory group, a trajectory development trend prediction value is obtained by weighted average calculation. The operation time of the device switching record is mapped to the trajectory time axis, and the device state change mark is inserted at the corresponding time to form an extended trajectory data set containing device operation information. For each time in the extended trajectory data set, the power transmission path from the power supply node to the load node is tracked according to the load flow data, the power flow value on each path is accumulated, the proportion of the power of each path in the total power is calculated, and the power transmission distribution is obtained.

[0073] It should be noted that the device switching record is obtained through the real-time data interface of the dispatch automation system. Whenever the state of a circuit breaker, disconnector or other switch device changes, the system will record the device number, action type, action time and operation reason.

[0074] Preferably, the load flow direction data is calculated by a state estimation program, containing the active power injection, the reactive power injection of each bus node, and the power flow direction and size of each branch. The formation process of the deviation sequence is to subtract each sampling time electrical parameter from the preset normal working condition reference value one by one to obtain the active power deviation, the reactive power deviation and the voltage amplitude deviation, and these deviation values are arranged in time sequence to form a deviation sequence, and the connection line of adjacent points in the sequence forms the operating point deviation trajectory.

[0075] It should be noted that the application principle of dynamic time warping algorithm in trajectory matching is to find the minimum matching path between two trajectories by constructing a cumulative distance matrix.

[0076] Illustratively, the current trajectory has 100 sampling points, and the historical trajectory segment has 120 sampling points. The algorithm finds the corresponding relationship that minimizes the cumulative distance of the two trajectories by dynamic programming method, that is, even if the time length of the two trajectories is not completely consistent, the trajectory pattern with similar shape can also be identified. The calculation of distance value adopts Euclidean distance, which comprehensively considers the difference of multi-dimensional electrical parameters of each sampling point. When the calculated distance value is less than the preset threshold value, it is considered that the two trajectories have similarity, and the historical trajectory is included in the similar trajectory group.

[0077] Preferably, the prediction of trajectory development trend is based on the subsequent evolution characteristics of each historical trajectory in the similar trajectory group.

[0078] In a specific embodiment, for each historical trajectory in the similar trajectory group, the trajectory development path after the matching period is extracted, including the power change direction, the change rate and the final stable value. According to the similarity of each historical trajectory and the current trajectory, a weight coefficient is assigned, and the higher the similarity of the trajectory, the greater the weight. The subsequent path of each historical trajectory is weighted and averaged to obtain the predicted development trend of the current trajectory.

[0079] In the embodiment, the security boundary of the target power grid is determined according to the power flow distribution data, specifically: according to the power flow distribution data, the active power value and the reactive power value of each key section of the target power grid are extracted to obtain a power combination point set, and the power value set is screened according to the preset voltage stability constraint and thermal stability limit to obtain a safe power combination point set; according to the safe power combination point set, a security boundary contour line is generated; wherein the horizontal and vertical coordinate values of each point on the security boundary contour line are the security boundary position coordinates.

[0080] In one specific embodiment, the preset voltage stability constraints include upper and lower limits of bus voltage and allowable voltage drop range, and the preset thermal stability limits include line current carrying capacity limit and transformer capacity limit. Active and reactive power values ​​for each section are extracted based on power transmission distribution data. These power values ​​are compared with the voltage stability constraints and thermal stability limits to identify power combination points that simultaneously meet both constraints. These power combination points are marked on a coordinate plane with active power as the horizontal axis and reactive power as the vertical axis. Connecting the combination points located at the constraint edges forms a safety boundary contour line. The horizontal and vertical coordinates of each point on the safety boundary contour line are the safety boundary position coordinates. For three consecutive adjacent position coordinate points on the safety boundary contour line, an arc is fitted based on the three coordinate values. The radius of the fitted arc is calculated, and the reciprocal of the radius is taken as the curvature value of the local boundary. The boundary curvature value distribution is calculated point by point along the boundary contour line.

[0081] It should be noted that the voltage stability constraints are set based on the stable operation requirements of the power system. The upper limit of the bus voltage is usually set at 1.1 times the rated voltage, and the lower limit is set at 0.9 times the rated voltage. The allowable range of voltage drop is determined according to the line length and load characteristics.

[0082] It should be noted that the thermal stability limit reflects the thermal load capacity of the equipment, the line current carrying limit is determined by the conductor material, cross-sectional area and ambient temperature, and the transformer capacity limit depends on its winding insulation class and heat dissipation conditions.

[0083] It should be noted that the power transmission distribution data includes real-time power flow information of each section of the system. By comparing the active and reactive power values ​​of each section with the constraints one by one, the power combinations that simultaneously meet the requirements of voltage stability and thermal stability are selected.

[0084] For example, in a regional power grid analysis, there are five main transmission channels from the western power base to the eastern load center. By tracking the load flow, it was found that the first channel carries 35% of the power transmission, the second channel carries 28%, the third channel carries 20%, and the fourth and fifth channels carry 12% and 5%, respectively.

[0085] For example, if a 500 kV section has an active power of 2000 MW and a reactive power of 500 Mvar, and this combination keeps the bus voltage within the allowable range and the line current does not exceed the current carrying capacity limit, then this point is identified as a safe operating point.

[0086] Preferably, the formation process of the safety boundary contour line adopts a boundary tracing method. On the two-dimensional coordinate plane, after marking all power combination points that satisfy the constraints, the set of points located at the edge of the safety area is identified. These edge points are characterized by having at least one point in an adjacent direction that does not satisfy the constraints. By connecting these edge points in sequence, a closed safety boundary contour line is formed. The inner region of the contour line represents the safe operating area, and the outer region represents the over-limit area.

[0087] Preferably, the boundary curvature is calculated using a three-point circular arc fitting method. Three consecutive points are selected on the safety boundary contour line, and the equation of a circle is established based on the coordinates of these three points. The coordinates of the center and the radius of the fitted circle are then obtained. The curvature value is defined as the reciprocal of the radius; a smaller radius indicates a greater degree of boundary curvature, and the corresponding curvature value is higher. The calculation window is slid along the entire boundary contour line, moving one point at a time, to calculate the complete boundary curvature distribution point by point. This distribution reflects the bending characteristics of the safety boundary at different locations.

[0088] S103, based on the safety boundary, the current safety margin of the target power grid is evaluated. If the current safety margin does not meet the preset conditions, a power grid operation control command is generated based on the pre-acquired power transmission distribution data, so as to realize the control of the safety margin through the power grid operation control command; wherein, the power grid operation control command determines the control priority based on the sensitivity coefficient of each control device in the target power grid to the safety margin.

[0089] In this embodiment, the step of evaluating the current safety margin of the target power grid based on the safety boundary specifically involves: obtaining the current active power and current reactive power of the target power grid, and mapping the active power and reactive power to the current operating point; calculating the minimum Euclidean distance from the current operating point to the safety boundary contour line, and determining the minimum Euclidean distance as the current safety margin; if the current safety margin is less than a preset safety margin threshold, then it is determined that the safety margin of the target power grid does not meet the preset conditions.

[0090] In one specific embodiment, mapping the active power and reactive power to the current operating point specifically involves: synchronously collecting the actual operating values ​​of active power and reactive power at each key transmission section from the real-time monitoring system of the target power grid at the current moment; wherein, key transmission sections include tie lines connecting different regional power grids, trunk lines supplying the main loads, and transmission lines for centralized grid connection of new energy sources; the collection frequency is consistent with the sampling frequency of real-time power data to ensure the timeliness and synchronization of power parameters; constructing a two-dimensional power coordinate system with active power as the abscissa and reactive power as the ordinate, the abscissa range of which covers the historical maximum and minimum operating values ​​of active power at the key sections of the target power grid, and the ordinate range covering the historical maximum and minimum operating values ​​of reactive power at the key sections; mapping the collected current active power value to the abscissa position of the two-dimensional power coordinate system, and mapping the current reactive power value to the ordinate position, the coordinate point formed by the intersection of the two is the current operating point.

[0091] In one specific embodiment, calculating the minimum Euclidean distance from the current operating point to the safety boundary contour line specifically involves: extracting all discrete coordinate points on the safety boundary contour line to form a boundary point set; for the current operating point, sequentially calculating the straight-line distance between it and each coordinate point in the boundary point set, ensuring that the dimensions of the horizontal and vertical coordinates are consistent during the distance calculation process, using per-unit values ​​or uniform physical quantity units (e.g., active power in megawatts, reactive power in megawatts); comparing all calculated straight-line distances and selecting the distance value with the smallest value, which is the minimum Euclidean distance from the current operating point to the safety boundary contour line; directly determining this minimum Euclidean distance as the current safety margin of the target power grid, the magnitude of the safety margin directly reflects the distance between the current power grid operating state and the safety boundary, the larger the value, the safer the power grid operation, and the smaller the value, the closer the power grid is to the safe operating limit.

[0092] It should be noted that the preset safety margin threshold needs to be determined based on the operating characteristics of the target power grid, historical fault data, and safety operation requirements. For urban power grids with frequent load fluctuations, the threshold can be appropriately increased to reserve more safety buffer space. For power grids with low renewable energy penetration and stable operating conditions, the threshold can be appropriately reduced under the premise of ensuring safety. After the threshold is determined, it needs to be stored in the system database and can be dynamically adjusted according to changes in power grid topology or operating needs.

[0093] In one specific embodiment, the current safety margin is compared with a preset safety margin threshold. If the current safety margin is less than the safety margin threshold, it is determined that the safety margin of the target power grid does not meet the preset conditions, and the subsequent power grid operation control process needs to be initiated. If the current safety margin is greater than or equal to the safety margin threshold, it is determined that the safety margin meets the preset conditions, the power grid is currently in a safe operating state, and no control needs to be initiated.

[0094] In this embodiment, a power grid operation control command is generated based on the pre-acquired power transmission distribution data to achieve safety margin control. Specifically, based on the power transmission distribution data, key transmission sections whose impact on the safety margin exceeds a preset impact threshold are identified to obtain a set of key transmission sections. The power margin of each key transmission section in the set is calculated sequentially. Based on the rate margin and the safety boundary, the required active power adjustment and reactive power adjustment are calculated, and the power grid operation control command is generated based on the active power adjustment and reactive power adjustment.

[0095] In one specific embodiment, the identification of key transmission sections involves: extracting the power transmission ratio, power fluctuation frequency, and correlation coefficient with safety margin for all transmission sections of the target power grid from pre-acquired power transmission distribution data; wherein, the power transmission ratio is the proportion of the power transmission value of the section to the total power transmission value of the entire network, the power fluctuation frequency is the number of times the power change of the section exceeds a preset fluctuation amplitude per unit time, and the correlation coefficient is obtained through statistical analysis of historical data, reflecting the degree of impact of section power change on the overall safety margin. A preset impact threshold is set, which is determined by comprehensively considering the power grid safe operation standards, historical fault section characteristics, and dispatch experience values. For example, sections with a power transmission ratio exceeding 15%, a power fluctuation frequency exceeding 5 times per hour, and a correlation coefficient greater than 0.6 are set as high impact threshold intervals. The power transmission ratio, power fluctuation frequency, and correlation coefficient of each transmission section are compared with the corresponding thresholds. If at least two of the three indicators of any section exceed the corresponding threshold, or if a single indicator far exceeds the threshold (e.g., the power transmission ratio exceeds 25%), then the section is included in the set of key transmission sections.

[0096] In one specific embodiment, the power margin calculation is as follows: For each section in the key transmission section cluster, firstly, obtain the upper limit of the rated transmission power of the section (determined according to the section line type, conductor material, heat dissipation conditions and power grid design standards) and the current actual transmission power; then calculate the difference between the upper limit of the rated transmission power and the current actual transmission power, which is the active power margin of the section; simultaneously, obtain the limit value of reactive power compensation of the section (determined by the capacity of the reactive power compensation device matched to the section and the power grid voltage stability requirements) and the current actual reactive power, and calculate the difference between the two to obtain the reactive power margin; integrate the active power margin and the reactive power margin to form the comprehensive power margin of the key transmission section, which comprehensively reflects the remaining safety space of the section in terms of power transmission.

[0097] In one specific embodiment, the power adjustment calculation is as follows: based on the comprehensive power margin of key transmission sections and combined with the safety boundary contour line, the deviation between the current power status of each key section and the safety boundary is analyzed. For active power adjustment, if the active power margin of a key section is less than the minimum active power margin requirement corresponding to the safety boundary, the difference between the current active power margin of the section and the minimum active power margin requirement is calculated, and this difference is the active power adjustment to be supplemented; if the active power margin exceeds the reasonable range corresponding to the safety boundary, the value of the excess part is calculated as the active power adjustment to be reduced. Similarly, for reactive power adjustment, the reactive power adjustment to be supplemented or reduced is determined based on the deviation between the reactive power margin of the key section and the minimum reactive power margin requirement corresponding to the safety boundary. During the calculation process, the power balance between each key section must be taken into account to avoid the power imbalance of other sections caused by the adjustment of a single section. For example, when the active power of a key section in a certain area needs to be increased, the active power output capacity of the surrounding power sources must be considered simultaneously to ensure that the adjustment is within the overall power balance range of the power grid.

[0098] In this embodiment, a power grid operation control command is generated based on the active power adjustment and reactive power adjustment. Specifically, the sensitivity coefficients of each control device in the target power grid to the safety margin are calculated using a preset sensitivity analysis algorithm. The control devices include generators, reactive power compensation devices, and transformers. Based on the sensitivity coefficients, the control priority is determined, and a power grid operation control command is generated based on the control priority. The power grid operation control command includes at least one of adjusting generator active power, adjusting generator reactive power, switching capacitor banks, or switching reactors.

[0099] In one specific embodiment, the preset sensitivity analysis algorithm employs a stepwise perturbation method. This algorithm requires constructing a calculation model based on the topology, equipment parameters, and real-time operating status of the target power grid. First, basic parameters of each control device are extracted from the power grid dispatch database. For generators, rated power, maximum output, minimum output, adjustment response time, and voltage adjustment range are required; for reactive power compensation devices (including capacitor banks and reactors), rated compensation capacity, switching step size, and allowed switching frequency are required; for transformers, turns ratio adjustment range, tap changer adjustment step size, and adjustment response delay are required. Simultaneously, the active power adjustment amount, reactive power adjustment amount, and safety boundary parameters calculated earlier are imported as input conditions for the sensitivity calculation.

[0100] Furthermore, the sensitivity coefficient is calculated based on the equipment type:

[0101] (1) Calculation of generator sensitivity coefficient: For each generator, based on the current operating output, its active power output is gradually increased or decreased by a preset step size (such as 5% of the rated power), and the change in the safety margin of the target power grid is monitored synchronously. The change in safety margin caused by the unit adjustment of active power output is calculated, which is the active power sensitivity coefficient of the generator. Similarly, the reactive power output of the generator is gradually adjusted, and the change in safety margin corresponding to the unit adjustment of reactive power output is calculated to obtain the reactive power sensitivity coefficient. Finally, the coefficients are integrated into the comprehensive sensitivity coefficient of the generator.

[0102] (2) Calculation of sensitivity coefficient of reactive power compensation device: For each group of capacitor bank or reactor, switch it gradually according to its switching step size (such as 20% of the single group compensation capacity), record the change of the grid safety margin after each switching, calculate the change of safety margin caused by the switching of unit compensation capacity, and use it as the sensitivity coefficient of the reactive power compensation device; if there are multiple groups of parallel devices, the sensitivity coefficients of single group switching and multiple groups joint switching need to be calculated separately, and the average value is taken as the final coefficient.

[0103] (3) Calculation of transformer sensitivity coefficient: For each transformer, the turns ratio is gradually adjusted according to the tap adjustment step size. The influence of changes in grid voltage distribution and power flow on the safety margin is monitored. The change value of safety margin corresponding to unit turns ratio adjustment is calculated, which is the transformer sensitivity coefficient. At the same time, the transformer load rate needs to be considered. If the load rate exceeds 80%, the sensitivity coefficient needs to be corrected to avoid the coefficient distortion due to overload.

[0104] Furthermore, after all equipment sensitivity coefficients are calculated, the coefficient data are compared with those under similar operating conditions in the same period of history. If the deviation exceeds 10%, the disturbance step size is readjusted (e.g., reduced to 3% of the rated parameter) and the calculation is repeated to ensure the accuracy of the coefficients. At the same time, the calculation results under abnormal equipment conditions (such as generator failure or compensation device maintenance) are excluded to avoid invalid data affecting subsequent priority determination.

[0105] In one specific embodiment, a sensitivity coefficient priority classification standard is set, and the sensitivity coefficients are divided into three levels according to their numerical values. Among them, the coefficient with an absolute value greater than 0.8 is high priority (the unit adjustment has a significant effect on improving the safety margin), the coefficient with an absolute value between 0.3 and 0.8 is medium priority (the improvement effect is moderate), and the coefficient with an absolute value less than 0.3 is low priority (the improvement effect is weak). If multiple devices are in the same priority, the devices are sorted in combination with their adjustment response time. Devices with shorter response times (such as generator active power regulation response time less than 10 seconds) are given priority over devices with longer response times (such as transformer turns ratio regulation response time greater than 30 seconds).

[0106] Furthermore, priority is given to allocating adjustment tasks to high-priority equipment. For example, if a generator has an active power sensitivity coefficient of 0.9 and a response time of 8 seconds, it is given priority to undertake the main active power adjustment tasks, with an allocation ratio of no less than 60% of the total adjustment amount. If the total adjustment capacity of high-priority equipment cannot meet the adjustment requirements, the remaining portion is then allocated to medium-priority equipment.

[0107] It should be noted that medium-priority equipment mainly undertakes the adjustment volume that high-priority equipment cannot cover, and the allocation ratio shall not exceed 30% of the total adjustment volume; low-priority equipment is only activated when the adjustment volume is extremely small (such as within 10% of the total adjustment volume) or when other equipment is at full load, and it is necessary to monitor the changes of other grid parameters during the adjustment process to avoid causing new operational risks.

[0108] Furthermore, based on the priority allocation results and in accordance with the instruction format requirements of the power grid dispatch automation system, control instructions are generated, including equipment identification, adjustment type, adjustment range, adjustment time limit, and safety verification requirements. Specifically, instructions adjusting generator active power must specify the target output value and adjustment rate (e.g., an increase of 5 MW per minute); instructions adjusting generator reactive power must specify the target reactive power output value and voltage control range; instructions switching capacitor banks or reactors must specify the number of banks to be switched, the capacity of each bank, and the switching interval (e.g., 30 seconds per bank). All instructions must include verification conditions; if the equipment status is abnormal during execution (e.g., generator output exceeds the limit), instruction execution must be automatically suspended and feedback must be sent to the dispatch center.

[0109] Furthermore, the generated control commands are imported into a pre-built power grid simulation model (with parameters consistent with the target power grid twin model) to simulate the command execution process and verify whether the power grid safety margin meets the preset conditions after execution. If the simulation results show that the safety margin is still not up to standard, the priority allocation ratio is readjusted (such as increasing the adjustment amount of high-priority equipment) and verified again until the simulation results are qualified. Finally, the final command is sent to the control terminal of the corresponding control equipment through the scheduling data network.

[0110] In this embodiment, the method further includes: simulating the execution of the power grid operation control command through a pre-constructed target power grid twin model to obtain a simulated power flow distribution, and predicting the safety margin after control based on the simulated power flow distribution to obtain a predicted safety margin; if the predicted safety margin still does not meet the preset conditions, the control command is regenerated until the predicted safety margin meets the requirements, and the finally determined control command is sent to the target power grid to control the equipment to execute.

[0111] In one specific embodiment, the twin model is pre-built and synchronized with parameters. Specifically, the pre-built target power grid twin model is based on the physical topology of the actual power grid and includes digital models of all key equipment such as generators, transmission lines, transformers, and reactive power compensation devices. The equipment parameters are consistent with the actual equipment: the generator model includes rated power, governor response characteristics, and excitation system parameters; the transmission line model includes line impedance, admittance, and thermal stability limits; the transformer model includes turns ratio, short-circuit voltage, and tap adjustment range; and the reactive power compensation device model includes compensation capacity and switching step size. After model construction, it is interfaced with the target power grid's SCADA (Supervisory Control and Data Acquisition) system and EMS (Energy Management System) system via a real-time data interface. Real-time power data (active power, reactive power, voltage amplitude, and equipment operating status) of the actual power grid is synchronized every 10 seconds to ensure a high degree of consistency between the twin model and the actual power grid's operating status, avoiding distortion of simulation results due to parameter deviations.

[0112] Furthermore, the power grid operation and control commands are imported and simulated for execution: The generated power grid operation and control commands are imported into the command simulation module of the twin model according to a standardized format (including command number, equipment ID, adjustment type, adjustment range, and execution sequence). During simulation execution, the model executes the commands step-by-step according to the actual power grid's equipment response logic—for example, when executing the command "adjust the active power of a generator," the model first simulates the delay time of the generator governor receiving the command signal (usually 0.5-2 seconds), and then gradually changes the generator output according to the required adjustment rate (e.g., an increase of 5 MW per minute); when executing the command "switching capacitor banks," the model simulates the circuit breaker's operating time (usually 0.1-0.3 seconds) and simultaneously calculates the changes in grid node voltage and reactive power distribution after switching. During simulation execution, power flow data for each node and transmission section of the power grid is recorded every 2 seconds, forming a complete simulated power flow distribution dataset. The dataset includes key parameters such as the direction and value of active power flow, the direction and value of reactive power flow, node voltage amplitude, and line current for each section.

[0113] Furthermore, after the simulated power flow distribution is generated, it is compared with the real-time power flow data of the actual power grid synchronized with the twin model. If the simulated active power of a transmission section deviates from the actual active power by more than 5%, or the simulated voltage amplitude of a node deviates from the actual voltage amplitude by more than 2%, the simulation result is considered to have a deviation. At this time, it is necessary to check whether the command import format is correct and whether the parameters of the corresponding equipment in the model are consistent with the actual parameters (such as whether the generator excitation system parameters have been updated). If there is a parameter deviation, the model parameters are corrected. If there is a command format problem, the command is re-imported, and the simulation process is executed again until the deviation between the simulated power flow distribution and the actual power flow data meets the preset accuracy requirements (section power deviation ≤ 3%, node voltage deviation ≤ 1%), ensuring the accuracy of subsequent safety margin prediction.

[0114] Furthermore, referring to the aforementioned safety margin assessment method, the active power and reactive power values ​​of each key transmission section are extracted from the simulated power flow distribution dataset and mapped to simulated operating points in the twin model. Then, safety boundary contour parameters are extracted, and the minimum Euclidean distance from each simulated operating point to the safety boundary contour is calculated. This distance is the predicted safety margin after regulation. During the calculation, it is necessary to ensure unit consistency—active power is in megawatts and reactive power is in megavars, consistent with the coordinate units of the safety boundary contour. Simultaneously, the minimum predicted safety margin for multiple key sections is taken as the predicted safety margin for the entire target power grid, avoiding the risk of ignoring other vulnerable sections due to the compliance of a single section.

[0115] Furthermore, the preset conditions include two judgment criteria: the first is the "absolute threshold standard," which means that the predicted safety margin must be greater than or equal to the set safety margin threshold (such as a combined safety margin value of 50 MW·Mvar); the second is the "trend stability standard," which means that the fluctuation range of the predicted safety margin in three consecutive simulations must be less than 10%, ensuring the stability of the control effect and avoiding the situation of "instantaneous achievement of the target but subsequent decline." If the predicted safety margin meets both criteria simultaneously, it is determined that it meets the preset conditions; if either criterion is not met (such as the predicted safety margin being less than the threshold, or the fluctuation range exceeding 10%), it is determined that it does not meet the preset conditions, and the control command optimization process needs to be initiated.

[0116] Control command regeneration and iterative optimization: If the predicted safety margin does not meet the preset conditions, first analyze the reasons for the failure. If the low predicted safety margin is due to insufficient power adjustment at a key section, the active or reactive power adjustment at that section needs to be increased (e.g., if the original adjustment is 20 MW, it can be increased to 30 MW). If the insufficient adjustment capacity of the control equipment (e.g., a generator reaching its maximum output still cannot meet the adjustment requirements), the control equipment with a higher sensitivity coefficient needs to be replaced (e.g., the original generator adjustment task is replaced with another generator with a higher sensitivity coefficient) according to the aforementioned sensitivity coefficient calculation and priority determination methods. After regenerating the control command, import it into the twin model again to execute the simulation process, calculate the new predicted safety margin and compare it with the preset conditions. This iterative optimization continues until the predicted safety margin meets the preset conditions. A maximum number of iterations is set during the iteration process (e.g., 5 times). If the target is still not met after reaching the maximum number of iterations, an alarm mechanism is triggered, pushing a "manual intervention required" prompt message to the dispatch center to avoid infinite loops.

[0117] After all subsequent control commands have been executed, real-time power flow data of the actual power grid is collected, the actual safety margin is calculated, and it is compared with the safety margin predicted by the twin model. If the deviation is less than 5%, the control task is considered to be completed and the safety margin has achieved the expected effect. If the deviation exceeds 5%, the reasons for the deviation are analyzed (such as the twin model not fully simulating the interference factors of the actual power grid), and the reasons are recorded in the historical database to provide a basis for subsequent model optimization and control strategy improvement.

[0118] This invention continuously collects real-time power data from the target power grid, providing accurate and timely information for determining whether the grid's operating point has shifted. This ensures dynamic monitoring of the grid's operating status, avoiding misjudgments or omissions of abnormal grid conditions due to data lag. By determining whether there is an operating point shift, it promptly detects abnormal trends in grid operation, providing triggering conditions for subsequent safety boundary determination and safety margin control processes. This ensures that control is initiated only when necessary, avoiding unnecessary intervention. By determining the safety boundary of the target power grid based on equipment switching records and load flow data, it clarifies the "red line" for the grid's current safe operation, providing a basis for subsequent safety assessments. The safety margin provides standards and a basis for ensuring the relevance and accuracy of safety margin assessment results. When the safety margin fails to meet preset conditions, power grid operation control commands are generated based on pre-acquired power transmission distribution data. This ensures that the control commands target weak links in power transmission, achieving precise adjustments to the power grid's operating state and restoring the safety margin to a compliant level. Furthermore, by determining control priorities based on sensitivity coefficients, the system prioritizes control of equipment that most significantly improves the safety margin, increasing control efficiency, reducing unnecessary equipment adjustments, lowering control costs and disturbances to power grid operation, and ensuring the power grid returns to a safe and stable operating state in the shortest possible time. Compared to existing technologies, this invention improves the stability of power grid operation through precise and efficient dynamic control of the safety margin.

[0119] Example 2:

[0120] like Figure 2 As shown, this embodiment provides a dynamic control system for safety margin in power grid operation scheduling, including an operating point offset judgment module 201, a safety boundary determination module 202, and a safety margin control module 203, wherein...

[0121] The operating point offset judgment module 201 is used to continuously collect real-time power data of the target power grid and determine whether there is an operating point offset based on the real-time power data; wherein, the real-time power data includes active power, reactive power and voltage amplitude;

[0122] In this embodiment, the operating point offset judgment module 201 determines whether an operating point offset exists based on the real-time power data. Specifically, the operating point offset judgment module 201 extracts the active power sequence and reactive power sequence from the real-time power data through a preset time window, and calculates the active power deviation value and reactive power deviation value for each sampling point based on the active power sequence, reactive power sequence, and preset power reference data, to obtain the active power deviation sequence and reactive power deviation sequence; wherein, the power reference data includes active power reference value and reactive power reference value; extracts the voltage amplitude from the real-time power data, and calculates the voltage change rate between each adjacent sampling point based on the voltage amplitude, to obtain the voltage change rate sequence; if there is a deviation value in the active power deviation sequence or reactive power deviation sequence that is greater than a preset power deviation threshold, and there is a voltage change rate in the voltage change rate sequence that is greater than a preset voltage change rate threshold, then it is determined that the target power grid has an operating point offset.

[0123] The safety boundary determination module 202 is used to, if it is determined that there is an operating point offset, acquire the equipment switching records and load flow data of the target power grid, and determine the safety boundary of the target power grid based on the equipment switching records and load flow data;

[0124] In this embodiment, the safety boundary determination module 202 determines the safety boundary of the target power grid based on the equipment switching records and load flow data. Specifically, the safety boundary determination module 202 predicts the operation and development of the target power grid based on the real-time power data to obtain an operation and development prediction set; it aligns the equipment switching records and the operation and development prediction set in time using a preset timestamp to obtain an extended trajectory dataset; and it generates power flow distribution data based on the extended trajectory dataset and the load flow data using a preset power flow tracing algorithm; and it determines the safety boundary of the target power grid based on the power flow distribution data.

[0125] The safety margin control module 203 is used to evaluate the current safety margin of the target power grid according to the safety boundary. If the current safety margin does not meet the preset conditions, it generates a power grid operation control command based on the pre-acquired power transmission distribution data, so as to realize the control of the safety margin through the power grid operation control command. The power grid operation control command determines the control priority according to the sensitivity coefficient of each control device in the target power grid to the safety margin.

[0126] In this embodiment, the safety margin control module 203 evaluates the current safety margin of the target power grid based on the safety boundary. Specifically, the safety margin control module 203 obtains the current active power and current reactive power of the target power grid and maps the active power and reactive power to the current operating point; calculates the minimum Euclidean distance from the current operating point to the safety boundary contour line and determines the minimum Euclidean distance as the current safety margin; if the current safety margin is less than a preset safety margin threshold, it is determined that the safety margin of the target power grid does not meet the preset conditions.

[0127] In this embodiment, the safety margin control module 203 generates a power grid operation control command based on the pre-acquired power transmission distribution data, so as to realize the control of the safety margin through the power grid operation control command. Specifically, the safety margin control module 203 identifies key transmission sections whose impact on the safety margin exceeds a preset impact threshold based on the power transmission distribution data, obtains a set of key transmission sections, and calculates the power margin of each key transmission section in the set of key transmission sections in sequence; calculates the required active power adjustment and reactive power adjustment based on the rate margin and the safety boundary, and generates a power grid operation control command based on the active power adjustment and reactive power adjustment.

[0128] For a more detailed explanation of the working principle and procedures of this embodiment, please refer to the relevant description in Embodiment 1.

[0129] This invention embodiment uses an operating point offset judgment module 201 to continuously collect real-time power data of the target power grid, providing real-time and accurate basic information for subsequent judgment of whether the power grid operating point has shifted. This ensures dynamic monitoring of the power grid's operating status, avoids misjudgment or omission of abnormal power grid states due to data lag, and promptly detects abnormal trends in power grid operation by judging whether there is an operating point offset. This provides triggering conditions for subsequent initiation of safety boundary determination and safety margin control processes, ensuring that control is initiated only when necessary and avoiding unnecessary intervention. The safety boundary determination module 202 determines the safety boundary of the target power grid based on equipment switching records and load flow data, clarifying the "red line" for the current safe operation of the power grid. Subsequent assessments of safety margins provide standards and basis, ensuring the relevance and accuracy of safety margin assessment results. Through the safety margin control module 203, when the safety margin does not meet preset conditions, grid operation control commands are generated based on pre-acquired power transmission distribution data. This ensures that the control commands target weak links in grid power transmission, achieving precise adjustments to the grid's operating state and restoring the safety margin to a compliant level. Furthermore, by determining control priorities based on sensitivity coefficients, the devices with the most significant safety margin improvement effects can be prioritized for control, improving control efficiency, reducing unnecessary device adjustments, lowering control costs and disturbances to grid operation, and ensuring the grid returns to a safe and stable operating state in the shortest possible time.

[0130] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0131] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for dynamic regulation of safety margin for power grid operation scheduling, characterized in that, The method comprises: continuously collecting real-time power data of a target power grid, and determining whether there is an operating point deviation according to the real-time power data; wherein the real-time power data comprises active power, reactive power and voltage amplitude; if it is determined that there is an operating point deviation, obtaining device switching record and load flow direction data of the target power grid, and determining the safety boundary of the target power grid according to the device switching record and load flow direction data; wherein, according to the device switching record and load flow direction data, the safety boundary of the target power grid is determined, specifically: according to the real-time power data, the development of the operation of the target power grid is predicted to obtain a development prediction set; through a preset time stamp, the device switching record and the development prediction set are time-aligned to obtain an extended trajectory data set, and through a preset power flow tracking algorithm, the power flow distribution data is generated according to the extended trajectory data set and the load flow direction data; according to the power flow distribution data, the safety boundary of the target power grid is determined; wherein, according to the real-time power data, the development of the operation of the target power grid is predicted to obtain a development prediction set, specifically: according to the real-time power data, a current operating point trajectory is generated; a plurality of historical operating point trajectory segments are obtained from a preset database, and a distance value between the current operating point trajectory and each historical operating point trajectory segment is calculated in turn through a preset dynamic time warping algorithm; according to a preset distance threshold and the distance value, the historical operating point trajectory segments are screened to obtain a similar trajectory group; the subsequent development paths of each historical operating point trajectory segment in the similar trajectory group are obtained from the database to obtain a prediction path group, and a weighted average of each subsequent development path in the prediction path group is obtained to obtain a development prediction set; According to the safety boundary, the current safety margin of the target power grid is evaluated, and if the current safety margin does not meet the preset condition, power transmission distribution data is obtained, and power grid operation control instructions are generated according to the power transmission distribution data, so that the safety margin is controlled through the power grid operation control instructions; wherein the power grid operation control instructions determine the control priority according to the sensitivity coefficient of each control device in the target power grid to the safety margin.

2. The method for dynamic regulation of safety margin for power grid operation scheduling according to claim 1, wherein, According to the real-time power data, it is determined whether there is an operating point deviation, specifically: through a preset time window, active power sequence and reactive power sequence are extracted from the real-time power data, and active power deviation value and reactive power deviation value of each sampling point are calculated according to the active power sequence, reactive power sequence and preset power reference data to obtain active power deviation sequence and reactive power deviation sequence; wherein the power reference data comprises active power reference value and reactive power reference value; extract the voltage amplitude in the real-time power data, and calculate the voltage change rate between each adjacent sampling point according to the voltage amplitude to obtain the voltage change rate sequence; If there is a deviation value greater than a preset power deviation threshold in the active power deviation sequence or the reactive power deviation sequence, and there is a voltage change rate greater than a preset voltage change rate threshold in the voltage change rate sequence, it is determined that the target power grid has an operating point deviation.

3. The method of claim 1, wherein the method further comprises: The safety boundary of the target power grid is determined according to the power flow distribution data, specifically: According to the power flow distribution data, the active power and reactive power values of each key section of the target power grid are extracted to obtain a power combination point set, and the power value set is screened according to a preset voltage stability constraint and a thermal stability limit to obtain a safe power combination point set; According to the safe power combination point set, a safety boundary contour line is generated, and the horizontal and vertical coordinate values of each point on the safety boundary contour line are safety boundary position coordinates.

4. The method of claim 3, wherein the safety margin is dynamically adjusted according to the grid operation schedule. The current safety margin of the target power grid is evaluated according to the safety boundary, specifically: The current active power and current reactive power of the target power grid are obtained, and the active power and reactive power are mapped to a current operating point; The minimum Euclidean distance from the current operating point to the safety boundary contour line is calculated, and the minimum Euclidean distance is determined as the current safety margin; If the current safety margin is less than a preset safety margin threshold, it is determined that the safety margin of the target power grid does not meet the preset condition.

5. The method of claim 1, wherein the method further comprises: According to the pre-obtained power transmission distribution data, a power grid operation control instruction is generated to realize the control of the safety margin through the power grid operation control instruction, specifically: According to the power transmission distribution data, key power transmission sections that affect the safety margin beyond a preset impact threshold are identified to obtain a key power transmission section set, and the power margin of each key power transmission section in the key power transmission section set is calculated in turn; According to the rate margin and the safety boundary, the required active power adjustment amount and reactive power adjustment amount are calculated, and the power grid operation control instruction is generated according to the active power adjustment amount and the reactive power adjustment amount.

6. The method for dynamic regulation of safety margin for power grid operation scheduling according to claim 5, wherein, According to the active power adjustment amount and the reactive power adjustment amount, a power grid operation control instruction is generated, specifically: The sensitivity coefficients of each control device in the target power grid to the safety margin are calculated through a preset sensitivity analysis algorithm; wherein the control devices include generators, reactive power compensation devices and transformers; According to the sensitivity coefficients, the control priority is determined, and the power grid operation control instruction is generated according to the control priority; wherein the power grid operation control instruction includes at least one of adjusting the active power of the generator, adjusting the reactive power of the generator, switching the capacitor bank or switching the reactor.

7. The method of claim 5, wherein the safety margin is dynamically adjusted based on the grid operation schedule. Further comprising: Through a pre-constructed target power grid twin model, the power grid operation control instruction is simulated to obtain a simulated power flow distribution, and the safety margin after control is predicted according to the simulated power flow distribution to obtain a predicted safety margin; If the predicted safety margin still does not meet the preset condition, the control instruction is regenerated until the predicted safety margin meets the requirement, and the finally determined control instruction is issued to the target power grid to control the equipment to execute.

8. A security margin dynamic regulation system for power grid operation scheduling, characterized in that, The operation point deviation judgment module, the safety boundary determination module and the safety margin regulation module are included, wherein The operation point deviation judgment module is configured to continuously collect real-time power data of the target power grid, and determine whether there is an operation point deviation according to the real-time power data; wherein the real-time power data includes active power, reactive power and voltage amplitude; The safety boundary determination module is configured to, if it is determined that there is an operation point deviation, obtain device switching record and load flow direction data of the target power grid, and determine the safety boundary of the target power grid according to the device switching record and the load flow direction data; The safety boundary determination module is configured to, if it is determined that there is an operation point deviation, obtain device switching record and load flow direction data of the target power grid, and determine the safety boundary of the target power grid according to the device switching record and the load flow direction data; The safety boundary determination module is configured to, if it is determined that there is an operation point deviation, obtain device switching record and load flow direction data of the target power grid, and determine the safety boundary of the target power grid according to the device switching record and the load flow direction data; The safety boundary determination module is configured to, if it is determined that there is an operation point deviation, obtain device switching record and load flow direction data of the target power grid, and determine the safety boundary of the target power grid according to the device switching record and the load flow direction data; The safety margin regulation module is configured to evaluate the current safety margin of the target power grid according to the safety boundary, and if the current safety margin does not meet a preset condition, generate a power grid operation regulation instruction according to pre-obtained power transmission distribution data, so as to regulate the safety margin through the power grid operation regulation instruction; wherein the power grid operation regulation instruction determines a regulation priority according to a sensitivity coefficient of each regulation device in the target power grid to the safety margin.

Images