Intelligent regulation management system for power voltage control

Abstract

The invention relates to the technical field of voltage control, in particular to an intelligent regulation management system for power voltage control, which comprises a disturbance identification module, a path response module, a trend prediction module, a feedforward judgment module and a gear regulation module. According to the method, agile identification of voltage disturbance is realized by associating slope change with direction characteristics, dynamic cross influence in a multi-node network can be identified by combining response time sequence and spatial distribution of bus network nodes and constructing structured path perception of disturbance propagation, and the dynamic cross influence in the multi-node network can be identified by utilizing periodic trend comparison of a load and voltage. According to the method, the prospective insight of a voltage abnormal evolution trajectory is realized, risk assessment is carried out and early warning information is generated in advance according to the difference between an equipment adjustable range and a predicted trajectory before an adjustment action, adjustment gear optimization is executed according to multivariate comparison between a current gear and a system state, and the integration degree of adjustment is improved; and through multi-dimensional parameter linkage and dynamic trend analysis, the response capability to complex load fluctuation is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of voltage control, and in particular to an intelligent regulation and management system for electric voltage control. Background Art

[0002] The field of voltage control is a core component of power system operation and management. It mainly involves the monitoring, adjustment and optimization of voltage levels in the power grid to ensure the safety, stability and efficiency of power supply. This field covers a variety of control strategies and equipment, including transformer tap adjustment, capacitor bank switching, reactive power compensation, synchronous phase regulators and modern power electronic devices. With the increasing complexity of power grid structure, especially the large-scale access of distributed energy, smart grids and renewable energy, voltage control technology is developing towards intelligent, adaptive, distributed and coordinated control to adapt to the operation requirements of multi-source, variable and volatile power systems.

[0003] Among them, the power voltage control intelligent regulation and management system is a comprehensive intelligent control system used in power grids or distribution networks, aiming to realize real-time monitoring, automatic judgment and precise regulation of voltage. Its main purpose is to improve the operating efficiency and voltage quality of the power system, prevent voltage over-limit, reduce power loss, and enhance the grid's adaptability to load fluctuations and new energy access.

[0004] Existing technologies generally adopt single-cycle or single-point sampling methods. Voltage disturbance capture is limited to a single judgment of real-time data fluctuations. Bus response and path identification are mostly static structure judgments, which cannot accurately reflect the interaction relationship and actual propagation path between network nodes in dynamic operation. Load and voltage trend analysis mostly relies on traditional fixed value judgments, which can easily miss abnormal offsets caused by periodic changes. The adjustment strategy is based on fixed rules and cannot dynamically adapt to different operating conditions. Risk assessment is delayed, early warning capabilities are insufficient, and the adjustment action has a low match with the current system status, resulting in slow system adjustment response, a large voltage fluctuation range, and difficulty in dealing with operational problems caused by distributed energy and unstable loads. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, such as the common use of single-cycle or single-point sampling methods, voltage disturbance capture is limited to a single judgment of real-time data fluctuations, bus response and path identification are mostly static structure judgments, which are difficult to accurately reflect the interaction relationship and actual propagation path between network nodes in dynamic operation, load and voltage trend analysis mostly relies on traditional fixed value judgments, which are prone to miss abnormal offsets caused by periodic changes, adjustment strategies are based on fixed rules and cannot dynamically adapt to different operating conditions, risk assessment is delayed, early warning capabilities are insufficient, and the adjustment action has a low match with the current system state, resulting in slow system adjustment response, large voltage fluctuation range, and difficulty in coping with the operation problems caused by distributed energy and unstable loads, the embodiment of the present invention provides an intelligent adjustment and management system for power voltage control. The technical solution is as follows: On the one hand, it provides an intelligent regulation and management system for power voltage control, including: The disturbance identification module is based on the substation voltage monitoring equipment. It analyzes the voltage data of consecutive cycles, calculates the voltage slope between adjacent cycles, compares the amplitude difference between the maximum and minimum slopes, and determines the consistency of the slope direction to obtain the key feature level of the disturbance. The path response module screens the bus monitoring data at the corresponding time based on the disturbance key feature level, compares the time sequence of each bus response, determines whether the response interval is within the reference range, and combines the path length and disturbance level with the number of path intersection nodes to obtain the path cross response amount; The trend prediction module optimizes and selects the target bus based on the path cross response amount, analyzes the voltage change and load fluctuation of ten consecutive monitoring cycles, compares the load change and voltage change of each cycle, selects the deviation amplitude key points in the trend fitting, and obtains the voltage trend offset characteristics; The feedforward judgment module determines the overlap with the current interval of the tap transformer gear control unit based on the voltage trend offset characteristics, selects the time period in the predicted trajectory that exceeds the current adjustment interval, compares the difference between the load average amplitude and the voltage change, and obtains the adjustment risk warning parameter.

[0006] On the other hand, the key feature level of the disturbance includes the abnormal fluctuation amplitude, stable change direction, and monitoring cycle label; the path cross response quantity includes the number of bus intersections, response delay distribution, and node correlation strength; the voltage trend offset feature includes the fitting trend amplitude, cycle offset status, and load response characteristics; the adjustment risk warning parameters include interval coverage status, risk difference level, and abnormal warning mark.

[0007] On the other hand, the disturbance identification module includes: The data acquisition submodule is based on the substation voltage monitoring equipment. It analyzes three consecutive cycles of voltage sampling data, compares the time distribution characteristics of the voltage curve within each cycle, determines whether each sampling segment is continuous and representative, and generates a periodic sampling voltage sequence. The slope analysis submodule calculates the rate of change between the end and start voltages of each voltage sequence between adjacent cycles based on the periodic sampling voltage sequence, compares the amplitude differences of the rate changes, identifies data combinations with obvious fluctuation characteristics, and obtains the slope amplitude range; The direction consistency determination submodule calls the slope amplitude interval to determine whether the direction of voltage change between adjacent cycles continues to rise or fall, and selects the sections with continuous and consistent directions and critical fluctuation amplitudes to obtain the key feature level of the disturbance.

[0008] On the other hand, the path response module includes: The data screening submodule analyzes the bus monitoring data at the corresponding moment based on the disturbance key feature level, screens the bus node monitoring results in the same cycle, determines whether each data segment has integrity and continuity, and arranges them in chronological order to obtain a bus time series monitoring sequence; The sequential comparison submodule calls the bus timing monitoring sequence, compares the order of occurrence of each group of bus monitoring signals, analyzes the response time intervals between different nodes, determines whether each response interval falls within the reference range, selects nodes that meet the requirements, and obtains the bus response interval distribution; The cross-node response submodule analyzes the path length of each node and the connection status of each node in the network based on the bus response interval distribution, determines the number of intersection nodes on the path corresponding to the disturbance level, integrates the bus network topology relationship, and obtains the path cross response amount.

[0009] On the other hand, the trend prediction module includes: The target screening submodule screens target buses with correlation characteristics based on the path cross response amount, organizes the voltage and load data of the target buses within ten consecutive monitoring cycles, completes data collection in cycle order, and obtains a cycle bus data set; The trend analysis submodule analyzes the corresponding relationship between load change and voltage change in each cycle based on the periodic bus data set, compares the synchronous change of voltage and load in each cycle, and classifies the fluctuation state of the difference time period to obtain the trend correspondence distribution; The key point screening submodule determines the periodic data in the trend correspondence distribution, screens the periodic key points with obvious fluctuation amplitude deviation in the trend fitting analysis, and identifies their positions and change states in the monitoring sequence to obtain voltage trend offset characteristics.

[0010] On the other hand, the screening is to identify the key points of the period where the fluctuation amplitude deviates significantly in the trend fitting analysis, and to identify their position and change status in the monitoring sequence, using the formula: ; Calculate the periodic fluctuation deviation value to obtain the voltage trend deviation characteristics, where: Representative The fluctuation deviation value of the key points of each period, Represents the monitoring sequence The voltage value at the key point of each cycle, Represents the mean value of the voltage value at the key points of the cycle in the trend fitting analysis, Represents the total number of cycle key points, Represents the monitoring sequence The voltage value at the key point of each cycle.

[0011] On the other hand, the feedforward judgment module includes: The interval judgment submodule judges the coverage of the offset feature within the current adjustment range of the tap transformer gear control unit based on the voltage trend offset feature, selects overlapping voltage change segments, and integrates the corresponding time series according to the segment order to obtain an interval coverage sequence; The trajectory screening submodule screens the time periods where the predicted trajectory continuously exceeds the current regulation interval according to the interval coverage sequence, analyzes the voltage fluctuation and load change trends within the section, summarizes the change characteristics of the difference section, and obtains the trajectory offset section; The risk parameter generation submodule compares the difference between the load average amplitude and the voltage prediction change in the trajectory deviation section, determines the corresponding relationship between the load and voltage changes in the key section, and integrates the fluctuation data of each section to obtain the adjustment risk warning parameter.

[0012] On the other hand, the difference between the load average amplitude and the voltage prediction change in the trajectory offset section is calculated using the formula: ; Determine the corresponding relationship between load and voltage changes in key sections, and integrate the fluctuation data of each section to obtain the adjustment risk warning parameters, among which, Representative A composite indicator of the difference between the load average amplitude and the voltage prediction change within a trajectory deviation section, Representative The average value of the load amplitude at all sampling moments in the trajectory deviation section, Representative The average value of the voltage prediction change at all sampling moments within the trajectory offset segment, Representative The first track in the deviation section The load average amplitude at each sampling moment, Representative The first track in the deviation section The predicted voltage change at each sampling moment, Representative The total number of sampling moments in the trajectory deviation segment, Representative The i-th sampling moment in the segment.

[0013] In another aspect, the system further comprises: The gear adjustment module adjusts the gear of the tap transformer based on the adjustment risk warning parameter, analyzes the change range of the target gear in the current cycle, selects the target gear with the optimal change range, executes the switch, and collects the maximum bus voltage range in the switching cycle to obtain the gear switching response range; The gear switching response amplitude includes a gear change amplitude, a voltage response amplitude, and a periodic response interval.

[0014] On the other hand, the gear adjustment module includes: The gear adjustment submodule determines the relationship between the current gear of the tap transformer and the risk characteristics based on the adjustment risk warning parameters, optimizes the gear adjustment configuration, adjusts the available gears according to the periodic data, screens the switchable target gears, and obtains the gear change range; The target comparison submodule compares the change characteristics of the corresponding target gears within the cycle based on the gear change amplitude, analyzes the response performance of each target gear, selects the target gear with the best change amplitude performance, and obtains the gear response difference; The switching response acquisition submodule performs the optimal target gear switching based on the gear response difference, collects the bus voltage change during the switching cycle, and analyzes the voltage fluctuation range to obtain the gear switching response amplitude.

[0015] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: By correlating slope changes with directional characteristics, agile identification of voltage disturbances is achieved. Combined with the response timing and spatial distribution of bus network nodes, structured path perception of disturbance propagation is constructed, which can identify dynamic cross-influences within multi-node networks. By comparing the periodic trends of load and voltage, forward-looking insights into the evolution trajectory of voltage anomalies are achieved. Before any adjustment action is taken, risk assessment is carried out and early warning information is generated in advance based on the difference between the adjustable range of the equipment and the predicted trajectory. Based on the multi-dimensional comparison of the current gear and the system status, the adjustment gear is optimized to improve the fit of the adjustment. Through multi-dimensional parameter linkage and dynamic trend analysis, the system's rapid response capability to complex load fluctuations and new energy access is enhanced, thereby improving the initiative, intelligence level and overall stability of voltage quality management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A schematic diagram of the system of the present invention; Figure 2 Schematic diagram of the system framework of the present invention; Figure 3 This is a flow chart of the disturbance identification module of the present invention; Figure 4 This is a flow chart of the path response module of the present invention; Figure 5 is a flow chart of the trend prediction module of the present invention; Figure 6 This is a flow chart of the feedforward judgment module of the present invention; Figure 7 This is a flow chart of the gear adjustment module of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0020] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same. The terms "of," "corresponding," and "corresponding" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same.

[0021] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0022] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0023] The embodiment of the present invention provides an intelligent regulation and management system for power voltage control, such as Figure 1 As shown, the system includes: The disturbance identification module, based on substation voltage monitoring equipment, analyzes voltage data sampled over three consecutive cycles, calculates the voltage slope between adjacent cycles, determines the direction of change for each set of slopes, compares the amplitude difference between the maximum and minimum slopes, and determines whether the slope directions are consistent. By screening data segments with both key amplitude changes and consistent directions, the key feature level of the disturbance is determined. The path response module screens the bus monitoring data at the corresponding moment based on the key feature level of the disturbance, compares the order of the bus response signals, and determines whether the response interval is within the reference range. It then combines the path length of each node with the disturbance level and the number of nodes that the path intersects to obtain the path cross response amount. The trend prediction module optimizes and selects target buses based on the path cross-response quantity, analyzes the voltage change and load fluctuation curves of the target buses for ten consecutive monitoring cycles, compares the correspondence between load change and voltage change in each cycle, selects key points with significant deviations in the trend fitting analysis, and obtains the voltage trend offset characteristics; The feedforward judgment module, based on the voltage trend deviation characteristics, determines the overlap with the current range of the tap transformer gear control unit, selects the time period in the predicted trajectory that continuously exceeds the current regulation range, compares the difference between the load average amplitude and the predicted voltage change within the range, and obtains the regulation risk warning parameter; The gear adjustment module adjusts the tap transformer gear based on the adjustment risk warning parameters, analyzes the change range of the adjustable target gear in the current cycle, compares the optional target gears, selects the target gear with the optimal change range, and executes the switch. It then collects the maximum amplitude of the bus voltage in the switching cycle to obtain the gear switching response amplitude.

[0024] The key feature levels of disturbances include abnormal fluctuation amplitude, stable change direction, and monitoring cycle labels; path cross response quantities include the number of busbar intersections, response delay distribution, and node correlation strength; voltage trend offset characteristics include fitting trend amplitude, cycle offset status, and load response characteristics; adjustment risk warning parameters include interval coverage status, risk difference level, and abnormal warning mark; gear switching response amplitude includes gear change amplitude, voltage response amplitude, and cycle response interval.

[0025] The voltage slope refers to the rate of change of the substation node voltage over time within two consecutive sampling periods, that is, the change in voltage per unit time, which reflects the speed of voltage change; the amplitude difference refers to the difference between the maximum slope and the minimum slope in the voltage slope of multiple periods, which is used to measure the severity of the voltage change within this period; the slope direction refers to the changing trend of the voltage slope, whether it is positive (increasing) or negative (decreasing), which determines the continuity of voltage rise or fall in different periods. Bus monitoring data refers to real-time sampling of parameters such as voltage and current at each bus node in the power system, and is an important basis for determining the propagation of disturbances in the network. The response interval refers to the time difference between different bus monitoring points detecting the same voltage disturbance signal, and is used to analyze the speed and order of disturbance propagation in the power grid. The reference range refers to the pre-set numerical interval used to determine whether the bus response time interval is reasonable, and is used to screen effective response signals. Each node refers to the various monitoring points or measurement units distributed in the power system bus network, which are used for multi-point synchronous monitoring of electrical parameters. Path intersection nodes refer to network nodes in the power grid topology where different buses or branches are interconnected and signals intersect. Nodes have a key influence on the propagation characteristics of disturbances. Trend fitting analysis refers to the analysis of voltage trends over time or load changes by mathematically fitting the voltage change and load fluctuation data of the target bus over a period of time, and identifying abnormal points that deviate from the normal trend. The tap transformer gear control unit refers to a transformer control device with gear adjustment function, which can adjust the transformer tap according to system instructions to achieve fine voltage regulation; the predicted trajectory refers to the expected path or sequence of voltage changes in the future period generated by the trend prediction module, which is used to determine whether subsequent adjustment operations are required.

[0026] like Figure 2 and Figure 3 As shown, the disturbance identification module includes: The data acquisition submodule is based on the substation voltage monitoring equipment. It analyzes three consecutive cycles of voltage sampling data, compares the time distribution characteristics of the voltage curve within each cycle, determines whether each sampling segment is continuous and representative, and generates a periodic sampling voltage sequence. At the substation, the busbar voltage is sampled and a voltage value is automatically recorded at very short intervals. Hundreds of data points are continuously collected in one cycle. All sampled values in three cycles are integrated into a time series list. The specific time corresponding to each sampling point is recorded separately. The sampling time intervals in three consecutive cycles are compared to see if they are basically consistent. If the first data sample of the first cycle is at 0.00 seconds, the first data sample of the second cycle is at 0.02 seconds, and the first data sample of the third cycle is at 0.04 seconds, the sampling is considered continuous. If it is found that a sampling point is missing at some time in a cycle due to network fluctuations or equipment problems, and the interval is greater than the normal time interval, the sampling time interval is calculated based on the sampling interval. When the interval is half, the discontinuous data segments are removed, and only the data segments with the same time interval in each cycle are retained. Then, the number of sampling points in each cycle is checked to see if it is the same. If only 190 data are collected in one cycle and 200 in others, the system automatically discards the missing cycle and only saves the sequence with 200 data in three cycles. For substation bus A, the three cycles of a certain sampling record data of 220.5, 220.7, and 221.2 volts respectively. If data is missing, the corresponding segment is removed so that the remaining sequence completely covers the three cycle times. Finally, the sampling point screening and merging process is completed to form a periodic sampling voltage sequence for analysis.

[0027] The slope analysis submodule calculates the rate of change between the end and start voltages of each voltage sequence between adjacent cycles based on the periodic sampling voltage sequence, compares the amplitude differences of the rate changes, identifies data combinations with obvious fluctuation characteristics, and obtains the slope amplitude range; For each filtered voltage sequence, the voltage difference between the last data point and the first data point of the first and second cycles is calculated. The voltage change amplitude is compared with the time interval between the two cycles to convert it into the voltage change rate per unit time. The same step is repeated for the second and third cycles, subtracting the larger of the two rates from the smaller. If the difference exceeds a pre-set standard threshold, such as exceeding 10 volts per second, the fluctuation is considered significant. Based on experience with different busbar locations and power flow directions in the power grid, the system sets the fluctuation threshold for the main bus at 12 volts per second and for the branch bus at 8 volts per second. For example, if the voltage rate from the first cycle to the second cycle is 13 volts per second and from the second to the third cycle is 1.5 volts per second, the difference is 11.5 volts per second, exceeding the 10 volts per second threshold. Therefore, this data segment is recorded as a data combination with obvious voltage fluctuation characteristics. The system assigns each set of analysis results to a corresponding fluctuation amplitude range, such as 0 to 5, 5 to 10, or 10 to 15 volts per second. Finally, the fluctuation amplitude range of each data segment is calculated to complete the selection of data segments with fluctuation characteristics.

[0028] The direction consistency determination submodule uses the slope amplitude interval to determine whether the direction of voltage change between adjacent cycles is continuously rising or falling. It selects the sections with continuous and consistent direction and critical fluctuation amplitude to obtain the key feature level of the disturbance. For each group of voltage change rate data segments obtained by screening, the voltage change trend of two consecutive cycles is judged in turn. If the first cycle and the second cycle are both rising, or both cycles are falling, the direction is considered to be consistent. If the first cycle is rising and the second cycle is falling, or vice versa, the direction is considered inconsistent. The system only screens out data segments with consistent direction and previously determined to be significant fluctuations as key disturbance features. For example, the voltage rate from the first to the second cycle is 13 volts per second, and from the second to the third cycle is 12 volts per second. Both are positive and consistent in direction, and the rate difference is only 1 volt per second, which does not exceed 10 volts per second. They are not considered key disturbances. If the first to the second cycle is 13 volts per second and the second to the third cycle is 1 volt per second, although the direction is consistent, the difference is 12 volts per second, which exceeds the standard. In this case, it will be marked as a key feature segment. If the voltage rate of two consecutive cycles is one positive and the other negative, that is, the trends are opposite, then the data segment is not selected. In this way, the system completes the direction consistency judgment and outputs the data segments with consistent direction and critical fluctuation amplitude as the disturbance key feature level.

[0029] like Figure 2 and Figure 4 As shown, the path response module includes: The data screening submodule analyzes the bus monitoring data at the corresponding moment based on the disturbance key feature level, screens the bus node monitoring results within the same cycle, determines whether each data segment has integrity and continuity, and arranges them in chronological order to obtain the bus time series monitoring sequence; According to the specific time point when the disturbance occurs, the voltage and current real-time data of all bus nodes at the corresponding time are retrieved on the whole station monitoring platform, and all bus monitoring data belonging to the same cycle are aggregated. For each bus monitoring point, the integrity of the data in the cycle is checked. For example, the standard requires that there should be 200 sampling points in a cycle. If it is found that the number of sampling points of a bus node in a certain cycle is less than 190, the data of the node is considered incomplete and automatically eliminated. The intervals between the sampling moments of each cycle sampling data are further verified to ensure that the time interval between consecutive data points is always the fixed sampling cycle interval. If there is an abnormal time interval, the abnormal point and all subsequent data are excluded, and only the data without abnormal time interval is retained. For interrupted continuous data segments, when disturbances occur simultaneously on bus A, bus B, and bus C, the system will sort the voltage sampling data of the three within the same period separately, and arrange each set of data in order from early to late according to the time of occurrence. For example, bus A fluctuates at 12:00:01.00, bus B at 12:00:01.04, and bus C at 12:00:01.08. It is confirmed that the arrangement order of the three sets of sampling data within the same period is not missing. If bus B has only 195 sampling points in a certain period, its data segment will be eliminated, and only the complete data of A and C will be retained, forming a bus timing monitoring sequence with strict time sequence correspondence and the sampling interval of each data segment completely matching the number of data points.

[0030] The sequential comparison submodule calls the bus timing monitoring sequence, compares the order of appearance of each group of bus monitoring signals, analyzes the response time intervals between different nodes, determines whether each response interval falls within the reference range, selects nodes that meet the requirements, and obtains the bus response interval distribution; After receiving the bus timing monitoring sequence, first compare the acquisition time of each set of bus data one by one according to the timestamp, arrange the first appearance time of the voltage disturbance signal of different bus nodes, confirm the specific time when bus A, B, C and other nodes each first detect the disturbance signal, compare the order of each node, and then calculate the time difference of the disturbance response signal between any two buses. For example, bus A detects the disturbance at 12:00:01.00, bus B at 12:00:01.04, and the response time interval between A and B is 0.04 seconds. Count the response intervals between all nodes and compare the statistical results with the pre-set reference range. The range is usually set according to actual engineering experience. For example, the reasonable response interval between trunk buses is set to 0 to 0.05 seconds, and that of branch buses is set to 0 to 0.10 seconds. If the response interval between two nodes falls within the reference interval, the response is determined to be valid. If it exceeds the interval, it is considered an abnormal response and is not adopted. For example, the response interval between buses A and B is 0.04 seconds, which is within the reference range of the trunk bus and is determined to be a valid response. Bus C detects a disturbance at 12:00:01.20, and the interval with A is 0.20 seconds, which exceeds the reference range of the trunk bus and is automatically eliminated. All nodes that pass the screening are arranged in order to obtain the bus response interval distribution of each node within the reference interval.

[0031] The cross-node response submodule analyzes the path length of each node and the connection status of each node in the network based on the bus response interval distribution, determines the number of intersection nodes on the path corresponding to the disturbance level, integrates the bus network topology, and obtains the path cross response amount; First, the physical distance between the starting and ending busbars of each disturbance signal's propagation path in the network is read. Combined with the power system topology database, the actual path length between each busbar node is determined. All nodes traversed along each path are searched and recorded one by one. For nodes where multiple paths intersect—that is, where the response data from multiple busbar nodes appear synchronously or nearly synchronously at the same time—the system counts the number of intersecting nodes along a path corresponding to a disturbance level, based on their node numbers. If the disturbances on buses A, B, and C all briefly overlap at node X, this is recorded as a cross-response. The system then retrieves the number of intersecting nodes along each path and counts their frequency of occurrence. For different busbar topologies, the typical spacing between trunk busbar nodes in actual projects is 500 meters, and between branch busbars is 200 meters. Combining their physical lengths and busbar network connectivity, the system compiles and outputs the statistical count of intersecting nodes along each path as the disturbance signal propagates throughout the network, forming a path cross-response corresponding to the disturbance level.

[0032] like Figure 2 and Figure 5 As shown, the trend forecast module includes: The target screening submodule selects target buses with correlation characteristics based on the path cross-response quantity, organizes the voltage and load data of the target buses within ten consecutive monitoring cycles, completes data collection in cycle order, and obtains the cycle bus data set; First, read the path intersection node data corresponding to each disturbance level, and search for all bus nodes closely related to the path intersection node in the power network diagram. For each intersection node, the bus directly or indirectly connected to it is used as an alternative target bus. By counting the number and duration of voltage disturbance responses of each bus at the intersection node, the bus with a frequency higher than the set reference value is screened out. In actual scenarios, the system can set the frequency reference value to a disturbance response of no less than three times within ten cycles. If a bus has a disturbance response with the intersection node five times in ten cycles, it is judged as an associated bus and the bus is added to the target bus list. For each bus in the target bus list, the system automatically captures its voltage data and load data within ten consecutive cycles. The voltage of each cycle The voltage data is the maximum, minimum, and average values within the sampling period, and the load data is the average value of the active power and reactive power within the same period. For example, in ten periods of bus A, the maximum voltage is 220.2, 220.0, 219.8, 220.4, 220.1, 219.9, 220.3, 220.5, 220.2, and 220.0 volts, respectively, and the average load is 450, 460, 445, 470, 455, 460, 465, 468, 460, and 457 kilowatts. The data of all periods are classified and arranged in chronological order according to the period sequence to ensure data continuity. The voltage and load data of each bus within ten consecutive periods are sorted to obtain the complete sampling value of each period, which is compiled into a periodic bus data set.

[0033] The trend analysis submodule analyzes the corresponding relationship between load change and voltage change in each cycle based on the periodic bus data set, compares the synchronous changes of voltage and load in each cycle, and classifies the fluctuation state of the difference period to obtain the trend correspondence distribution; After obtaining the periodic bus data set, first call the voltage mean and load mean within each period respectively, and pair the two period by period according to the time series. For each period, directly compare the change amplitude of the voltage and load in the period to determine the positive and negative increase and decrease relationship. If the voltage in this period increases compared with the previous period and the load also increases, it is recorded as synchronous positive correlation. If the voltage decreases and the load also decreases, it is also recorded as synchronous positive correlation. If the voltage increases and the load decreases, or the voltage decreases and the load increases, it is recorded as anti-correlation. For example, from period 1 to period 2, the voltage increases from 220.2 to 220.4, and the load increases from 450 to 470, which is determined to be synchronous positive correlation. From period 3 to period 4, the voltage decreases from 220.4 to 2 20.1, the load dropped from 470 to 455, which is also a synchronous positive correlation. From period 4 to period 5, the voltage increased from 220.1 to 220.5, and the load dropped from 455 to 445, which is recorded as anti-correlation. For all period pairs within ten periods, the above comparative statistics are completed one by one, all positively correlated and anti-correlated data segments are marked, and then the duration of positive and anti-correlated periods are classified, and the length of consecutive positive and anti-correlated periods is counted. Special marks are made for anti-correlated periods that appear for more than two consecutive periods. In practice, a distinction threshold can be set. If the voltage or load change is less than 0.1 volt or less than 2 kilowatts, it is considered that the change is not significant and is not included in the relevant statistics. The trend correspondence distribution within all periods is output.

[0034] The key point screening submodule determines the periodic data in the trend correspondence distribution, screens the periodic key points with obvious fluctuation amplitude deviation in the trend fitting analysis, and identifies their position and change status in the monitoring sequence to obtain the voltage trend offset characteristics; Screen out the key points of the cycle where the fluctuation amplitude deviates significantly in the trend fitting analysis, and identify their position and change status in the monitoring sequence, using the formula: ; Calculate the periodic fluctuation deviation value to obtain the voltage trend deviation characteristics, where: Representative The fluctuation deviation value of the key point of each cycle is used to measure the voltage fluctuation deviation degree of the cycle. Represents the monitoring sequence The voltage value of the key point of each cycle, that is, the voltage measurement value of the corresponding cycle in the sequence, Represents the mean value of the voltage values at the key points of the cycle in the trend fitting analysis, which is used as the benchmark value to calculate the deviation. Represents the total number of cycle key points, Represents the monitoring sequence Voltage value at key points of each cycle; Assume that the voltage data (unit: volt) at the following key points in the cycle are obtained from the power monitoring system: , , , , ; Data is collected periodically in the power system by voltage sensors with a sampling frequency of 1 Hz and a sampling period of 1 second. The mean voltage values at key points in the period used in the trend fitting analysis are calculated as follows: ; Calculate the volatility deviation value of the key point of the third period: ; Calculate the molecular part: ; Calculate the sum of squares part: ; ; ; Calculate the denominator: ; Substitute the above calculation results into the formula: ; The results show that the fluctuation deviation value of the key point of the third cycle is 0.000261, which means that the voltage fluctuation amplitude of this cycle deviates less from the average voltage value in the trend fitting analysis.

[0035] Parameter setting basis: Voltage data The acquisition frequency and period are determined by the design and requirements of the power monitoring system and are usually set to 1Hz to ensure that the details of voltage fluctuations can be captured; Mean in Trend Fitting Analysis It is obtained by performing trend analysis on the collected voltage data, fitting the trend line using the least squares method, and calculating the average voltage value of the trend line; The total number of period key points It is determined by the number of periodic key points in the monitoring sequence that are selected for calculation, and is usually selected based on the periodicity of the data and the analysis requirements.

[0036] like Figure 2 and Figure 6 As shown, the feedforward judgment module includes: The interval judgment submodule determines the coverage of the voltage trend offset feature within the current adjustment range of the tap transformer gear control unit based on the voltage trend offset feature, selects overlapping voltage change segments, and integrates the corresponding time series according to the segment order to obtain the interval coverage sequence; First, the offset feature data for all key cycles is acquired. For each offset feature, the upper and lower voltage limits of the current actual adjustment range of the tap transformer's gear control unit are retrieved. For example, the current gear adjustment range is 219.5 volts to 221.5 volts. The voltage extremes of each cycle's offset feature are then compared with the upper and lower limits of the adjustment range. Data for cycles with voltage extremes falling within this range are directly marked as covered segments. Data falling outside this range is not collected by the system, and only the overlapping segments are recorded. The system then extracts the cycle numbers and specific timing information for all marked covered cycles, sorts them from smallest to largest, and aggregates all interval coverage cycles within a continuous time period to form an interval coverage sequence for each continuous time period. For example, if the offset feature voltages in cycles 3, 4, and 5 are 220.8, 220.3, and 221.0 volts, respectively, all falling within the gear adjustment range, cycles 3-5 are merged into an interval coverage sequence. The start cycle, end cycle, and specific time point information of this sequence are automatically output and organized into an interval coverage sequence.

[0037] The trajectory screening submodule selects the time periods where the predicted trajectory continuously exceeds the current regulation interval based on the interval coverage sequence, analyzes the voltage fluctuation and load change trends within the section, summarizes the change characteristics of the difference section, and obtains the trajectory offset segment; The system then calls up the voltage prediction trajectory data corresponding to all interval coverage sequences and compares each continuous time segment of the prediction trajectory with the duration of the current adjustment interval of the tap changer. For any time segments in the prediction trajectory that continuously exceed the duration of the current adjustment interval, the system marks them as exceeding the interval. For example, if the maximum allowable duration of the current adjustment interval of the tap changer is 2 seconds, and a segment of the prediction trajectory is outside this interval for 3.5 consecutive seconds, then this 3.5-second segment is selected as a trajectory offset segment. The system then analyzes the voltage change trend and load data within each trajectory offset segment, statistically analyzing the voltage fluctuation amplitude and load change trend within each cycle to determine whether the voltage within the offset segment shows a continuous rise, continuous fall, or rapid fluctuation, and whether the load change trend is consistent with or opposite to the voltage change. In practice, if the load fluctuation amplitude within the trajectory offset segment exceeds 10 kilowatts and the voltage fluctuation amplitude exceeds 0.4 volts, the segment is considered to have a significant difference. The system then integrates the change characteristics of each difference segment in chronological order, outputting the start and end periods, duration, and fluctuation description of each trajectory offset segment to form the complete trajectory offset segment.

[0038] The risk parameter generation submodule compares the difference between the load average amplitude and the voltage prediction change within the trajectory deviation segment, determines the corresponding relationship between load and voltage changes in the key section, and integrates the fluctuation data of each section to obtain the adjustment risk warning parameters; The difference between the load average and the voltage prediction change during the trajectory offset segment is calculated using the formula: ; Determine the corresponding relationship between load and voltage changes in key sections, and integrate the fluctuation data of each section to obtain the adjustment risk warning parameters, among which, Representative The composite index of the gap between the load average amplitude and the voltage prediction change in the trajectory deviation section is used to measure the The overall difference between the load average and voltage prediction change data in the trajectory deviation section is Representative The average value of the load amplitude at all sampling moments in the trajectory deviation section, Representative The average value of the voltage prediction change at all sampling moments within the trajectory offset segment, Representative The first track in the deviation section The load average amplitude at each sampling moment, Representative The first track in the deviation section The predicted voltage change at each sampling moment, Representative The total number of sampling moments in the trajectory deviation segment, Representative The i-th sampling moment in the segment; : A composite indicator representing the difference between the average load amplitude and the predicted voltage change within the k-th trajectory offset segment. By calculating the difference in load and voltage changes at each sampling moment and combining the information of all sampling points in the segment, the overall change difference level of the segment is obtained.

[0039] : The average value of the load amplitude at all sampling moments in the k-th trajectory offset segment, which is calculated by the arithmetic mean of all sampling values in the segment.

[0040] : The average value of the predicted voltage change at all sampling moments within the k-th trajectory offset segment, similar to the calculation method of the load average, is obtained by the arithmetic average of all sampling values in the segment.

[0041] : The average load amplitude at the i-th sampling moment in the k-th trajectory offset segment, representing the load data of the specific sampling point collected in the k-th segment.

[0042] : The predicted voltage change at the i-th sampling moment in the k-th trajectory offset segment, representing the voltage change data of the specific sampling point collected in the k-th segment.

[0043] : The total number of sampling moments in the k-th trajectory offset segment, indicating the number of sampling points in the segment, used for normalization calculation.

[0044] Calculate the average value of load amplitude and voltage variation: ; ; The average load and voltage changes are obtained by summing the average load amplitude and predicted voltage changes at all sampling moments and dividing them by the number of sampling points in the segment. The sum of the squares of the differences is calculated: The sum of the squares of the difference values of the entire segment is obtained by squaring the difference between the load average amplitude and the voltage change at each sampling moment and then summing the square differences of all sampling moments.

[0045] ; The value represents the degree of difference between the load and voltage changes at each sampling point, and the final value of the difference within the segment is calculated: Add the sum of the squares of the above differences to the square of the difference between the load average and the voltage prediction change average, and then divide it by the total number of sampling points in the segment. , get the final difference value; ; Assume that for the first trajectory deviation segment (k=1), the number of sampling moments is 3 ( ), the load average amplitude and voltage change data are as follows: Load averaging data: , , ; Voltage prediction change data: , , ; First, calculate the average value of the load amplitude and voltage variation: ; ; Compute the sum of squared differences: ; Finally, substitute the formula to calculate : ; Indicates the difference between the load average and the predicted voltage change within the first trajectory offset segment. Specifically, a larger value indicates a more significant difference between the load and voltage changes within the segment.

[0046] like Figure 2 and Figure 7 As shown, the gear adjustment module includes: The gear adjustment submodule determines the relationship between the current gear of the tap transformer and the risk characteristics based on the adjustment risk warning parameters, optimizes the gear adjustment configuration, adjusts the available gears according to the periodic data, selects the switchable target gear, and obtains the gear change range; First, read the gear number and corresponding voltage range of the current gear of the tap transformer and all available gears, compare the current gear range with the risk parameter level one by one, set the risk parameter 0 as no risk, 1 as mild risk, 2 as moderate risk, and 3 as severe risk. If the current cycle risk parameter is 2 or 3, it is judged that the current gear is not suitable for continued maintenance. Then retrieve the voltage range of each gear in the switchable gear, and count which gears' voltage range can cover the voltage offset segment. If the upper limit of the voltage range is greater than the current busbar maximum voltage offset value, and the lower limit is lower than If the busbar voltage is at the minimum offset value, the gear is determined to be a switchable target gear, and the numbers of all switchable target gears are recorded. The difference between the number of each gear and the current gear is used as the gear change amplitude. The larger the gear change amplitude, the larger the switching amplitude. For example, the current gear is 5, and the target gears can be 4 and 6. 5 to 4 is a decrease of one gear, and 5 to 6 is an increase of one gear, with a change amplitude of 1 and -1 respectively. If there is 7 gears, 5 to 7 is an increase of two gears, with a change amplitude of 2. All gear change amplitudes are sorted in sequence, and a gear change amplitude list is output.

[0047] The target comparison submodule compares the change characteristics of each target gear within the cycle based on the gear change amplitude, analyzes the response performance of each target gear, selects the target gear with the best change amplitude performance, and obtains the gear response difference; After obtaining the fluctuation amplitudes of all gears, the target comparison submodule retrieves the historical operating performance of each target gear under similar operating conditions within the cycle. It then calculates the maximum, minimum, and average bus voltage response within the first cycle after the gear switch, as well as the load fluctuation amplitude within the switching cycle. The bus voltage stability after each target gear switch is compared. If the maximum voltage fluctuation amplitude is less than 0.5V and the load fluctuation amplitude is less than 5kW, the response performance is considered excellent. Otherwise, the response performance is fair. In practice, the target gears are classified into three levels: excellent, good, and medium according to the above standards. For example, after switching to gear 6, the bus voltage fluctuation is 0.3V and the load fluctuation is 3kW, which is judged as excellent. After switching to gear 4, the voltage fluctuation is 0.6V and the load fluctuation is 7kW, which is judged as medium. The data of the change characteristics, response performance, and fluctuation amplitude of all target gears within the cycle are collected and graded according to the response performance. The target gear with the best performance is selected and designated as the optimal target. The response performance difference of each target gear is output and the optimal target gear number is marked.

[0048] The switching response acquisition submodule performs the optimal target gear switching based on the gear response difference, collects the bus voltage changes during the switching cycle, and analyzes the voltage fluctuation range to obtain the gear switching response amplitude; The switching response acquisition submodule receives the optimal target gear number, issues the tap transformer gear switching instruction, and collects all the sampling data of the bus voltage within the switching cycle in real time. First, the voltage difference between the last sampling point before the switching and the first sampling point after the switching is obtained, the maximum and minimum values of all voltage samples within the switching cycle are counted, and the maximum amplitude fluctuation is calculated. Then, the fluctuation range of the voltage sampling points within the switching cycle is compared to analyze whether the fluctuation range falls within the set gear switching response safety range. The actual voltage fluctuation safety range is set to no more than 0.8 volts. If the bus voltage collected after a gear switching varies between 220.0 volts and 220.6 volts, the maximum amplitude is 0.6 volts, which falls within the safety range. All the collected voltage points within the switching cycle are arranged in chronological order, the maximum voltage amplitude of the first cycle after the switching is marked, and the gear switching response amplitude and corresponding data sequence number of this period are output to complete the acquisition of the gear switching response amplitude.

[0049] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0050] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0051] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0052] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0053] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0054] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0055] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0056] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0057] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical disks.

[0058] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. The intelligent regulation and management system for electric power voltage control is characterized by: The system comprises: The disturbance identification module is based on the substation voltage monitoring equipment. It analyzes the voltage data of consecutive cycles, calculates the voltage slope between adjacent cycles, compares the amplitude difference between the maximum and minimum slopes, and determines the consistency of the slope direction to obtain the key feature level of the disturbance. The path response module screens the bus monitoring data at the corresponding time based on the disturbance key feature level, compares the time sequence of each bus response, determines whether the response interval is within the reference range, and combines the path length and disturbance level with the number of path intersection nodes to obtain the path cross response amount; The trend prediction module optimizes and selects the target bus based on the path cross response amount, analyzes the voltage change and load fluctuation of ten consecutive monitoring cycles, compares the load change and voltage change of each cycle, selects the deviation amplitude key points in the trend fitting, and obtains the voltage trend offset characteristics; The feedforward judgment module determines the overlap with the current interval of the tap transformer gear control unit based on the voltage trend offset characteristics, selects the time period in the predicted trajectory that exceeds the current adjustment interval, compares the difference between the load average amplitude and the voltage change, and obtains the adjustment risk warning parameter.

2. The intelligent power voltage control and management system according to claim 1, characterized in that: The key feature level of the disturbance includes abnormal fluctuation amplitude, stable change direction, and monitoring cycle label; the path cross response quantity includes the number of bus intersections, response delay distribution, and node association strength; the voltage trend offset feature includes fitting trend amplitude, cycle offset status, and load response characteristics; the adjustment risk warning parameters include interval coverage status, risk difference level, and abnormal warning mark.

3. The intelligent power voltage control and management system according to claim 1, characterized in that: The disturbance identification module includes: The data acquisition submodule is based on the substation voltage monitoring equipment. It analyzes three consecutive cycles of voltage sampling data, compares the time distribution characteristics of the voltage curve within each cycle, determines whether each sampling segment is continuous and representative, and generates a periodic sampling voltage sequence. The slope analysis submodule calculates the rate of change between the end and start voltages of each voltage sequence between adjacent cycles based on the periodic sampling voltage sequence, compares the amplitude differences of the rate changes, identifies data combinations with obvious fluctuation characteristics, and obtains the slope amplitude range; The direction consistency determination submodule calls the slope amplitude interval to determine whether the direction of voltage change between adjacent cycles continues to rise or fall, and selects the sections with continuous and consistent directions and critical fluctuation amplitudes to obtain the key feature level of the disturbance.

4. The intelligent power voltage control and management system according to claim 1, characterized in that: The path response module includes: The data screening submodule analyzes the bus monitoring data at the corresponding moment based on the disturbance key feature level, screens the bus node monitoring results in the same cycle, determines whether each data segment has integrity and continuity, and arranges them in chronological order to obtain a bus time series monitoring sequence; The sequential comparison submodule calls the bus timing monitoring sequence, compares the order of occurrence of each group of bus monitoring signals, analyzes the response time intervals between different nodes, determines whether each response interval falls within the reference range, selects nodes that meet the requirements, and obtains the bus response interval distribution; The cross-node response submodule analyzes the path length of each node and the connection status of each node in the network based on the bus response interval distribution, determines the number of intersection nodes on the path corresponding to the disturbance level, integrates the bus network topology relationship, and obtains the path cross response amount.

5. The intelligent power voltage control and management system according to claim 1, characterized in that: The trend prediction module includes: The target screening submodule screens target buses with correlation characteristics based on the path cross response amount, organizes the voltage and load data of the target buses within ten consecutive monitoring cycles, completes data collection in cycle order, and obtains a cycle bus data set; The trend analysis submodule analyzes the corresponding relationship between load change and voltage change in each cycle based on the periodic bus data set, compares the synchronous change of voltage and load in each cycle, and classifies the fluctuation state of the difference time period to obtain the trend correspondence distribution; The key point screening submodule determines the periodic data in the trend correspondence distribution, screens the periodic key points with obvious fluctuation amplitude deviation in the trend fitting analysis, and identifies their positions and change states in the monitoring sequence to obtain voltage trend offset characteristics.

6. The intelligent power voltage control and management system according to claim 5, characterized in that: The screening process is to find the key points of the period where the fluctuation amplitude deviates significantly in the trend fitting analysis, and to identify their positions and change states in the monitoring sequence, using the formula: ； Calculate the periodic fluctuation deviation value to obtain the voltage trend deviation characteristics, where: Representative The fluctuation deviation value of the key points of each period, Represents the monitoring sequence The voltage value at the key point of each cycle, Represents the mean value of the voltage value at the key points of the cycle in the trend fitting analysis, Represents the total number of cycle key points, Represents the monitoring sequence The voltage value at the key point of each cycle.

7. The intelligent power voltage control and management system according to claim 1, characterized in that: The feedforward judgment module includes: The interval judgment submodule judges the coverage of the offset feature within the current adjustment range of the tap transformer gear control unit based on the voltage trend offset feature, selects overlapping voltage change segments, and integrates the corresponding time series according to the segment order to obtain an interval coverage sequence; The trajectory screening submodule screens the time periods where the predicted trajectory continuously exceeds the current regulation interval according to the interval coverage sequence, analyzes the voltage fluctuation and load change trends within the section, summarizes the change characteristics of the difference section, and obtains the trajectory offset section; The risk parameter generation submodule compares the difference between the load average amplitude and the voltage prediction change in the trajectory deviation section, determines the corresponding relationship between the load and voltage changes in the key section, and integrates the fluctuation data of each section to obtain the adjustment risk warning parameter.

8. The intelligent power voltage control and management system according to claim 7, characterized in that: The difference between the load average amplitude and the voltage prediction change in the trajectory offset section is calculated using the formula: ； Determine the corresponding relationship between load and voltage changes in key sections, and integrate the fluctuation data of each section to obtain the adjustment risk warning parameters, among which, Representative A composite indicator of the difference between the load average amplitude and the voltage prediction change within a trajectory deviation section, Representative The average value of the load amplitude at all sampling moments in the trajectory deviation section, Representative The average value of the voltage prediction change at all sampling moments within the trajectory offset segment, Representative The first track in the deviation section The load average amplitude at each sampling moment, Representative The first track in the deviation section The predicted voltage change at each sampling moment, Representative The total number of sampling moments in the trajectory deviation segment, Representative The i-th sampling moment in the segment.

9. The intelligent power voltage control and management system according to claim 1, characterized in that: The system further comprises: The gear adjustment module adjusts the gear of the tap transformer based on the adjustment risk warning parameter, analyzes the change range of the target gear in the current cycle, selects the target gear with the optimal change range, executes the switch, and collects the maximum bus voltage range in the switching cycle to obtain the gear switching response range; The gear switching response amplitude includes a gear change amplitude, a voltage response amplitude, and a periodic response interval.

10. The intelligent power voltage control and management system according to claim 9, characterized in that: The gear adjustment module includes: The gear adjustment submodule determines the relationship between the current gear of the tap transformer and the risk characteristics based on the adjustment risk warning parameters, optimizes the gear adjustment configuration, adjusts the available gears according to the periodic data, screens the switchable target gears, and obtains the gear change range; The target comparison submodule compares the change characteristics of the corresponding target gears within the cycle based on the gear change amplitude, analyzes the response performance of each target gear, selects the target gear with the best change amplitude performance, and obtains the gear response difference; The switching response acquisition submodule performs the optimal target gear switching based on the gear response difference, collects the bus voltage change during the switching cycle, and analyzes the voltage fluctuation range to obtain the gear switching response amplitude.

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