Test system for new energy power access scenarios

Abstract

The present application relates to the technical field of electric power test, specifically to a test system for new energy power access scene, which comprises an electric parameter data module, a fluctuation extraction module, a stability determination module, an adaptive analysis module and a test conclusion module.In the present application, the signal change range of the new energy power generation equipment access node is structured and sorted through the screening of the boundary set, the joint constraint identification of core parameters such as voltage frequency and power factor is realized, the multi-parameter co-occurrence relationship is captured by means of the periodic change extraction and synchronization screening mechanism, the interaction relationship between the fluctuation sections is effectively described, the determination standard of the unstable interval is refined through the linkage analysis of the response offset time and the signal persistence relationship, the continuity stability atlas is established, the unstable response repeated area is identified by means of the cross mapping of the equipment type and the node number, the equipment response behavior during the test is summarized, and the visual evaluation of the equipment operation consistency and the stable adaptive ability is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power testing, in particular to a test system for a new energy power access scenario. BACKGROUND

[0002] The technical field of power testing mainly involves testing and evaluation for power systems, devices, and power quality. It covers performance verification of power devices, load testing, stability analysis of power transmission and distribution systems, etc. With the continuous development of power systems, especially the increase of new energy access, power testing technology has gradually expanded to smart grids, distributed energy, and new energy power generation devices, aiming to ensure the reliability and safety of power systems. Among them, the test system for new energy power access scenario refers to the performance testing of new energy power generation devices connected to the power grid through fixed test equipment. It mainly includes the detection of output power, power quality, stability and other parameters of new energy devices such as wind power and solar power, to ensure compliance with the access requirements of the power system. Customized measuring instruments are usually used, equipped with power quality analyzers, current and voltage measuring instruments, and data acquisition devices, to test various loads, frequencies and power factors of new energy devices connected to the power grid, and verify their performance and grid matching.

[0003] In the existing test process of new energy power access scenario, traditional test equipment is mainly used for static parameter measurement and power quality analysis of new energy power generation devices. In the face of frequent fluctuations and multi-node grid connection scenarios, there is a lack of systematic identification means for multi-parameter synchronous fluctuations and their periodic change trends, making it difficult to accurately extract the causes and evolution paths of fluctuations, and easily leading to the neglect of some short-term instability phenomena. In complex access environments, it is difficult to track the overlapping response of devices between multiple nodes, causing some devices to have insufficient adaptability problems that have not been discovered for a long time. Especially in the process of frequent participation of wind or photovoltaic power generation devices in load regulation, stability evaluation cannot reflect the full picture of dynamic response, affecting the comprehensiveness and accuracy of power grid access evaluation. SUMMARY

[0004] To solve the technical problems existing in the prior art, the present application provides a test system for a new energy power access scenario. The technical solution is as follows:

[0005] On the one hand, a test system for a new energy power access scenario is provided, which includes:

[0006] The electric parameter data module obtains the voltage time sequence, frequency time sequence and power factor time sequence of the new energy power generation device access node, obtains the instantaneous signal sequence, combines the maximum change range at different times to screen the signal fluctuation boundary data, and generates three types of fluctuation boundary sets;

[0007] The fluctuation extraction module extracts a periodic characteristic change range according to the voltage and frequency time period signal sequence in the three types of fluctuation boundary set, filters fluctuation co-occurrence sections according to signal synchronicity, and correlates corresponding power factor change trajectories to generate a fluctuation co-occurrence section set;

[0008] The stability determination module extracts frequency trajectory and power factor trajectory time sequences according to the fluctuation co-occurrence section set, detects response offset time between trajectories, determines unstable intervals through offset time and signal persistence relationship, records all unstable intervals and marks distribution range in the overall time sequence, and generates an unstable distribution atlas;

[0009] The adaptive analysis module covers time periods based on the unstable distribution atlas, retrieves new energy equipment types and corresponding access node numbers in the corresponding time period, analyzes unstable response overlap of the same type of equipment on multiple access nodes, and generates a repeated response number list.

[0010] As a further scheme of the application, the three types of fluctuation boundary set include voltage fluctuation boundary, frequency fluctuation boundary, and power factor fluctuation boundary, the fluctuation co-occurrence section set includes periodic change section, voltage frequency synchronous section, and power factor correlation section, the unstable distribution atlas includes response offset section distribution graph, trajectory offset relationship graph, and time period stability annotation graph, and the repeated response number list includes equipment type number, access node number, and unstable response overlap record.

[0011] As a further scheme of the application, the electric parameter data module includes:

[0012] The signal acquisition sub-module acquires voltage time sequence, frequency time sequence, and power factor time sequence of the new energy power generation equipment access node, acquires instantaneous signal values at each time point in each time sequence, forms an instantaneous signal sequence at a millisecond level sampling interval, detects change values between different time points in each signal sequence, extracts maximum change amplitude in each time sequence per unit time, and generates a maximum change amplitude sequence.

[0013] The fluctuation boundary filtering sub-module compares the change value of each time point in each signal time sequence with the standard voltage allowable deviation limit value, the standard frequency allowable deviation limit value, judges whether the voltage change amplitude exceeds the standard voltage allowable deviation limit value, judges whether the frequency change amplitude exceeds the standard frequency allowable deviation limit value, judges whether the power factor change amplitude exceeds the set reference threshold, filters the time points and corresponding signal values of the boundary fluctuation in each signal sequence, and generates a fluctuation signal boundary interval.

[0014] The boundary set generation submodule generates three types of fluctuation boundary sets based on the fluctuation signal boundary interval, combines the boundary interval values of voltage, frequency and power factor corresponding to each time point, performs synchronous time axis aggregation on the combined multi-dimensional boundary interval values, obtains the maximum fluctuation boundary of voltage, frequency and power factor of the new energy power generation equipment access node at different time, and generates three types of fluctuation boundary sets.

[0015] As a further scheme of the application, the fluctuation extraction module comprises:

[0016] The feature extraction submodule obtains the time period signal sequence of voltage and frequency in the three types of fluctuation boundary sets, and according to the numerical change curve in each continuous time period, the time interval and amplitude difference between adjacent wave peaks and wave troughs are counted, and if the fluctuation interval change amplitude between adjacent periodic segments is within a preset range, the periodic segment is marked, the time interval meeting the periodic change characteristic is selected, and the periodic change interval is generated.

[0017] The co-occurrence screening submodule compares whether the start and end times of the periodic change interval of voltage and frequency respectively have time coincidence one by one, sets a maximum time deviation threshold between the start and end points of the period, judges whether the two belong to the coincidence segment under the time synchronization condition, screens the time period index of the synchronous fluctuation of the two types of signals in the same time interval, eliminates the time period that does not meet the synchronization, and obtains the periodic co-occurrence segment.

[0018] The trajectory correlation submodule extracts the continuous change sequence of power factor in the time period according to the time period index corresponding to the periodic co-occurrence segment, counts the sequence fluctuation gradient and change amplitude of power factor in each time period, performs structure mapping on each co-occurrence segment and the corresponding power factor change curve, forms a one-to-one correspondence relationship between the synchronous segment and the change trajectory, integrates the correlation information of all co-occurrence segments, and generates a fluctuation co-occurrence segment set.

[0019] As a further scheme of the application, the stability determination module comprises:

[0020] The offset extraction submodule obtains the frequency trajectory and power factor trajectory corresponding to each time period in the fluctuation co-occurrence segment set, extracts the start time of the rising segment and the falling segment of each frequency change curve, extracts the start time of the change in the same direction of the power factor change curve, calculates the response start time difference of the two types of trajectories in the same direction, and if the time difference value is greater than the time response offset threshold, the offset time is recorded as the response time difference of the current segment, and the trajectory offset time is generated.

[0021] The segment identification submodule judges whether there is a phenomenon of delayed response and continuous fluctuation coinciding according to the response time difference of each segment in the trajectory offset time, in combination with the continuous duration of the power factor change in the corresponding segment, if the offset time is greater than the response delay threshold and the duration of the power factor in the continuous change state is higher than the minimum persistence reference value, the time segment is marked as an unstable segment, a mapping structure of the time interval and the unstable identification is established, and an unstable segment index is obtained;

[0022] The distribution marking submodule performs time axis marking processing on the overall time sequence based on the unstable segment index, divides the original time axis according to a set segmentation interval, judges whether there is an interval marked by the unstable segment index in each time segment, marks an unstable state in the corresponding time segment if there is, and performs visual mapping to obtain an unstable distribution map.

[0023] As a further scheme of the application, the rising segment and falling segment starting time of each frequency change curve is extracted, specifically by calculating the first derivative of the frequency change curve in time, identifying the turning point where the sign of the first derivative changes, determining the time corresponding to the turning point where the first derivative changes from negative to positive as the rising segment starting time, and determining the time corresponding to the turning point where the first derivative changes from positive to negative as the falling segment starting time; the starting time of the same direction change of the power factor change curve is extracted, specifically by synchronously calculating the first derivative of the power factor change curve at the determined rising segment starting time and falling segment starting time, and judging whether the sign of the first derivative of the power factor change curve is consistent with the sign of the first derivative of the frequency change curve at the same time point, if the signs are consistent, the time point is determined as the starting time.

[0024] As a further scheme of the application, the adaptive analysis module includes:

[0025] The device retrieval submodule extracts the time interval range of each segment based on the unstable time segments marked in the unstable distribution map, retrieves the new energy power generation device operation record in the corresponding time segment, judges each record based on the time stamp, device type and access node in the device operation record, if the time stamp of the operation record falls within the unstable time interval, the corresponding device type and access node number are extracted, and the retrieval operation of all segments is completed in turn to generate an unstable segment device number.

[0026] The response overlapping submodule classifies and aggregates according to the device type extracted from the unstable section device number and the access node number information, groups the same type of devices according to the access node, cross-compares the unstable time sections corresponding to all devices in the group, identifies the situation that the same type of devices in two or more different access nodes all appear unstable state in the same time period, and records the intersection period, device type and node number, and obtains the device response overlapping section.

[0027] The number summary submodule based on the device type, access node number and overlapping time period information identified in the device response overlapping section, de-duplicates and summarizes the device numbers of the same type of devices with overlapping response time on multiple nodes, constructs a repeated number list structure, outputs the device type, repeated response time interval and involved node number set, and generates a repeated response number list.

[0028] As a further scheme of the present application, the system further comprises:

[0029] The test conclusion module based on the device number in the repeated response number list, summarizes the information of all unstable marked time periods of the device during the test and marks, marks according to the label difference and node distribution of each device group, and generates a new energy power test record.

[0030] As a further scheme of the present application, the new energy power test record is specifically a device response label distribution record, node abnormal distribution information and test phase unstable statistical result.

[0031] As a further scheme of the present application, the test conclusion module comprises:

[0032] The information summary submodule obtains all the device numbers listed in the repeated response number list, retrieves all the unstable time periods recorded by the device during the test one by one, matches the unstable section index and timestamp corresponding to each device, and if the timestamp belongs to the unstable marked range, it is filed under the corresponding device number, and a device unstable time list is generated;

[0033] The difference marking submodule groups the records of the same type of devices on different access nodes according to the device unstable time list, extracts the device number, node number and unstable time period of each group, cross-compares the unstable time sections of each group, and labels the device groups according to the difference between different nodes. If the unstable distribution of the same type of devices between different nodes partially overlaps, it is marked as an overlapping label, and if it does not overlap at all, it is marked as a scattered label, and the node distribution label is obtained.

[0034] The record generation sub-module integrates the device number, the unstable time period and the distribution label of the node to which the device belongs based on the node distribution label, constructs a unified data table, records the device type, the access node number, the unstable time interval and the corresponding distribution label for each device group, and generates a new energy power test record.

[0035] The technical scheme provided by the embodiment of the application has at least the following beneficial effects:

[0036] The signal change range of the new energy power generation device access node is structured and sorted by screening the boundary set, the joint constraint identification of core parameters such as voltage frequency and power factor is realized, the multi-parameter co-occurrence relationship is captured by means of periodic change extraction and synchronization screening mechanism, the interaction between fluctuation sections is effectively described, the determination standard of the unstable interval is refined through the linkage analysis of the response offset time and the signal persistence relationship, the continuity stability atlas is established in the global perspective of time series, the unstable response repeated area is identified by means of the cross mapping of the device type and the node number, the device response behavior during the test is induced based on the node distribution and label difference, and the visual evaluation of the device operation consistency and stable adaptability is realized. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical scheme in the embodiment of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0038] Figure 1 It is a schematic diagram of the test system of the new energy power access scene provided by the embodiment of the application;

[0039] Figure 2 It is a system framework schematic diagram of the application;

[0040] Figure 3 It is an electric parameter data module flowchart of the application;

[0041] Figure 4 It is a fluctuation extraction module flowchart of the application;

[0042] Figure 5 It is a stability determination module flowchart of the application;

[0043] Figure 6 It is an adaptability analysis module flowchart of the application;

[0044] Figure 7 It is a test conclusion module flowchart of the application. DETAILED DESCRIPTION

[0045] The technical solutions in the present application will be described below with reference to the drawings.

[0046] In the embodiments of the present application, the words such as "example", "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0047] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized. "Of", "corresponding" and "corresponding" can be used interchangeably at times, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0048] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0049] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0050] The embodiments of the present application provide a test system for a new energy power access scene, as shown in Figures 1-2 The test system for the new energy power access scene is shown in the schematic diagram of the test system for the new energy power access scene, and the system comprises:

[0051] The electrical parameter data module obtains the voltage time sequence, the frequency time sequence and the power factor time sequence of the new energy power generation equipment access node, obtains the instantaneous signal sequence through millisecond-level sampling, combines the maximum change range at different time points, and screens the fluctuation boundary data (including the standard voltage and frequency allowable deviation limit value) of each signal to generate three types of fluctuation boundary sets;

[0052] The fluctuation extraction module extracts the periodic characteristic change range through a power quality analysis algorithm (a power fluctuation characteristic evaluation method used for identifying periodic fluctuation characteristics) according to the time period signal sequence of the voltage and the frequency in the three types of fluctuation boundary sets, screens the fluctuation co-occurrence section according to signal synchronicity and associates the corresponding power factor change trajectory to generate a fluctuation co-occurrence section set;

[0053] The stability determination module detects the response offset time between each trajectory in each segment according to the extracted frequency trajectory and power factor trajectory time series in the fluctuation co-occurrence segment set, determines whether the time segment constitutes an unstable interval through the offset time and signal persistence relationship, records all unstable intervals and marks the distribution range in the overall time sequence, and generates an unstable distribution map;

[0054] The adaptive analysis module retrieves the reference new energy equipment types and corresponding access node numbers in the time period covered by the unstable distribution map, analyzes the unstable response overlap of the same type of equipment on multiple access nodes, and generates a repeated response number list;

[0055] The test conclusion module summarizes the information of all unstable marked time segments of the equipment during the test period based on all the equipment numbers listed in the repeated response number list, labels according to the label differences and node distribution of each equipment group, and generates a new energy power test record.

[0056] The three types of fluctuation boundary sets include voltage fluctuation boundaries, frequency fluctuation boundaries, and power factor fluctuation boundaries. The fluctuation co-occurrence segment set includes periodic change segments, voltage frequency synchronization segments, and power factor correlation segments. The unstable distribution map includes response offset segment distribution map, trajectory offset relationship map, and time segment stability labeling map. The repeated response number list includes equipment type number, access node number, and unstable response overlap record. The new energy power test record specifically includes equipment response label distribution record, node abnormal distribution information, and test phase instability statistical result.

[0057] Specifically, as shown in Figure 2 , 3 The electrical parameter data module includes:

[0058] The signal acquisition submodule acquires the voltage time sequence, frequency time sequence, and power factor time sequence of the new energy power generation equipment access node, acquires the instantaneous signal value of each time point in each time sequence, forms an instantaneous signal sequence with a millisecond-level sampling interval, detects the change value between different time points of each signal sequence, extracts the maximum change amplitude in each time sequence per unit time, and generates a maximum change amplitude sequence.

[0059] To acquire the voltage time sequence, frequency time sequence, and power factor time sequence of the new energy power generation equipment access node, a sampler needs to be set up at the equipment access point and connected to the electrical parameter data module. The sampling frequency is set to 1000 times per second. The voltage value, frequency value, and power factor value at each millisecond corresponding time point are acquired in turn to construct three time sequences, each sequence containing a series of instantaneous numerical values arranged by time. The voltage time sequence can be represented as , the frequency time sequence is , and the power factor time sequence is , for the voltage value sequence, calculate the difference between adjacent time points , and so on to get the frequency change value , power factor change value , select the maximum difference value in the sampling period as the maximum change amplitude per unit time, for example, in a 10ms time window, assuming the voltage sequence is {230.1, 229.9, 229.6, 230.4, 230.0}, the maximum change amplitude is V, and the maximum change of each type of parameter per unit time is calculated in this way, and all sequences are shifted backward by time points to form a complete maximum change amplitude sequence, generating a maximum change amplitude sequence.

[0060] The fluctuation boundary screening submodule compares the change value of each time point in each signal sequence with the standard voltage allowable deviation limit value, the standard frequency allowable deviation limit value, and the set reference threshold value, judges whether the voltage change amplitude exceeds the standard voltage allowable deviation limit value, whether the frequency change amplitude exceeds the standard frequency allowable deviation limit value, and whether the power factor change amplitude exceeds the set reference threshold value, screens the time points and corresponding signal values of the boundary fluctuation in each signal sequence, and generates the fluctuation signal boundary interval;

[0061] According to the maximum change amplitude sequence, first set the voltage allowable deviation limit value as ±7%, for example, with 220V rated voltage, the allowable change amplitude is ±15.4V, the frequency allowable deviation is ±0.5Hz, and the power factor allowable deviation is based on 0.05 as the reference threshold value. Based on each item in the maximum change amplitude sequence and compared with the above deviation limit value, if the voltage change amplitude is 17.2V, which has exceeded the limit value of 15.4V, the voltage fluctuation at this time point is identified as a boundary fluctuation item, the frequency change amplitude is 0.3Hz, which is not included in the boundary sequence, and the power factor change is 0.06, which exceeds 0.05 and is included in the boundary item. Use conditional screening to judge the voltage, frequency, and power factor change value of each time point one by one to generate the boundary points of the three types of fluctuation data. Assuming that there are 1000 sampling points in a certain period of time, 68 points are detected with voltage change exceeding the limit, 35 points are detected with frequency change exceeding the limit, and 120 points are detected with power factor exceeding the limit. Record the corresponding time points, corresponding signal values, and fluctuation amplitudes to form a data structure in the form of "time point-signal type-change amplitude", and generate the fluctuation signal boundary interval.

[0062] The boundary set generation submodule combines the voltage, frequency, and power factor boundary interval values at each time point based on the fluctuation signal boundary interval, synchronously aggregates the combined multi-dimensional boundary interval values on the time axis, obtains the maximum fluctuation boundary of the voltage, frequency, and power factor of the new energy power generation equipment access node at different times, and generates three types of fluctuation boundary sets;

[0063] Based on the boundary interval of the fluctuation signal, the boundary data of the screened voltage, frequency and power factor are uniformly combined. Firstly, the boundary data of the three types of signals is aligned on the time axis according to the time points. The time points are t1, t2, t3, etc. The boundary data of voltage, frequency and power factor are uniformly mapped to the time axis. The isolated items without corresponding data are eliminated. For example, only the voltage boundary changes at t2, and other signals are missing. The point is eliminated. The time points with boundary changes of the three types of signals are reserved. A multi-dimensional data table with the structure of "time point-voltage boundary value-frequency boundary value-power factor boundary value" is formed. If the voltage boundary value is 18.3V, the frequency boundary is 0.7Hz, and the power factor boundary is 0.065 at t3, the set item (t3, 18.3, 0.7, 0.065) is recorded. All data are arranged in time sequence. The fluctuation boundary data table in the form of final set is generated. All boundary data items meeting the conditions are outputted. Three types of fluctuation boundary sets are generated.

[0064] Specifically, as shown in Figure 2 、 4 the fluctuation extraction module includes:

[0065] The feature extraction submodule obtains the time period signal sequence of voltage and frequency in the three types of fluctuation boundary sets. According to the numerical change curve in each sequence, the time interval and amplitude difference between adjacent wave peaks and wave troughs are counted. If the fluctuation interval change amplitude between adjacent period segments is within the preset range, the period segment is marked. The time interval meeting the periodic change characteristics is selected. The periodic change interval is generated.

[0066] The time period signal sequences of the voltage and the frequency in the three types of fluctuation boundary sets are acquired. First, the original time sequence of each type of signal is sorted according to the time stamp, and a sequence data set based on time is established. Then, the voltage signal sequence and the frequency signal sequence are respectively cut by a sliding window, the window length is a fixed time length, and the step length is half of the window length. For the signal values in each sliding window, the time interval of the continuous wave peak and wave trough in the segment is calculated. The average period interval value of the sequence segment is obtained by cumulatively averaging the time difference between adjacent extreme points. At the same time, the signal difference value of the wave peak and the wave trough is recorded as the amplitude value. Two conditions need to be met to determine whether the signal segment is a periodic segment: one is that the fluctuation amplitude needs to be greater than the set amplitude threshold, and the other is that the period interval change range needs to be within the set range. If the difference between the wave peak value and the previous wave trough value in the voltage signal is greater than the set amplitude reference value of the signal type, and the time interval change difference between adjacent periods is less than the set period stability threshold, the window segment is marked as a periodic segment. Taking 10-second voltage sampling data of a new energy access node as an example, the sampling frequency is 1000 Hz, the window length is set to 1 second, and the step length is 0.5 seconds. There are 6 groups of wave peak and wave trough pairs in the window from the 1st second to the 2nd second of the voltage signal, the average period interval is 167 milliseconds, and the average difference between the wave peak and the wave trough is 13 volts. If the set amplitude threshold is 10 volts and the period threshold is 20 milliseconds, the voltage signal in this segment meets the periodicity determination condition. The frequency signal is identified by the same operation process. After the identification is completed, the voltage and frequency time periods that meet the periodicity requirement are recorded and output respectively, and the period change interval is generated.

[0067] The co-occurrence screening submodule compares whether the start and end time of each voltage and frequency period has time coincidence one by one according to the time position of each voltage and frequency period in the period change interval. The maximum time deviation threshold between the start and end points of the period is set to determine whether they belong to the coincident segment under the time synchronization condition. The time period indexes of the two types of signals that fluctuate synchronously in the same time interval are screened out, and the time periods that do not meet the synchronization are eliminated to obtain the period co-occurrence section.

[0068] According to the time position of the voltage and frequency cycle period in the cycle change interval, first, the start and end time of each signal corresponding to the cycle period is compared along the time axis. Taking the voltage cycle period as the reference, the start time and end time of each cycle period are read in turn. Then, the section closest to the start time is selected from the frequency cycle period for comparison. If the start time difference and the end time difference are both less than the set synchronization deviation threshold, the two cycle periods are determined as time synchronization sections. Otherwise, the voltage or frequency cycle period is excluded and does not participate in subsequent synchronization determination. In this process, a time synchronization threshold is set to define the maximum allowed deviation range of the start and end points. This value is set according to the time calibration accuracy in the sampling system. For example, if the sampling time interval is 1 millisecond and the allowed deviation is set to within 3 milliseconds, it is considered acceptable. If a voltage cycle period is 2.500 seconds to 3.250 seconds and a frequency cycle period is 2.503 seconds to 3.247 seconds, the start deviation is 3 milliseconds and the end deviation is 3 milliseconds, which meets the synchronization requirement and is marked as a cycle co-occurrence section. All time sections that meet this condition are numbered and recorded as a cycle co-occurrence section index set. This set serves as the time basis for subsequent correlation of the power factor fluctuation trajectory and obtains the cycle co-occurrence section.

[0069] The trajectory correlation submodule extracts the continuous change sequence of the power factor in the time period corresponding to the cycle co-occurrence section, and calculates the sequence fluctuation gradient and change amplitude of the power factor in each time period. It maps each co-occurrence section and the corresponding power factor change curve to form a one-to-one correspondence between the synchronization section and the change trajectory. It integrates the correlation information of all co-occurrence sections to generate a fluctuation co-occurrence section set.

[0070] Based on the time period index corresponding to the cycle co-occurrence section, the original continuous change value of the power factor in the same time period is extracted. The start and end times of each co-occurrence section are set as t1 and t2. All sampling points between t1 and t2 in the power factor sequence are extracted in time matching mode, and their signal values are recorded to construct the complete sequence trajectory of the power factor in this time period. This sequence can be used to calculate the change gradient value and the maximum fluctuation amplitude value. The gradient value can be calculated using the linear change rate method, i.e., the difference between the start and end signal values is divided by the time length of the section. If the start power factor value is 0.91 and the end value is 0.86, and the section length is 1.2 seconds, the slope is calculated as (0.86-0.91) / 1.2=-0.0417. The fluctuation amplitude is the difference between the maximum and minimum values in the section, which is set as 0.93 and 0.85, respectively. The fluctuation amplitude is 0.08. The start and end times, change slope, and fluctuation amplitude of the section are combined as the power factor change characteristic item of the cycle co-occurrence section. All co-occurrence sections are processed in turn to establish a mapping structure with the voltage and frequency co-occurrence sections, and finally a one-to-one correspondence data table based on the time index is formed to generate the fluctuation co-occurrence section set.

[0071] Specifically, as shown in Figure 2 , 5 , the stability determination module includes:

[0072] The offset extraction submodule obtains the frequency trajectory and the power factor trajectory corresponding to each time period in the fluctuation co-occurrence section set, extracts the starting time of the rising section and the falling section for each frequency change curve, extracts the starting time of the change in the same direction for the power factor change curve, calculates the response start time difference in the same direction of the two types of trajectories, and if the time difference value is greater than the time response offset threshold, records the offset time as the response time difference of the current section, and generates the trajectory offset time;

[0073] To obtain the frequency trajectory and the power factor trajectory corresponding to each time period in the fluctuation co-occurrence section set, the sampling point sequence of the frequency and the power factor in each start and end time period marked by the set needs to be extracted, and assuming that the start and end time of a section is to , the frequency trajectory is denoted as , and the power factor trajectory is denoted as , the first derivative sequences and are extracted by performing derivative operations on and , respectively, and the first time point in where the non-zero value turns to a positive value is selected as the frequency change starting point , and similarly, the first time point in where the non-zero value turns to a positive value is selected as the power factor change starting point , and the difference between the two is the response offset time , if , , then , the time difference value needs to be compared with the offset time threshold set by the average duration time of the frequency change, and the average duration time of the frequency change is calculated by summing the time length of the continuous non-zero in the section and taking the average value, if the average duration time is , and , then it can be determined that there is a response delay phenomenon in the section, and the is recorded as the response offset time of the current section, and all the trajectories of the frequency and the power factor in the section are processed in turn to generate the trajectory offset time.

[0074] The segment identification submodule judges whether there is a phenomenon of delayed response and continuous fluctuation coinciding according to the response time difference of each segment in the trajectory offset time, in combination with the continuous duration of the power factor change in the corresponding segment. If the offset time is greater than the response delay threshold and the duration of the power factor in the continuous change state is higher than the minimum persistence reference value, the time segment is marked as an unstable segment, a mapping structure of the time interval and the unstable identification is established, and an unstable segment index is obtained.

[0075] According to the response time difference of each segment in the trajectory offset time, it is further necessary to judge whether there is a phenomenon of obvious delayed response and continuous change in the corresponding segment based on the continuous change data of the power factor trajectory. The specific operation is as follows: first, the signal slope is extracted from the power factor change sequence of each segment. There are sampling points in the segment, and the power factor values are The linear regression slope in the time dimension is calculated as If is not zero, it indicates that the power factor in the segment presents a continuous change trend. Then the continuous change duration of the segment is extracted , that is, the continuous time length from the change starting point to the change stopping point. If the value is greater than the set minimum persistence reference value , for example , and , in combination with the trajectory offset time , if , wherein is the response delay judgment threshold, such as , it indicates that the response delay exceeds the allowed range, and the continuous change phenomenon of the power factor exists, which meets the unstable condition. The time segment is marked as an unstable segment, and the segment start and end time, the response time difference value and the power factor continuous change duration are output to form a structured record, and an unstable segment index is obtained.

[0076] The distribution marking submodule performs time axis marking processing on the overall time sequence based on the unstable segment index. The original time axis is divided according to the set segmentation interval. It is judged whether there is an interval marked by the unstable segment index in each time segment. If there is, the unstable state is marked in the corresponding time segment, and a visual mapping is performed to obtain an unstable distribution map.

[0077] Based on the unstable segment index, the complete time sequence structure is segmented and marked. First, the original time sequence is divided into continuous and equal-length time segments, each with a length of , and sequentially numbered as . For each time segment , judge whether the time range has overlapping part with the time interval recorded in any of the unstable section index value, if there is interval overlap, mark as unstable section, in the visualization process, construct time-state image structure, the horizontal axis is time, the vertical axis is state label, mark state value is 1, indicating unstable, 0 indicates stable, all unstable state time period is marked with color block, and is labeled according to its position in time sequence, finally form section distribution diagram based on time axis, obtain unstable distribution atlas.

[0078] Specifically, as shown in Figure 2 , 6 , the adaptive analysis module comprises:

[0079] The device retrieval sub-module extracts the time interval range of each section based on the marked unstable time period in the unstable distribution atlas, retrieves the new energy power generation device operation record in the corresponding time period, judges each record based on the timestamp, device type and access node in the device operation record, if the timestamp of the operation record falls within the unstable time interval, extracts the corresponding device type and access node number, and completes the retrieval operation of all sections in turn to generate the unstable section device number.

[0080] Based on the marked unstable time period in the unstable distribution atlas, first extract the time start and end information of each marked place in the atlas, and arrange it into a section set structure, then traverse the operation record of new energy equipment, extract the timestamp field , device type field and access node number field , compare with the time section in the atlas , if is satisfied , record the corresponding and of the operation data, repeat the judgment process for each unstable section, retrieve the operation data and extract the device type and node number one by one, and use the timestamp as an index to verify the accuracy of the time period, for example, if a device type is photovoltaic inverter, the access number is N01, the operation record time is 10.352 seconds to 10.425 seconds, and the atlas marks the unstable section as 10.300 seconds to 10.400 seconds, then determine that the device is in the unstable time period, extract the photovoltaic inverter and N01 and add them to the record set, all device records are arranged according to time sequence and device type number, and the unstable section device number is generated.

[0081] The response overlap submodule classifies and aggregates the devices according to the device type extracted from the unstable section device number and the access node number information, groups the same type of devices according to the access node, cross-compares the unstable time sections of all devices in the group, identifies the situation that the same type of devices in two or more different access nodes appear unstable state in the same time period, and records the intersection period, device type and node number, and obtains the device response overlap section.

[0082] According to the device type and access node number information extracted from the unstable section device number, the device type classification operation is performed on the data set, the same device type items are aggregated into a group, and then the access node numbers are subdivided in each group. The unstable time sections of the device type under each node are extracted into a time interval list. The time intervals between any two nodes in the group are cross-detected, that is, the time interval of node A is , the time interval of node B is , if and , it is indicated that there is overlap in time, it is determined that the same type of devices exists in multiple nodes, the device type, the corresponding two access node numbers and the overlap time period are recorded into the response overlap data set, and all overlap records are sorted by time to be structured output. A group of wind power devices appear unstable sections in nodes N05 and N07, respectively, wherein the unstable section of N05 is 12.300 seconds to 12.500 seconds, the unstable section of N07 is 12.400 seconds to 12.600 seconds, the overlap interval of the two is 12.400 seconds to 12.500 seconds, the data is written into the result set as an effective intersection record, and the device response overlap section is obtained.

[0083] The number summary submodule based on the device type, access node number and overlap time period information identified in the device response overlap section, aggregates the device numbers of the same device type that exist in multiple nodes with overlap response time, constructs a repeated number list structure, outputs the device type, repeated response time interval and involved node number set, and generates a repeated response number list.

[0084] Based on the device type, access node number, and overlapping time period information identified in the overlapping device response segments, each record in the set is first grouped by device type. All relevant access node numbers are extracted from each group, and duplicates of the same node number are removed. A mapping table is constructed between the device number and its overlapping time period. All numbers are then summarized to generate a complete list consisting of device type, repeated response time interval, and involved node numbers. For example, if a device type is an energy storage device, overlapping responses exist at nodes N02, N03, and N04. The overlapping interval between N02 and N03 is 15.000 seconds to 15.100 seconds, and the overlapping interval between N03 and N04 is 15.050 seconds to 15.120 seconds. Therefore, the nodes involved in the repeated responses for this device type are N02, N03, and N04, which are uniformly included in the list record entries, with the repeated interval range marked as 15.000 seconds to 15.120 seconds. All results are summarized to form structured data items, generating a list of repeated response numbers.

[0085] Specifically, such as Figure 2 , 7 As shown, the test conclusion module includes:

[0086] The information aggregation submodule retrieves all device numbers listed in the duplicate response number list, retrieves all unstable time periods recorded by each device during the test, matches the unstable segment index corresponding to each device with the timestamp, and archives the timestamp under the corresponding device number if the timestamp belongs to the unstable marker range, generating a device unstable time list.

[0087] To retrieve all device numbers listed in the duplicate response number list, first, based on the device numbers listed in the list... An index table is created to retrieve the runtime log data generated by each device during the test, with each data entry containing a timestamp. Unstable flag (Value is 1 or 0) and node number For each data entry, based on the timestamp and unstable state Make a judgment when When this occurs, it indicates that the data is in an unstable state, and the corresponding... Recorded as unstable time points, further consolidating continuous... The sequence segments are merged to construct the time segment. and with the equipment number Binding to form a structure This operation is repeated for each device, constructing a dataset containing the unstable behavior intervals of all devices within the test period. If a device is numbered PV01, its continuous unstable time period is recorded as follows: to , the segment of data is recorded in the form of , and the final output device number index and the complete mapping structure of the time segment are generated, and the device unstable time list is generated.

[0088] The difference labeling submodule groups the records of the same type of device on different access nodes according to the device unstable time list, extracts the device number, the node number to which it belongs, and the unstable time segment of each group, compares the intersection of the unstable time segments of each group, and labels the device groups according to the difference between different nodes. If the unstable distribution of the same type of device between different nodes partially overlaps, it is marked as an overlapping label, and if it does not overlap at all, it is marked as a scattered label, and the node distribution label is obtained.

[0089] According to the device unstable time list, the same type of device is classified according to the device type label , and each type is grouped according to the access node number , and the device number corresponding to the unstable time segment in each group is extracted, and a device distribution mapping table is constructed with the node number as the main index, and then the unstable segments between each node group are compared to see if there is an intersection interval. If the time segment of node A is , the time segment of node B is , if and , it is determined that there is a time intersection, and it is marked as an overlapping label , if the time segments of all node groups do not overlap, it is marked as a scattered label . In addition, in order to exclude the influence of some interference segments, the length of each time segment is screened, and records with a length less than the minimum stable interval threshold are removed, and is set to ensure that the recorded segments have time continuity, and finally a multi-field structure table of device type, node number, and corresponding label is formed, and the node distribution label is obtained.

[0090] The record generation submodule integrates the device number, unstable time segment, and distribution label of the node based on the node distribution label, constructs a unified data table, records the device type, access node number, unstable time interval, and corresponding distribution label for each device group, and generates a new energy power test record.

[0091] Based on the node distribution label, the labeled distribution label is integrated with the device number and time segment information to construct a unified record table. The fields in the table include device type , device number , access node number , unstable time segment , and distribution label , according to the device type, each device outputs a record table page, and example records are as follows In the aggregation process, each record is arranged in ascending order according to the node number, and the number of overlapping labels and scattered labels under the device type is counted at the tail of the table, which is used for subsequent statistical ratio indicators, and the structured record output table is formed through field merging and aggregation, and finally a structured and consistent test information set is established, and a new energy power test record is generated.

[0092] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. Test system for testing new energy power access scenarios, characterized in that, The system comprises: The electric parameter data module obtains the voltage time sequence, frequency time sequence and power factor time sequence of the new energy power generation equipment access node, obtains the instantaneous signal sequence, combines the maximum change range at different time, screens the signal fluctuation boundary data, and generates three types of fluctuation boundary sets; The fluctuation extraction module extracts the periodic characteristic change range according to the voltage and frequency time period signal sequence in the three types of fluctuation boundary sets, screens the fluctuation co-occurrence section according to signal synchronicity, and associates the corresponding power factor change trajectory, to generate a fluctuation co-occurrence section set; The stability determination module extracts the frequency trajectory and power factor trajectory time sequence according to the fluctuation co-occurrence section set, detects the response offset time between trajectories, judges the unstable interval through the offset time and signal persistence relationship, records all unstable intervals and marks the distribution range in the overall time sequence, and generates an unstable distribution map; The adaptive analysis module covers the time period based on the unstable distribution map, retrieves the new energy equipment types and corresponding access node numbers in the corresponding period, analyzes the unstable response overlap of the same type of equipment on multiple access nodes, and generates a repeated response number list; The stability determination module comprises: The offset extraction submodule obtains the frequency trajectory and power factor trajectory corresponding to each time period in the fluctuation co-occurrence section set, extracts the starting time of the rising section and the falling section of each frequency change curve, extracts the starting time of the change in the same direction of the power factor change curve, calculates the response start time difference of the two types of trajectories in the same direction, and if the time difference value is greater than the time response offset threshold, the offset time is recorded as the response time difference of the current section, and the trajectory offset time is generated; The section identification submodule judges whether there is a phenomenon of delayed response and continuous fluctuation overlap according to the response time difference of each section in the trajectory offset time, in combination with the continuous duration of the power factor change in the corresponding section, if the offset time is greater than the response delay threshold and the continuous change duration of the power factor is higher than the minimum persistence reference value, the time period is marked as an unstable section, a mapping structure of time interval and unstable identification is established, and an unstable section index is obtained; The distribution marking submodule performs time axis marking processing on the overall time sequence based on the unstable section index, divides the original time axis according to the set section interval, judges whether there is an interval marked by the unstable section index in each time period, if there is, marks the unstable state in the corresponding time period, and performs visual mapping, to obtain an unstable distribution map. The rising section and the falling section starting time of each frequency change curve are extracted, specifically, the first order derivative of the frequency change curve in time is calculated, the turning point where the sign of the first order derivative changes is identified, the time corresponding to the turning point where the first order derivative changes from negative to positive is determined as the rising section starting time, and the time corresponding to the turning point where the first order derivative changes from positive to negative is determined as the falling section starting time; the starting time of the same direction change of the power factor change curve is extracted, specifically, the first order derivative of the power factor change curve is calculated at the determined rising section starting time and falling section starting time, and it is judged whether the sign of the first order derivative of the power factor change curve is consistent with the sign of the first order derivative of the frequency change curve at the same time point, if the signs are consistent, the time point is determined as the starting time.

2. The test system for new energy power access scenarios according to claim 1, characterized in that, The three types of fluctuation boundary sets include voltage fluctuation boundaries, frequency fluctuation boundaries, and power factor fluctuation boundaries, the fluctuation co-occurrence section set includes periodic change sections, voltage frequency synchronization sections, and power factor correlation sections, the unstable distribution atlas includes response offset section distribution maps, trajectory offset relationship maps, and time section stability annotation maps, and the repeated response number list includes device type numbers, access node numbers, and unstable response overlap records.

3. The test system for new energy power access scenarios of claim 1, wherein, The electrical parameter data module includes: The signal acquisition submodule acquires the voltage time sequence, the frequency time sequence, and the power factor time sequence of the new energy power generation equipment access node, acquires the instantaneous signal value of each time point in each time sequence, forms an instantaneous signal sequence with a millisecond-level sampling interval, detects the change value between different time points of each signal sequence, extracts the maximum change amplitude in each time sequence per unit time, and generates a maximum change amplitude sequence; The fluctuation boundary screening submodule compares the change value of each time point in each signal sequence with the standard voltage allowable deviation limit value, the standard frequency allowable deviation limit value, judges whether the voltage change amplitude exceeds the standard voltage allowable deviation limit value, judges whether the frequency change amplitude exceeds the standard frequency allowable deviation limit value, judges whether the power factor change amplitude exceeds the set reference threshold, screens the time points and corresponding signal values of the boundary fluctuation in each signal sequence, and generates a fluctuation signal boundary interval; The boundary set generation submodule generates three types of fluctuation boundary sets based on the fluctuation signal boundary interval, combines the boundary interval values of voltage, frequency, and power factor at each time point, synchronously aggregates the combined multi-dimensional boundary interval values on the time axis, acquires the maximum fluctuation boundary of voltage, frequency, and power factor of the new energy power generation equipment access node at different time points, and generates three types of fluctuation boundary sets.

4. The test system for new energy power access scenarios of claim 1, wherein, The fluctuation extraction module includes: The feature extraction submodule acquires the time section signal sequence of voltage and frequency in the three types of fluctuation boundary sets, according to the numerical change curve in each sequence, the time interval and amplitude difference between adjacent wave peaks and troughs are counted, if the fluctuation interval change amplitude between adjacent periodic sections is within a preset range, it is marked as a periodic section, the time interval meeting the periodic change characteristic is selected, and a periodic change interval is generated. The co-occurrence screening submodule compares each start and end time for time coincidence according to the respective period segment time position of voltage and frequency in the period variation interval, sets a maximum time deviation threshold between the start and end points of the period, determines whether the two belong to a coincident segment under time synchronization conditions, screens time segment indexes of the two types of signals that fluctuate synchronously within the same time interval, eliminates time segments that do not meet the synchronization, and obtains a period co-occurrence segment; The trajectory correlation submodule extracts a continuous change sequence of the power factor in the time segment according to the time segment index corresponding to the period co-occurrence segment, counts the sequence fluctuation gradient and change amplitude of the power factor in each time segment, performs structure mapping on each co-occurrence segment and the corresponding power factor change curve, forms a one-to-one correspondence relationship between the synchronous segment and the change trajectory, integrates the correlation information of all co-occurrence segments, and generates a fluctuation co-occurrence segment set.

5. The test system for new energy power access scenarios of claim 1, wherein, The adaptive analysis module includes: The device retrieval submodule extracts the time interval range segment by segment based on the unstable time segments marked in the unstable distribution map, retrieves the new energy power generation device operation record in the corresponding time segment, performs time matching judgment on each record based on the time stamp, device type and access node in the device operation record, extracts the corresponding device type and access node number if the time stamp of the operation record falls within the unstable time interval, sequentially completes the retrieval operation of all segments, and generates an unstable segment device number; The response overlap submodule classifies and aggregates the device type according to the device type and access node number information extracted from the unstable segment device number, groups the same type of devices according to the access node, cross-compares the unstable time segments corresponding to all devices in each group, identifies the situation that the same type of devices in two or more different access nodes appear unstable in the same time segment, records the intersection period, device type and node number, and obtains a device response overlap segment; The number summary submodule de-duplicates and summarizes the device numbers of the same device type that have overlapping response times on multiple nodes based on the device type, access node number and overlapping time segment information in the device response overlap segment, constructs a duplicate number list structure, outputs the device type, duplicate response time interval and involved node number set, and generates a duplicate response number list.

6. The test system for new energy power access scenarios of claim 1, wherein, The system further includes: The test conclusion module summarizes and labels all unstable marked time segments of the devices during the test period based on the device numbers in the duplicate response number list, labels according to the label difference and node distribution of each device group, and generates a new energy power test record.

7. The test system for new energy power access scenarios of claim 6, wherein, The new energy power test record is specifically a device response label distribution record, node abnormal distribution information and test phase instability statistical result.

8. The test system for new energy power access scenarios of claim 6, wherein, The test conclusion module includes: The information summary submodule obtains all device numbers listed in the duplicate response number list, retrieves all unstable time segments recorded by the devices during the test period one by one, matches the unstable segment index and time stamp corresponding to each device, and if the time stamp belongs to the unstable marked range, it is filed under the corresponding device number to generate a device unstable time list; The difference labeling sub-module groups the records of the same type of equipment on different access nodes according to the equipment unstable time list, extracts the equipment number, the node number to which the equipment belongs and the unstable time period of each group, compares the intersection of the unstable time period of each group, labels the equipment groups according to the difference between different nodes, marks the overlapping label if the unstable distribution of the same type of equipment between different nodes partially overlaps, and marks the scattered label if the unstable distribution of the same type of equipment between different nodes does not overlap at all, and obtains the node distribution label. The record generation sub-module integrates the equipment number, the unstable time period and the distribution label of the node based on the node distribution label, constructs a unified data table, records the equipment type, the access node number, the unstable time interval and the corresponding distribution label for each equipment group, and generates a new energy power test record.

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