Impedance model construction method and system for new energy flexible low-frequency transmission system

Abstract

The invention relates to the technical field of electric signal processing, in particular to an impedance model construction method and system of a new energy flexible low-frequency sending-out system. The method comprises the following steps: recording real-time timing sequences of voltage and current of a converter bridge arm under different working conditions; extracting a time interval between the voltage peak value and the current peak value, a voltage waveform slope change rate and a current waveform oscillation period, and labeling corresponding working condition labels to form a bridge arm dynamic feature library; and identifying the voltage waveform and the current waveform of the converter bridge arm, and synchronously recording the line resistance and the line reactance between the converter stations. According to the invention, through integration of the bridge arm dynamic features, construction of the bridge arm dynamic feature library and high-frequency correction cooperation, adaptive optimization of bridge arm parameters and construction of the impedance model of high and low frequency bands are realized, so that the matching efficiency of the impedance model is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrical signal processing, and in particular to an impedance model construction method and system of a new energy flexible low-frequency sending-out system. BACKGROUND

[0002] The core of the new energy flexible low-frequency sending-out system is composed of a multi-level matrix converter bridge arm and an inter-conversion station line, and is a key equipment for new energy power grid connection and transmission. As the core basis for system optimization design and stable control, the impedance model needs to cover the bridge arm dynamic characteristics, line parameters and different working conditions, and the adaptation requirements of high and low frequency bands. However, the traditional impedance model construction method has obvious deficiencies: only a small amount of static characteristics of the bridge arm are extracted, and a binding system of multi-dimensional dynamic characteristics and working condition labels is not formed, and the parameter matching efficiency and accuracy are insufficient; the bridge arm parameters are fixedly configured, and there is no real-time waveform preprocessing and dynamic calibration mechanism, so it is difficult to adapt to the working condition fluctuation; the line connection relationship is determined without precise topological mapping, and the resistance and reactance are mostly measured once, so the parameter access accuracy is not good; and the model only focuses on low-frequency characteristics, ignores the influence of high-frequency oscillation, and does not set a high-frequency correction link, so it cannot fully represent the impedance characteristics of the bridge arm-line whole link, which restricts the integrity and accuracy of the impedance model. SUMMARY

[0003] Therefore, it is necessary to provide an impedance model construction method and system of a new energy flexible low-frequency sending-out system to solve at least one of the above technical problems.

[0004] To achieve the above-mentioned purpose, an impedance model construction method of a new energy flexible low-frequency sending-out system, the new energy flexible low-frequency sending-out system comprising a multi-level matrix converter bridge arm and an inter-conversion station line, the method comprising the following steps: Step S1: recording the real-time time sequence of the voltage and current of the converter bridge arm under different working conditions; extracting the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate and the current waveform oscillation period, and labeling the corresponding working condition label to form a bridge arm dynamic characteristic library; Step S2: identifying the voltage waveform and current waveform of the converter bridge arm, and synchronously recording the resistance and reactance of the inter-conversion station line; Step S3: extracting the voltage waveform and current waveform, matching the same label characteristics in the bridge arm dynamic characteristic library, and dynamically calibrating the bridge arm parameters in the pre-set impedance parameter framework; Step S4: determining the connection relationship of the inter-conversion station line, and connecting the line resistance and line reactance to the corresponding connection nodes of the calibrated impedance parameter framework; Step S5: analyze the high-frequency waveform timing output by the calibrated impedance parameter framework, identify the repeated oscillation signal period, calculate the compensation coefficient and perform high-frequency correction on the impedance parameter framework, and obtain the impedance model of the new energy flexible low-frequency sending-out system.

[0005] The application also provides a new energy flexible low-frequency sending-out system impedance model construction system for executing the new energy flexible low-frequency sending-out system impedance model construction method. The bridge arm characteristic library construction module is configured to record the real-time timing of the voltage and current of the converter bridge arm under different working conditions, extract the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate and the current waveform oscillation period, and label the corresponding working condition label to form a bridge arm dynamic characteristic library. The bridge arm and line parameter acquisition module is configured to identify the voltage waveform and current waveform of the converter bridge arm and synchronously record the line resistance and line reactance between the converter stations. The bridge arm parameter calibration module is configured to extract the voltage waveform and current waveform voltage flow change characteristics, match the same label characteristics in the bridge arm dynamic characteristic library, and dynamically calibrate the bridge arm parameters in the preset impedance parameter framework. The line parameter access module is configured to determine the connection relationship of the line between the converter stations, and access the line resistance and line reactance to the corresponding connection node of the calibrated impedance parameter framework. The high-frequency correction and model construction module is configured to analyze the high-frequency waveform timing output by the calibrated impedance parameter framework, identify the repeated oscillation signal period, calculate the compensation coefficient, and perform high-frequency correction on the impedance parameter framework to obtain the impedance model of the new energy flexible low-frequency sending-out system.

[0006] The application has the following advantages: I. The multi-dimensional characteristics and working condition labels of the bridge arm dynamic characteristic library are bound and designed, realizing accurate mapping of the working condition and the bridge arm characteristics. The characteristic library covers three types of core dynamic characteristics, i.e., the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate, and the current waveform oscillation period. Each characteristic group is labeled with a corresponding working condition label (such as load level and operation mode), which not only ensures comprehensive representation of the characteristics to the bridge arm operation state, but also enables the subsequent matching process to directly lock the effective characteristic group under the same working condition, avoids invalid matching interference across working conditions, and significantly improves the efficiency and initial accuracy of the bridge arm parameter matching.

[0007] II. Dynamic calibration mechanism combines real-time waveform preprocessing and step-by-step parameter adjustment to realize precise adaptive optimization of bridge arm parameters. Through baseline correction, the overall waveform offset is eliminated, and abnormal pulses are replaced by interpolation, ensuring the reliability of the extraction of pressure flow change characteristics; after matching the characteristics, the adjustment trend of resistance and inductance is determined according to the difference direction, and the parameters are adjusted step by step at a fixed ratio and locked through waveform deviation verification (peak deviation ≤2%, cycle deviation ≤1ms), so that the equivalent resistance and equivalent inductance are always dynamically matched with the real-time running state, solving the problem that traditional fixed parameters are difficult to adapt to system working condition fluctuations.

[0008] III. The collaborative design of precise line parameter access and high-frequency correction builds a complete impedance model covering the bridge arm-line full link and considering the characteristics of high and low frequency bands. By comparing the terminal identification and topology table, the line connection node is determined, and the line resistance and reactance measured multiple times and averaged (measurement accuracy 0.5% FS) are accessed to ensure the accuracy of line parameter access; for high-frequency waveforms, the repeated oscillation period is identified and the compensation coefficient is calculated to correct the parameter framework, which makes up for the defects of traditional models that only focus on low-frequency characteristics and ignore high-frequency oscillation effects, so that the final model can not only accurately reflect the core impedance characteristics of the system in low-frequency operation, but also adapt to high-frequency dynamic response, fully improving the representation integrity and accuracy of the impedance characteristics of new energy flexible low-frequency sending systems. BRIEF DESCRIPTION OF DRAWINGS

[0009] Fig. 1 A step flowchart of a new energy flexible low-frequency sending system impedance model construction method; Fig. 2 A high-frequency voltage and current waveform timing diagram; Fig. 3 A new energy flexible low-frequency sending system impedance model construction system interface diagram; The implementation, functional characteristics and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0010] The technical method of the present application will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0011] Furthermore, the accompanying drawings are included to provide a further understanding of the present application, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application. In the drawings:

[0012] It should be understood that, although terms such as "first", "second", and so on can be used herein to describe various information, the information should not be limited by these terms. These terms are used only to distinguish one information from another. For example, without departing from the scope of the example embodiments, a first information can be referred to as a second information, and similarly a second information can be referred to as a first information. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0013] To achieve the above object, there is provided Figs. 1 to 3 A method for constructing an impedance model of a new energy flexible low-frequency sending-out system, the new energy flexible low-frequency sending-out system comprising a multi-level matrix converter bridge arm and an inter-station line, the method comprising the following steps: Preferably, step S1: recording real-time time series of voltages and currents of the converter bridge arm under different working conditions; extracting time interval between voltage peak value and current peak value, voltage waveform slope change rate and current waveform oscillation period, and labeling corresponding working condition labels to form a bridge arm dynamic characteristic library; Optionally, the recording of the real-time time series of the voltages and currents of the converter bridge arm in step S1 comprises: For each working condition, the bridge arm is switched from the current working condition to the target working condition, and after the output waveform is continuously stable for 3 low-frequency periods, the time series recording is started; During the recording process, every time a low-frequency period is passed, the working condition stable state in the period is marked synchronously; After the recording is completed, the real-time time series of the voltages and currents of the converter bridge arm are segmented according to the marked stable periods, and only the time series data of the stable periods are retained.

[0014] In the present embodiment, for the rated load output current 1000A, 50% load output current 500A, and light load output current 200A three working conditions, the working condition switching module of the new energy flexible low-frequency sending-out system supports continuous adjustment of trigger angle 0°-90° and linear adjustment of modulation ratio 0.1-1.0, and the converter bridge arm is switched from the current working condition parameters to the target working condition parameters through the module.

[0015] In another embodiment, after the switching is completed, the bridge arm voltage real-time timing is collected by using a Hall voltage sensor, the sensor measures 0-3000V, the accuracy is 0.1% FS, and the bandwidth is 20 kHz; the bridge arm current real-time timing is collected by using a Rogowski coil current sensor, the sensor measures 0-2000A, the accuracy is 0.2% FS, and the bandwidth is 50 kHz. The sensor output signal is processed by a 16-bit resolution data acquisition card, the data acquisition card sampling rate is 100 kHz, the input impedance is 1MΩ, the signal is converted into a digital signal and then transmitted to a real-time data recording unit, and the real-time data recording unit stores a delay of ≤1ms.

[0016] It should be noted that setting the low-frequency period to 20ms corresponds to 50Hz low frequency, and the waveform analysis module built-in the data recording unit monitors the voltage peak value and the current peak value in real time within 60ms, i.e. 3 consecutive low-frequency periods. When the voltage peak value deviation of adjacent periods is ≤2% of the rated voltage peak value 3000V and the current peak value deviation is ≤2% of the rated current peak value 1000A, it is determined that there is no obvious jump, and the timing record is started.

[0017] In another embodiment, the data recording unit generates a timestamp with a unit of μs based on a GPS timing module with a synchronization accuracy of 1μs, adds a working condition stable state marker field in the data frame every 1 low-frequency period, i.e. 20ms, and assigns a value to the field according to the real-time monitoring result as stable or unstable. Stable corresponds to meeting the peak value deviation condition, and unstable corresponds to not meeting the peak value deviation condition.

[0018] After the record is completed, the storage data format is a CSV file containing the timestamp μs, the bridge arm voltage V, the bridge arm current A, the working condition label, and the working condition stable state marker field. The file is read by a timing segmentation tool, the timing segmentation tool supports batch processing based on field filtering, the data is filtered according to the condition that the working condition stable state marker = stable, the timing segment with continuous stable markers is extracted, the timing segment with unstable markers is deleted, and finally the stable period timing data that needs to be retained contains the timing information corresponding to at least 5 continuous stable markers, i.e. 100ms, which is used as the basic data for subsequent feature extraction.

[0019] Optionally, the bridge arm dynamic feature library formed in step S1 is specifically: The voltage peak value and the current peak value within 5 consecutive low-frequency periods are extracted, the time interval of the two in each period is calculated, and the average of the time intervals of the 5 periods is taken as the time interval feature of the timing; The slope change value of the voltage waveform at each rising edge is extracted, and the average of the slope change values of the continuous 3 rising edges is taken as the voltage waveform slope change rate feature; The complete oscillation continuously appearing in the current waveform is identified, the period values of 3 adjacent oscillations are calculated, and the average is taken as the current waveform oscillation period feature; The time interval feature, the voltage waveform slope change rate feature, and the current waveform oscillation period feature are bound with the corresponding working condition label, and are stored in the bridge arm dynamic feature library in the structure of working condition label-feature group-original time sequence index.

[0020] In an embodiment, from the reserved stable period time sequence data, a time sequence segment of 5 continuous low frequency periods is intercepted, each period being 20 ms, and the total time length being 100 ms. The peak detection module scans the time sequence segment period by period, captures the maximum value of the voltage waveform in each period as the voltage peak value, and the maximum value of the current waveform as the current peak value, and synchronously records the time stamp (unit: μs) corresponding to each peak value. The module detects the delay ≤1 ms. The difference between the voltage peak value time stamp and the current peak value time stamp in each period is calculated to obtain 5 time interval values (unit: μs). The sum of the 5 values is divided by 5 to obtain the time interval feature value.

[0021] In another embodiment, the voltage waveform amplitude change is monitored. When the voltage gradually rises from 300 V to 2700 V, the interval is determined as a rising edge. For each rising edge, the voltage values (unit: V) and corresponding time values (unit: ms) of the starting point and the ending point are read, the ratio of the voltage difference value and the time difference value is calculated to obtain the slope change value (unit: V / ms) of the rising edge. The slope change values of 3 continuously occurring rising edges are summed and divided by 3 to obtain the voltage waveform slope change rate feature value.

[0022] In another embodiment, the current waveform fluctuation is continuously monitored. When the current fluctuation amplitude exceeds 50 A and presents a continuous form of two wave peaks and one wave trough, it is determined as a complete oscillation. The starting time stamp and the ending time stamp (unit: μs) of each complete oscillation are recorded, and the difference between the starting time stamps of adjacent two oscillations is calculated as a single oscillation period value (unit: μs). The 3 adjacent oscillation period values continuously occurring are selected, summed and divided by 3 to obtain the current waveform oscillation period feature value.

[0023] The time interval feature value, the voltage waveform slope change rate feature value, and the current waveform oscillation period feature value are bound with the corresponding working condition label (rated load 1000 A, 50% load 500 A, light load 200 A) to form a feature group. The feature group is stored in the bridge arm dynamic feature library by the data storage unit in the structure of “working condition label-feature group-original time sequence index”. The original time sequence index is the time stamp range (format: “starting time stamp μs-ending time stamp μs”) of the time sequence data based on the feature extraction in the CSV file.

[0024] Preferably, step S2: identifying the voltage waveform and the current waveform of the converter bridge arm, and synchronously recording the line resistance and the line reactance between the converter stations; In this embodiment, the Hall voltage sensor is used to collect the voltage analog signal of the converter bridge arm, the sensor measurement range is 0-3000V, the accuracy is 0.1%FS, and the output analog signal is filtered by a low-pass filter (cutoff frequency 1kHz, attenuation slope 40dB / decade) to remove high-frequency interference, then connected to a 16-bit resolution data acquisition card, the sampling rate of the acquisition card is set to 100kHz, the input impedance is 1MΩ, the analog signal is converted into digital signal and transmitted to the waveform recognition unit.

[0025] It should be noted that the waveform recognition unit monitors the amplitude fluctuation of the voltage digital signal in real time, sets the effective fluctuation range of the voltage to 300V to 2700V, and counts the signal repetition period through the period detection circuit. When the fluctuation range of the continuous 5 periods is stable within the effective range and the period deviation is ≤1ms (target low frequency period 20ms), it is determined that the voltage waveform recognition is completed, and the voltage value (unit: V) corresponding to each time stamp (unit: μs) is recorded synchronously.

[0026] In an embodiment, the Rogowski coil current sensor is used to collect the current analog signal of the converter bridge arm, the sensor measurement range is 0-2000A, the accuracy is 0.2%FS, and the output signal is transmitted to the signal conditioning module through the shielded cable. The module optimizes the signal amplitude through the differential amplification circuit (amplification factor 100 times, input offset voltage ≤5μV), and then connects to the same data acquisition card to convert into digital signal.

[0027] It should be noted that the waveform recognition unit sets the effective fluctuation range of the current digital signal to 20A to 1800A, and verifies the signal periodicity through the same period detection logic as the voltage waveform. When the fluctuation range of the continuous 5 periods meets the requirements and the period deviation is ≤1ms, the current waveform recognition is completed, and the current value (unit: A) corresponding to each time stamp (unit: μs) is recorded.

[0028] In another embodiment, the input terminals of the line impedance tester are connected to the two ends of the interchanger station line respectively, the measurement range of the tester is resistance 0-10Ω and reactance 0-100mH, the measurement accuracy is 0.5%FS, and the four-wire measurement method is used to eliminate the influence of wiring resistance. The tester has a built-in GPS time module (synchronization accuracy 1μs), which realizes clock calibration with the data acquisition card through the time synchronization protocol, ensures that the measurement timing is consistent with the waveform collection timing, and the measurement interval is set to 10ms.

[0029] It should be noted that the tester collects the resistance value (unit: Ω) and the reactance value (unit: mH) of the line in real time, and transmits the measurement data and the corresponding timestamp (unit: μs) to the data recording unit after each measurement. The data recording unit aligns the voltage waveform data, the current waveform data, the line resistance data and the line reactance data according to the timestamp, and forms a standardized data set containing the fields of "timestamp μs, bridge arm voltage V, bridge arm current A, line resistance Ω, line reactance mH".

[0030] Preferably, step S3: extracting the voltage waveform and the current waveform, matching the same label characteristics in the bridge arm dynamic characteristic library, and dynamically calibrating the bridge arm parameters in the preset impedance parameter framework; Optionally, before extracting the voltage waveform and the current waveform in step S3, the following steps are included: Real-time acquisition of the voltage waveform and the current waveform, and baseline correction, taking the average amplitude of the waveform as the reference to eliminate the overall offset of the waveform; After correction, comparing the amplitudes of each local segment of the voltage waveform and the current waveform with the overall average amplitude, and determining that the segment is an abnormal pulse when the amplitude of the local segment exceeds the preset multiple of the overall average amplitude; Replacing the local waveform where the abnormal pulse is located with the interpolation of the adjacent normal waveform, and then extracting the voltage waveform and the current waveform.

[0031] In this embodiment, the data preprocessing unit reads the voltage waveform data and the current waveform data of 3 consecutive low-frequency periods (total duration: 60 ms), calculates the voltage amplitude average value and the current amplitude average value of all sampling points in the interval, and subtracts the voltage amplitude average value from the original value of the voltage waveform at each time, and subtracts the current amplitude average value from the original value of the current waveform at each time, to complete the baseline correction and eliminate the overall offset of the waveform.

[0032] In another embodiment, after correction, the voltage waveform and the current waveform are divided into independent local segments with a length of 1 ms, the maximum amplitude is calculated for each segment, and the maximum amplitude is compared with the average amplitude of the corresponding waveform. When the maximum amplitude of the local segment exceeds 3 times the average amplitude of the corresponding waveform, it is determined to be an abnormal pulse, and the start timestamp and the end timestamp of the segment are recorded synchronously.

[0033] It should be noted that for the determined abnormal pulse segment, the end sampling value of the previous 1 ms normal segment and the start sampling value of the subsequent 1 ms normal segment are extracted, the interpolation nodes are equally divided based on the time interval of the abnormal pulse segment, the amplitude data of each node is obtained through linear calculation, the original data of the abnormal pulse segment is completely replaced with the interpolation data, and the voltage waveform data and the current waveform data without offset and abnormal pulse are formed, providing a basis for subsequent pressure flow change characteristic extraction.

[0034] Optionally, the voltage waveform and the current waveform in step S3 are extracted by the following method: The real-time voltage waveform and the current waveform are divided into continuous analysis units according to low-frequency periods, and each analysis unit contains one complete period; For each analysis unit, the voltage zero-crossing point and the current zero-crossing point are marked, and the positions and time of the voltage peak value and the current peak value are extracted respectively, taking the zero-crossing point as the starting point; The time difference between the voltage peak value and the current peak value in the same analysis unit is calculated as the time interval feature of the unit; The slope change of the voltage waveform and the current waveform in the rising section is calculated, and the average value of the change is taken as the voltage-current change feature.

[0035] In this embodiment, the data processing unit reads the preprocessed voltage waveform data and current waveform data, divides the waveform data into continuous analysis units according to 20ms low-frequency periods, and each analysis unit contains complete period data from one voltage zero-crossing point to the next voltage zero-crossing point in the same direction, and synchronously associates the current waveform data of the corresponding period. In each analysis unit, the zero-crossing point detection circuit monitors the voltage waveform amplitude change in real time, and marks the voltage zero-crossing point when the voltage value jumps from -5mV to +5mV, and records the time stamp (unit: μs) of this time; for the current waveform, when the current value jumps from -10mA to +10mA, mark the current zero-crossing point, and record the corresponding time stamp (unit: μs).

[0036] In an embodiment, taking the voltage zero-crossing point timestamp as the starting point, the peak value detection circuit scans the subsequent voltage waveform data, captures the sampling point with the maximum amplitude as the voltage peak value, and records the time stamp (unit: μs) corresponding to its position; taking the current zero-crossing point timestamp as the starting point, scanning the subsequent current waveform data, capturing the sampling point with the maximum amplitude as the current peak value, and recording its time stamp (unit: μs). Calculate the difference between the voltage peak value timestamp and the current peak value timestamp in the same analysis unit to obtain the time interval feature (unit: μs) of the unit.

[0037] In another embodiment, for the voltage waveform rising section, taking the interval from the voltage zero-crossing point to the voltage peak value as the rising section, calculating the difference (unit: V) between the starting voltage value (zero-crossing voltage value 0V) and the voltage peak value, and dividing by the time difference (unit: ms) of the interval to obtain the voltage slope change (unit: V / ms); for the current waveform, taking the interval from the current zero-crossing point to the current peak value as the rising section, calculating the difference (unit: A) between the starting current value (zero-crossing current value 0A) and the current peak value, and dividing by the time difference (unit: ms) of the interval to obtain the current slope change (unit: A / ms); sum the voltage slope change and the current slope change and divide by 2 to obtain the voltage-current change feature of the analysis unit.

[0038] Optionally, the matching of the same label characteristics in the bridge arm dynamic characteristic library in step S3 includes: All characteristic groups consistent with the current working condition label are called from the bridge arm dynamic characteristic library; The called characteristic groups are compared in order of time interval, slope change rate, and oscillation period, and the characteristic group in which each dimension is within the preset matching range is retained; From the retained characteristic groups, the comprehensive deviation value of the current characteristic and each group of characteristics is calculated, and the characteristic with the smallest comprehensive deviation value is selected as the matching result.

[0039] In the embodiment, the characteristic matching unit inputs the current working condition label (such as rated load 1000A, 50% load 500A, light load 200A) through the query interface of the bridge arm dynamic characteristic library, calls all characteristic groups in the library that are completely consistent with the label, each group of characteristics includes time interval characteristic value (unit: μs), voltage waveform slope change rate characteristic value (unit: V / ms), and current waveform oscillation period characteristic value (unit: μs), and the query response time is ≤100 ms.

[0040] In an embodiment, the characteristic comparison circuit compares the called characteristic groups in order of time interval, slope change rate, and oscillation period, the preset matching ranges are time interval ±50 μs, slope change rate ±0.5 V / ms, and oscillation period ±10 μs, and only the characteristic group in which the three-dimensional characteristic values fall within the corresponding ranges is retained.

[0041] In another embodiment, the deviation calculation unit calculates the absolute difference value of the time interval value of the current characteristic and each group of time interval characteristic values, the absolute difference value of the current voltage slope change rate value and each group of corresponding values, and the absolute difference value of the current current oscillation period value and each group of corresponding values, respectively, sums the three absolute difference values after dividing by the upper limit of the preset matching range of the corresponding dimension (50 μs, 0.5 V / ms, 10 μs), obtains the comprehensive deviation value of each group, selects the characteristic group with the smallest comprehensive deviation value as the matching result, and records the original time sequence index of the characteristic group.

[0042] Optionally, the dynamic calibration of the bridge arm parameters in the preset impedance parameter framework in step S3 includes: The reference parameters of the current bridge arm are called from the preset impedance parameter framework, including equivalent resistance and equivalent inductance; According to the difference direction of the matched characteristics and the preset reference characteristics, the adjustment trend of the resistance and the inductance is determined; The equivalent resistance is adjusted according to the difference proportion, and the resistance correlation characteristic deviation of the simulated waveform output by the parameter framework and the real-time acquisition waveform is compared each time the adjustment is made; When the resistance deviation meets the requirements, the equivalent inductance is adjusted according to the same logic until the inductance correlation characteristic deviation also meets the requirements.

[0043] In the embodiment, the parameter calling interface calls the reference parameters of the current bridge arm from the preset impedance parameter framework, including the equivalent resistance reference value 2Ω and the equivalent inductance reference value 50mH, and the calling response time is less than or equal to 50ms.

[0044] In an embodiment, the deviation analysis circuit extracts the resistance correlation characteristic (voltage peak decay rate, unit: % / ms) in the matching characteristic and the resistance correlation characteristic (reference voltage peak decay rate 0.5% / ms) in the preset reference characteristic, calculates the difference between the two, and determines that the equivalent resistance needs to be increased if the matching characteristic value is greater than the reference characteristic value; otherwise, the equivalent resistance needs to be decreased. Meanwhile, the inductance correlation characteristic (current rise time, unit: ms) in the matching characteristic and the inductance correlation characteristic (reference current rise time 10ms) in the reference characteristic are extracted, and the equivalent inductance needs to be increased if the matching characteristic value is greater than the reference characteristic value; otherwise, the equivalent inductance needs to be decreased.

[0045] It should be noted that the equivalent resistance is adjusted according to the initial 5% difference ratio. After each adjustment, the waveform comparison unit aligns the analog voltage waveform output by the impedance parameter framework with the real-time collected voltage waveform according to the time axis, calculates the absolute deviation value of the resistance correlation characteristics (voltage peak decay rate) of the two, and stops adjusting the equivalent resistance and locks the current value when the deviation value is less than or equal to 3%. Then, the equivalent inductance is adjusted according to the same logic, and the initial adjustment ratio is 5%. After each adjustment, the absolute deviation value of the inductance correlation characteristics (current rise time) of the simulated current waveform and the real-time collected current waveform is compared, until the deviation value is less than or equal to 5%, the current equivalent inductance value is locked, and the bridge arm parameter dynamic calibration is completed.

[0046] Especially important is that if there is no feature in the same tag feature group that meets the preset matching range, the following operations are performed: Expand the matching range of each dimension step by step, and re-screen the same tag feature group after each expansion; If there is still no feature group that meets the conditions after expanding to the maximum allowed range, the feature with the smallest comprehensive deviation value in the same tag feature group is selected, and the matching is marked as a low matching degree matching. The number of parameter verification is increased in the subsequent calibration process.

[0047] In the present embodiment, when there is no feature group in the same tag feature group that meets the preset matching range (time interval ± 50 μs, slope change rate ± 0.5 V / ms, oscillation period ± 10 μs), the feature screening module starts the range expansion mechanism, and each time the matching range of each dimension is expanded by 20%, i.e. after the first expansion, the time interval is ± 60 μs, the slope change rate is ± 0.6 V / ms, and the oscillation period is ± 12 μs. After expansion, the same tag feature group is called again for dimension-by-dimension comparison, and all feature groups within the new range are retained. Each expansion and screening process takes ≤200 ms.

[0048] In another embodiment, if the continuous expansion reaches the maximum allowed range (time interval ± 150 μs, slope change rate ± 1.5 V / ms, oscillation period ± 30 μs) and still no feature group meets the conditions, the deviation calculation unit recalculates the comprehensive deviation value (calculation method consistent with the original logic) for all same tag feature groups, and selects the feature group with the smallest comprehensive deviation value as the matching result. At the same time, a "low matching degree matching" label (label field value "1") is added to the feature matching result; in the subsequent calibration process, the parameter verification module increases the original set parameter verification number (3 times) to 5 times, and each verification is judged according to the original deviation threshold (resistance associated feature deviation ≤3%, inductance associated feature deviation ≤5%). Only after all verifications are passed, the calibration parameters are locked.

[0049] Optionally, the verification parameter adjustment effect in the calibration process includes: The simulated waveform output by the preset impedance parameter framework is accurately aligned with the real-time collected waveform on the time axis; The peak deviation, period deviation and slope deviation of the aligned waveform are calculated respectively; When the three types of deviations are within the allowed range of the corresponding dimension, it is determined that the calibration is qualified, the parameter adjustment is stopped, and the current parameters are locked.

[0050] In the present embodiment, based on the timestamps (unit: μs) of the simulated voltage waveform and the simulated current waveform output by the calibration preset impedance parameter framework and the timestamps of the real-time collected voltage waveform and current waveform, the time axis error between the two is controlled within ≤10 μs, achieving accurate alignment.

[0051] In one embodiment, the aligned waveform is extracted to obtain the simulated voltage peak value (unit: V) and the real-time voltage peak value (unit: V) within each low-frequency period (20 ms), the absolute difference value and the real-time voltage peak value are calculated to obtain the voltage peak value deviation (unit: %); the same operation is performed on the current waveform to obtain the current peak value deviation (unit: %). At the same time, the absolute difference between the duration of each period of the simulated waveform (unit: ms) and the corresponding period duration of the real-time waveform is calculated as the period deviation (unit: ms).

[0052] In another embodiment, for the voltage waveform rising segment (zero-crossing to peak interval), the absolute difference between the simulated slope (unit: V / ms) and the real-time slope (unit: V / ms) and the ratio of the real-time slope are calculated to obtain the voltage slope deviation (unit: %); the same operation is performed on the current waveform rising segment to obtain the current slope deviation (unit: %). The peak value deviation allowed range is ≤2%, the period deviation allowed range is ≤1 ms, and the slope deviation allowed range is ≤5%. When the voltage peak value deviation, the current peak value deviation, the period deviation, the voltage slope deviation, and the current slope deviation are all within the corresponding allowed range, the parameter adjustment is stopped and the current equivalent resistance value (unit: Ω) and the equivalent inductance value (unit: mH) are stored.

[0053] Especially important is that after completing the bridge arm parameter calibration in step S3, the following operations are performed: The calibrated parameters, matching characteristics, and corresponding real-time waveform segments are packaged as calibration records. The calibration records are stored in order of bridge arm number and calibration time, and the historical calibration log of the parameter framework is automatically updated every time a calibration is completed. The log includes the value comparison before and after parameter adjustment and the calibration qualification determination result.

[0054] In this embodiment, after completing the bridge arm parameter calibration, the calibrated equivalent resistance value (unit: Ω), equivalent inductance value (unit: mH), matching obtained time interval characteristic value (unit: μs), voltage waveform slope change rate characteristic value (unit: V / ms), current waveform oscillation period characteristic value (unit: μs), and corresponding real-time waveform segment (60 ms long, containing 3 complete low-frequency periods, time stamp range from calibration start time stamp to calibration end time stamp, unit: μs) of the calibration process are packaged as calibration records. The record file is named as "bridge arm number (01-10)-calibration time stamp (based on GPS timing accurate to μs, format is YYYY-MM-DDHH:MM:SS.μs)", and is stored in order of bridge arm number and calibration time in the storage medium.

[0055] It should be noted that every time a calibration is completed, the system automatically extracts the equivalent resistance reference value (2 Ω) and the equivalent inductance reference value (50 mH) before parameter adjustment and the calibrated value after adjustment to generate a value comparison table, and records the bridge arm number, calibration time, and calibration qualification determination result (qualified / failed, based on the determination result that the peak value deviation is ≤2%, the period deviation is ≤1 ms, and the slope deviation is ≤5%) to integrate into a calibration log entry, which is written into the historical calibration log of the impedance parameter framework. The log is arranged in reverse order of calibration time, each entry is assigned a unique 10-digit identification number, and is stored in a log file in a specified path. The log file is named by date (YYYY-MM-DD), a new file is generated every day, and historical files are archived.

[0056] Preferably, step S4: determine the connection relationship of the line between converter stations, and connect the line resistance and line reactance to the corresponding connection node of the calibrated impedance parameter framework; In this embodiment, the physical terminal identification (such as etching number or label information) at both ends of the line between converter stations is identified, the terminal identification is compared with the preset line topology relationship table (containing the mapping relationship between terminal identification and impedance parameter framework node), and the corresponding nodes of both ends of the line in the impedance parameter framework are confirmed. For example, if one end of the line is identified as "T-01" and the other end is identified as "T-02", the node "N1" corresponding to "T-01" and the node "N2" corresponding to "T-02" in the topology table are determined, and the connection relationship of the line is determined as the connection link of the nodes "N1" and "N2" in the framework.

[0057] In an embodiment, the line resistance and reactance are measured by a line impedance tester. The tester uses four-wire connection (the current end is connected to both ends of the line for injecting test current, and the voltage end is connected in parallel to both ends of the line for collecting voltage). The test current is set as a low-frequency sine wave (for example, frequency 50Hz, amplitude 5A), the measurement interval is set as a fixed value (for example, 10ms), and the average value of multiple measurements (for example, 3 times) is calculated as the real-time value of the line resistance (for example, 3 measurement values 0.58Ω, 0.62Ω, 0.60Ω, average value 0.60Ω) and the real-time value of the line reactance (for example, 3 measurement values 41mH, 43mH, 42mH, average value 42mH).

[0058] In another embodiment, in the calibrated impedance parameter framework, the connection link of the nodes "N1" and "N2" is located according to the determined connection relationship, and the calculated line resistance value and line reactance value are written to the resistance parameter bit and reactance parameter bit corresponding to the link. After writing, the consistency of the parameter value and the measurement average value is confirmed by the verification function of the framework (the deviation is within the preset range, for example, ≤0.5%), and after confirming that there is no error, the line connection relationship, the resistance value, the reactance value and the measurement original data are stored to the history record module of the framework in a fixed format (containing time stamp, line identification).

[0059] Please refer to Fig. 2 , step S5: analyze the high-frequency waveforms output by the calibrated impedance parameter framework, identify the period of repeated oscillation signals, calculate the compensation coefficient and perform high-frequency correction on the impedance parameter framework according to the compensation coefficient, and obtain the impedance model of the new energy flexible low-frequency sending-out system.

[0060] In the embodiment, the high-frequency waveform timing data output from the calibrated impedance parameter framework includes high-frequency voltage waveform timing (frequency range 2-20 kHz, unit V) and high-frequency current waveform timing (frequency range 2-20 kHz, unit A), and the corresponding time stamp (unit μs) is recorded synchronously. The high-frequency waveform timing is divided into analysis windows according to a fixed time length of 1 ms, and each window contains 1 ms of time-continuous data (such as the start time stamp t0 to t0+1000 μs), and it is ensured that there are at least 5 complete potential oscillation periods in each window (calculated based on the minimum high-frequency oscillation period of 200 μs).

[0061] It should be noted that, for each window, the oscillation signal is identified by the peak detection circuit: the peak determination threshold is set to 1.5 times the average amplitude of the waveform in the window, when the amplitude of a certain point of the waveform exceeds the threshold and the amplitudes of the adjacent points on both sides are less than the point, it is marked as a peak and its time stamp (unit μs) is recorded; the time stamp difference of adjacent peaks is calculated to obtain the single oscillation period value (unit μs), and the occurrence frequency of all period values in the window is counted (such as 220 μs appearing 4 times and 230 μs appearing 6 times in a certain window). The period value frequency of all windows is summarized, and the period value with the highest total occurrence frequency is selected as the repeated oscillation signal period (such as 230 μs, with a total occurrence frequency of 72 times).

[0062] In another embodiment, the compensation coefficient is calculated based on the repeated oscillation signal period: the resistance compensation coefficient is (repeated oscillation period ÷ reference oscillation period) x 0.8 (the reference oscillation period is preset to 200 μs), and the inductance compensation coefficient is (repeated oscillation period ÷ reference oscillation period) x 0.7; the resistance compensation coefficient is multiplied by the current equivalent resistance value in the framework to obtain the modified equivalent resistance value (unit Ω), and the inductance compensation coefficient is multiplied by the current equivalent inductance value to obtain the modified equivalent inductance value (unit mH). The modified equivalent resistance value, equivalent inductance value, and line resistance and line reactance are re-entered into the impedance parameter framework, and the modified high-frequency waveform timing is output by starting the framework. The oscillation period deviation (modified deviation ≤5 μs) and peak value deviation (modified deviation ≤3%) of the waveform before and after the modification are compared, and the deviation is confirmed to meet the requirements, and the framework is the impedance model of the new energy flexible low-frequency sending-out system.

[0063] Optionally, the high-frequency waveform timing output by the calibrated impedance parameter framework is analyzed in step S5. The high-frequency waveform is divided into a plurality of analysis windows according to a fixed time length, and each window contains at least 5 complete potential oscillation periods; For each window, the period values of all oscillation signals therein are identified and the occurrence frequency is counted; The statistical results of all windows are summarized, and the period value with the highest occurrence frequency is taken as the repeated oscillation signal period.

[0064] In the present embodiment, high-frequency band waveform timing data (frequency range 2kHz-20kHz) is retrieved from the calibrated impedance parameter framework, including high-frequency band voltage waveform timing data (unit: V) and high-frequency band current waveform timing data (unit: A), and the corresponding time stamp (unit: s) is synchronously associated. The high-frequency band waveform timing is divided into multiple analysis windows by a waveform segmentation tool according to a fixed time length of 1ms, and the time stamp range of each window is 1ms continuously (such as the starting time stamp t1 to the ending time stamp t1+1000 s), ensuring that each window contains at least 5 complete potential oscillation periods (calculated according to the minimum oscillation period of 200 s in the high-frequency band, and 1ms window can accommodate 5 periods). For each analysis window, the wave peak position of the oscillation signal is identified by a wave peak detection circuit: the wave peak determination threshold is set to 1.5 times the average amplitude of the waveform in the window, and when the waveform amplitude exceeds the threshold and the amplitudes of the adjacent points before and after the threshold are less than the threshold, it is marked as a wave peak, and the time stamp (unit: s) corresponding to each wave peak is recorded; the time stamp difference of adjacent two wave peaks is calculated to obtain the period value (unit: s) of a single oscillation signal, and the same operation is performed on all wave peaks in the window to obtain multiple period values and count the occurrence frequency of each period value (such as 180 s appearing 3 times and 200 s appearing 5 times in a window). The period value frequency statistics results of all analysis windows (for example, a total of 20 windows) are summarized to form a summary table containing "period value s-total occurrence frequency", and the period value with the highest total occurrence frequency in the summary table (such as 200 s, total occurrence frequency 68 times) is selected as the repeated oscillation signal period.

[0065] Please refer to Fig. 3 The present application also provides a new energy flexible low-frequency sending-out system impedance model construction system for executing the new energy flexible low-frequency sending-out system impedance model construction method, and the new energy flexible low-frequency sending-out system impedance model construction system comprises: A bridge arm feature library construction module is configured to record the real-time timing of the voltage and current of the converter bridge arm under different working conditions, extract the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate and the current waveform oscillation period, and label the corresponding working condition label to form a bridge arm dynamic feature library. A bridge arm and line parameter acquisition module is configured to identify the voltage waveform and current waveform of the converter bridge arm and synchronously record the line resistance and line reactance between the converter stations. A bridge arm parameter calibration module is configured to extract the voltage waveform and current waveform pressure flow change characteristics, match the same label characteristics in the bridge arm dynamic feature library, and dynamically calibrate the bridge arm parameters in the pre-set impedance parameter framework. A line parameter access module is configured to determine the connection relationship of the line between the converter stations, and access the line resistance and line reactance to the corresponding connection node in the calibrated impedance parameter framework. The high-frequency correction and model construction module is used for analyzing a high-frequency waveform time sequence output by the calibrated impedance parameter framework, identifying a repeated oscillation signal period, calculating a compensation coefficient according to the repeated oscillation signal period, and correcting the impedance parameter framework at a high frequency to obtain an impedance model of the new energy flexible low-frequency sending-out system.

[0066] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the application being defined by the appended claims and not by the above description, and all variations falling within the meaning and the scope of the equivalent elements of the application file are intended to be included in the application.

[0067] The above description is merely illustrative of the application and is not intended to limit the scope of the application. Various modifications to the embodiments will be readily apparent to persons skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Therefore, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for constructing an impedance model of a new energy flexible low-frequency sending-out system, characterized in that, The new energy flexible low-frequency sending-out system comprises a multi-level matrix converter bridge arm and an interconverter station line, and the method comprises the following steps: Step S1: recording the real-time time sequence of the voltage and current of the converter bridge arm under different working conditions; extracting the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate and the current waveform oscillation period, and labeling the corresponding working condition label to form a bridge arm dynamic feature library; Step S2: identifying the voltage waveform and current waveform of the converter bridge arm, and synchronously recording the resistance and reactance of the interconverter station line; Step S3: extracting the voltage and current change characteristics in the voltage waveform and current waveform, matching the same label characteristics in the bridge arm dynamic feature library, and dynamically calibrating the bridge arm parameters in the preset impedance parameter framework; Step S4: determining the connection relationship of the interconverter station line, and connecting the line resistance and line reactance to the corresponding connection node of the calibrated impedance parameter framework; Step S5: analyzing the high-frequency waveform time sequence output by the calibrated impedance parameter framework, identifying the repeated oscillation signal period, calculating the compensation coefficient and high-frequency correcting the impedance parameter framework according to the compensation coefficient, and obtaining the impedance model of the new energy flexible low-frequency sending-out system. 2.The method of claim 1, wherein, The recording of the real-time time sequence of the voltage and current of the converter bridge arm in step S1 comprises: For each working condition, the bridge arm is switched from the current working condition to the target working condition, and after the output waveform is continuously stable for 3 low-frequency periods, the time sequence recording is started; During the recording process, the working condition stable state in each low-frequency period is synchronously marked every time a low-frequency period is passed; After the recording is completed, the recorded real-time time sequence of the voltage and current of the converter bridge arm is segmented according to the marked stable period, and only the time sequence data of the stable period is retained.

3. The method of claim 1, wherein the impedance model of the new energy flexible low-frequency sending-out system is constructed by, The formation of the bridge arm dynamic feature library in step S1 is specifically: The voltage peak value and the current peak value in the continuous 5 low-frequency periods are extracted, the time interval of the two in each period is calculated, and the average of the time intervals of the 5 periods is taken as the time interval feature of the time sequence; The slope change value of the voltage waveform at each rising edge is extracted, and the average of the slope change values of the continuous 3 rising edges is taken as the voltage waveform slope change rate feature; The complete oscillation continuously appearing in the current waveform is identified, the period values of 3 adjacent oscillations are calculated, and the average is taken as the current waveform oscillation period feature; The time interval feature, voltage waveform slope change rate feature and current waveform oscillation period feature are bound with the corresponding working condition label, and stored in the bridge arm dynamic feature library in the structure of working condition label-feature group-original time sequence index.

4. The method of claim 1, wherein the impedance model of the new energy flexible low-frequency sending-out system is constructed. Before the extraction of the voltage and current change characteristics in the voltage waveform and current waveform in step S3 comprises: The voltage waveform and current waveform are collected in real time, and baseline correction is performed, taking the average amplitude of the waveform as the reference to eliminate the overall offset of the waveform; After correction, the amplitudes of each local segment of the voltage waveform and current waveform are compared with the overall average amplitude, and when the local segment amplitude exceeds the preset multiple of the overall average amplitude, it is determined that the segment is an abnormal pulse; The local waveform where the abnormal pulse is located is replaced with the interpolation of the adjacent normal waveform, and then the voltage and current change characteristics in the voltage waveform and current waveform are extracted.

5. The method of claim 1, wherein the impedance model of the new energy flexible low-frequency sending-out system is constructed. The extraction of the voltage and current change characteristics in the voltage waveform and current waveform in step S3 is specifically: Divide the real-time voltage waveform and current waveform into continuous analysis units according to low-frequency periods, and each analysis unit contains one complete period; For each analysis unit, mark the voltage zero-crossing point and the current zero-crossing point, and extract the position and time of the voltage peak value and the current peak value from the zero-crossing point as the starting point; Calculate the time interval between the voltage peak value and the current peak value in the same analysis unit as the time interval feature of the unit; Calculate the slope change of the voltage waveform and the current waveform in the rising section, and take the average of the change as the voltage-current change feature.

6. The method of claim 1, wherein the impedance model of the new energy flexible low-frequency sending-out system is constructed. The matching of the bridge arm dynamic feature library in step S3 includes: Call all feature groups consistent with the current working condition label from the bridge arm dynamic feature library; For the called feature groups, compare them in order of time interval, slope change rate, and oscillation period, and keep the feature groups that meet the preset matching range in each dimension; From the retained feature groups, calculate the comprehensive deviation value of the current feature and each group of features, and select the feature with the smallest comprehensive deviation value as the matching result.

7. The method of claim 6, wherein the method further comprises: The dynamic calibration of the bridge arm parameters in the preset impedance parameter framework in step S3 includes: Call the reference parameters of the current bridge arm from the preset impedance parameter framework, including equivalent resistance and equivalent inductance; According to the difference between the matching features and the preset reference features, determine the adjustment trend of the resistance and the inductance; Adjust the equivalent resistance according to the difference ratio, and compare the resistance-related feature deviation between the simulation waveform output by the parameter framework and the real-time collected waveform after each adjustment; When the resistance deviation meets the requirements, adjust the equivalent inductance according to the same logic until the inductance-related feature deviation also meets the requirements. 8.The method of claim 7, wherein, The verification of parameter adjustment effect during calibration includes: Align the simulation waveform output by the preset impedance parameter framework with the real-time collected waveform according to the time axis; Calculate the peak value deviation, period deviation, and slope deviation of the aligned waveform respectively; When the peak value deviation, period deviation, and slope deviation are within the allowed range of the corresponding dimension, it is determined that the calibration is qualified, and the parameter adjustment is stopped and the current parameters are locked. 9.The method of claim 1, wherein, The analysis of the high-frequency waveform timing output by the calibrated impedance parameter framework in step S5 is as follows: Divide the high-frequency waveform into multiple analysis windows according to a fixed time length, and each window contains at least 5 complete potential oscillation periods; For each window, identify the period values of all oscillation signals and count the occurrence frequency; Summarize the statistical results of all windows, and take the period value with the highest occurrence frequency as the period of the repeated oscillation signal.

10. An impedance model construction system of a new energy flexible low-frequency sending-out system, characterized in that, The new energy flexible low-frequency sending system impedance model construction method and system includes: A bridge arm feature library construction module is configured to record the real-time timing of the voltage and current of the converter bridge arm under different working conditions, extract the time interval of the voltage peak value and the current peak value, the voltage waveform slope change rate, and the current waveform oscillation period, and label the corresponding working condition label to form a bridge arm dynamic feature library; A bridge arm and line parameter acquisition module is configured to identify the voltage waveform and current waveform of the converter bridge arm, and synchronously record the line resistance and line reactance between the converter stations. The bridge arm parameter calibration module is configured to extract a voltage waveform and a current waveform, match a same tag feature in a dynamic characteristic library of a bridge arm, and dynamically calibrate a bridge arm parameter in a preset impedance parameter framework. The line parameter access module is configured to determine a connection relationship of a line between converter stations, and access a line resistance and a line reactance to a corresponding connection node of the calibrated impedance parameter framework. The high-frequency correction and model construction module is configured to analyze a high-frequency waveform time sequence output by the calibrated impedance parameter framework, identify a repeated oscillation signal period, calculate a compensation coefficient according to the repeated oscillation signal period, and perform high-frequency correction on the impedance parameter framework to obtain an impedance model of the new energy flexible low-frequency sending-out system.

Images