Automatic control methods applied to static converters and static converters

Abstract

This application relates to the field of converter control technology, specifically to an automatic control method for static converters and a static converter itself. The method includes: during the process of a static converter supplying power to a single industrial device, acquiring in real-time the output voltage waveform data of each phase of the inverter in the static converter and the effective value data of the static converter's output voltage; dividing the current operating time interval of the single industrial device into sub-intervals, acquiring the harmonic anomaly factor of each phase within each sub-interval; acquiring the voltage difference degree and harmonic distortion coefficient within each sub-interval, acquiring the comprehensive anomaly value, overall anomaly coefficient, and unsteady-state coefficient within each sub-interval; and adjusting the carrier frequency of the static converter for the next operation of the single industrial device. This application aims to improve the stability of the static converter's output voltage by adjusting the carrier frequency of the static converter.

Description

Technical Field

[0001] This application relates to the field of converter control technology, specifically to an automatic control method for static converters and a static converter. Background Technology

[0002] A static converter is a device that uses power semiconductor devices to convert direct current (DC) power into alternating current (AC) power. It is widely used in secondary power conversion of DC power sources, mainly DC generators and batteries, as well as in grid-connected power generation of renewable energy sources such as solar and wind power, and in the power systems of industrial equipment.

[0003] With the continuous development and advancement of industrial equipment, higher requirements are being placed on the output voltage waveform quality and control performance of static converters. Due to the complexity and special nature of the operating environment of industrial equipment, the control of static converters is easily affected by various factors, such as load changes and sudden input voltage fluctuations. This leads to problems such as waveform distortion, amplitude instability, and frequency deviation in the output voltage of the static converter, thereby affecting the normal operation of industrial equipment and reducing its performance and efficiency. Existing control methods fail to fully consider the influence of nonlinear loads and input voltage changes in the actual operation of static converters, resulting in output voltage instability. Summary of the Invention

[0004] In view of the above, it is necessary to provide an automatic control method and a static converter for static converters. Compared with traditional automatic control methods for static converters, this method improves the stability of the output voltage of the static converter by adjusting its carrier frequency.

[0005] In a first aspect, embodiments of this application provide an automatic control method for a static converter, the method comprising the following steps:

[0006] During the process of a static converter supplying power to a single industrial device, the output voltage waveform data of each phase of the inverter in the static converter and the effective value data of the output voltage of the static converter are acquired in real time.

[0007] The time interval of the current operation of the single industrial equipment is divided into sub-intervals. By comparing the output voltage waveform data of each phase in each sub-interval with the harmonic components therein, and combining the amplitude distribution of the output voltage waveform data of each phase in each sub-interval in the frequency domain, the harmonic anomaly factor of each phase in each sub-interval is obtained.

[0008] By comparing the output voltage waveform data of different phases in each sub-interval, the voltage difference in each sub-interval is obtained. Then, by combining the difference in harmonic anomaly factors between different phases in each sub-interval, the harmonic distortion coefficient in each sub-interval is obtained, the comprehensive anomaly value in each sub-interval is obtained, and by combining the distribution of harmonic anomaly factors of all phases in each sub-interval, the overall anomaly coefficient in each sub-interval is obtained.

[0009] Each sub-interval is pre-defined as a control sub-interval. The unsteady-state coefficient within each sub-interval is obtained by analyzing the fluctuation of the effective output voltage data within all control sub-intervals of each sub-interval and its correlation with the overall anomaly coefficient.

[0010] The carrier frequency of the static converter during the next operation of the single industrial equipment is adjusted by using the unsteady-state coefficients in each sub-interval within the current operating time interval of the single industrial equipment.

[0011] In one embodiment, the process of obtaining the harmonic anomaly factor is as follows:

[0012] For each sub-interval, calculate the difference between the output voltage waveform data of each phase and its harmonic components within the sub-interval;

[0013] Obtain the spectrum of the output voltage waveform data of each phase in the sub-interval and perform curve fitting. Calculate the mean value of the kurtosis of the peaks at all harmonic frequencies except the fundamental frequency in the spectrum.

[0014] Calculate the sum of the amplitudes of all harmonic frequencies except the fundamental frequency in the spectrum diagram; calculate the ratio of the sum to the amplitude of the fundamental frequency in the spectrum diagram;

[0015] The harmonic anomaly factors of each phase within the sub-interval are directly proportional to the difference and the ratio, and inversely proportional to the mean.

[0016] In one embodiment, the harmonic anomaly factor is calculated as follows:

[0017] Calculate the product of the normalized value of the difference and the ratio; map the mean to a positive number, and the harmonic anomaly factor is the ratio of the product to the positive number.

[0018] In one embodiment, the voltage difference is the mean of the normalized values ​​of the metric distances between any two phases in each sub-interval.

[0019] In one embodiment, the harmonic distortion coefficient is the mean of the differences in harmonic anomaly factors between any two phases within each sub-interval.

[0020] In one embodiment, the overall anomaly value is the product of the voltage difference and the harmonic distortion coefficient.

[0021] In one embodiment, the process of obtaining the overall anomaly coefficient is as follows:

[0022] Calculate the average value of the harmonic anomaly factor for all phases within each sub-interval;

[0023] The overall anomaly coefficient is positively correlated with the average value and the comprehensive anomaly value, respectively.

[0024] In one embodiment, the process of obtaining the unsteady-state coefficient is as follows:

[0025] The fluctuation degree within each sub-interval is calculated by measuring the fluctuation degree of the effective value data of the output voltage within each sub-interval.

[0026] Calculate the correlation coefficient between the volatility within all control sub-intervals and the overall anomaly coefficient for each sub-interval; the non-steady-state coefficient is positively correlated with the volatility within each sub-interval and the correlation coefficient, respectively.

[0027] In one embodiment, the method for adjusting the carrier frequency of the static converter during the next operation of the individual industrial equipment is as follows:

[0028] Calculate the arithmetic mean of the unsteady-state coefficients in all sub-intervals within the time interval of the current operation of the single industrial equipment, and use the product of the normalized value of the arithmetic mean and the preset initial value of the carrier frequency as the carrier frequency of the static converter for the next operation of the single industrial equipment.

[0029] Secondly, embodiments of this application also provide a static converter, wherein the static converter contains:

[0030] The data acquisition module is used to acquire, in real time, the output voltage waveform data of each phase of the inverter in the static converter and the effective value data of the output voltage of the static converter during the process of the static converter providing power to a single industrial device.

[0031] The carrier frequency adjustment module is used to divide the time interval of the current operation of the single industrial equipment into sub-intervals, and obtain the harmonic anomaly factor of each phase in each sub-interval by comparing the output voltage waveform data of each phase in each sub-interval with the harmonic components therein, and combining the amplitude distribution of the output voltage waveform data of each phase in each sub-interval in the frequency domain.

[0032] By comparing the output voltage waveform data of different phases in each sub-interval, the voltage difference in each sub-interval is obtained. Then, by combining the difference in harmonic anomaly factors between different phases in each sub-interval, the harmonic distortion coefficient in each sub-interval is obtained, the comprehensive anomaly value in each sub-interval is obtained, and by combining the distribution of harmonic anomaly factors of all phases in each sub-interval, the overall anomaly coefficient in each sub-interval is obtained.

[0033] Each sub-interval is pre-defined as a control sub-interval. The unsteady-state coefficient within each sub-interval is obtained by analyzing the fluctuation of the effective output voltage data within all control sub-intervals of each sub-interval and its correlation with the overall anomaly coefficient.

[0034] The carrier frequency of the static converter during the next operation of the single industrial equipment is adjusted by using the unsteady-state coefficients in each sub-interval within the current operating time interval of the single industrial equipment.

[0035] This application has at least the following beneficial effects:

[0036] This application can identify the degree of harmonic distortion by comparing output voltage waveform data with harmonic components. By analyzing harmonic components in the frequency domain, the degree of harmonic distortion can be assessed more accurately, thus better reflecting the output voltage quality. By comparing the output voltage waveform data of different phases, the degree of imbalance of the three-phase voltage can be quantified. Combined with the differences in the harmonic distortion state of different phases, the abnormal situation of output voltage in each sub-interval can be comprehensively assessed, providing a more comprehensive basis for subsequent calculation of the unsteady-state coefficient.

[0037] Furthermore, by analyzing the consistency between the distortion characteristics of the inverter output voltage waveform and the irregular fluctuations of the output voltage RMS value, the instability of the static converter under the influence of comprehensive factors is analyzed. By adjusting the carrier frequency of the static converter based on the instability, the automatic control effect of the static converter is optimized. This can reduce the influence of waveform distortion caused by nonlinear loads and input voltage changes during the operation of the static converter, thereby improving the stability of the static converter's output voltage. Attached Figure Description

[0038] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating the steps of an automatic control method for a static converter provided in one embodiment of this application;

[0040] Figure 2 This is a schematic diagram illustrating the process of obtaining the overall anomaly coefficient;

[0041] Figure 3 This is a schematic diagram illustrating the process of obtaining the unsteady-state coefficients. Detailed Implementation

[0042] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It should be understood that, unless otherwise stated, " / " in this application means "or".

[0044] It should also be noted that the terms "first" and "second" in this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0045] The automatic control method for static converters and the specific scheme for static converters provided in this application are described in detail below with reference to the accompanying drawings.

[0046] Please see Figure 1 This document illustrates a flowchart of an automatic control method for a static converter according to an embodiment of this application. The method includes the following steps:

[0047] Step 1: During the process of the static converter supplying power to a single industrial device, the output voltage waveform data of each phase of the inverter in the static converter and the effective value data of the output voltage of the static converter are acquired in real time.

[0048] In the process of a static converter converting direct current (DC) to alternating current (AC) to supply power to individual industrial equipment, the changes in the output voltage waveforms of each phase of the inverter and the effective value of the static converter's output voltage reflect the operating status of the static converter. This embodiment uses an oscilloscope to acquire real-time data on the output voltage waveforms of each phase of the inverter and the effective value of the static converter's output voltage.

[0049] In this embodiment, the sampling frequency of the output voltage waveform data is 2000 Hz, and the sampling frequency of the output voltage RMS data is 500 Hz. The sampling frequencies of the output voltage waveform data and the output voltage RMS data are preset by the user. The implementer can set them according to the actual situation. This application does not impose any special restrictions.

[0050] Step 2: Divide the time interval of the current operation of the single industrial equipment into sub-intervals. Analyze the output voltage waveform data of each phase of the inverter and the effective value data of the output voltage of the static converter collected in each sub-interval to obtain the unsteady-state coefficient in each sub-interval.

[0051] In industrial power systems, the operating state of static converters is frequently affected by various disturbances, such as load changes and sudden input voltage fluctuations. Especially when the inverter in a static converter is connected to a nonlinear load, such as an RCD rectifier load composed of resistors and capacitors, it often leads to severe voltage waveform distortion. This phenomenon not only alters the output voltage waveform but may also cause significant changes in the effective value of the static converter's output voltage. Therefore, to ensure the stable operation and power quality of the power system, it is necessary to analyze the waveform changes of the inverter's output voltage in the static converter and the relevant characteristics of the effective value of the static converter's output voltage.

[0052] Industrial equipment typically relies on three-phase AC power. Inverters convert direct current (DC) to AC to meet the power demands of these devices. However, during this conversion, the greater the influence of nonlinear loads, the more pronounced the distortion of the inverter's output voltage waveform becomes, primarily manifesting as harmonic distortion and three-phase imbalance. Harmonic distortion causes the output voltage waveform of each phase of the inverter to no longer be a standard sine wave, but rather to contain harmonic components.

[0053] Step 2.1: Divide the time interval of the current operation of the single industrial equipment into sub-intervals. By comparing the output voltage waveform data of each phase in each sub-interval with the harmonic components therein, and combining the amplitude distribution of the output voltage waveform data of each phase in each sub-interval in the frequency domain, obtain the harmonic anomaly factor of each phase in each sub-interval.

[0054] Based on the above analysis, the time interval of the current operation of the single industrial device is divided into sub-intervals. The fundamental and harmonic components of the output voltage waveform data for each phase within each sub-interval are obtained, with the fundamental component approximating a standard sine wave. Under good operating conditions, the influence of nonlinear loads is minimal, resulting in significantly lower harmonic component content in the inverter output voltage. The obtained fundamental component is also closer to the acquired output voltage waveform. Furthermore, the obtained harmonic components are mainly concentrated in specific frequencies, such as integer multiples of the fundamental frequency, exhibiting a relatively concentrated spectral distribution without widespread spectral spread.

[0055] Furthermore, taking the i-th sub-interval as an example, the difference between the output voltage waveform data of each phase in the i-th sub-interval and its harmonic components is calculated. The smaller the difference, the closer the obtained fundamental component is to the output voltage waveform. Obtain the spectrum of the output voltage waveform data for each phase within the i-th sub-interval. The spectrum shows the frequency components and amplitudes of the output voltage waveform data. In the spectrum, the data is mainly concentrated near the frequencies corresponding to the fundamental and harmonic components. Taking a 50Hz AC current as an example, 50Hz is taken as the fundamental frequency, and the harmonic frequencies are integer multiples of the fundamental frequency, such as 100Hz and 150Hz. Curve fitting is performed using all frequencies and their amplitudes in the spectrum. The fitted curves show peak patterns at the fundamental and harmonic frequencies. Calculate the kurtosis of the peaks at each harmonic frequency in the spectrum, excluding the fundamental frequency. When the static converter is less affected by the nonlinear load, the amplitude of the harmonic frequencies in the spectrum is lower than that of the fundamental frequency, and the spectral distribution is relatively concentrated, without widespread spectral diffusion. In this case, the peak shape will be sharper, resulting in a larger kurtosis at the harmonic frequencies. Calculate the mean kurtosis of the peaks at all harmonic frequencies in the spectrum, excluding the fundamental frequency. The larger the mean, the more concentrated the spectral distribution at the harmonic frequencies. The calculation of kurtosis is a well-known technique and will not be described in detail in this application.

[0056] Furthermore, calculate the sum of the amplitudes of all harmonic frequencies except the fundamental frequency in the spectrum diagram; calculate the ratio of the sum to the amplitude of the fundamental frequency in the spectrum diagram; the smaller the ratio, the lower the proportion of harmonic frequencies in the output voltage waveform.

[0057] Furthermore, the product of the normalized value of the difference and the ratio is calculated, and the mean is mapped to a positive number. The ratio of the product to the positive number is used as the harmonic anomaly factor for each phase in the i-th sub-interval. The larger the harmonic anomaly factor, the lower the similarity between the output voltage waveform and the fundamental component, and the more abnormal the harmonic frequency distribution. In this case, the harmonic distortion of the output voltage of each phase is more significant.

[0058] In this embodiment, since the voltage waveform has a short period, in order to obtain its short-term rapid change characteristics, the length of each sub-interval is 1 second. The length of each sub-interval is preset by the user and the implementer can set it according to the actual situation. This application does not impose any special restrictions.

[0059] In this embodiment, the sliding window iterative discrete Fourier transform algorithm is used to obtain the fundamental component and harmonic components. The sliding window iterative discrete Fourier transform algorithm is a well-known technology and will not be described in detail in this application. As other implementation methods, based on the ability to obtain the fundamental component and harmonic components of the output voltage waveform data of each phase in each sub-interval, the implementer may use other existing feasible technologies. This application does not impose any special restrictions.

[0060] In this embodiment, the difference between the output voltage waveform data of each phase and its harmonic components in the i-th sub-interval is the DTW (Dynamic Time Warping) distance. The DTW distance is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to measure the degree of difference between the output voltage waveform data of each phase and its harmonic components in the i-th sub-interval, the implementer may adopt other existing feasible technologies, which will not be described in detail here.

[0061] In this embodiment, the discrete Fourier transform technique is used to obtain the spectrum of the output voltage waveform data of each phase in the i-th sub-interval. The discrete Fourier transform technique is a well-known technique and will not be described in detail in this application. As other implementation methods, based on the ability to obtain the spectrum of the output voltage waveform data of each phase in the i-th sub-interval, the implementer may use other existing techniques, such as fast Fourier transform, etc. This application does not impose any special restrictions.

[0062] In this embodiment, the least squares method is used for curve fitting. The least squares method is a well-known technique and will not be described in detail here. As other implementation methods, based on the ability to perform curve fitting on the spectrum, the implementer may use other existing techniques, such as local weighted regression, K-nearest neighbor regression, etc. This application does not impose any special restrictions.

[0063] In this embodiment, the hyperbolic tangent function is used to obtain the normalized value of the difference. The hyperbolic tangent function is a well-known technique and will not be described in detail in this application.

[0064] In this embodiment, the mean is mapped to a positive number by calculating the sum of the mean and a preset value greater than 0. The value of the preset value greater than 0 is preset by the user and can be set by the implementer. In this embodiment, the preset value greater than 0 is 0.01. There are many ways to map data to a positive number, and the implementer can choose other existing feasible methods.

[0065] Step 2.2: By comparing the output voltage waveform data of different phases in each sub-interval, the voltage difference in each sub-interval is obtained. Then, by combining the difference in harmonic anomaly factors between different phases in each sub-interval, the harmonic distortion coefficient in each sub-interval is obtained, and the comprehensive anomaly value in each sub-interval is obtained. Finally, by combining the distribution of harmonic anomaly factors of all phases in each sub-interval, the overall anomaly coefficient in each sub-interval is obtained.

[0066] Furthermore, under the influence of nonlinear loads, the output voltage of each phase of the inverter is prone to three-phase imbalance, and the difference between the output voltages of different phases will increase. Therefore, the mean of the normalized distance of the output voltage waveform data between any two phases in the i-th sub-interval is taken as the voltage difference degree in the i-th sub-interval. The larger the voltage difference degree, the greater the difference in output voltage between different phases in the i-th sub-interval.

[0067] In this embodiment, since there is a certain phase difference between the output voltage waveforms of different phases, that is, there is a certain time delay between the output voltages of different phases, the distance is measured as SBD (Shape Based Distance). SBD distance is a well-known technology and will not be described in detail in this application. As another implementation, considering that there is a certain time delay between the output voltages of different phases, the implementer can use other existing feasible technologies to calculate the degree of difference between the output voltage waveform data of different phases.

[0068] In this embodiment, the hyperbolic tangent function is used to obtain the normalized value of the distance measurement. The hyperbolic tangent function is a well-known technique and will not be described in detail in this application.

[0069] Meanwhile, under severe waveform distortion, the harmonic distortion state between different phases will also show a certain degree of difference. Therefore, the average value of the difference between the harmonic anomaly factors between any two phases in the i-th sub-interval is taken as the harmonic distortion coefficient in the i-th sub-interval. The larger the harmonic distortion coefficient, the more obvious the difference in the degree of waveform distortion between different phases.

[0070] In this embodiment, the difference between harmonic anomaly factors is the absolute value of the difference. As other implementation methods, based on the ability to measure the degree of difference between harmonic anomaly factors, the implementer may use other calculation methods, such as ratio, square of difference, etc. This application does not impose any special restrictions.

[0071] Furthermore, the product of the voltage difference degree and the harmonic distortion coefficient in the i-th sub-interval is taken as the comprehensive anomaly value in the i-th sub-interval. The larger the comprehensive anomaly value, the more significant the differences in output voltage waveform and harmonic distortion state between different phases in the i-th sub-interval.

[0072] Furthermore, by combining the comprehensive anomaly value within the i-th sub-interval with the distribution of harmonic anomaly factors of all phases within the i-th sub-interval, the overall anomaly coefficient within the i-th sub-interval is obtained. Specifically, the average value of the harmonic anomaly factors of all phases within the i-th sub-interval is calculated to reflect the overall harmonic distortion degree of the inverter's output voltage across all phases. The overall anomaly coefficient within the i-th sub-interval is positively correlated with both the average value and the comprehensive anomaly value within the i-th sub-interval. A larger overall anomaly coefficient indicates a greater degree of overall harmonic distortion in the inverter's output voltage and a greater degree of state difference between different phases. A schematic diagram of the overall anomaly coefficient acquisition process is shown below. Figure 2 As shown.

[0073] In this embodiment, the product of the average value and the comprehensive outlier value in the i-th sub-interval is used as the overall outlier coefficient in the i-th sub-interval.

[0074] In another embodiment, the sum of the average value and the comprehensive outlier value in the i-th sub-interval is used as the overall outlier coefficient in the i-th sub-interval.

[0075] Calculate the overall anomaly coefficients for the remaining sub-intervals using the same method as for the overall anomaly coefficient in the i-th sub-interval.

[0076] Step 2.3: Preset each control sub-interval for each sub-interval, and obtain the unsteady-state coefficient in each sub-interval by the fluctuation degree of the effective value data of the output voltage in all control sub-intervals of each sub-interval and its correlation with the overall anomaly coefficient.

[0077] Load changes and sudden input voltage fluctuations can cause significant changes in the RMS output voltage of a static converter. For example, when a sudden load is applied to the power system containing the static converter, the RMS output voltage of the static converter will drop instantaneously. Subsequently, under the regulation of the control system, the RMS output voltage of the static converter will gradually recover and reach a relatively stable state. However, during the steady-state operation of the static converter, fluctuations in the input voltage will cause irregular fluctuations in the RMS output voltage. Therefore, the volatility within the i-th sub-interval is calculated by measuring the degree of fluctuation in the RMS output voltage data within the i-th sub-interval. The greater the volatility, the more irregular the changes in the RMS output voltage data within the i-th sub-interval. The volatility within the remaining sub-intervals is calculated using the same method as for the i-th sub-interval.

[0078] In this embodiment, the fractal dimension of all voltage effective value data in the i-th sub-interval obtained using the Higuchi technique is used as the volatility in the i-th sub-interval. The Higuchi technique is a well-known technique and will not be described in detail in this application. As other implementation methods, based on the ability to measure the volatility of the output voltage effective value data in the i-th sub-interval, the implementer may use other existing techniques, such as information entropy, etc. This application does not impose any special restrictions.

[0079] Furthermore, the severe output voltage waveform distortion caused by the nonlinear load of the inverter can seriously affect the effective value of the output voltage of the static converter. Therefore, it is necessary to better suppress the harmonics in the AC output of the inverter in the static converter. The more consistent the distortion characteristics of the inverter's output voltage waveform with the irregular fluctuations of the output voltage effective value, the more severely the AC power provided by the static converter is affected by external factors.

[0080] Based on the above analysis, each sub-interval is pre-defined as a control sub-interval. The correlation coefficient between the volatility and the overall anomaly coefficient within all control sub-intervals of the i-th sub-interval is calculated. A larger correlation coefficient indicates a more consistent relationship between the distortion characteristics of the inverter output voltage waveform and the degree of anomaly in the effective value of the output voltage. Combining the correlation coefficient and volatility within the i-th sub-interval, the unsteady-state coefficient within the i-th sub-interval is obtained. A larger unsteady-state coefficient indicates a greater degree of instability in the output voltage of the static converter under the influence of various factors. A schematic diagram of the unsteady-state coefficient acquisition process is shown below. Figure 3 As shown.

[0081] In this embodiment, the first preset number of sub-intervals adjacent to each sub-interval are used as the reference sub-intervals of each sub-interval. The preset number is 8. The preset number is preset by human intervention. Based on the premise that the preset number is an integer within the range of [8,10], the implementer can set the specific value of the preset number by himself.

[0082] In this embodiment, the product of the correlation coefficient of the i-th sub-interval and the volatility within the i-th sub-interval is used as the non-steady-state coefficient within the i-th sub-interval.

[0083] In another embodiment, the cumulative value of the correlation coefficient of the i-th sub-interval and the volatility within the i-th sub-interval is used as the non-steady-state coefficient within the i-th sub-interval.

[0084] In this embodiment, the process of calculating the correlation coefficient between the volatility and the overall anomaly coefficient in all control sub-intervals of the i-th sub-interval is as follows: the volatility and the overall anomaly coefficient in all control sub-intervals of the i-th sub-interval are arranged in chronological order to form a volatility sequence and an overall anomaly coefficient sequence, and the Pearson correlation coefficient between the volatility sequence and the overall anomaly coefficient sequence is calculated. The Pearson correlation coefficient is a well-known technique and will not be described in detail in this application. As other implementation methods, based on the ability to measure the correlation between the volatility and the overall anomaly coefficient in all control sub-intervals of the i-th sub-interval, the implementer may use other existing techniques, such as the Spearman correlation coefficient, etc. This application does not impose any special restrictions.

[0085] Step 3: Adjust the carrier frequency of the static converter for the next operation of the single industrial equipment by using the unsteady-state coefficients in each sub-interval within the time interval of the current operation of the single industrial equipment.

[0086] This application analyzes the harmonic distortion and three-phase imbalance characteristics of the inverter output voltage waveform, as well as the irregular variation characteristics of the converter output voltage RMS value, and calculates the unsteady-state coefficient based on the consistency between the two. Then, it optimizes the automatic control of the static converter using the unsteady-state coefficient. Specifically, this application employs sinusoidal pulse width modulation (SPWM) control technology to improve the stability of the static converter's output voltage. A larger calculated unsteady-state coefficient indicates a greater susceptibility of the static converter to external influences, resulting in a more unstable output voltage that may affect the normal operation of industrial equipment. In this case, a higher carrier frequency needs to be set during SPWM control to improve the stability of the static converter's output voltage. Conversely, a smaller calculated unsteady-state coefficient allows for a lower carrier frequency to avoid excessive changes in the electrical signal in the line, which could affect the normal operation of the power system. Based on the above analysis, the arithmetic mean of the unsteady-state coefficients in all sub-intervals within the time interval of the current operation of the single industrial equipment is calculated. The product of the normalized value of the arithmetic mean and the preset initial value of the carrier frequency is used as the carrier frequency of the static converter for the next operation of the single industrial equipment.

[0087] In this embodiment, the hyperbolic tangent function is used to obtain the normalized value of the arithmetic mean. The hyperbolic tangent function is a well-known technique and will not be described in detail in this application.

[0088] In this embodiment, the preset initial value of the carrier frequency is 16kHz. The preset initial value of the carrier frequency is preset manually, and the implementer can set it according to the actual situation. This application does not impose any special restrictions. In addition, in order to avoid affecting the output voltage quality of the static converter due to the carrier frequency being too low, when the calculated carrier frequency of the static converter for the next operation of the single industrial equipment is less than 2kHz, the carrier frequency of the static converter for the next operation of the single industrial equipment is set to 2kHz.

[0089] Based on the same inventive concept as the above method, this application also provides a static converter, including: an inverter, an amplifier, a filter module, and a control module;

[0090] The inverter is used to convert the input DC power into AC power through the high-frequency switching action of semiconductor devices, and is the core part of the static converter to realize the conversion of electrical energy form.

[0091] The amplifier is used to amplify the AC output of the inverter;

[0092] The filtering module is used to filter the output electrical signal, suppress harmonic components in the current and voltage, and thus obtain a more ideal sinusoidal alternating current.

[0093] The control module compares the output AC power with a reference signal, outputs a feedback signal, and adjusts the voltage, frequency, and phase through corresponding calculations to ensure the stable and efficient operation of the static converter. The control module includes a data acquisition module and a carrier frequency adjustment module. The data acquisition module is used to acquire the output voltage waveform data of each phase of the inverter in the static converter and the effective value data of the output voltage of the static converter in real time during the process of the static converter providing power to a single industrial device.

[0094] The carrier frequency adjustment module is used to divide the time interval of the current operation of the single industrial equipment into sub-intervals, and obtain the harmonic anomaly factor of each phase in each sub-interval by comparing the output voltage waveform data of each phase in each sub-interval with the harmonic components therein, and combining the amplitude distribution of the output voltage waveform data of each phase in each sub-interval in the frequency domain.

[0095] By comparing the output voltage waveform data of different phases in each sub-interval, the voltage difference in each sub-interval is obtained. Then, by combining the difference in harmonic anomaly factors between different phases in each sub-interval, the harmonic distortion coefficient in each sub-interval is obtained, the comprehensive anomaly value in each sub-interval is obtained, and by combining the distribution of harmonic anomaly factors of all phases in each sub-interval, the overall anomaly coefficient in each sub-interval is obtained.

[0096] Each sub-interval is pre-defined as a control sub-interval. The unsteady-state coefficient within each sub-interval is obtained by analyzing the fluctuation of the effective output voltage data within all control sub-intervals of each sub-interval and its correlation with the overall anomaly coefficient.

[0097] The carrier frequency of the static converter during the next operation of the single industrial equipment is adjusted by using the unsteady-state coefficients in each sub-interval within the current operating time interval of the single industrial equipment.

[0098] In summary, this application can identify the degree of harmonic distortion by comparing output voltage waveform data with harmonic components. By analyzing harmonic components in the frequency domain, the degree of harmonic distortion can be assessed more accurately, thus better reflecting the output voltage quality. By comparing the output voltage waveform data of different phases, the degree of imbalance of the three-phase voltage can be quantified. Combined with the differences in the harmonic distortion state of different phases, the abnormal situation of the output voltage in each sub-interval can be comprehensively assessed, providing a more comprehensive basis for the subsequent calculation of the unsteady-state coefficient.

[0099] Furthermore, by analyzing the consistency between the distortion characteristics of the inverter output voltage waveform and the irregular fluctuations of the output voltage RMS value, the instability of the static converter under the influence of comprehensive factors is analyzed. By adjusting the carrier frequency of the static converter based on the instability, the automatic control effect of the static converter is optimized. This can reduce the influence of waveform distortion caused by nonlinear loads and input voltage changes during the operation of the static converter, thereby improving the stability of the static converter's output voltage.

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0101] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects.

Claims

1. An automatic control method applied to a static converter, characterized in that, The method comprises the following steps: In the process of providing power supply for a single industrial equipment by a static converter, real-time acquisition of output voltage waveform data of each phase of an inverter in the static converter and output voltage effective value data of the static converter; Each sub-interval of a time interval of a current operation of the single industrial equipment is divided, and a harmonic abnormality factor of each phase in each sub-interval is acquired by comparing the output voltage waveform data of each phase in each sub-interval with a harmonic component therein and combining amplitude distribution of the output voltage waveform data of each phase in the frequency domain in each sub-interval; A voltage difference degree in each sub-interval is acquired by comparing the output voltage waveform data of different phases in each sub-interval, and then a harmonic distortion coefficient in each sub-interval is acquired by combining a difference between the harmonic abnormality factors of different phases in each sub-interval, and a comprehensive abnormality value in each sub-interval is acquired, and a global abnormality coefficient in each sub-interval is acquired by combining distribution of the harmonic abnormality factors of all phases in each sub-interval; Each control sub-interval of each sub-interval is preset, and a non-steady state coefficient in each sub-interval is acquired by a fluctuation degree of the output voltage effective value data in all control sub-intervals of each sub-interval and a correlation between the fluctuation degree and the global abnormality coefficient; The non-steady state coefficient in each sub-interval in the time interval of the current operation of the single industrial equipment is used to adjust a carrier frequency of the static converter in a next operation of the single industrial equipment. The acquisition process of the harmonic abnormality factor is as follows: For each sub-interval, a difference between the output voltage waveform data of each phase in the sub-interval and a harmonic component thereof is calculated. A spectrum diagram of the output voltage waveform data of each phase in the sub-interval is acquired and curve fitting is performed, and a mean value of kurtosis of peaks at all harmonic frequencies except a fundamental frequency in the spectrum diagram is calculated. A sum value of amplitudes of all harmonic frequencies except the fundamental frequency in the spectrum diagram is calculated, and a ratio of the sum value to an amplitude of the fundamental frequency in the spectrum diagram is calculated. The harmonic abnormality factor of each phase in the sub-interval is directly proportional to the difference and the ratio and inversely proportional to the mean value. The calculation method of the harmonic abnormality factor is as follows: A product of a normalized value of the difference and the ratio is calculated, the mean value is mapped to a positive number, and the harmonic abnormality factor is a ratio of the product to the positive number.

2. The automatic control method for a static converter according to Claim 1, wherein The voltage difference degree is a mean value of normalized values of metric distances of the output voltage waveform data between any two phases in each sub-interval.

3. The automatic control method for a static converter according to Claim 1, wherein The harmonic distortion coefficient is a mean value of differences between the harmonic abnormality factors of any two phases in each sub-interval.

4. The automatic control method for a static converter according to Claim 1, wherein The comprehensive abnormality value is a product of the voltage difference degree and the harmonic distortion coefficient.

5. The automatic control method for a static converter according to Claim 1, wherein The acquisition process of the global abnormality coefficient is as follows: A mean value of the harmonic abnormality factors of all phases in each sub-interval is calculated. The global abnormality coefficient is positively correlated to the mean value and the comprehensive abnormality value.

6. The automatic control method for a static converter according to Claim 1, wherein The acquisition process of the non-steady state coefficient is as follows: A fluctuation degree in each sub-interval is calculated by a fluctuation degree of the output voltage effective value data in the sub-interval. A correlation coefficient between the fluctuation degree in each sub-interval and the global abnormality coefficient is calculated, and the non-steady state coefficient is positively correlated to the fluctuation degree and the correlation coefficient.

7. The automatic control method for a static converter according to Claim 1, wherein The method for adjusting the carrier frequency of the static converter during the next operation of the single industrial equipment comprises the following steps: An arithmetic mean of the non-steady-state coefficients in all subintervals in the time interval of the current operation of the single industrial equipment is calculated, and a product of a normalized value of the arithmetic mean and a preset initial value of the carrier frequency is taken as the carrier frequency of the static converter during the next operation of the single industrial equipment.

8. A static converter, using the automatic control method for a static converter as claimed in claim 1, characterized in that, The static converter comprises: a data acquisition module configured to acquire, in real time, output voltage waveform data of each phase of the inverter and output voltage effective value data of the static converter during the process in which the static converter provides power supply for the single industrial equipment; a carrier frequency adjustment module configured to divide the time interval of the current operation of the single industrial equipment into subintervals, compare the output voltage waveform data of each phase in each subinterval with harmonic components in the output voltage waveform data, and obtain a harmonic abnormality factor of each phase in each subinterval according to the amplitude distribution of the output voltage waveform data of each phase in the frequency domain in each subinterval; the carrier frequency adjustment module is further configured to compare the output voltage waveform data of different phases in each subinterval, obtain a voltage difference degree in each subinterval, and further obtain a harmonic distortion coefficient in each subinterval according to the difference between the harmonic abnormality factors of different phases in each subinterval, obtain a comprehensive abnormality value in each subinterval, and obtain an overall abnormality coefficient in each subinterval according to the distribution of the harmonic abnormality factors of all phases in each subinterval; the carrier frequency adjustment module is further configured to preset each comparison subinterval of each subinterval, obtain a non-steady-state coefficient in each subinterval according to the fluctuation degree of the output voltage effective value data in all comparison subintervals of each subinterval and the correlation between the overall abnormality coefficient and the non-steady-state coefficient; and the carrier frequency adjustment module is further configured to adjust the carrier frequency of the static converter during the next operation of the single industrial equipment according to the non-steady-state coefficients in each subinterval in the time interval of the current operation of the single industrial equipment.

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