A method for calculating converter transformer DC bias intrusion current based on even harmonic absolute content

Abstract

The application discloses a method for calculating DC bias intrusion current based on even harmonic absolute content, which comprises the following steps: establishing a magnetic flux-current relationship curve according to no-load test data; establishing an excitation current even harmonic and a reference data group based on the magnetic flux-current relationship curve; performing linear fitting on the excitation current even harmonic and the reference data group by using a support vector machine algorithm to form a DC bias intrusion current-even harmonic sum relationship function; analyzing actual recording data collected on site to obtain actual even harmonic sum of the recording data; and bringing the actual even harmonic sum into the DC bias intrusion current-even harmonic sum relationship function to obtain a quantitative result of the DC bias intrusion current of the recording data.

Description

Technical Field

[0001] This invention relates to the field of DC bias technology for transformers, and more specifically, to a method for inverting and estimating the DC bias intrusion current of a converter transformer based on the absolute content of even harmonics. Background Technology

[0002] DC bias is an abnormal operating condition of a transformer. The DC component of the winding current generates a constant-direction DC magnetic flux in the core, causing the operating point of the magnetization curve to enter the saturation region. This leads to distortion of the excitation current, the appearance of even-order harmonic components in the frequency spectrum, and adverse effects such as increased temperature rise and intensified vibration, threatening the safe and stable operation of the transformer and the power system. To ensure the safe and stable operation of the transformer, abnormal DC bias conditions are typically monitored using direct DC bias measurement or indirect acoustic and vibration measurement.

[0003] Existing research generally suggests that transformer DC bias primarily originates from extremely low-frequency currents induced at the neutral point by ground currents from geomagnetic storms or high-voltage direct current transmission systems. These currents typically have a frequency of 0.001-1 Hz, which is approximately DC compared to the power frequency of 50 Hz. Therefore, direct measurement methods generally involve installing a measuring device with a low-pass filter at the neutral point. However, in practice, due to insufficient complementarity in valve control strategies or deviations in the symmetry of valve arm parameters, the asymmetrical DC component generated by the converter valve flows into the converter transformer's valve-side windings, causing valve-side DC bias. Since converter transformers often use delta connections on the valve side, the line and phase currents are inconsistent, and dedicated measuring devices are not installed on-site, making direct monitoring of the valve-side current DC component difficult. Indirect assessment methods using acoustic and vibration measurements are affected by ambient noise levels, only reflecting the relative severity of bias and unable to quantitatively estimate the DC bias experienced by the converter transformer.

[0004] Therefore, none of the above methods can efficiently and accurately obtain the DC bias intrusion current under the bias condition on the valve side in the engineering site, making it difficult to accurately assess the bias state and meet the needs of bias control. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for inverting and estimating the DC bias intrusion current of a converter transformer based on the absolute content of even-order harmonics.

[0006] According to one aspect of the present invention, a method for inverting and estimating the DC bias intrusion current of a converter transformer based on the absolute content of even harmonics is provided, comprising:

[0007] Establish the flux-current relationship curve based on the no-load test data;

[0008] Establish even-order harmonics of excitation current and a reference data set based on the flux-current relationship curve;

[0009] The support vector machine algorithm is used to linearly fit the even harmonics of the excitation current and the reference data set to form a relationship function between DC bias current intrusion current and even harmonics.

[0010] Analyze the actual waveform data collected on site to obtain the actual even harmonics of the waveform data;

[0011] By substituting the actual even-order harmonics into the DC bias intrusion current-even-order harmonics relationship function, the quantitative result of the DC bias intrusion current in the recorded waveform data is obtained.

[0012] Optionally, a flux-current relationship curve is established based on the no-load test data, including:

[0013] Linear extrapolation of the excitation voltage-current relationship was performed based on the no-load test data to obtain the voltage-current relationship curve;

[0014] Based on the pre-constructed voltage-magnetic flux relationship function and voltage-current relationship curve, the magnetic flux value corresponding to the excitation current is calculated point by point;

[0015] A regression algorithm is used to construct a flux-current relationship curve based on each excitation current and its corresponding flux value.

[0016] Optionally, the voltage-flux relationship function is:

[0017]

[0018] In the formula, Φ m is the magnetic flux value; N is the number of coil turns; f is the frequency; E is the effective value of the induced electromotive force.

[0019] Optionally, an even-order harmonic excitation current and a reference data set are established based on the flux-current relationship curve, including:

[0020] According to the preset target DC bias magnetic intrusion current I DC_set Determine the initial calculation interval containing the target DC magnetic flux;

[0021] Based on the flux-current relationship curve, a piecewise linear interpolation algorithm is used to calculate the discretized time-domain waveform of the theoretical excitation current corresponding to the median point of the initial calculation interval.

[0022] The DC component I of the discretized time-domain waveform of the theoretical excitation current is extracted by frequency domain decomposition. DC ;

[0023] When DC component I DC and the preset target DC bias magnetic intrusion current I DC_set If the preset criteria are met, the iteration terminates, and the preset target DC bias intrusion current I is determined. DC_setIf the excitation current time-domain solution is not found, a binary search strategy is used to dynamically shrink the initial calculation interval, and the above steps are iterated until the preset criteria are met.

[0024] Optionally, the preset criterion is: |I DC_set -I DC |<ε.

[0025] Optionally, the waveform data includes grid-side current and valve-side current, and

[0026] The actual waveform data collected on-site is analyzed to obtain the actual even-order harmonics of the waveform data, including:

[0027] High-pass filtering is performed on the recorded waveform data to obtain the corrected grid-side current and the corrected valve-side current;

[0028] The time-domain waveform of the excitation current is calculated based on the modified grid-side current and the modified valve-side current.

[0029] The excitation current time-domain waveform is decomposed by fast Fourier transform to extract the superposition value of even harmonic content and obtain the actual even harmonic sum.

[0030] Optionally, the calculation expression for the time-domain waveform of the excitation current is:

[0031]

[0032] In the formula, I m I1 and I2 are the excitation current, grid-side current, and valve-side current, respectively, and N1 and N2 are the number of turns on the grid side and valve side, respectively.

[0033] According to another aspect of the present invention, a converter transformer DC bias intrusion current inversion and estimation device based on the absolute content of even harmonics is provided, comprising:

[0034] The first module is used to establish the magnetic flux-current relationship curve based on the no-load test data.

[0035] The second module is used to establish the even harmonics of the excitation current and the reference data set based on the flux-current relationship curve.

[0036] The fitting module is used to perform linear fitting of the even harmonics of the excitation current and the reference data set using the support vector machine algorithm, so as to form a relationship function of DC bias intrusion current-even harmonics.

[0037] The analysis module is used to analyze the actual waveform data collected on site and obtain the actual even harmonics of the waveform data;

[0038] The module is used to input the actual even harmonic sum into the DC bias intrusion current-even harmonic sum relationship function to obtain the quantitative result of the DC bias intrusion current of the recorded waveform data.

[0039] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0040] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0041] Therefore, this invention proposes a method for inverting and estimating the DC bias intrusion current of converter transformers based on the absolute content of even harmonics. This method effectively separates the interference factors of field recording and realizes the calculation of DC bias intrusion current based on conventional measurement and monitoring devices of converter transformers. Moreover, this method is not limited by the winding connection method and does not require additional monitoring equipment. It can be used as a technical means for monitoring and evaluating the DC bias condition of converter transformers in operation. Attached Figure Description

[0042] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0043] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention, showing a method for inverting and extrapolating the DC bias intrusion current of a converter transformer based on the absolute content of even harmonics.

[0044] Figure 2 This is a schematic diagram of the basic process for performing DC bias intrusion current inversion calculation provided by an exemplary embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the algorithm flow for dynamically optimizing and estimating the theoretical excitation current waveform using a binary search strategy, provided by an exemplary embodiment of the present invention.

[0046] Figure 4 This is a scatter plot of the relationship between the even harmonics of the excitation current and the DC bias intrusion current of a 500kV converter transformer obtained by the method of the present invention in an exemplary embodiment of the present invention.

[0047] Figure 5 This is a schematic diagram of the structure of the converter transformer DC bias intrusion current inversion and calculation device based on the absolute content of even harmonics provided in an exemplary embodiment of the present invention.

[0048] Figure 6 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0049] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0050] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0051] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0052] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0053] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0054] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0055] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0056] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0057] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0058] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0059] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0060] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0061] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0062] Exemplary methods

[0063] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention, showing a method for inverting and extrapolating the DC bias intrusion current of a converter transformer based on the absolute content of even-order harmonics. This embodiment can be applied to electronic devices, such as... Figure 1 As shown, the converter transformer DC bias intrusion current inversion calculation method 100 based on the absolute content of even harmonics includes the following steps:

[0064] Step 101: Establish the magnetic flux-current relationship curve based on the no-load test data;

[0065] Step 102: Establish the even harmonics of the excitation current and the reference data set based on the flux-current relationship curve;

[0066] Step 103: The support vector machine algorithm is used to linearly fit the even harmonics of the excitation current and the reference data set to form the DC bias intrusion current-even harmonics relationship function.

[0067] Step 104: Analyze the actual waveform data collected on site to obtain the actual even harmonics of the waveform data;

[0068] Step 105: Substitute the actual even harmonic sum into the DC bias intrusion current-even harmonic sum relationship function to obtain the quantitative result of the DC bias intrusion current of the recorded waveform data.

[0069] Specifically, the purpose of the invention is to combine existing monitoring methods for transformers in operation with the quantitative analysis of the DC distribution characteristics of the converter transformer valve-side winding based on the operating waveform data, solve the engineering problem that the intrusion current cannot be obtained efficiently and accurately under the DC bias magnetic condition of the converter transformer valve side, and provide a new technical approach for assessing and mastering the DC bias magnetic state of the converter transformer.

[0070] A method for inverting and estimating the DC bias intrusion current of a converter transformer based on the absolute content of even harmonics, such as... Figure 2 As shown, the main calculation process includes four steps: 1. Establishing the magnetic flux-current relationship; 2. Establishing the even harmonics of the excitation current and the reference data set; 3. Extracting the characteristic quantities of the recorded current; 4. Inverting and calculating the DC bias intrusion current.

[0071] 1. Establishment of the magnetic flux-current relationship

[0072] To calculate the theoretical waveform of the excitation current under DC bias of a converter transformer with specified structural parameters, it is necessary to establish a flux-current relationship curve. Assume the peak value of the AC flux linked to the coil is Φ. m ,have:

[0073] Φ AC =Φ m sinωte=-NωΦ m cosωt=Ε m sin(ωt-90°) (1)

[0074] Where ω = 2πf is the alternating angular frequency of the magnetic flux, and the unit is rad / s.

[0075] According to Faraday's law of electromagnetic induction, the electromotive force e in an N-turn coil is related to the magnetic flux. The relationship is:

[0076]

[0077] in, The velocity is the relative velocity between the coil and the magnetic field.

[0078] Since the transformer coil is relatively stationary with respect to the magnetic field during operation, v = 0. Substituting into (2), we get:

[0079]

[0080] Among them, E m =NωΦ m , where is the amplitude of the induced electromotive force; E is the effective value of the induced electromotive force.

[0081] According to equation (4), the voltage-magnetic flux relationship can be obtained as follows:

[0082]

[0083] Based on the above theoretical derivation, the main calculation steps for establishing the flux-current curve of an engineering converter transformer are as follows:

[0084] Linear extrapolation is performed based on the excitation voltage-current data from the no-load test.

[0085] (1) Calculate the magnetic flux value corresponding to the excitation current point by point according to formula (4).

[0086] (2) Obtain the flux-current relationship curve that meets the calculation accuracy requirements by using a regression algorithm.

[0087] 2. Establishment of even-order harmonic reference data set for excitation current

[0088] Under normal operating conditions, the excitation current is generated by the alternating magnetic flux Φ AC (t) is established, and can be deduced from equation (4):

[0089]

[0090] Among them, U N N is the rated voltage on the excitation side, and N is the number of turns on the excitation side.

[0091] When a DC current component exists in the transformer winding, a DC magnetic flux Φ is generated in the iron core. DC At this point, the total magnetic flux is composed of two superimposed parts, namely:

[0092] Φ(t)=Φ AC (t)+Φ DC (6)

[0093] The superimposed DC flux causes the curve to shift overall, leading to the core operating point entering the saturation region. The φ-I relationship in the saturation region is nonlinear, resulting in half-cycle distortion of the excitation current.

[0094] According to formula (5), The steps for calculating the theoretical waveform of the excitation current using the relationship curve are as follows:

[0095] (1) According to the preset target DC bias intrusion current I DC_set Determine the initial calculation interval containing the target DC magnetic flux.

[0096] (2) Based on the flux-current relationship curve, the piecewise linear interpolation algorithm is used to calculate the discretized time-domain waveform of the theoretical excitation current corresponding to the median point of the initial calculation interval of the target DC flux.

[0097] (3) Extract the DC component I of the discretized time-domain waveform of the excitation current by frequency domain decomposition. DC Construct the target deviation evaluation function I DC_set -I DC The iteration terminates if the objective function satisfies the following criterion. If not, the boundary is contracted.

[0098] (4) Figure 3 As shown, a binary search strategy is used to dynamically shrink the initial calculation interval boundary of the target DC flux. When |I DC_set -I DC The iteration terminates when | < ε, and the time-domain solution of the excitation current that meets the accuracy requirements is output.

[0099] Based on the required calculation accuracy, a set of reference bias current values ​​are selected. The theoretical excitation current waveforms under each bias current are calculated sequentially using the above method. Frequency domain decomposition is performed using Fast Fourier Transform (FFT) to obtain the corresponding even harmonics and reference values, thus forming a reference data set of even harmonic excitation currents for a transformer with a specified structure.

[0100] 3. Extraction of characteristic quantities of recorded current

[0101] During the operation of a power transformer, the time-domain waveform of the excitation current satisfies:

[0102]

[0103] In the formula, I m I1 and I2 are the excitation current, grid-side current, and valve-side current, respectively, and N1 and N2 are the number of turns on the grid side and valve side, respectively.

[0104] In actual engineering field recordings, unavoidable measurement errors exist, and their impact on the excitation current calculation results needs to be considered. The rated current of UHV converter transformers is typically around 1000-2000A, while the measurement accuracy of conventional bushing current transformers (CTs) is approximately 0.1% of the rated current, resulting in a measurement error of 1-2A. Simultaneously, the peak excitation current under normal operating conditions is only 0.5-1A, with the error on the same order of magnitude as the excitation current. This causes the time-domain calculation results of the excitation current to be overwhelmed by noise, making them unusable for direct inversion calculations.

[0105] To eliminate the influence of measurement errors on the inversion calculation results, a spectrum analysis method is used to separate the measurement errors from the characteristic spectrum components of the excitation current under biased magnetization.

[0106] Measurement errors in CT scanners include phase shift, ratio shift, and zero drift. Phase shift only causes phase displacement and does not affect the measurement amplitude. Ratio shift remains consistent across all frequency bands. Since the current at the grid and valve ports is predominantly at the fundamental frequency under normal operating conditions, with low harmonic components, the measurement error caused by phase shift is mainly the fundamental frequency component. Zero drift is generated by calibration error and is not affected by the CT's operating state, appearing as a stable DC component in the measurement results. Therefore, the DC and fundamental frequency components of the measurement error are significant, and other frequency bands can be ignored.

[0107] Frequency domain decomposition of both sides of equation (7) yields:

[0108]

[0109] Among them, I m(0) I 1(0) I 2(0) These are the DC components of the excitation current, grid-side current, and valve-side current, respectively; I m(n) I 1(n) I 2(n) These are the nth harmonic effective values ​​of the excitation current, grid-side current, and valve-side current, respectively.

[0110] From (8), we can obtain:

[0111]

[0112] According to equation (9), the measurement error component contained in the grid and valve current only affects the corresponding frequency.

[0113] Literature review indicates that the presence of DC bias disrupts the symmetry of the positive and negative half-cycles of the excitation current, introducing significant even-order harmonic components into the frequency spectrum. The occurrence of even-order harmonics has a clear correspondence with DC bias and does not involve the frequency band where measurement errors occur, thus being less affected by measurement errors. Therefore, using the total amount of even-order harmonics in the excitation current as a characteristic quantity to measure the degree of DC bias can effectively characterize the bias phenomenon and significantly reduce the interference of measurement errors on the analysis results, improving the accuracy and robustness of the calculations.

[0114] Based on the above analysis results, the method for extracting on-site waveform characteristics is as follows:

[0115] (1) High-pass filtering is performed on the waveform data collected on site to eliminate the DC bias caused by zero drift in the current signal and obtain the corrected grid-side and valve-side currents.

[0116] (2) Formula (7) is used to calculate the time-domain waveform of the excitation current based on the corrected grid-side and valve-side currents. Fast Fourier Transform (FFT) is used to decompose the spectrum and extract the superposition value of even harmonic content (n is 2, 4, 6, 8...) as the bias magnetic analysis characteristic quantity, so as to realize the separation of feature extraction and error.

[0117] 4. DC bias intrusion current inversion calculation

[0118] Based on the results obtained in calculations 2 and 3, the steps for inverting the DC bias intrusion current are as follows:

[0119] (1) The reference data set of even harmonic excitation current of a transformer with a specified structure is nonlinearly fitted by the support vector machine (SVM) algorithm to form the DC bias intrusion current-even harmonic relationship function.

[0120] (2) Substitute the even harmonics and characteristic quantities of the field recording waveform to calculate the quantitative result of the DC bias intrusion current borne by the transformer at the recording time.

[0121] In one embodiment of the present invention, the specific implementation mainly includes four calculation processes: (1) constructing the flux-current relationship based on the no-load test results of the converter transformer and calculating the theoretical excitation current waveform under the biased magnetic condition; (2) constructing the even harmonics of the excitation current and the reference data set under different DC biased magnetic intrusion currents based on the converter transformer design parameters; (3) separating the measurement error from the characteristic spectrum components of the excitation current under biased magnetic condition and extracting the characteristic quantity of the recorded current on site; (4) performing nonlinear fitting on the even harmonics of the excitation current and the reference data set, and performing DC biased magnetic intrusion current inversion calculation based on the fitting function.

[0122] Based on the above methods, such as Figure 4 As shown, a DC bias magnetization detection test system was established in a 500kV UHV converter station to verify its effectiveness. A high-precision fiber optic current sensor (FOCS) was installed in a VSC unit of the converter station, and valve-side phase-by-phase DC measurements and inversion calculations based on the proposed algorithm were carried out simultaneously. The test results show that the inversion calculation method proposed in this invention can calculate the bias magnetization intrusion current based on the measurement results of the conventional monitoring device of the converter transformer, and the calculation results have high accuracy.

[0123] 1. On-site installation and measurement

[0124] Test verification was conducted using a 500kV converter transformer at a certain UHV converter station. There are a total of 6 VSC units in the station, each containing one transformer for each of the three phases A, B, and C, for a total of 18 converter transformers with the same structure. The rated parameters are shown in Table 1.

[0125] Table 1 Rated parameters of the test commutator

[0126]

[0127] All 18 converter transformers at the station exhibit varying degrees of valve-side DC bias. Conventional external waveform recorders are installed at the grid and valve bushings for DC bias inversion calculations. The external waveform recorder sampling frequency is 10000Hz, and the measurement accuracy is 0.1%. The first group of VSC units was selected as the test object, including units A, B, and C.

[0128] An additional FOCS is installed on the riser seat of the first end bushing on the C-phase three converter transformer valve side.

[0129] During the test, the circuit remained at the 1000MW and 3000MW operating power points for 40 minutes each, and an external waveform recorder current acquisition was performed once at each point. The FOCS DC current of the first group of converter transformers was measured every minute. Since the DC current on the valve side remained relatively stable for a long period, changing only with power variations, the average value was used to characterize the measurement results at the corresponding operating power points.

[0130] 2. Verification of the validity of the inversion calculation results

[0131] Inversion calculations were performed using the current from an external waveform recorder, and the average DC current measured over 40 minutes using FOCT was compared with the results shown in Table 2. The results indicate that the error between the inversion results and the measured values ​​under different operating conditions is within 0.1A, proving the effectiveness of the inversion calculation method.

[0132] Table 2 Comparison of Inversion Results and Measured Data

[0133]

[0134] Therefore, this invention proposes a method for inverting and estimating the DC bias intrusion current of converter transformers based on the absolute content of even harmonics. This method effectively separates the interference factors of field recording and realizes the calculation of DC bias intrusion current based on conventional measurement and monitoring devices of converter transformers. Moreover, this method is not limited by the winding connection method and does not require additional monitoring equipment. It can be used as a technical means for monitoring and evaluating the DC bias condition of converter transformers in operation.

[0135] Exemplary device

[0136] Figure 5 This is a schematic diagram of the structure of a converter transformer DC bias intrusion current inversion and calculation device based on the absolute content of even harmonics, provided in an exemplary embodiment of the present invention. Figure 5 As shown, the device 500 includes:

[0137] The first module 510 is used to establish a magnetic flux-current relationship curve based on no-load test data;

[0138] The second module 520 is used to establish the even harmonics of the excitation current and the reference data set based on the flux-current relationship curve.

[0139] The fitting module 530 is used to perform linear fitting of the even harmonics of the excitation current and the reference data set using the support vector machine algorithm to form a DC bias intrusion current-even harmonics relationship function.

[0140] Analysis module 540 is used to analyze the actual waveform data collected on site and obtain the actual even harmonics of the waveform data;

[0141] Module 550 is obtained, which is used to input the actual even harmonic sum into the DC bias intrusion current-even harmonic sum relationship function to obtain the quantitative result of DC bias intrusion current of the recorded data.

[0142] Exemplary electronic devices

[0143] Figure 6 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. For example... Figure 6 As shown, the electronic device 60 includes one or more processors 61 and a memory 62.

[0144] The processor 61 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0145] The memory 62 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 61 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above, and / or other desired functions. In one example, the electronic device may also include an input device 63 and an output device 64, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0146] In addition, the input device 63 may also include, for example, a keyboard, a mouse, etc.

[0147] The output device 64 can output various information to the outside. The output device 64 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0148] Of course, for the sake of simplicity, Figure 6 Only some of the components of this electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0149] Exemplary computer program products and computer-readable storage media

[0150] In addition to the methods and apparatus described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0151] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0152] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0153] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0154] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0155] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0156] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0157] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0158] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0159] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for inverting and estimating the DC bias intrusion current of a converter transformer based on the absolute content of even-order harmonics, characterized in that, include: Establish the flux-current relationship curve based on the no-load test data; Based on the flux-current relationship curve, establish the even-order harmonics of the excitation current and the reference data set; The support vector machine algorithm is used to linearly fit the even harmonics of the excitation current and the reference data set to form a DC bias intrusion current-even harmonics relationship function. The actual waveform data collected on site is analyzed to obtain the actual even-order harmonics of the actual waveform data, which includes grid-side current and valve-side current. Substituting the actual even-order harmonics into the DC bias intrusion current-even-order harmonics relationship function, the quantitative result of the DC bias intrusion current of the recorded waveform data is obtained. Based on the aforementioned flux-current relationship curve, an even-order harmonic excitation current and a reference data set are established, including: Based on the preset target DC bias intrusion current Determine the initial calculation interval containing the target DC magnetic flux; Based on the flux-current relationship curve, a piecewise linear interpolation algorithm is used to calculate the discretized time-domain waveform of the theoretical excitation current corresponding to the median point of the initial calculation interval. The DC component of the discretized time-domain waveform of the theoretical excitation current is extracted by frequency domain decomposition. ; When the DC component and preset target DC bias intrusion current If the preset criteria are met, the iteration terminates, and the preset target DC bias intrusion current is determined. The excitation current time-domain solution is obtained; otherwise, a binary search strategy is used to dynamically shrink the initial calculation interval, and the above steps are iterated until the preset criterion is met. The actual waveform data collected on-site is analyzed to obtain the actual even-order harmonics of the actual waveform data, including: The actual waveform data is high-pass filtered to obtain the corrected grid-side current and the corrected valve-side current; The time-domain waveform of the excitation current is calculated based on the corrected grid-side current and the corrected valve-side current. The excitation current time-domain waveform is decomposed using Fast Fourier Transform to extract the superposition value of even-order harmonic content and obtain the actual even-order harmonic sum.

2. The method according to claim 1, characterized in that, Based on the no-load test data, a magnetic flux-current relationship curve was established, including: Linear extrapolation of the excitation voltage-current relationship was performed based on the no-load test data to obtain the voltage-current relationship curve; Based on the pre-constructed voltage-magnetic flux relationship function and voltage-current relationship curve, the magnetic flux value corresponding to the excitation current is calculated point by point; A regression algorithm is used to construct a flux-current relationship curve based on each excitation current and its corresponding flux value.

3. The method according to claim 2, characterized in that, The voltage-magnetic flux relationship function is: In the formula, This represents the magnetic flux value. N This refers to the number of coil turns. f For frequency; E This is the effective value of the induced electromotive force.

4. The method according to claim 1, characterized in that, The preset criterion is: .

5. The method according to claim 1, characterized in that, The calculation expression for the time-domain waveform of the excitation current is: In the formula, , , These are the excitation current, grid-side current, and valve-side current, respectively. N 1 and N 2 represents the number of turns on the mesh side and the valve side, respectively.

6. A converter transformer DC bias intrusion current inversion and calculation device based on the absolute content of even harmonics, used to implement the method of claim 1, characterized in that, include: The first module is used to establish the magnetic flux-current relationship curve based on the no-load test data. The second module is used to establish the even harmonics of the excitation current and the reference data set based on the flux-current relationship curve. The fitting module is used to perform linear fitting of the even harmonics of the excitation current and the reference data set using the support vector machine algorithm to form a DC bias intrusion current-even harmonics relationship function. The analysis module is used to analyze the actual waveform data collected on site and obtain the actual even harmonics of the waveform data; The module is used to input the actual even-order harmonics into the DC bias intrusion current-even-order harmonics relationship function to obtain the quantitative result of the DC bias intrusion current of the recorded waveform data.

7. The apparatus according to claim 6, characterized in that, Based on the no-load test data, a magnetic flux-current relationship curve was established, including: Linear extrapolation of the excitation voltage-current relationship was performed based on the no-load test data to obtain the voltage-current relationship curve; Based on the pre-constructed voltage-magnetic flux relationship function and voltage-current relationship curve, the magnetic flux value corresponding to the excitation current is calculated point by point; A regression algorithm is used to construct a flux-current relationship curve based on each excitation current and its corresponding flux value.

8. The apparatus according to claim 7, characterized in that, The voltage-magnetic flux relationship function is: In the formula, This represents the magnetic flux value. N This refers to the number of coil turns. f For frequency; E This is the effective value of the induced electromotive force.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-5.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-5.

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