High-low voltage ride-through result automatic evaluation method and related device

Abstract

The application discloses a high-low voltage ride-through result automatic evaluation method and related device, comprising: performing high-low voltage ride-through test on a test point of a target wind turbine, and collecting test working data of the test point; extracting a fundamental positive sequence component from the test working data; determining a first reactive current value according to the fundamental positive sequence component; judging whether the first reactive current value meets a preset condition; when the first reactive current value meets the preset condition, processing the test working data based on an improved Hough transform straight line detection algorithm to obtain a plurality of ride-through indexes; and determining a target evaluation result corresponding to the target wind turbine according to the plurality of ride-through indexes. The application can improve the evaluation efficiency of the high-low voltage ride-through capability of the wind turbine.

Description

Technical Field

[0001] This application relates to the field of power system automation technology, and in particular to an automatic evaluation method and related apparatus for high and low voltage ride-through results. Background Technology

[0002] As the proportion of new energy sources in the power system increases, wind turbines are required to have high and low voltage ride-through capabilities to ensure grid stability. Existing verification methods include field testing, simulation, and data collection.

[0003] Currently, multiple rounds of testing are generally required under different voltage and power conditions, and the wind farm's ride-through capability also needs to be analyzed after a fault. However, the existing analysis relies on manual work, which is labor-intensive and time-consuming. In addition, the results of manual analysis are easily affected by the personnel's ability and may be biased. Furthermore, the delayed results may delay the test progress, resulting in low evaluation efficiency.

[0004] Therefore, improving the evaluation efficiency of high and low voltage ride-through capability of wind turbines has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides an automatic evaluation method and related apparatus for high and low voltage ride-through results, which can improve the evaluation efficiency of the high and low voltage ride-through capability of wind turbine units.

[0006] In a first aspect, embodiments of this application provide an automatic evaluation method for high and low voltage ride-through results, including: High and low voltage ride-through tests were performed on the test points of the target wind turbine, and test data were collected at the test points. Extract the fundamental positive sequence component from the test data; The first reactive current value is determined based on the fundamental positive sequence component. Determine whether the first reactive current value meets the preset conditions; When the first reactive current value meets the preset condition, the test data is processed based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. Based on the multiple crossing indicators, the target evaluation result corresponding to the target wind turbine is determined; the target evaluation result includes one of the following: qualified or unqualified.

[0007] Secondly, embodiments of this application provide an automatic evaluation device for high and low voltage ride-through results, comprising: a testing unit, a data analysis unit, and an evaluation unit, wherein: The test unit is used to perform high and low voltage ride-through tests on the test points of the target wind turbine and collect test data at the test points. The data analysis unit is used to extract the fundamental positive sequence component from the test data; determine the first reactive current value based on the fundamental positive sequence component; determine whether the first reactive current value meets the preset conditions; and when the first reactive current value meets the preset conditions, process the test data based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. The evaluation unit is used to determine the target evaluation result corresponding to the target wind turbine based on the multiple crossing indicators; the target evaluation result includes one of the following: qualified or unqualified.

[0008] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for performing the steps in the first aspect of embodiments of this application.

[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of embodiments of this application.

[0010] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of embodiments of this application. The computer program product may be a software installation package.

[0011] Implementing this application will have the following beneficial effects: As can be seen, the automatic evaluation method for high and low voltage ride-through results described in this application obtains test data by conducting high and low voltage ride-through tests on the test points of the target wind turbine; it then processes and analyzes the test data using an improved Hough transform linear detection algorithm to automatically output multiple ride-through indices; and finally, it determines the evaluation results based on these multiple ride-through indices. This avoids the problem of manual analysis being affected by experience and ability, and eliminates the need for repeated data verification, thereby improving the evaluation efficiency of the high and low voltage ride-through capability of wind turbines. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0013] Figure 1 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 2 This is an application scenario diagram of an electronic device provided in an embodiment of this application; Figure 3 This is a flowchart of an automatic evaluation method for high and low voltage ride-through results provided in an embodiment of this application; Figure 4 This is a flowchart of a method for determining a binarized edge pattern provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a method for determining multiple crossing indicators provided in an embodiment of this application; Figure 6 This is a schematic diagram of the test results of a target wind turbine provided in an embodiment of this application; Figure 7 This is a functional unit block diagram of an automatic evaluation device for high and low voltage ride-through results provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of another electronic device provided in an embodiment of this application. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0015] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0016] It should be understood that the term "and / or" in this document 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 document indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, "multiple" refers to two or more.

[0017] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0018] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0019] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0020] The electronic devices described in this application embodiment may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablet computers, PDAs, laptops, video matrices, monitoring platforms, mobile internet devices (MIDs), or wearable devices, etc. The above are merely examples and not exhaustive, and include but are not limited to the above devices.

[0021] Of course, the aforementioned electronic devices can also be servers, such as cloud servers.

[0022] The following describes the relevant content, concepts, meanings, technical issues, technical solutions, and beneficial effects involved in the embodiments of this application.

[0023] First, let me explain some of the technical terms used in this application: Wind turbine: refers to a complete set of power generation equipment that converts wind energy into electrical energy. It mainly consists of core components such as rotor, nacelle, tower, generator, and converter. It can capture wind energy and convert it into electrical energy to be transmitted to the power grid. It is the core unit of the wind farm power generation system.

[0024] High and low voltage ride-through results: This refers to the performance assessment conclusion of wind turbine units in maintaining grid-connected operation and outputting active and reactive power according to grid technical specifications when the grid voltage experiences a drop (low voltage ride-through) or rise (high voltage ride-through) fault. This result is comprehensively judged by quantitative indicators such as the duration of voltage anomalies, reactive current response speed, and active power recovery rate, reflecting whether the unit's ability to cope with grid voltage faults meets the standards.

[0025] Fundamental positive sequence component: This refers to the electrical quantity component extracted from the mixed three-phase voltage and current signal collected from the wind turbine test point after removing harmonic components, negative sequence components, and zero sequence components. It has the same rated frequency as the power grid, a three-phase phase difference of 120°, and the same phase sequence as the power grid. It includes the fundamental positive sequence voltage component and the fundamental positive sequence current component, and is a core fundamental parameter for evaluating the electrical performance of the unit.

[0026] Hough transform line: Based on the principle of Hough transform, this line maps edge points in the waveform image space to a polar coordinate parameter space. An accumulator counts the number of "votes" from edge points to the parameters of each line in the parameter space, and the line corresponding to the peak value of the accumulator is used to determine the core linear characteristics of the waveform. This line can accurately locate key characteristic intervals such as stable segments and abrupt changes in the waveform.

[0027] Watershed Algorithm: This refers to a region segmentation algorithm based on "topography". It treats the gradient magnitude of the waveform grayscale image as the terrain height (regions with high gradient magnitude are "ridges" and those with low gradient magnitude are "valleys"). By simulating the "water filling" process, the image is segmented into multiple non-overlapping connected regions. The boundary line between different regions is the "watershed line".

[0028] Discrete Full-Wave FFT Algorithm: This is a frequency domain analysis method for discrete time-domain signals based on the Fast Fourier Transform (FFT). Its core is to perform frequency domain decomposition on discrete time-domain sampled data of a complete cycle to achieve accurate extraction of the fundamental wave and each harmonic component. It is widely used in harmonic analysis and fundamental wave component calculation of electrical quantities (voltage, current) in power systems.

[0029] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. As can be seen, the electronic device may include: a communication module, a control module, and an evaluation output module, wherein: The communication module is responsible for establishing connections with external devices (such as wind turbine testing systems, data acquisition systems, etc.) to receive and transmit test data. It serves as the "data entry point" for electronic equipment to obtain the raw data required for evaluation.

[0030] The control module is the core processing unit of the electronic device, responsible for data processing and logical operations. For example, it extracts the fundamental positive sequence component from the test data, calculates the reactive current value, executes the improved Hough transform line detection algorithm, and generates the crossing index. It is the core execution module for realizing "automatic evaluation".

[0031] The evaluation output module is used to determine the passability of the high and low voltage ride-through capability of the wind turbine based on the ride-through index generated by the control module, and output the "evaluation pass or fail" result in the form of visualization (e.g., evaluation report) or signal. It is the "result output" of the electronic equipment to provide feedback on the evaluation conclusion to the user.

[0032] Please see Figure 2 , Figure 2 This is an application scenario diagram of an electronic device provided in an embodiment of this application. As can be seen, the electronic device is bidirectionally connected to the target wind turbine, and the target wind turbine can transmit data to the electronic device: during the high and low voltage ride-through test, the wind turbine sends the collected test data (such as voltage and current waveform data) to the electronic device. Electronic devices can provide feedback results (or instructions) to the target wind turbine: After completing the automatic evaluation, the electronic devices can provide the "pass / fail" evaluation result to the control system of the target wind turbine, or send subsequent operation instructions (e.g., test adjustment instructions or shutdown instructions) to the target wind turbine based on the result.

[0033] Figure 2 The double-headed arrows indicate that there is a data interaction relationship between the two.

[0034] Please see Figure 3 , Figure 3 This is a flowchart of an automatic evaluation method for high and low voltage ride-through results provided in an embodiment of this application. The method may include the following steps: S301. Perform high and low voltage ride-through tests on the test points of the target wind turbine and collect the test data of the test points.

[0035] In this embodiment of the application, the method can be applied to, for example... Figure 1 The electronic device shown.

[0036] In a specific embodiment, test points for the target wind turbine (e.g., the turbine end or the high-voltage side of the step-up transformer) can be selected first according to the evaluation requirements. Voltage sensors, current sensors, power sensors, etc., can be deployed at the test points, without limitation. In addition, all sensors can be connected to a data acquisition system (e.g., a waveform recorder) for subsequent data acquisition. Next, a test system is built. Specifically, a grid simulation device (e.g., a voltage drop generator or a voltage rise generator) can be configured to simulate faults at different voltage levels, such as low voltage 20%Un and high voltage 130%Un, where Un represents the rated voltage of the target wind turbine. At the same time, a communication link is established between the test system and the control system of the target wind turbine to ensure coordinated control of fault triggering and turbine status.

[0037] Furthermore, a testing system can be used to conduct high and low voltage ride-through tests on the target wind turbine. During the test, the data acquisition system collects the working data of the test points, thereby obtaining the test working data.

[0038] Let me illustrate with an example, taking the "20% Un three-phase fault test" as an example: 1. Initial status confirmation of the unit: The target wind turbine is controlled to operate at its rated power. After the voltage and current output by the turbine stabilize, the initial operating parameters (e.g., rated voltage Un, rated current In) are recorded.

[0039] 2. Fault condition triggering: Using a power grid simulation device, a three-phase fault with voltage drop to 20%Un is simulated at the test point, and the fault state is maintained for a preset duration (e.g., 625ms as required by the equipment specifications).

[0040] 3. Real-time data collection: Using a data acquisition system, electrical quantity data at test points are continuously collected, and the collection area needs to cover: Pre-fault period: Steady-state data from 100ms to 200ms before the fault is triggered (for benchmark comparison). Fault duration: During the voltage drop (or rise), the real-time voltage, current, power waveform data, etc. at the test point are not limited here; Fault recovery period: steady-state data for 100ms to 200ms after the voltage recovers to the rated value.

[0041] The acquisition frequency must meet the specifications (usually no less than 2kHz, to ensure the capture of waveform abrupt changes in detail).

[0042] 4. Data storage and preprocessing: After the test is completed, the collected voltage, current and power data will be stored in categories such as "test condition (e.g., 20%Un low voltage) + timestamp" to prepare for the subsequent extraction of the fundamental positive sequence component and calculation of the crossover index.

[0043] S302. Extract the fundamental positive sequence component from the test data.

[0044] In this embodiment of the application, the test data may include three-phase voltage data and three-phase current data.

[0045] In a specific embodiment, the discrete full-wave FFT algorithm can be used to process the test data to obtain the fundamental positive sequence component. The fundamental positive sequence component may include at least one of the following: fundamental positive sequence voltage, fundamental positive sequence current, fundamental positive sequence active power, fundamental positive sequence reactive power, fundamental positive sequence active current, and fundamental positive sequence reactive current, etc., which are not limited here.

[0046] S303. Determine the first reactive current value based on the fundamental positive sequence component.

[0047] In this embodiment, the fundamental positive-sequence voltage amplitude and its corresponding first phase, and the fundamental positive-sequence current amplitude and its corresponding second phase can be found from the fundamental positive-sequence components. Then, the phase difference can be obtained by subtracting the second phase from the first phase. The calculation is then performed based on the fundamental positive-sequence current amplitude and the phase difference, as follows: I q =I1*sinφ; Among them, I q Let I1 represent the amplitude of the fundamental positive sequence current, and φ represent the phase difference. The first reactive current value can be calculated according to the above formula.

[0048] S304. Determine whether the first reactive current value meets the preset conditions.

[0049] In this embodiment of the application, the preset conditions can be preset in advance or defaulted.

[0050] Optionally, step S304, determining whether the first reactive current value meets the preset conditions, may include the following steps: S41. Determine the device type corresponding to the test point; S42. When the equipment type includes a new energy generator unit, determine the preset reactive current value corresponding to the target wind turbine unit; determine the first deviation between the first reactive current value and the preset reactive current value; if the first deviation is less than or equal to the preset deviation, determine that the first reactive current value meets the preset condition; if the first deviation is greater than the preset deviation, determine that the first reactive current value does not meet the preset condition. S43. When the device end type includes the high voltage side of the booster transformer of the new energy unit, convert the first reactive current value to the second reactive current value at the machine end of the new energy unit; determine the second deviation degree between the second reactive current value and the preset reactive current value; if the second deviation degree is less than or equal to the preset deviation degree, determine that the first reactive current value meets the preset condition; if the second deviation degree is greater than the preset deviation degree, determine that the first reactive current value does not meet the preset condition.

[0051] In the embodiments of the present application, the preset deviation degree can be preset in advance or by default.

[0052] In specific embodiments, the device end type corresponding to the test point can be determined first. Specifically, the position of the test point in the target wind turbine can be obtained, and the device end type can be determined according to this position. For example, if the position of the test point obtained is the generator outlet terminal inside the wind turbine nacelle, or the bus position directly connected to the output side of the unit converter, it is determined that the device end type corresponding to the test point is the machine end of the new energy unit; if the position of the test point obtained is the high voltage winding outlet terminal of the booster transformer supporting the wind turbine, or the grid connection switch position on the high voltage side of the booster transformer, it is determined that the device end type corresponding to the test point is the high voltage side of the booster transformer of the new energy unit.

[0053] When the device end type includes the machine end of the new energy unit, the preset reactive current value corresponding to the target wind turbine can be determined. Specifically, the device model of the target wind turbine can be obtained to get the target device model, and the preset reactive current value can be determined according to this target device model. For example, the mapping relationship between the preset device model and the reactive current value can be stored in advance, and the preset reactive current value corresponding to the target device model can be determined based on this mapping relationship; then, the first deviation degree between the first reactive current value and the preset reactive current value can be determined as follows: The first deviation degree = |the first reactive current value - the preset reactive current value| / the preset reactive current value * 100%; According to the above formula, the first deviation degree can be obtained; if the first deviation degree is less than or equal to the preset deviation degree (for example, 10%), it means that the deviation between the actual reactive current output by the unit and the theoretical compliance value (i.e., the preset reactive current value) is within the allowable range, and the reactive power support ability of the unit meets the requirements of the power grid, then it is determined that the first reactive current value meets the preset condition; if the first deviation degree is greater than the preset deviation degree, it indicates that the reactive power response of the unit is insufficient or excessive, and it cannot effectively support the stability of the power grid voltage. It is necessary to further check the unit control strategy or hardware parameters. At this time, it can be determined that the first reactive current value does not meet the preset condition.

[0054] When the equipment type includes the high-voltage side of the step-up transformer of a new energy unit, the first reactive current value is converted into the second reactive current value at the generator terminal of the new energy unit. The specific conversion formula is as follows:

[0055] in, This represents the reactive current value (also known as the second reactive current value) at the target wind turbine generator terminal (i.e., the new energy generator terminal). This represents the reactive power value at the turbine terminal of the target wind turbine. This indicates the voltage at the terminals of the target wind turbine unit; This represents the susceptance value of the box-type transformer in the target wind turbine unit; This represents the transverse component of the voltage drop in the impedance of a box-type transformer. This represents the longitudinal component of the voltage drop in the impedance of a box-type transformer. This indicates the reactance value of the box-type transformer; This indicates the resistance value of the box-type transformer; This represents the reactive power value at the moment when the low-voltage ride-through ends and the voltage begins to recover; P start This represents the active power value at the moment when the low-voltage ride-through ends and the voltage begins to recover; U dip1 This indicates the fault voltage value during low-voltage ride-through. Based on the above formula, the second reactive current value can be calculated; then, the second deviation between the second reactive current value and the preset reactive current value can be determined, as follows: Second deviation = |Second reactive current value - Preset reactive current value| / Preset reactive current value * 100%; According to the above formula, the second deviation can be obtained; if the second deviation is less than or equal to the preset deviation, it can be directly determined that the first reactive current value meets the preset condition; if the second deviation is greater than the preset deviation, it can be directly determined that the first reactive current value does not meet the preset condition.

[0056] Thus, when the equipment type is the generator end of a new energy unit, the deviation is directly calculated; when the equipment type is the high-voltage side of the step-up transformer of a new energy unit, the reactive current is first converted into the second reactive current value of the generator end, and then the deviation is calculated, eliminating the influence of the difference in test point location and ensuring the uniformity of the judgment standard; in addition, it can also avoid misjudgment caused by different test point locations and improve the accuracy of reactive current judgment.

[0057] S305. When the first reactive current value meets the preset condition, the test data is processed based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators.

[0058] In this embodiment of the application, when the first reactive current value meets the preset conditions, the improved Hough transform linear detection algorithm is used to analyze and process the test data to obtain multiple crossing indicators.

[0059] It should be explained that if the first reactive current value does not meet the preset conditions, it means that the reactive power support capability of the unit does not meet the grid specifications. In this case, the target evaluation result corresponding to the target wind turbine can be directly determined as unqualified, and no further steps need to be performed.

[0060] Optionally, the test data includes: fundamental positive sequence voltage, fundamental positive sequence reactive current, and fundamental positive sequence active power; step S305, processing the test data based on the improved Hough transform line detection algorithm to obtain multiple crossover indicators, may include the following steps: A1. Determine the first waveform corresponding to the test data; the first waveform includes at least one of the following: the voltage waveform corresponding to the fundamental positive sequence voltage, the current waveform corresponding to the fundamental positive sequence reactive current, and the power waveform corresponding to the fundamental positive sequence active power. A2. The first waveform is processed using a preset edge extraction algorithm to obtain a binarized edge pattern; A3. Initialize the parameter space (ρ, θ) and accumulator of the polar coordinate system; ρ represents the polar radius, and θ represents the polar angle; the accumulator is a two-dimensional array, the dimension of which corresponds to the number of discrete intervals in the parameter space; A4. For each edge point in the binarized edge pattern, traverse each θ value in the parameter space, calculate the ρ value corresponding to the θ value according to the edge point and the first preset formula, and obtain multiple sets of parameter pairs. Each set of parameter pairs includes an θ value and its corresponding ρ value. Map each set of parameter pairs in the multiple sets of parameter pairs to the parameter space and count them at the corresponding position of the accumulator. A5. Determine the maximum count value corresponding to the accumulator, and determine the target parameter pair corresponding to the maximum count value in the multiple sets of parameter pairs; A6. Determine the first Hough transform line based on the target parameters; A7. Determine the multiple crossing indices based on the first Hough transform line and the multiple sets of parameter pairs.

[0061] In this embodiment, the first waveform corresponding to the test data can be determined first. Specifically, the continuous time-domain values ​​of the fundamental positive sequence voltage, fundamental positive sequence reactive current, and fundamental positive sequence active power can be extracted in the order of timestamps to form three sets of one-to-one "time-value" data pairs. Then, the timestamps of these three sets of data pairs can be checked for consistency. If there are missing timestamps or uneven intervals, linear interpolation is used to complete the data points to ensure that the time axes of the three sets of data pairs are completely synchronized. Then, with time as the horizontal axis (X-axis) and electrical quantity values ​​(e.g., voltage, current, power) as the vertical axis (Y-axis), the data pairs in the three sets of data pairs are connected sequentially in the same coordinate system or sub-coordinate system to form a continuous curve, resulting in three waveforms. The first waveform is determined based on these three waveforms. For example, the voltage waveform among these three waveforms can be selected as the first waveform.

[0062] Then, a preset edge extraction algorithm can be used to process the first waveform to obtain a binarized edge pattern. Next, the parameter space (ρ, θ) and accumulator of the polar coordinate system can be initialized. Specifically, the discrete interval can be set as needed. For example, the value range of θ in the parameter space can be -90° to 90°, and it can be discretized in 1° steps, resulting in a total of 181 intervals. Then, the diagonal length D of the binarized edge pattern can be obtained. The value range of ρ in the parameter space can be -D to D, and it can be discretized in a fixed step size (e.g., 1). Discretize the data (in pixels) to obtain 2D+1 intervals; use the discretized θ as the horizontal axis and ρ as the vertical axis to form a two-dimensional parameter space (the number of discrete intervals of θ × the number of discrete intervals of ρ). Then, initialize the accumulator and create a two-dimensional array that perfectly matches the dimension of the parameter space (for example, assuming θ is divided into 181 intervals and ρ is divided into 121 intervals, the two-dimensional array is 181×121). Set the initial value of all elements in the two-dimensional array to 0. This two-dimensional array is the accumulator (used to count the votes for each (ρ,θ) parameter pair).

[0063] Furthermore, the pixel coordinates (x, y) of all edge points can be read from the binarized edge image (only points with a pixel value of "edge" are retained, for example, points with a value of 255 in the binarized edge image). For each edge point in the binarized edge image, each θ value in the parameter space is traversed, and the ρ value corresponding to the θ value is calculated based on the edge point and the first preset formula, which is as follows: ρ = x*cos(θ) + y*sin(θ); Where x is the x-coordinate of the edge point and y is the y-coordinate of the edge point; according to the above formula, multiple sets of parameter pairs can be obtained, where the number of multiple sets of parameter pairs is equal to the number of edge points multiplied by the number of discrete intervals of θ. For example, assuming the number of discrete intervals of θ is 181 and the number of edge points is 1000, then the number of multiple sets of parameter pairs is 181*1000; map each of these multiple sets of parameter pairs to the parameter space and count them at the corresponding position in the accumulator. Specifically, for each set of parameter pairs, find its corresponding "cell" in the discretized parameter space (i.e., the index of the discrete interval of θ and the index of the discrete interval of ρ); in the accumulator, find the position corresponding to the cell and add 1 to the value at that position (equivalent to "voting" for the line corresponding to (ρ,θ).

[0064] Then, we can determine the maximum count value corresponding to the accumulator, and determine the target parameter pair corresponding to the maximum count value among multiple parameter pairs. Specifically, we can iterate through all values ​​in the accumulator, find the maximum value, which is the maximum count value. Next, we can obtain the row index (corresponding to the discrete index of θ) and column index (corresponding to the discrete index of ρ) of the cell containing the maximum count value. Based on the row index and column index, we can determine the target parameter pair. For example, assuming: θ ranges from -90° to 90° with a step size of 1°; ρ ranges from -500 to 500 pixels with a step size of 1 pixel; and the maximum count value in the accumulator appears at index (120, 600), then its corresponding target parameter pair is: θ value: θmin+i1*Δθ=-90°+120*1°=30°; ρ value: i2*Δρ-D=600*1-500=100 (pixels); Where θmin represents the minimum value of θ, i1 represents the row index, i2 represents the column index, Δθ represents the step size of θ, Δρ represents the step size of ρ, and D represents the diagonal length of the binarized edge graphic; thus, the target parameter pair can be obtained: (100, 30°).

[0065] It should be explained that if there are multiple identical maximum values ​​in the accumulator, all of them can be retained or one can be selected according to the first preset rule. For example, the first preset rule can be: take the maximum value with the smallest index.

[0066] Then, the first Hough transform line can be determined based on the target parameter pair. Specifically, the target parameter pair can be substituted into the line equation: ρ_detected=x*cos(θ_detected)+y*sin(θ_detected); Where θ_detected represents the θ value in the target parameter pair; ρ_detected represents the ρ value in the target parameter pair; then, the linear equation can be transformed into the slope-intercept form y=mx+c, which is the first Hough transform line; finally, multiple crossing indices can be determined based on the first Hough transform line and multiple sets of parameter pairs.

[0067] Thus, by fitting linear lines to discrete points at the waveform edges using the Hough transform, the linear change segments of the waveform (e.g., voltage stable drop segments and smooth recovery segments) can be accurately located, avoiding subjective errors from manual interpretation. In addition, based on the fitted first Hough transform line, key ride-through indicators such as voltage drop depth, recovery time, and reactive current response time can be directly derived, enabling automated and standardized calculation of these indicators, thereby improving the evaluation efficiency of wind turbine high and low voltage ride-through capabilities.

[0068] Optionally, the preset edge extraction algorithm includes a gradient-based watershed segmentation algorithm; please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a flowchart of a method for determining a binarized edge pattern according to an embodiment of this application; it can be seen that step A2, which involves processing the first waveform using a preset edge extraction algorithm to obtain a binarized edge pattern, includes... Figure 4 The steps shown are as follows: B1. Preprocess the first waveform to obtain a grayscale waveform. B2. Use an edge detection operator to detect the grayscale waveform to obtain a gradient amplitude image; B3. Determine the initial binarized image based on the preset threshold and the gradient magnitude image; B4. Determine the binarized edge pattern based on the watershed algorithm, the gradient magnitude image, and the initial binarized image.

[0069] In this embodiment, the preset threshold can be preset in advance or set by default.

[0070] In a specific embodiment, the first waveform is preprocessed to obtain a grayscale waveform image. Specifically, the first waveform can be filtered using a Gaussian filter, and then the filtered image can be converted into a grayscale image to obtain a grayscale waveform image. Specifically, the time series of the filtered first waveform can be mapped to the horizontal pixel axis (X-axis) of the grayscale image, and the electrical quantity value (e.g., current, voltage, power, etc.) series of the filtered first waveform can be mapped to the vertical pixel axis (Y-axis) of the grayscale image. The width of the grayscale image is determined based on the total time length of the waveform, and the height of the grayscale image is determined based on the extreme value range of the electrical quantity values. The pixel position corresponding to each time point and voltage value is then determined. A pure white grayscale canvas (pixel value 255) is initialized, and the filtered waveform data is traversed. The pixel position corresponding to each "time-electrical quantity value" data point is assigned a value of 0 (black), and finally a grayscale waveform image with clear black and white contrast is formed.

[0071] Then, edge detection operators can be used to detect the grayscale waveform to obtain a gradient magnitude image. Specifically, the edge detection operator can be convolved with the grayscale waveform to obtain the derivative matrix Gx (reflecting the grayscale change of pixels in the horizontal direction) and the derivative matrix Gy (reflecting the grayscale change of pixels in the vertical direction) in the horizontal (x) direction. If the waveform lines of the grayscale waveform are vertical / horizontal, Gx / Gy will show significant values ​​at the waveform edges (the derivative is close to 0 in non-edge areas). For each pixel in the grayscale waveform, the corresponding gradient magnitude is calculated by combining its x and y derivative values. The gradient magnitudes of all pixels are arranged according to the pixel positions in the original image (grayscale waveform) to form a two-dimensional matrix. This matrix is ​​the gradient magnitude image. The larger the pixel value in the image, the more obvious the edge features (waveform edges) at that position, and vice versa.

[0072] The edge detection operator can be one of the following: Sobel operator, Prewitt operator, Scharr operator, etc., without limitation; Furthermore, an initial binarized image can be determined based on a preset threshold and a gradient magnitude image. Specifically, the gradient magnitude of all pixels in the gradient magnitude image can be traversed. For each pixel's gradient magnitude, if the gradient magnitude is greater than or equal to the preset threshold, the pixel is determined to be an "edge pixel" and its pixel value is set to 255 (white); if the gradient magnitude is less than the preset threshold, the pixel is determined to be a "non-edge pixel" and its pixel value is set to 0 (black). After replacing all pixels according to the above rules, a two-dimensional matrix containing only two pixel values, 0 and 255, is formed, which is the initial binarized image (edge ​​areas are white, and non-edge areas are black).

[0073] Finally, based on the watershed algorithm, the gradient magnitude image, and the initial binarized image, the binarized edge pattern can be determined. Specifically, based on the initial binarized image, foreground pixels (i.e., the initially determined waveform edge pixels) and background pixels are identified and marked to obtain a marked image; the positions of all marked pixels in the marked image are recorded; then, all pixel values ​​corresponding to the marked pixel positions in the gradient magnitude image are forcibly set to 0 (extremely low values) to weaken the gradient changes in the marked regions and prevent the watershed algorithm from over-segmenting in these regions; the modified gradient magnitude image is used as the input to the watershed algorithm, and the marked image is used as the segmentation basis to execute the watershed algorithm, as follows: Using foreground / background markers in the labeled image as "water injection points," water is injected into the uncertain area (label-1). When the "water level" at different water injection points rises to the "terrain boundary" of the gradient amplitude, water injection is stopped and a watershed line is generated at the junction; The algorithm outputs a labeled segmented image: the foreground region is assigned a corresponding positive integer label, the background region is assigned a 0 label, and the watershed line is assigned a specific label value (e.g., -1). Iterate through all pixels of the labeled segmented image: If the pixel label value is equal to the watershed line label value, it is determined to be an edge pixel, and its grayscale value is set to 255 (white). If the pixel label value is not equal to the watershed label value, it is determined to be a non-edge pixel and its gray value is set to 0 (black). After all pixels are assigned values, a binary edge graphic containing only the waveform edges is obtained.

[0074] Thus, by extracting gradient features from the grayscale image through edge detection operators, the intensity of grayscale changes in the waveform is quantified, and the potential region of the waveform edge is accurately located. At the same time, by combining the labeling information of the gradient image and the initial binary image, the watershed algorithm is used to optimize the edge, making up for the incompleteness and discontinuity of conventional edge detection, thereby obtaining a closed and accurate waveform edge contour.

[0075] Optional, please refer to Figure 5 , Figure 5 This is a flowchart of a method for determining multiple crossing indicators provided in an embodiment of this application. Step A7 involves determining the multiple crossing indicators based on the first Hough transform line and the multiple sets of parameter pairs, including... Figure 5 The steps shown are as follows: C1. Determine the parameter pair that corresponds to the first Hough transform line among the multiple sets of parameter pairs to obtain at least one parameter pair; C2. Determine the edge point corresponding to the at least one parameter pair in the binarized edge graphic to obtain at least one edge point; C3. Determine the plurality of crossing indices based on the at least one edge point.

[0076] In this embodiment, the parameter pairs corresponding to the first Hough transform line among multiple parameter pairs can be determined to obtain at least one parameter pair. Specifically, the cell index corresponding to the maximum count value in the accumulator can be obtained, and the cell index can be reverse-mapped to the corresponding θ and ρ values ​​according to the parameter space discretization rule, thereby obtaining at least one parameter pair. Then, the edge points corresponding to at least one parameter pair in the binary edge graphic can be determined to obtain at least one edge point. Specifically, at least one pixel coordinate can be obtained by reverse solving according to the first preset formula and at least one parameter pair, and at least one edge point can be determined according to the at least one pixel coordinate. Finally, multiple crossing indicators can be determined according to at least one edge point.

[0077] Thus, by locking the parameter pair corresponding to the first Hough transform line, the linear feature segment with the core trend in the waveform can be accurately anchored. Then, by reverse matching the corresponding edge points in the binarized edge graph, noise interference can be filtered out, invalid discrete points can be eliminated, and key coordinate data strongly related to the crossing characteristics can be directly obtained. Based on these precise edge points, crossing indicators such as voltage drop depth and recovery time can be calculated, avoiding subjective errors in manual interpretation and improving the accuracy, consistency, and automation of indicator calculation.

[0078] Optionally, step C3, when the first waveform includes the voltage waveform corresponding to the fundamental positive sequence voltage, determining the plurality of crossover indices based on the at least one edge point may include the following steps: D1. Obtain the coordinates of at least one edge point corresponding to the at least one edge point; the horizontal axis of each edge point coordinate is time, and the vertical axis is voltage value; D2. Determine the maximum and minimum abscissa values, as well as the maximum and minimum ordinate values, among the coordinates of the at least one edge point. D3. Obtain the target slope corresponding to the first Hough transform line; D4. Determine the multiple crossing indicators based on the target slope, the maximum horizontal coordinate value, the minimum horizontal coordinate value, the maximum vertical coordinate value, and the minimum vertical coordinate value.

[0079] In this embodiment of the application, at least one edge point coordinates corresponding to at least one edge point can be obtained. Specifically, at least one pixel coordinates corresponding to at least one edge point can be obtained, and at least one pixel coordinates can be converted into physical coordinates of voltage waveforms to obtain at least one edge point coordinates. Specifically, a preset mapping relationship between pixel coordinates and edge point coordinates can be stored in advance, and at least one edge point coordinates corresponding to at least one pixel coordinate can be determined based on the mapping relationship.

[0080] Then, the maximum and minimum x-coordinate values, as well as the maximum and minimum y-coordinate values, can be determined from the coordinates of at least one edge point. Specifically, all x-coordinate (time) data can be separated from the coordinates of at least one edge point to form a time series. The time series is traversed, and the time value with the largest value is selected and recorded as the maximum x-coordinate value. In addition, the time value with the smallest value can also be selected and recorded as the minimum x-coordinate value. Similarly, all y-coordinate (voltage) data can be separated from the coordinates of at least one edge point to form a voltage series. The voltage value with the largest value is selected and recorded as the maximum y-coordinate value. Similarly, the voltage value with the smallest value can also be selected and recorded as the minimum y-coordinate value.

[0081] Furthermore, the target slope corresponding to the first Hough transform line can be obtained. Specifically, the slope-intercept equation of the first Hough transform line, y=mx+c, can be obtained, where m is the target slope. Finally, multiple crossing indicators can be determined based on the target slope, the maximum abscissa value, the minimum abscissa value, the maximum ordinate value, and the minimum ordinate value.

[0082] Thus, by extracting the extreme values ​​of time and voltage coordinates of edge points and combining them with the target slope of the first Hough transform line, the key change range and trend characteristics of the voltage waveform can be directly anchored, avoiding the interference of discrete noise points on the index calculation, and quickly deriving core crossing indicators such as voltage drop / rise time, amplitude change magnitude and duration, significantly improving the accuracy and automation efficiency of index calculation.

[0083] Optionally, step D4, determining the multiple crossing indicators based on the target slope, the maximum abscissa value, the minimum abscissa value, the maximum ordinate value, and the minimum ordinate value, may include the following steps: E1. When the target slope is greater than or equal to a preset value, determine the voltage rise period corresponding to the first Hough transform line, determine the voltage rise duration based on the maximum and minimum abscissa values, determine the voltage rise change value based on the maximum and minimum ordinate values, and determine the multiple crossing indicators based on the voltage rise duration and voltage rise change value. E2. When the target slope is less than the preset value, determine the voltage drop period corresponding to the first Hough transform line; determine the voltage drop duration based on the maximum and minimum abscissa values; determine the voltage drop change value based on the maximum and minimum ordinate values; determine the multiple crossover indicators based on the voltage drop duration and voltage drop change value.

[0084] In this embodiment of the application, the preset value can be preset in advance or defaulted. For example, the preset value can be 0.

[0085] In a specific embodiment, when the target slope is greater than or equal to a preset value, the voltage rise period corresponding to the first Hough transform line can be determined. The voltage rise duration is determined based on the maximum and minimum abscissa values. Specifically, the difference between the maximum and minimum abscissa values ​​can be used to obtain the abscissa difference, i.e., the voltage rise duration. The voltage rise change value is determined based on the maximum and minimum ordinate values. Specifically, the difference between the maximum and minimum ordinate values ​​can be used to obtain the ordinate difference, i.e., the voltage rise change value. Then, the voltage rise duration and voltage rise change value can be used as crossing indicators, thereby obtaining multiple crossing indicators.

[0086] When the target slope is less than the preset value, the voltage drop period corresponding to the first Hough transform line can be determined; the voltage drop duration is obtained by subtracting the minimum abscissa value from the maximum abscissa value; the voltage drop change value is obtained by subtracting the minimum ordinate value from the maximum ordinate value; the voltage drop duration and voltage drop change value can be used as crossover indicators, thus obtaining multiple crossover indicators.

[0087] Optionally, in some embodiments, the maximum x-axis value, minimum x-axis value, maximum y-axis value, and minimum y-axis value can also be used as crossing indicators. These values ​​can be added to the above-mentioned multiple crossing indicators. For example, the minimum x-axis value represents the start time of the voltage anomaly, and the maximum x-axis value represents the recovery time of the voltage anomaly; the maximum y-axis value represents the maximum value of the voltage anomaly, and the minimum y-axis value represents the minimum value of the voltage anomaly. In addition, the voltage drop depth can be obtained by dividing the minimum y-axis value by the rated voltage of the target wind turbine; the voltage rise rate can be obtained by dividing the maximum y-axis value by the rated voltage of the target wind turbine. The voltage drop depth and voltage rise rate can also be used as crossing indicators and added to the above-mentioned multiple crossing indicators.

[0088] Optionally, in some embodiments, the key moments of the two types of voltage characteristic waveforms can be calibrated based on an improved Hough transform line detection algorithm: To calibrate the fundamental positive-sequence voltage drop waveform during low-voltage ride-through (or the fundamental positive-sequence voltage rise waveform during high-voltage ride-through), the starting time of the calibration straight line is denoted as t. Ustart1 The final time is denoted as t. Ustart2 ; To calibrate the fundamental positive-sequence voltage rise waveform during low-voltage ride-through (or the fundamental positive-sequence voltage drop waveform during high-voltage ride-through), the starting time of the calibration straight line is denoted as t. Uend1 The final time is denoted as t. Uend2 .

[0089] Therefore, the duration of the voltage drop (or rise) t dip =t Uend1 -t Ustart2 .

[0090] Optionally, when the first waveform includes the current waveform corresponding to the fundamental positive-sequence reactive current, the first waveform can be processed based on the improved Hough transform linear detection algorithm to calibrate the two types of characteristic waveforms of the fundamental positive-sequence reactive current respectively: The response of the fundamental positive-sequence reactive current is calibrated along the waveform. The time corresponding to the end of the calibration straight line is denoted as the reactive current response start time t. Iqstart ; The recovery waveform of the calibrated fundamental positive-sequence reactive current is used to define the time corresponding to the start of the calibration straight line as the time t when the reactive current continues to arrive. Iqend The time corresponding to the endpoint of the calibration straight line is denoted as the reactive current exit time t. Iqtuichu .

[0091] Reactive current response time t res1 =t Iqstart -t Ustart1 ; Reactive current withdrawal time t ree1 =t Iqtuichu -t Uend2 ; The duration of reactive current is t sus =t Iqend -t Iqstart .

[0092] Optionally, in some embodiments, the fundamental positive-sequence active power after the voltage recovery time is calibrated using an improved Hough transform linear detection algorithm. Assuming the calibrated linear equation is y = mx + b, it can be expressed using polar coordinates as follows: ρ=x*cosθ+y*sinθ Where y represents active power, m represents the recovery rate of active power, x represents time, b represents the intercept of the line, ρ represents the polar radius, and θ represents the polar angle. According to ρ = x*cosθ + y*sinθ, we can solve for... ; Due to the active power recovery rate P rate equal m ,therefore, m Specifically as follows:

[0093] Thus, by using the polar coordinate parameters of the Hough transform to calculate the active power recovery rate, the influence of power oscillation caused by wind speed fluctuations in manual point selection is avoided, thereby improving the calculation accuracy. This method is also applicable to the calculation of indicators such as reactive current response time and exit time.

[0094] In some embodiments, please refer to Figure 6 , Figure 6 This is a schematic diagram of the test results of a target wind turbine provided in an embodiment of this application; Figure 6 The horizontal axis t represents time, and the vertical axis represents the per-unit (pu) values ​​of the three types of parameters. pu stands for per-unit value, which is a dimensionless value obtained by dividing the actual value of a physical quantity by its corresponding nominal value (reference value). U / pu: Represents the per-unit value of the fundamental positive sequence voltage; P / pu: Represents the per-unit value of active power; Iq / pu: Represents the per-unit value of reactive current; from Figure 6 It can be seen that the voltage curve U is initially at the rated voltage value, and at t Ustart1 The moment began to fall, t Ustart2 Stable at a low level (low voltage stage); at t Uend1 The recovery process begins at the moment, and eventually at t Uend2 It should always return to the rated voltage value.

[0095] The active power curve P is initially at the rated power value (P end After the voltage drops, it quickly decreases to a lower value (P). start And maintain; after the voltage recovers, the active power gradually increases, eventually reaching t Pend The power will be restored to the rated power value at any time. The reactive current curve Iq initially has 0, but increases rapidly when the voltage drops (wind turbines need to inject reactive power into the grid to support the voltage), at t Iqstart When the voltage reaches its maximum value, it recovers at time t. Iqend The time gradually decreased, eventually reaching t Iqtuichu The timeline is restored to 0.

[0096] Figure 6 The t marked with a dashed line Ustart1 t Ustart2 t Iqstart t Uend1 t Uend2 t Iqend t Iqtuichu t Pend The timing is the voltage stage switching point calibrated by the improved Hough transform linear detection algorithm (corresponding to the start point of voltage drop, the steady-state point of voltage drop, the recovery start point, etc.), which can be used to calculate the voltage drop duration, power response time and other ride-through indicators.

[0097] S306. Based on the multiple crossing indicators, determine the target evaluation result corresponding to the target wind turbine; the target evaluation result includes one of the following: qualified or unqualified.

[0098] In this embodiment, the normal index range corresponding to each of the multiple crossing indicators can be obtained, resulting in multiple normal index ranges. Specifically, a preset mapping relationship between crossing indicators and adjustment coefficients can be stored in advance, and multiple normal index ranges corresponding to the multiple crossing indicators can be determined based on this mapping relationship. Then, for each crossing indicator, it is determined whether it is within the corresponding normal index range. If all of the above multiple crossing indicators are within the corresponding normal index range, the target evaluation result is determined to be qualified. Conversely, if one of the multiple crossing indicators is not within the corresponding normal index range, the target evaluation result is determined to be unqualified. For example, assuming that the voltage rise time among the multiple crossing indicators is 600ms, and the normal index range of the voltage rise time is [100ms, 500ms], 600ms exceeds the normal index range. In this case, even if all other indicators are qualified, the target evaluation result still needs to be determined to be unqualified.

[0099] In some embodiments, the automatic evaluation method for high and low voltage ride-through results provided in this application is used to automatically evaluate the low-voltage side results of a low-voltage ride-through test of a wind turbine with a rated active power of 5MW and a rated voltage of 35kV. Specifically, a 20%Un three-phase low-voltage ride-through test is performed on the wind turbine. The test results show a voltage drop depth of 18.1%Un, a reactive current coefficient of 1.8, a theoretical reactive current of 1.29 pu, and an actual reactive current of 1.32 pu, meeting the error requirements. The duration t is calculated using the improved Hough transform linear detection algorithm. dip Given a reactive current response time t of 624ms, calculate the reactive current response time t. res1 The duration is 38.1 ms and the duration is t. sus The time to exit is 619ms and the time to exit is t. ree1 The active power recovery rate is 28.7 ms, P rate The reactive current response time during low voltage ride-through is 18.9 Pn / s; res1 Less than 60ms, exit time t ree1 The active power recovery rate P is less than 60ms. rate If the value is greater than 20% Pn / s, analysis shows that the active current, reactive current response time, and reactive current exit time, among other ride-through indicators, fully meet the requirements, and the target evaluation result is deemed satisfactory. Here, Pn / s represents the multiple of the rated active power recovered per second.

[0100] The test results of the wind turbine under all operating conditions for low voltage ride-through are shown in Table 1: Table 1

[0101] In some embodiments, the automatic evaluation method for high and low voltage ride-through results provided in this application is used to automatically evaluate the low-voltage side results of a high voltage ride-through test of a wind turbine with a rated active power of 5MW and a rated voltage of 35kV. Specifically, a 130%Un three-phase high voltage ride-through test is performed on the wind turbine. The test results show that the voltage rises to 124.5%Un, the reactive current coefficient is 2, the theoretical reactive current should be -0.29, and the actual reactive current is -0.24pu, meeting the error requirements. The duration t is calculated using the improved Hough transform linear detection algorithm. dip Given a reactive current response time t of 499ms, calculate the reactive current response time t. res1 The duration is 97.5ms and the duration is t. sus The timeout is 391.5ms, and the exit time is t. ree1 The active power recovery rate is 48.5 ms. rate The value is infinite, meaning the active power recovers immediately; the reactive current response time t during high-voltage ride-through is... res1 Greater than 60ms, exit time t ree1 The active power recovery rate P is less than 40ms. rate Active current I greater than 20%Pn / s p1 If the reactive current exit time meets the requirements, but the reactive current response time does not, then some pass-through indicators do not meet the requirements, and the evaluation result is unqualified.

[0102] The test results of the high voltage ride-through of the wind turbine under all operating conditions are shown in Table 2: Table 2

[0103] In summary, the automatic evaluation method for high and low voltage ride-through results described in this application obtains test data by conducting high and low voltage ride-through tests on the test points of the target wind turbine; it then processes and analyzes the test data using an improved Hough transform linear detection algorithm to automatically output multiple ride-through indices; and finally, it determines the evaluation results based on these indices. This method avoids the problems of manual analysis being affected by experience and ability, and eliminates the need for repeated data verification, thereby improving the evaluation efficiency of the high and low voltage ride-through capability of wind turbines.

[0104] Please see Figure 7 , Figure 7 This is a functional unit block diagram of an automatic evaluation device for high and low voltage ride-through results provided in this application embodiment; the automatic evaluation device 700 for high and low voltage ride-through results includes: a testing unit 701, a data analysis unit 702, and an evaluation unit 703, wherein: The test unit 701 is used to perform high and low voltage ride-through tests on the test points of the target wind turbine and collect test data at the test points. The data analysis unit 702 is used to extract the fundamental positive sequence component from the test working data; determine the first reactive current value based on the fundamental positive sequence component; determine whether the first reactive current value meets the preset conditions; and when the first reactive current value meets the preset conditions, process the test working data based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. The evaluation unit 703 is used to determine the target evaluation result corresponding to the target wind turbine based on the multiple crossing indicators; the target evaluation result includes one of the following: qualified or unqualified.

[0105] It should be explained that the automatic evaluation device 700 for high and low voltage ride-through results can also perform some or all of the steps of any of the methods described in the above method embodiments.

[0106] Please see Figure 8 , Figure 8 This is a schematic diagram of another electronic device provided in an embodiment of this application. The electronic device may include a processor, a memory, a communication interface, and one or more programs. The processor, memory, and communication interface can be interconnected via a bus. The one or more programs are stored in the memory and configured to be executed by the processor. In this embodiment, the programs include instructions for performing the following steps: High and low voltage ride-through tests were performed on the test points of the target wind turbine, and test data were collected at the test points. Extract the fundamental positive sequence component from the test data; The first reactive current value is determined based on the fundamental positive sequence component. Determine whether the first reactive current value meets the preset conditions; When the first reactive current value meets the preset condition, the test data is processed based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. Based on the multiple crossing indicators, the target evaluation result corresponding to the target wind turbine is determined; the target evaluation result includes one of the following: qualified or unqualified.

[0107] It should be explained that the electronic device can also perform some or all of the steps of any of the methods described in the above method embodiments.

[0108] This application also provides a computer-readable storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0109] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

[0110] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0111] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0113] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0114] The steps of the methods or algorithms described in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disk, portable hard disk, read-only optical disk (CD-ROM), or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Furthermore, the ASIC can reside in a terminal device or management device. Alternatively, the processor and storage medium can exist as discrete components in the terminal device or management device.

[0115] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in the embodiments of this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated.

[0116] The aforementioned computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media.

[0117] The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0118] The modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both. For example, for devices and products applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits. For devices and products applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The implementation is achieved through a software program that runs on the processor integrated within the chip module. The remaining modules / units (if any) can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into terminal equipment, each of their modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the terminal equipment. Alternatively, at least some modules / units can be implemented through a software program that runs on the processor integrated within the terminal equipment, while the remaining modules / units (if any) can be implemented using hardware methods such as circuits.

[0119] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the embodiments of this application. It should be understood that the above descriptions are merely specific embodiments of the embodiments of this application and are not intended to limit the protection scope of the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solutions of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. An automatic evaluation method for high and low voltage ride-through results, characterized in that, include: High and low voltage ride-through tests were performed on the test points of the target wind turbine, and test data were collected at the test points. Extract the fundamental positive sequence component from the test data; The first reactive current value is determined based on the fundamental positive sequence component. Determine whether the first reactive current value meets the preset conditions; When the first reactive current value meets the preset condition, the test data is processed based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. Based on the multiple crossing indicators, the target evaluation result corresponding to the target wind turbine is determined; The target evaluation result includes one of the following: qualified or unqualified.

2. The method as described in claim 1, characterized in that, The test data includes: fundamental positive sequence voltage, fundamental positive sequence reactive current, and fundamental positive sequence active power. The improved Hough transform line detection algorithm is used to process the test data to obtain multiple crossing indicators, including: Determine the first waveform corresponding to the test data; the first waveform includes at least one of the following: the voltage waveform corresponding to the fundamental positive sequence voltage, the current waveform corresponding to the fundamental positive sequence reactive current, and the power waveform corresponding to the fundamental positive sequence active power. The first waveform is processed using a preset edge extraction algorithm to obtain a binarized edge pattern; Initialize the parameter space (ρ, θ) and accumulator of the polar coordinate system; ρ represents the polar radius and θ represents the polar angle; the accumulator is a two-dimensional array whose dimension corresponds to the number of discrete intervals in the parameter space. For each edge point in the binarized edge pattern, traverse each θ value in the parameter space, calculate the ρ value corresponding to the θ value according to the edge point and the first preset formula, and obtain multiple sets of parameter pairs. Each set of parameter pairs includes an θ value and its corresponding ρ value. Map each set of parameter pairs to the parameter space and count it at the corresponding position of the accumulator. Determine the maximum count value corresponding to the accumulator, and determine the target parameter pair corresponding to the maximum count value among the multiple sets of parameter pairs; Determine the first Hough transform line based on the target parameters; The multiple crossing indices are determined based on the first Hough transform line and the multiple sets of parameter pairs.

3. The method as described in claim 2, characterized in that, The preset edge extraction algorithm includes a gradient-based watershed segmentation algorithm; The step of processing the first waveform using a preset edge extraction algorithm to obtain a binarized edge pattern includes: The first waveform is preprocessed to obtain a grayscale waveform. The grayscale waveform is detected using an edge detection operator to obtain a gradient magnitude image; Based on the preset threshold and the gradient magnitude image, an initial binarized image is determined; The binarized edge pattern is determined based on the watershed algorithm, the gradient magnitude image, and the initial binarized image.

4. The method as described in claim 2, characterized in that, The determination of the multiple crossing indices based on the first Hough transform line and the multiple sets of parameter pairs includes: Determine the parameter pair that corresponds to the first Hough transform line among the multiple sets of parameter pairs to obtain at least one parameter pair; Determine the edge point corresponding to the at least one parameter pair in the binarized edge pattern to obtain at least one edge point; The plurality of crossing indices are determined based on the at least one edge point.

5. The method as described in claim 4, characterized in that, When the first waveform includes the voltage waveform corresponding to the fundamental positive sequence voltage, determining the plurality of crossover indices based on the at least one edge point includes: Obtain the coordinates of at least one edge point corresponding to the at least one edge point; the horizontal axis of each edge point coordinate is time, and the vertical axis is voltage value; Determine the maximum and minimum abscissa values, as well as the maximum and minimum ordinate values, among the coordinates of the at least one edge point; Obtain the target slope corresponding to the first Hough transform line; The plurality of crossing indicators are determined based on the target slope, the maximum x-coordinate value, the minimum x-coordinate value, the maximum y-coordinate value, and the minimum y-coordinate value.

6. The method as described in claim 5, characterized in that, The determination of the multiple crossing indicators based on the target slope, the maximum abscissa value, the minimum abscissa value, the maximum ordinate value, and the minimum ordinate value includes: When the target slope is greater than or equal to a preset value, the voltage rise period corresponding to the first Hough transform line is determined, and the voltage rise duration is determined based on the maximum and minimum abscissa values; the voltage rise change value is determined based on the maximum and minimum ordinate values; and the multiple crossing indicators are determined based on the voltage rise duration and the voltage rise change value. When the target slope is less than the preset value, the voltage drop period corresponding to the first Hough transform line is determined; the voltage drop duration is determined based on the maximum and minimum abscissa values; the voltage drop change value is determined based on the maximum and minimum ordinate values; and the multiple crossover indicators are determined based on the voltage drop duration and the voltage drop change value.

7. The method according to any one of claims 1-6, characterized in that, The step of determining whether the first reactive current value meets the preset conditions includes: Determine the device type corresponding to the test point; When the equipment type includes a new energy generator unit, a preset reactive current value corresponding to the target wind turbine unit is determined; a first deviation between the first reactive current value and the preset reactive current value is determined; if the first deviation is less than or equal to the preset deviation, the first reactive current value is determined to meet the preset condition; if the first deviation is greater than the preset deviation, the first reactive current value is determined not to meet the preset condition. When the equipment type includes the high-voltage side of the step-up transformer of a new energy unit, the first reactive current value is converted into a second reactive current value at the generator terminal of the new energy unit; a second deviation between the second reactive current value and the preset reactive current value is determined; if the second deviation is less than or equal to the preset deviation, the first reactive current value is determined to meet the preset condition; if the second deviation is greater than the preset deviation, the first reactive current value is determined not to meet the preset condition.

8. An automatic evaluation device for high and low voltage ride-through results, characterized in that, include: The testing unit, data analysis unit, and evaluation unit are as follows: The test unit is used to perform high and low voltage ride-through tests on the test points of the target wind turbine and collect test data at the test points. The data analysis unit is used to extract the fundamental positive sequence component from the test data; determine the first reactive current value based on the fundamental positive sequence component; determine whether the first reactive current value meets the preset conditions; and when the first reactive current value meets the preset conditions, process the test data based on the improved Hough transform line detection algorithm to obtain multiple crossing indicators. The evaluation unit is used to determine the target evaluation result corresponding to the target wind turbine based on the multiple crossing indicators; the target evaluation result includes one of the following: qualified or unqualified.

9. An electronic device, characterized in that, include: Processor, memory, communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange, wherein the computer program causes a computer to perform the method as described in any one of claims 1-7.

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