Hydropower station electrical equipment insulation online analysis method and system

Abstract

The invention discloses a hydropower station electrical equipment insulation online analysis method and system, and relates to the technical field of electrical equipment analys.The method comprises the steps that a potential abnormal area with insulation defects is preliminarily screened out, the degree of erosion of moisture and gas decomposition products to insulation performance is analyzed, and the evolution trend of the potential abnormal area is predicted; the method comprises the following steps: collecting monitoring data of electrical equipment around a transformer, analyzing the operation state of the electrical equipment, collecting current time domain and frequency domain waveform data of the transformer and an associated loop, analyzing a conduction path of electrical disturbance in a power grid, and evaluating the influence of abnormal insulation of the transformer on the operation stability of the surrounding electrical equipment. The electrical equipment operation risk is analyzed by combining the evolution trend of the potential abnormal area and the influence of the transformer insulation abnormity on the operation stability of the surrounding electrical equipment, the electrical equipment operation risk is comprehensively evaluated by fusing the internal insulation evolution trend and the external electrical stability influence, and the accuracy of fault early warning is improved.

Description

Technical Field

[0001] This invention relates to the field of electrical equipment analysis technology, and in particular to an online insulation analysis method and system for electrical equipment in hydropower stations. Background Technology

[0002] As an important component of the power system, the insulation condition of the core equipment transformer of a hydropower station is directly related to the operational safety of the entire station. During long-term operation, the transformer insulation layer is susceptible to defects such as aging, dampness, or partial discharge due to the influence of factors such as electric field, heat, mechanical stress, and environmental humidity. In severe cases, this can lead to insulation breakdown accidents and cause losses.

[0003] Currently, there are the following shortcomings in the monitoring of transformer insulation status: Existing methods usually treat the transformer as a whole for monitoring, and independently analyze the data of gas, moisture or electrical quantities in the oil. They do not conduct correlation analysis between the internal insulation status and oiling parameters of the transformer and external electrical disturbances, making it difficult to assess the dynamic impact of insulation defects on the operational stability of surrounding power grid equipment.

[0004] To address the aforementioned problems, this invention provides a method and system for online insulation analysis of electrical equipment in hydropower stations. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an online insulation analysis method and system for electrical equipment in hydropower stations. By integrating the internal insulation evolution trend with the influence of external electrical stability, this invention comprehensively assesses the operational risks of electrical equipment, thereby improving the accuracy of fault early warning.

[0006] To achieve the above objectives, the present invention provides an online insulation analysis method for electrical equipment in hydropower stations, comprising the following specific steps: Step 1: Divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. Step 2: Based on the monitoring data of dissolved gas and moisture content in transformer oil, analyze the degree of erosion of insulation performance by moisture and gas decomposition products, and predict the evolution trend of potential abnormal areas. Step 3: Collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; Step 4: Collect current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the transmission path of electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. Step 5: Analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

[0007] Preferably, step one includes the following specific steps: Step 11: Divide the transformer into several monitoring areas evenly, number each monitoring area and obtain the coordinates of the monitoring area; Step 12: Use sensors to collect coating status data of the insulation layer in each monitoring area. The coating status data includes coating thickness and bubble area. Step 13: Obtain the average thickness and standard deviation of the coating thickness in a single monitoring area, and obtain the outlier values ​​of the coating thickness by dividing the standard deviation of the coating thickness by the average thickness of the area. Step 14: Obtain the total area of ​​all bubbles in a single monitoring area, and obtain the bubble anomaly value by dividing the total area of ​​all bubbles by the total area of ​​the single monitoring area; Step 15: Obtain the regional anomaly value of a single monitoring area by weighted summation of coating thickness anomalies and bubble anomalies; Step 16: Obtain the preset regional anomaly threshold, filter regional anomaly values ​​that are greater than or equal to the preset regional anomaly threshold, and set the monitoring area corresponding to the regional anomaly value as a potential anomaly area with insulation defects.

[0008] Preferably, step two includes the following specific steps: Step 21: Combine the monitoring data of dissolved gas and moisture content inside the transformer. The monitoring data of dissolved gas includes the gas concentration of dissolved gas inside the transformer, and the monitoring data of moisture content includes oil temperature and moisture concentration in oil. Step 22: Obtain the relative saturation by dividing the water concentration in the oil by the saturation solubility corresponding to the oil temperature, and obtain the water erosion factor by using the water erosion calculation formula; Step 23: Obtain the total hydrocarbon gas generation rate through the gas generation rate calculation formula; obtain the generation rate threat value by dividing the total hydrocarbon gas generation rate by the gas rate alarm threshold; obtain the total hydrocarbon content by the gas concentration of internal dissolved gas; obtain the gas concentration threat value by dividing the total hydrocarbon content by the concentration alarm threshold; obtain the gas dissolution erosion factor by weighted summing of the generation rate threat value and the gas concentration threat value. Step 24: Obtain the comprehensive erosion index by weighted summation of moisture erosion factor and gas dissolved erosion factor; Step 25: Calculate the comprehensive erosion index of the potential anomaly area at a future set time using the evolution trend prediction formula.

[0009] Preferably, step three includes the following specific steps: Step 31: Collect monitoring data of electrical equipment within a designated area around the transformer. The monitoring data includes current, temperature, and vibration acceleration. Step 32: Obtain the current offset value, temperature offset value, and vibration acceleration offset value through the parameter offset value calculation formula, and obtain the abnormal operating value of the electrical equipment by weighted summation of the current offset value, temperature offset value, and vibration acceleration offset value.

[0010] Preferably, step four includes the following specific steps: Step 41: Collect the time-domain and frequency-domain waveform data of the transformer and related circuits; Step 42: Obtain the electrical disturbance signal using the electrical disturbance difference calculation formula; Step 43: Construct the power grid impedance matrix of the transformer and related circuits, and obtain the voltage disturbance amplitude by multiplying the disturbance current component with the elements of the impedance matrix. Step 44: Obtain the voltage deviation value by dividing the voltage disturbance amplitude by the rated voltage; obtain the total harmonic distortion rate change by using the formula for calculating the total harmonic distortion rate change; and obtain the impact index of transformer insulation abnormality on the operational stability of surrounding electrical equipment by first dividing the voltage deviation value and the total harmonic distortion rate increment by their respective allowable safety thresholds, and then weighted summing them.

[0011] Preferably, step five includes the following specific steps: Step 51: Obtain the risk factor for internal insulation degradation of electrical equipment by dividing the comprehensive erosion index of the potential abnormal area at a future set time by the critical erosion index threshold for insulation failure. Step 52: Obtain the external stability impact risk factor by dividing the maximum value of the impact index of transformer insulation abnormality on the operational stability of surrounding electrical equipment by the threshold of the impact index of electrical equipment operational stability; Step 53: Obtain the comprehensive operational risk value of the electrical equipment by weighted summing of the risk factors for internal insulation degradation and external stability impact. Step 54: Obtain the preset operating risk threshold, filter the comprehensive operating risk values ​​that are greater than or equal to the preset operating risk threshold, and issue an early warning to the electrical equipment corresponding to the comprehensive operating risk value.

[0012] This invention also provides an online insulation analysis system for electrical equipment in hydropower stations, comprising: The abnormal area screening module is used to divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. The evolution trend prediction module is used to combine the monitoring data of dissolved gas and moisture content in transformer oil to analyze the degree of erosion of insulation performance by moisture and gas decomposition products and predict the evolution trend of potential abnormal areas. The proximity equipment analysis module is used to collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; The stability impact analysis module is used to collect the current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the conduction path of the electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. The risk analysis module is used to analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

[0013] The present invention also provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-described method for online insulation analysis of electrical equipment in a hydropower station by calling the computer program stored in the memory.

[0014] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for online insulation analysis of electrical equipment in a hydropower station.

[0015] Compared with the prior art, the beneficial effects of the present invention are: By dividing the transformer into monitoring areas and conducting preliminary screening, early-stage minor insulation defects can be accurately located, avoiding the problem of missing local degradation due to signal averaging effects, and improving the timeliness and accuracy of fault warning. By combining data on dissolved gases and moisture in the oil, we can conduct in-depth analysis of the extent to which chemical factors erode insulation performance, predict the evolution trend of potential abnormal areas, and facilitate the determination of the best maintenance time. By integrating the internal insulation evolution trend with the influence of external electrical stability, a comprehensive assessment of the operational risks of electrical equipment can help reduce the risk of cascading failures and improve the overall operational reliability of hydropower stations. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the online insulation analysis method for electrical equipment in a hydropower station according to the present invention. Figure 2 This is a schematic diagram of step two of the online insulation analysis method for electrical equipment in a hydropower station according to the present invention. Figure 3 This is a schematic diagram of step four of the online insulation analysis method for electrical equipment in a hydropower station according to the present invention. Figure 4 This is a schematic diagram of the overall framework of an online insulation analysis system for electrical equipment in a hydropower station according to the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0019] Please see Figure 1 This invention provides an online insulation analysis method for electrical equipment in hydropower stations, comprising the following specific steps: Step 1: Divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. In this embodiment, step one includes the following specific steps: Step 11: Divide the transformer into several monitoring areas evenly, number each monitoring area and obtain the coordinates of the monitoring area. In this embodiment, based on the transformer's geometric structure, such as the winding height or the perimeter of the core column, the transformer is divided into uniform grids in the spatial dimension to achieve fixed-point monitoring. Step 12: Based on the sensor resolution and coating quality detection accuracy requirements, set the spacing between sampling points. Deploy corresponding sensors, such as ultrasonic thickness gauges and high-frequency ultrasonic imaging, at the sampling points in each monitoring area, and acquire data from all valid sampling points within the monitoring area to construct a local dataset. Use sensors to collect coating status data of the insulation layer in each monitoring area. The coating status data includes coating thickness and bubble area. Where the coating is too thin, the electric field strength will increase sharply, becoming a breakthrough point for insulation breakdown. Monitoring coating uniformity can ensure that the electric field is evenly distributed in the insulation layer, avoiding breakdown caused by excessively high local electric fields. When bubbles exist inside the transformer insulation layer, under the action of a high electric field, the bubbles are prone to partial discharge. The discharge process releases energy instantaneously, generating high temperature and high pressure, causing the surrounding oil medium to expand rapidly and excite pressure waves, forming ultrasonic signals. Since the dielectric constant of air is much smaller than that of solid or liquid insulating materials, the electric field concentrates at the bubbles, leading to an increase in local field strength, becoming the discharge initiation point. Partial discharge is the main cause of insulation aging. Bubbles can cause uneven stress on the cross-section of the insulation layer. During the thermal expansion and contraction process of the transformer during operation, micro-cracks are easily generated around the bubbles, which will gradually corrode the surrounding insulation material and eventually lead to complete insulation breakdown. Monitoring bubbles can detect potential partial discharge sources in advance and avoid rapid deterioration of insulation performance during operation. Step 13: Obtain the average thickness and standard deviation of the coating thickness in a single monitoring area, and obtain the outlier values ​​of the coating thickness by dividing the standard deviation of the coating thickness by the average thickness of the area. Step 14: Obtain the total area of ​​all bubbles in a single monitoring area, and obtain the bubble anomaly value by dividing the total area of ​​all bubbles by the total area of ​​the single monitoring area; Step 15: Obtain the regional anomaly value of a single monitoring area by weighted summation of coating thickness anomalies and bubble anomalies; Step 16: Obtain the preset regional anomaly threshold, filter regional anomaly values ​​that are greater than or equal to the preset regional anomaly threshold, and set the monitoring area corresponding to the regional anomaly value as a potential anomaly area with insulation defects.

[0020] Step 2: Based on the monitoring data of dissolved gas and moisture content in transformer oil, analyze the degree of erosion of insulation performance by moisture and gas decomposition products, and predict the evolution trend of potential abnormal areas. Please see Figure 2 In this embodiment, step two includes the following specific steps: Step 21: Combine the monitoring data of dissolved gas and moisture content inside the transformer. The monitoring data of dissolved gas includes the gas concentration of dissolved gas inside the transformer. In this embodiment, oil samples are collected and the concentration of dissolved gas in the oil is analyzed by gas chromatography. The monitoring data of moisture content includes oil temperature and moisture concentration in the oil. In this embodiment, the top oil temperature of the transformer is measured by a temperature sensor and the dissolved moisture content in the oil is measured by a moisture sensor. Step 22: Obtain the relative saturation by dividing the water concentration in the oil by the saturation solubility corresponding to the oil temperature. Obtain the water erosion factor using the water erosion calculation formula. In this embodiment, the method for obtaining the saturation solubility corresponding to the oil temperature is as follows: monitor the transformer oil temperature in real time, and calculate the saturation solubility at the current oil temperature using the empirical formula of the Oommen curve. The water erosion calculation formula can be expressed as: In the formula, As a moisture-eroding factor, Relative saturation The moisture saturation threshold is set according to the design specifications of the transformer insulation system or historical experience, for example, 20%. Based on the erosion coefficient, The degradation acceleration index (DAC) is obtained as follows: Transformer insulation samples are selected, and the same batch of transformer oil is used. Deionized water is added to adjust the moisture content, creating different relative saturations. The oil temperature is kept constant, for example, 85℃, simulating the transformer's operating temperature. Five relative saturations are set, such as 0.1, 0.3, 0.5, 0.7, and 0.9. At each level, aging is performed at four time points, such as 1 month, 3 months, 6 months, and 12 months. The degree of insulation degradation is measured. With water erosion factor as the independent variable and water erosion factor as the dependent variable, the formula was obtained using the nonlinear least squares method. and ; Step 23: Obtain the total hydrocarbon gas generation rate using the gas generation rate calculation formula, which can be expressed as: In the formula, The generation rate of a single internal dissolved gas. for The gas concentration of a single internal dissolved gas at a given time. for The gas concentration of a single internal dissolved gas at a given time. To monitor the time interval, this embodiment sums the generation rates of the gases contained in the total hydrocarbons to obtain the generation rate of the total hydrocarbon gases. The gases contained in the total hydrocarbons may include H2, CH4, C2H6, C2H4, and C2H2. Total hydrocarbons are typical products of the cracking of insulating oil under thermal / electrical stress (alkanes, alkenes, alkynes), which directly reflect the degree of oil cracking. The generation rate threat value is obtained by dividing the generation rate of the total hydrocarbon gases by the gas rate alarm threshold. The total hydrocarbon content is obtained by the gas concentration of the internal dissolved gases. The gas concentration threat value is obtained by dividing the total hydrocarbon content by the concentration alarm threshold. The gas dissolution erosion factor is obtained by weighted summing the generation rate threat value and the gas concentration threat value. Step 24: Obtain the comprehensive erosion index by weighted summation of moisture erosion factor and gas dissolved erosion factor; Step 25: Calculate the comprehensive erosion index of the potential anomaly region at a predetermined future time using the evolution trend prediction formula. The evolution trend prediction formula can be expressed as: In the formula, Setting time for the future of potential anomaly regions The comprehensive erosion index, The comprehensive erosion index at the current time t. To mitigate the deterioration of the growth rate, regression analysis using historical data was conducted: In the formula, and The start and end times of the historical fitted data segment. This is a regional outlier.

[0021] Step 3: Collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; In this embodiment, step three includes the following specific steps: Step 31: Set the location of the transformer as the origin of the coordinate system, draw a circle with a set radius, and the effective electrical equipment within the circle is the equipment to be monitored. Collect the monitoring data of the electrical equipment in the set area around the transformer. The monitoring data includes current, temperature and vibration acceleration. In this embodiment, the current is obtained through a current transformer, the temperature is obtained through an infrared sensor, and the vibration acceleration is obtained through a piezoelectric acceleration sensor. Step 32: Obtain the current offset value, temperature offset value, and vibration acceleration offset value using the parameter offset value calculation formula. The parameter offset value calculation formula can be expressed as: In the formula, These are parameter offset values ​​used to quantify the degree of anomalies in current, temperature, and vibration acceleration. For the monitoring data of the nth type of electrical equipment, it can be current, temperature, or vibration acceleration. The historical average value corresponding to the monitoring data. To monitor the historical standard deviation of the data, abnormal operating values ​​of electrical equipment are obtained by weighted summation of current offset, temperature offset, and vibration acceleration offset.

[0022] Step 4: Collect current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the transmission path of electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. Please see Figure 3 In this embodiment, step four includes the following specific steps: Step 41: Deploy high-precision sampling devices at the transformer and its associated critical circuit nodes to acquire current data containing transient and steady-state information. Select the high-voltage side and low-voltage side bushings of the transformer, as well as the connection points of adjacent critical busbars and feeders, as monitoring nodes. Collect the time-domain and frequency-domain waveform data of the current of the transformer and its associated circuits. In this embodiment, the time-domain waveform of the current at each node is collected at a set sampling frequency, and its frequency-domain spectrum is calculated by fast Fourier transform. The formula for obtaining the frequency-domain spectrum can be expressed as: In the formula, To monitor the node index, For frequency variables, For nodes Current at frequency Spectral components at that location For nodes The instantaneous current at time T For time integration, The unit is imaginary. It should be noted that in actual monitoring, the finite-duration signal is mapped to the frequency domain through the Fast Fourier Transform. At this time, the integration interval is equivalent to the interval corresponding to the number of sampling points. Step 42: Obtain the electrical disturbance signal using the electrical disturbance difference calculation formula. In this embodiment, the actual waveform collected is compared with the reference healthy waveform to separate the disturbance component caused by the insulation abnormality area. The electrical disturbance difference calculation formula can be expressed as: In the formula, This refers to the electrical disturbance signal, specifically the electrical disturbance difference. For nodes The current waveform under normal operating conditions is obtained by monitoring historical data to obtain the current data when there are no abnormalities at this node; Step 43: Construct the power grid impedance matrix of the transformer and related circuits. In this embodiment, a power grid model is established, which includes the impedance parameters of the transformer and surrounding related nodes. The impedance matrix is ​​obtained by inverting the node admittance matrix. The voltage disturbance amplitude is obtained by multiplying the disturbance current component with the elements of the impedance matrix. In this embodiment, the elements of the impedance matrix are the mutual impedance between node m and the transformer node. The frequency domain transformation result of the electrical disturbance signal is obtained by Fourier transform. The disturbance current component is the frequency domain vector at a specific node of the transformer. Step 44: Obtain the voltage deviation value by dividing the voltage disturbance amplitude by the rated voltage. Then, obtain the total harmonic distortion (THD) change using the formula for calculating the THD change. The formula for calculating the THD change can be expressed as: In the formula, Let r be the change in total harmonic distortion rate at point r of the electrical equipment. To determine the highest harmonic order, this embodiment sets the highest harmonic order, for example, 50th, based on the harmonic characteristics of the power grid (transformer excitation harmonics are mainly in the 3rd, 5th, and 7th orders), thus covering the main harmonic range. Let be the voltage disturbance amplitude of the h-th harmonic at point r of the electrical equipment. Given the rated voltage, the impact index of transformer insulation abnormalities on the operational stability of surrounding electrical equipment is obtained by first dividing the voltage deviation value and the total harmonic distortion rate increment by their respective allowable safety thresholds, and then weighting and summing them.

[0023] Step 5: Analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

[0024] In this embodiment, step five includes the following specific steps: Step 51: Obtain the risk factor for internal insulation degradation of electrical equipment by dividing the comprehensive erosion index of the potential abnormal area at a future set time by the critical erosion index threshold for insulation failure. Step 52: Obtain the external stability impact risk factor by dividing the maximum value of the impact index of transformer insulation abnormality on the operational stability of surrounding electrical equipment by the threshold of the impact index of electrical equipment operational stability; Step 53: Obtain the comprehensive operational risk value of the electrical equipment by weighted summing of the risk factors for internal insulation degradation and external stability impact. Step 54: Obtain the preset operating risk threshold, filter the comprehensive operating risk values ​​that are greater than or equal to the preset operating risk threshold, and issue an early warning to the electrical equipment corresponding to the comprehensive operating risk value.

[0025] The method for obtaining all weights and thresholds in this embodiment is as follows: obtain historical monitoring data and historical fault information of potential abnormal areas of transformers, import the obtained historical monitoring data into each step of this embodiment to obtain the comprehensive operating risk value of electrical equipment and determine whether an early warning is required, import the historical fault information and early warning judgment results into the trained MATLAB fitting software for fitting, and obtain the set of all weight and threshold values ​​with the highest prediction accuracy.

[0026] Please see Figure 4 This invention also provides an online insulation analysis system for electrical equipment in hydropower stations, comprising: The abnormal area screening module is used to divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. The evolution trend prediction module is used to combine the monitoring data of dissolved gas and moisture content in transformer oil to analyze the degree of erosion of insulation performance by moisture and gas decomposition products and predict the evolution trend of potential abnormal areas. The proximity equipment analysis module is used to collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; The stability impact analysis module is used to collect the current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the conduction path of the electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. The risk analysis module is used to analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

[0027] This invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-described method for online insulation analysis of electrical equipment in hydropower stations by calling the computer program stored in the memory.

[0028] The electronic device can vary considerably depending on its configuration or performance. It may include one or more Central Processing Units (CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the online insulation analysis method for hydropower station electrical equipment provided in the above-described embodiment. The electronic device may also include other components for implementing its functions; for example, it may have wired or wireless network interfaces and input / output interfaces for data input and output. Further details are omitted in this embodiment.

[0029] This invention also provides a computer-readable storage medium storing instructions that, when a computer program is run on a computer device, cause the computer device to execute the above-described method for online insulation analysis of electrical equipment in a hydropower station.

[0030] For example, computer-readable storage media can be read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage devices.

[0031] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0032] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, they generate in whole or in part the flow or function according to the embodiments of the present invention. The 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, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network and / or wireless network. 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 contains one or more sets of available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be solid-state drives.

[0033] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this invention.

[0034] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only one, and there may be other division methods in actual implementation. 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 mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical or other forms.

[0035] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units. That is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0036] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0037] The preferred embodiments of the present invention disclosed above are only for the purpose of illustrating the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to specific implementation methods. Obviously, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for online insulation analysis of electrical equipment in hydropower stations, characterized in that, The specific steps include the following: Step 1: Divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. Step 2: Based on the monitoring data of dissolved gas and moisture content in transformer oil, analyze the degree of erosion of insulation performance by moisture and gas decomposition products, and predict the evolution trend of potential abnormal areas. Step 3: Collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; Step 4: Collect current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the transmission path of electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. Step 5: Analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

2. The method for online insulation analysis of electrical equipment in a hydropower station according to claim 1, characterized in that, Step one includes the following specific steps: Step 11: Divide the transformer into several monitoring areas evenly, number each monitoring area and obtain the coordinates of the monitoring area; Step 12: Use sensors to collect coating status data of the insulation layer in each monitoring area. The coating status data includes coating thickness and bubble area. Step 13: Obtain the average thickness and standard deviation of the coating thickness in a single monitoring area, and obtain the outlier values ​​of the coating thickness by dividing the standard deviation of the coating thickness by the average thickness of the area. Step 14: Obtain the total area of ​​all bubbles in a single monitoring area, and obtain the bubble anomaly value by dividing the total area of ​​all bubbles by the total area of ​​the single monitoring area; Step 15: Obtain the regional anomaly value of a single monitoring area by weighted summation of coating thickness anomalies and bubble anomalies; Step 16: Obtain the preset regional anomaly threshold, filter regional anomaly values ​​that are greater than or equal to the preset regional anomaly threshold, and set the monitoring area corresponding to the regional anomaly value as a potential anomaly area with insulation defects.

3. The online insulation analysis method for electrical equipment in a hydropower station according to claim 2, characterized in that, Step two includes the following specific steps: Step 21: Combine the monitoring data of dissolved gas and moisture content inside the transformer. The monitoring data of dissolved gas includes the gas concentration of dissolved gas inside the transformer, and the monitoring data of moisture content includes oil temperature and moisture concentration in oil. Step 22: Obtain the relative saturation by dividing the water concentration in the oil by the saturation solubility corresponding to the oil temperature, and obtain the water erosion factor by using the water erosion calculation formula; Step 23: Obtain the total hydrocarbon gas generation rate through the gas generation rate calculation formula; obtain the generation rate threat value by dividing the total hydrocarbon gas generation rate by the gas rate alarm threshold; obtain the total hydrocarbon content by the gas concentration of internal dissolved gas; obtain the gas concentration threat value by dividing the total hydrocarbon content by the concentration alarm threshold; obtain the gas dissolution erosion factor by weighted summing of the generation rate threat value and the gas concentration threat value. Step 24: Obtain the comprehensive erosion index by weighted summation of moisture erosion factor and gas dissolved erosion factor; Step 25: Calculate the comprehensive erosion index of the potential anomaly area at a future set time using the evolution trend prediction formula.

4. The method for online insulation analysis of electrical equipment in a hydropower station according to claim 3, characterized in that, Step three includes the following specific steps: Step 31: Collect monitoring data of electrical equipment within a designated area around the transformer. The monitoring data includes current, temperature, and vibration acceleration. Step 32: Obtain the current offset value, temperature offset value, and vibration acceleration offset value through the parameter offset value calculation formula, and obtain the abnormal operating value of the electrical equipment by weighted summation of the current offset value, temperature offset value, and vibration acceleration offset value.

5. The method for online insulation analysis of electrical equipment in a hydropower station according to claim 4, characterized in that, Step four includes the following specific steps: Step 41: Collect the time-domain and frequency-domain waveform data of the transformer and related circuits; Step 42: Obtain the electrical disturbance signal using the electrical disturbance difference calculation formula; Step 43: Construct the power grid impedance matrix of the transformer and related circuits, and obtain the voltage disturbance amplitude by multiplying the disturbance current component with the elements of the impedance matrix. Step 44: Obtain the voltage deviation value by dividing the voltage disturbance amplitude by the rated voltage; obtain the total harmonic distortion rate change by using the formula for calculating the total harmonic distortion rate change; and obtain the impact index of transformer insulation abnormality on the operational stability of surrounding electrical equipment by first dividing the voltage deviation value and the total harmonic distortion rate increment by their respective allowable safety thresholds, and then weighted summing them.

6. The method for online insulation analysis of electrical equipment in a hydropower station according to claim 5, characterized in that, Step five includes the following specific steps: Step 51: Obtain the risk factor for internal insulation degradation of electrical equipment by dividing the comprehensive erosion index of the potential abnormal area at a future set time by the critical erosion index threshold for insulation failure. Step 52: Obtain the external stability impact risk factor by dividing the maximum value of the impact index of transformer insulation abnormality on the operational stability of surrounding electrical equipment by the threshold of the impact index of electrical equipment operational stability; Step 53: Obtain the comprehensive operational risk value of the electrical equipment by weighted summing of the risk factors for internal insulation degradation and external stability impact. Step 54: Obtain the preset operating risk threshold, filter the comprehensive operating risk values ​​that are greater than or equal to the preset operating risk threshold, and issue an early warning to the electrical equipment corresponding to the comprehensive operating risk value.

7. An online insulation analysis system for electrical equipment in a hydropower station, used to implement the online insulation analysis method for electrical equipment in a hydropower station as described in any one of claims 1-6, characterized in that, include: The abnormal area screening module is used to divide the transformer into several monitoring areas evenly, use sensors to collect data on the coating status of the insulation layer in each monitoring area, and preliminarily screen out potential abnormal areas with insulation defects. The evolution trend prediction module is used to combine the monitoring data of dissolved gas and moisture content in transformer oil to analyze the degree of erosion of insulation performance by moisture and gas decomposition products and predict the evolution trend of potential abnormal areas. The proximity equipment analysis module is used to collect monitoring data of electrical equipment within a designated area around the transformer and analyze the operating status of the electrical equipment; The stability impact analysis module is used to collect the current time-domain and frequency-domain waveform data of the transformer and related circuits, analyze the electrical characteristic disturbances caused by the evolved potential abnormal areas, analyze the transmission path of electrical disturbances in the power grid, and evaluate the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment. The risk analysis module is used to analyze the operational risks of electrical equipment by combining the evolution trend of potential abnormal areas and the impact of transformer insulation abnormalities on the operational stability of surrounding electrical equipment.

8. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program that can be called by the processor, and the processor executes the online insulation analysis method for electrical equipment in a hydropower station according to any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that, The device stores instructions that, when executed on a computer, cause the computer to perform an online insulation analysis method for electrical equipment in a hydropower station as described in any one of claims 1-6.

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