A method and system for rapid fault early warning in large-scale substations

Abstract

This application relates to the field of fault early warning technology for power distribution stations, specifically to a method and system for rapid fault early warning in large-scale power distribution stations. The method includes: comparing the difference in the maximum amplitude of electromagnetic wave signals between any two sensors, and determining the amplitude deviation by combining the average interference coefficient of electromagnetic wave signals from all sensors; and selecting the maximum partial discharge signal by combining the distance between any two sensors; determining the partial discharge index by analyzing the energy of the maximum partial discharge signal in each frequency range, the dispersion of the maximum amplitude of electromagnetic wave signals from all sensors in each target period, and the proportion of all target periods in the total number of power frequency periods, thereby providing fault early warning for the switchgear under test in large-scale power distribution stations. This application aims to improve the accuracy of insulation fault detection in switchgear in large-scale power distribution stations.

Description

Technical Field

[0001] This application relates to the field of fault early warning technology for power distribution stations, specifically to a method and system for rapid fault early warning in large-scale power distribution stations. Background Technology

[0002] As the core component of the power distribution network, the operation characteristics of large-scale distribution substations have changed significantly with the integration of numerous distributed power sources and energy storage devices, placing higher demands on their fault detection. Switchgear is the key equipment in large-scale distribution substations for power transmission and distribution. Insulation breakdown faults in switchgear first cause circuit breaker tripping, resulting in power outages. In severe cases, it can damage electrical equipment, leading to explosions and fires, seriously affecting the reliability of the power grid. Therefore, achieving rapid fault early warning and troubleshooting for insulation faults in switchgear of large-scale distribution substations is crucial for ensuring the safety of power equipment and improving the safe and stable operation of the power grid.

[0003] Partial discharge is a precursor and important warning sign of insulation breakdown faults. Partial discharge detection in large-scale substation switchgear is an effective method for insulation condition assessment and insulation fault diagnosis. The ultra-high frequency (UHF) method effectively detects partial discharge by measuring the electromagnetic waves generated during the discharge process and is a commonly used technique in the industry for detecting partial discharge in switchgear. However, large-scale substation switchgear has a large number and variety of connected devices, and their corresponding operating states are complex, resulting in significant electromagnetic interference in the electromagnetic environment. This causes the UHF method to acquire signals mixed with numerous interference signals. Furthermore, current industry practices using the UHF method for partial discharge detection neglect the influence of the discharge location on the detection, reducing the accuracy of insulation fault detection in switchgear in large-scale substations. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for rapid fault early warning in large-scale substations, the specific technical solution of which is as follows:

[0005] In a first aspect, embodiments of this application provide a method for rapid fault early warning in large-scale substations, the method comprising the following steps:

[0006] Multiple ultra-high frequency sensors are installed on the switchgear under test in a large-scale substation. The electromagnetic wave signal, its maximum amplitude and phase are collected from each ultra-high frequency sensor in each power frequency cycle. The ultra-high frequency sensor is denoted as sensor.

[0007] The difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in each sensor within each power frequency cycle and the preset first phase and preset second phase is analyzed, and the interference coefficient of the electromagnetic wave signal in each sensor is determined in combination with the maximum amplitude.

[0008] Under each power frequency cycle, compare the difference in the maximum amplitude between the electromagnetic wave signals of any two sensors, and combine the mean interference coefficient of the electromagnetic wave signals in all sensors to determine the amplitude deviation between the electromagnetic wave signals of any two sensors under each power frequency cycle.

[0009] By analyzing the distance between any two sensors and combining it with the amplitude deviation, the comprehensive deviation of each power frequency cycle is determined, so as to select the target cycle from all power frequency cycles. The maximum amplitude of electromagnetic wave signals in all sensors within each target cycle is compared, and the maximum partial discharge signal within each target cycle is selected from the electromagnetic wave signals.

[0010] The frequency domain of the maximum partial discharge signal is divided into multiple frequency intervals. By analyzing the energy of the maximum partial discharge signal in each frequency interval and the dispersion of the maximum amplitude of the electromagnetic wave signal in all sensors in each target period, the partial discharge energy of each target period is determined.

[0011] Based on the partial discharge energy of all target cycles and the proportion of the number of all target cycles in the total number of power frequency cycles, the partial discharge index of the switchgear under test is determined, and fault early warning is provided for the switchgear under test in large-scale substations.

[0012] Preferably, the expression for the interference coefficient of the electromagnetic wave signal in each sensor is: In the formula, F k min represents the interference coefficient of the electromagnetic wave signal in sensor k; k,t This represents the minimum difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in sensor k under a power frequency period t and the preset first phase and preset second phase, respectively; A k,t represents the maximum amplitude of the electromagnetic wave signal in sensor k under power frequency cycle t; T represents the number of all power frequency cycles; norm[] represents the normalization function; γ represents a preset constant greater than 1.

[0013] Preferably, the expression for the amplitude deviation between the electromagnetic wave signals of any two sensors under each power frequency cycle is: In the formula, L represents the amplitude deviation between the electromagnetic wave signals of sensor i and sensor j within the power frequency cycle t; t This represents the average interference coefficient of electromagnetic wave signals in all sensors within a power frequency period t. This represents the difference in the maximum amplitude of the electromagnetic wave signal between sensor i and sensor j within the power frequency cycle t.

[0014] Preferably, the method for determining the comprehensive deviation of each power frequency cycle is as follows:

[0015] Calculate the product of the amplitude deviation between the electromagnetic wave signals of any two sensors within each power frequency cycle and the distance between the corresponding sensors. The sum of the product results between all sensors within each power frequency cycle is taken as the comprehensive deviation for each power frequency cycle.

[0016] Preferably, the method for determining the target period is as follows:

[0017] Calculate the mean of the comprehensive deviations of all power frequency cycles, and denot it as the mean deviation. The power frequency cycle corresponding to the comprehensive deviation being greater than or equal to the mean deviation is taken as the target cycle.

[0018] Preferably, the maximum partial discharge signal within each target period is the electromagnetic wave signal corresponding to the maximum value of the largest amplitude among all electromagnetic wave signals within each target period.

[0019] Preferably, the expression for the partial discharge energy of each target cycle is: H z Represents the partial discharge energy of the target period z; CV z This indicates the degree of dispersion of the maximum amplitude of all electromagnetic wave signals within the target period z; w z,n This represents the preset weight of the maximum partial discharge signal within the target period z in the frequency interval n, where w z,1 +w z,2 +w z,3 +w z,4 =1; E z,n N represents the energy of the maximum partial discharge signal within the frequency range during the target period z; z This represents the number of all frequency ranges of the maximum partial discharge signal within the target period z; ε represents a preset constant greater than 0.

[0020] Preferably, the method for determining the partial discharge index of the switchgear under test is as follows:

[0021] Calculate the sum of the partial discharge energy of all target cycles, and multiply the product of the proportion of all target cycles in the total number of power frequency cycles and the sum as the partial discharge index of the switchgear under test.

[0022] Preferably, the fault early warning for switchgear under test in large-scale substations includes:

[0023] According to the method for obtaining the partial discharge index, the partial discharge indices of a preset number of switchgears without insulation faults are obtained. The maximum value among the partial discharge indices is recorded as the absolute fault threshold. If the partial discharge index of the switchgear under test is greater than the absolute fault threshold, a fault warning is issued for the large-scale substation under test; otherwise, no fault warning is issued. Secondly, embodiments of this application also provide a rapid fault warning system for large-scale substations, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described rapid fault warning methods for large-scale substations.

[0024] This application has at least the following beneficial effects:

[0025] This application constructs an interference coefficient by analyzing the difference between the maximum replication and the peak-valley phase of electromagnetic wave signals. This coefficient reflects the degree of electromagnetic interference experienced by electromagnetic wave signals generated by AC voltage, helping to eliminate interference caused by electromagnetic interference in the partial discharge detection process. Furthermore, by comparing the differences in the maximum amplitude of electromagnetic wave signals from different sensors and combining this with the interference coefficient, an amplitude deviation is obtained, improving the detection capability for weak partial discharges. Further, based on the amplitude deviation, a comprehensive deviation is obtained, and the maximum partial discharge signal is selected from all construction periods. By analyzing the energy of the maximum partial discharge signal in various frequency ranges and combining this with the frequency of the partial discharge, a partial discharge index is constructed, providing a quantitative indicator for fault early warning. By comprehensively considering the location of the partial discharge and the impact of electromagnetic interference on partial discharge detection, the accuracy of insulation fault detection in switchgear in large-scale substations is improved. This application, by analyzing the differences and energy distribution of electromagnetic wave signals from sensors at different locations on the switchgear, can quickly and accurately detect insulation faults in the switchgear, improving the accuracy of insulation fault detection in switchgear in large-scale substations. Attached Figure Description

[0026] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating the steps of a rapid fault early warning method for a large-scale substation provided in one embodiment of this application;

[0028] Figure 2 This is a schematic diagram of a partial discharge energy extraction process provided in one embodiment of this application. Detailed Implementation

[0029] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a rapid fault early warning method and system for a large-scale power distribution station proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0031] The following description, in conjunction with the accompanying drawings, details the specific scheme of the rapid fault early warning method and system for large-scale substations provided in this application.

[0032] Please see Figure 1 The diagram illustrates a flowchart of a rapid fault early warning method for a large-scale substation according to an embodiment of this application. The method includes the following steps:

[0033] Step S1: Install multiple UHF sensors on the switchgear under test in a large-scale substation, and collect the electromagnetic wave signal, its maximum amplitude and phase from each UHF sensor in each power frequency cycle.

[0034] To improve the accuracy of partial discharge detection and considering the actual installation difficulty, an ultra-high frequency (UHF) sensor is installed on each of the two sides and the inner side of the back of the switchgear. This collects the electromagnetic wave signals from each UHF sensor within each power frequency cycle, as well as the phase and maximum amplitude of the electromagnetic wave signals. The installation position of the UHF sensor on different mounting surfaces can be determined based on the actual installation difficulty, especially for measuring electromagnetic wave signals in large-scale substation switchgear. In this embodiment, the UHF sensor is installed at the geometric center of each rectangular mounting surface on the switchgear. The UHF sensor uses an ultra-high frequency partial discharge detector, and it transmits the measured electromagnetic wave signals to a host computer.

[0035] It should be noted that, for ease of description, the term "ultra-high frequency sensor" (UHF) will be abbreviated as "sensor" in the following text.

[0036] Furthermore, it should be understood that in this embodiment, the acquisition period is set to one power frequency cycle during the electromagnetic wave signal acquisition process. The power frequency cycle is a known technology, and the duration of the power frequency cycle is 0.02s. In this embodiment, electromagnetic wave signals are acquired within 500 power frequency cycles, that is, electromagnetic wave signals are acquired for a total of 10s. In actual applications, implementers can also set the acquisition period and acquisition duration according to specific circumstances. This embodiment does not impose any special restrictions.

[0037] It should be noted that the electromagnetic wave signal collected by the UHF sensor in this embodiment is the electromagnetic pulse signal generated by the AC voltage in the UHF sensor in the large-scale substation. Electromagnetic interference refers to the electromagnetic interference generated by circuit breakers, contactors or transformers in the large-scale substation during startup or switching.

[0038] Step S2: Analyze the degree of electromagnetic interference to the electromagnetic wave signal in the sensor and determine the partial discharge energy of each target period.

[0039] The electromagnetic interference (EMI) characteristics generated by different types of electrical equipment in large-scale substation switchgear vary under different operating conditions. For example, circuit breakers, contactors, and transformers generate EMI of varying intensities during startup or switching. The strength of the interference source determines its impact on partial discharge signals. If the interference source is very strong, it may significantly reduce the signal-to-noise ratio (SNR) of the sensor's electromagnetic wave signal. Furthermore, the frequency range and distribution of the high-frequency harmonics of the EMI signal also have different effects on the partial discharge signal. If the high-frequency harmonics of the interference signal are concentrated in the frequency band of the partial discharge signal, the impact on partial discharge detection will be more severe.

[0040] Therefore, by analyzing the degree of electromagnetic interference experienced by the electromagnetic wave signal in the sensor, the partial discharge energy of each target period is determined. The specific process is as follows:

[0041] S201: Analyze the difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in each sensor within each power frequency cycle and the preset first phase and preset second phase, and determine the interference coefficient of the electromagnetic wave signal in each sensor in combination with the maximum amplitude.

[0042] The harmonics generated by changes in the operating status of electrical equipment within the switchgear of large-scale substations have relatively small amplitudes at ultra-high frequencies, but their duration is relatively long. Furthermore, the dense distribution of electrical equipment within the switchgear means that electromagnetic interference affects the entire switchgear. Therefore, the electromagnetic wave signal from the same sensor experiences relatively small changes in electromagnetic interference over a short period. Partial discharge pulse currents generate electromagnetic signals with larger amplitudes, but due to the attenuation characteristics of ultra-high frequency signals, the received amplitude is smaller at more distant sensors, resulting in significant differences in the impact of partial discharge signals on different locations within the switchgear.

[0043] To reduce the impact of electromagnetic interference signals within the switchgear on partial discharge detection, it is necessary to accurately identify the power frequency cycle of the partial discharge signal to improve the measurement capability of weak partial discharge signals under strong interference. The specific process is as follows:

[0044] When a partial discharge occurs due to the application of an external voltage, the phase of the applied voltage is the same as the phase of the partial discharge. Since the occurrence of partial discharge is closely related to the electric field strength in the insulating material, and the change in electric field strength under AC voltage is periodic, partial discharge events often concentrate near the peaks and troughs of the voltage waveform.

[0045] Based on the above analysis, by analyzing the difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in each sensor within each power frequency cycle and the preset first phase and preset second phase, and combining the maximum amplitude, the interference coefficient of the electromagnetic wave signal in each sensor is determined to judge the interference of electromagnetic interference on partial discharge detection, thereby initially limiting the degree of electromagnetic interference on partial discharge within different power frequency cycles. The specific process for determining the interference coefficient is as follows:

[0046] As a real-time method, in this embodiment, the interference coefficient F of the electromagnetic wave signal in sensor k is... k The expression is:

[0047] In the formula, min k,t This represents the minimum difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in sensor k under a power frequency period t and the preset first phase and preset second phase, respectively; A k,t The maximum amplitude of the electromagnetic wave signal in sensor k is represented by t at the power frequency cycle; T represents the number of all power frequency cycles; norm[] represents the normalization function; γ represents a preset constant greater than 1. In this embodiment, the weight of electromagnetic wave signals with amplitudes close to the peaks and troughs of the power frequency voltage is reduced.

[0048] It should be noted that the preset first phase and preset second phase values ​​are set manually. In this embodiment, the preset first phase value is 90° and the preset second phase value is 270°. The reason for this setting is that partial discharge is more likely to occur near the voltage peak, and the waveform of AC voltage is a sine wave with phases of 90° and 270° at the peak and trough. Therefore, in this embodiment, the preset first phase and preset second phase values ​​are 90° and 270°, respectively. In other embodiments, implementers can also set them according to specific circumstances. This embodiment does not impose any special restrictions.

[0049] By analyzing the interference coefficient of the electromagnetic wave signal in each sensor, it can be understood that: if the difference between the maximum amplitude of the current electromagnetic wave signal and the preset first phase or preset second phase is smaller, it means that the maximum amplitude of the electromagnetic wave signal is closer to the peak or trough of the waveform corresponding to the sinusoidal AC voltage within the power frequency cycle. This means that the current electromagnetic wave signal is less affected by electromagnetic interference generated by circuit breakers, transformers, etc. Therefore, a smaller weight is assigned to the maximum amplitude of the current electromagnetic wave signal, and the smaller the final electromagnetic interference coefficient, the more likely the current electromagnetic wave signal is to be generated by partial discharge, and the less likely it is to be affected by electromagnetic interference.

[0050] Conversely, if the maximum amplitude of the electromagnetic wave signal differs significantly from the peak or trough phase of the power frequency voltage waveform, it indicates that the current electromagnetic wave signal may be subject to electromagnetic interference from other sources, or it may not be a partial discharge signal synchronized with the voltage waveform. In this case, the maximum amplitude of the current electromagnetic wave signal will be given a larger weight, resulting in a larger calculated interference coefficient. This indicates that the current electromagnetic wave signal is more likely to be subject to electromagnetic interference, and therefore, the reliability of the current electromagnetic wave signal being generated by partial discharge is low.

[0051] Thus, by analyzing the difference between the maximum amplitude of the electromagnetic wave signal and the phase of the peak or trough of the power frequency voltage, the interference coefficient of the electromagnetic wave signal is obtained, which is used to characterize the degree of electromagnetic interference received by the electromagnetic wave signal generated by AC voltage.

[0052] S202: Compare the difference in the maximum amplitude between the electromagnetic wave signals of any two sensors under each power frequency cycle, and determine the amplitude deviation between the electromagnetic wave signals of any two sensors under each power frequency cycle by combining the interference coefficient.

[0053] Due to the dense distribution of electrical equipment within the switchgear, the high-frequency components of electromagnetic waves generated when the switchgear's operating state changes have a relatively uniform impact on the entire switchgear. This means that the intensity of the high-frequency components of electromagnetic waves caused by switch operations does not vary significantly across different locations within the switchgear. However, when the insulation material inside the switchgear ages, partial discharge may occur. The attenuation of electromagnetic waves generated by partial discharge varies considerably as they reach sensors at different distances, resulting in significant differences in the amplitude of the partial discharge signals received by different sensors. Compared to partial discharge signals, the amplitude of the high-frequency harmonic interference signals generated when the switchgear's operating state changes is smaller.

[0054] Therefore, the greater the amplitude deviation of electromagnetic wave signals from different sensors within the same power frequency cycle, the greater the probability of partial discharge in that power frequency cycle. In each power frequency cycle, the difference in the maximum amplitude between the electromagnetic wave signals of any two sensors is compared, and combined with the average interference coefficient of the electromagnetic wave signals from all sensors, the amplitude deviation between the electromagnetic wave signals of any two sensors in each power frequency cycle is determined, specifically as follows:

[0055] As one implementation method, in this embodiment, the amplitude deviation between the electromagnetic wave signals of sensor i and sensor j under the power frequency period t is... The expression is: In the formula, L t This represents the average interference coefficient of electromagnetic wave signals in all sensors within a power frequency period t. This represents the difference in the maximum amplitude of the electromagnetic wave signal between sensor i and sensor j within the power frequency cycle t.

[0056] It should be noted that there are many methods to measure the difference between data. In this embodiment, the absolute value of the difference between the maximum amplitude of the electromagnetic wave signal between sensor i and sensor j within the power frequency cycle t is taken as the difference between the maximum amplitude of the electromagnetic wave signal between sensor i and sensor j within the power frequency cycle t. In practical applications, as other implementation methods, the implementer may also use other methods such as the square or ratio of the difference to measure the difference between data. This embodiment does not impose any special restrictions on the selection of methods for measuring the difference between data.

[0057] The amplitude deviation between electromagnetic wave signals from any two sensors under each power frequency cycle indicates that the mean interference coefficient reflects the degree of influence of electromagnetic interference in the switch cabinet on partial discharge detection of the sensor under power frequency cycle t. The larger the mean interference coefficient, the greater the influence of electromagnetic interference on partial discharge detection. Furthermore, the greater the difference between the maximum amplitudes of electromagnetic wave signals from different sensors within power frequency cycle t, the greater the influence of the sensor installation position on the electromagnetic wave signal, and the greater the probability of partial discharge within the corresponding power frequency cycle. Therefore, to prevent the influence of strong interference signals when screening partial discharge signals, the mean interference coefficient is used as the calculation weight to increase the value of the amplitude deviation, thereby improving the detection capability for weak partial discharges.

[0058] Thus, by analyzing the differences in the maximum amplitude of electromagnetic wave signals in different sensors under the same power frequency cycle, and using the mean of the interference coefficient as the weighting factor, the amplitude deviation is obtained, thereby improving the detection capability of weak partial discharge.

[0059] S203: By analyzing the distance between any two sensors and combining it with the amplitude deviation, the comprehensive deviation of each power frequency cycle is determined, so as to select the target cycle from all power frequency cycles, compare the maximum amplitude of electromagnetic wave signals in all sensors in each target cycle, and select the maximum partial discharge signal in each target cycle from the electromagnetic wave signals.

[0060] Furthermore, considering the impact of different sensor positions on partial discharge detection, the comprehensive deviation for each power frequency cycle is determined by analyzing the distance between any two sensors and combining it with the amplitude deviation, specifically:

[0061] In one implementation method, this embodiment calculates the product of the amplitude deviation between the electromagnetic wave signals of any two sensors within each power frequency cycle and the distance between the corresponding sensors. The sum of the product results between all sensors within each power frequency cycle is used as the comprehensive deviation for each power frequency cycle. Since the partial discharge signal gradually attenuates during propagation, the greater the distance between different sensors within the current power frequency cycle and the greater the difference in amplitude deviation, the greater the possibility of partial discharge within the current power frequency cycle, and the greater the comprehensive deviation obtained.

[0062] Therefore, the mean of the comprehensive deviation of all power frequency cycles is calculated and denoted as the mean deviation. The power frequency cycle corresponding to the comprehensive deviation being greater than or equal to the mean deviation is taken as the target cycle.

[0063] Thus, by comprehensively analyzing the possibility of partial discharge phenomena within each power frequency cycle, target cycles with partial discharge phenomena were selected from all power frequency cycles.

[0064] S204: Divide the frequency domain of the maximum partial discharge signal into multiple frequency intervals. By analyzing the energy of the maximum partial discharge signal in each frequency interval and the dispersion of the maximum amplitude of the electromagnetic wave signal in all sensors within each target period, determine the partial discharge energy of each target period.

[0065] The frequency of electromagnetic waves excited by partial discharge is related to the pulse current generated by the discharge. The higher the steepness of the pulse current, the higher the frequency of the electromagnetic waves. The steepness of the pulse current is also related to the discharge gap. The smaller the discharge gap, the higher the steepness of the pulse current. Therefore, the more severe the insulation fault in the switchgear of a large-scale substation, the longer the duration of a single partial discharge, and the lower the frequency of the electromagnetic waves generated.

[0066] Considering that within the target period where the partial discharge phenomenon occurs, the larger the amplitude of the electromagnetic wave signal in the sensor, the closer it is to the current partial discharge location, the higher the signal-to-noise ratio of the electromagnetic wave signal, the lower the degree of influence from electromagnetic interference, and the more accurately it can reflect the severity of the current partial discharge.

[0067] Therefore, in this embodiment, the electromagnetic wave signal corresponding to the maximum amplitude of the largest electromagnetic wave signal in each target period is taken as the maximum partial discharge signal in each target period.

[0068] Furthermore, since the location of partial discharge has a significant impact on assessing the severity of insulation faults, the frequency domain of the maximum partial discharge signal is divided into multiple frequency intervals. By analyzing the energy of the maximum partial discharge signal in each frequency interval and the dispersion of the maximum amplitude of electromagnetic wave signals in all sensors within each target period, the partial discharge energy of each target period is determined. Specifically:

[0069] In this embodiment, the frequency of the maximum partial discharge signal in each target period is uniformly divided into N frequency intervals in the frequency domain. The number of frequency intervals N is set manually. In this embodiment, N is set to 4. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0070] Furthermore, based on the energy of the maximum partial discharge signal in each frequency range and the dispersion of the maximum amplitude of electromagnetic wave signals in all sensors within each target period, the partial discharge energy of each target period is determined, specifically:

[0071] Partial discharge energy H of target period z z The expression is: CV z This indicates the degree of dispersion of the maximum amplitude of all electromagnetic wave signals within the target period z; w z,n This represents the preset weight of the maximum partial discharge signal within the target period z in the frequency interval n, where w z,1 +w z,2 +w z,3 +w z,4 =1; E z,n N represents the energy of the maximum partial discharge signal within the frequency range during the target period z; z The value represents the number of all frequency intervals of the maximum partial discharge signal within the target period z; ε represents a preset constant greater than 0, used to prevent the denominator from being 0. The value of ε is set manually. In this embodiment, the value of ε is 0.01. Under the premise of ensuring that the denominator is not 0 and does not excessively affect the calculation result, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0072] It should be understood that w z,n The value of w is set manually; in this embodiment, w... z,1 The value is 0.4, w z,2 The value is 0.3, w z,3 The value is 0.2, w z,4 The value is 0.1. In other implementations, the implementer may set it according to the specific circumstances. This embodiment does not impose any special restrictions.

[0073] It should be noted that there are many methods to measure the dispersion of a set of data. In this embodiment, the dispersion coefficient of the maximum amplitude of all electromagnetic wave signals within the target period z is taken as the dispersion of the maximum amplitude of all electromagnetic wave signals within the target period z. In practical applications, as other real-time methods, implementers may also use other methods such as standard deviation or variance to measure the dispersion of data. This embodiment does not impose any special restrictions on the selection of methods for measuring the dispersion of data.

[0074] The method for calculating the coefficient of variation is a well-known technique, and its specific calculation process will not be elaborated here.

[0075] Analysis of the partial discharge energy in each target period reveals the following: Since the electromagnetic waves generated by partial discharge attenuate with increasing distance during propagation, a smaller dispersion of the maximum amplitude of the electromagnetic wave signal in all sensors within the current target period indicates that the signals generated by partial discharge undergo similar attenuation processes before reaching each sensor. Therefore, the signal amplitudes received by each sensor will be relatively close, meaning the signal amplitude consistency is high. This suggests that the current location of the partial discharge is far from all sensors, and a larger weight should be set to correct the energy of the electromagnetic wave signal to accurately reflect the severity of partial discharge in sensors farther from the location. Conversely, a smaller dispersion of the maximum amplitude of the electromagnetic wave signal in all sensors within the current target period indicates a smaller distance from the current location of the partial discharge to all sensors, and a smaller weight should be set to correct the energy of the electromagnetic wave signal to accurately reflect the severity of partial discharge in sensors farther from the location.

[0076] Thus, by analyzing the energy of the maximum partial discharge signal in each frequency range and the dispersion of the maximum amplitude of electromagnetic wave signals in all sensors within each target period, the partial discharge energy of each target period was obtained.

[0077] Preferably, the schematic diagram of the partial discharge energy extraction process provided in this embodiment is as follows: Figure 2 As shown.

[0078] Step S3: Based on the partial discharge energy of all target cycles and the proportion of the number of all target cycles in the total number of power frequency cycles, determine the partial discharge index of the switchgear under test and provide fault warning for the switchgear under test in large-scale substations.

[0079] The more power frequency cycles containing partial discharge signals, the higher the frequency of partial discharges, and the more severe the insulation faults within the switchgear. Simultaneously, the greater the energy of the partial discharge signal within the corresponding power frequency cycle, the greater the amount of charge released by the partial discharge, reflecting a more severe degree of a single partial discharge.

[0080] Therefore, based on the partial discharge energy of all target cycles and the proportion of all target cycles in the total number of power frequency cycles, the partial discharge index of the switchgear under test is determined as follows:

[0081] In one implementation method, this embodiment calculates the sum of the partial discharge energies of all target cycles. The product of the proportion of all target cycles in the total number of power frequency cycles and the sum is used as the partial discharge index of the switchgear under test. The larger the partial discharge index, the higher the frequency and energy of partial discharge, and the more severe the insulation fault of the switchgear. Conversely, the smaller the partial discharge index, the lower the frequency and energy of partial discharge, and the less severe the insulation fault of the switchgear.

[0082] According to the method for obtaining the partial discharge index described in steps S1-S3, the partial discharge index of a preset number of switchgear without insulation faults is obtained, and the maximum value among the partial discharge indices is recorded as the insulation fault threshold. If the partial discharge index of the switchgear under test is greater than the absolute fault threshold, a fault warning is issued for the large-scale substation under test. The host computer transmits the alarm signal to the audible and visual alarm, and the audible and visual alarm issues an insulation fault warning to remind the staff to carry out further inspection. Conversely, if the partial discharge index of the switchgear under test is less than or equal to the absolute fault threshold, no fault warning is issued.

[0083] It should be noted that the preset number is set manually. In this embodiment, the preset number is 10000. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0084] Based on the same inventive concept as the above method, this application embodiment also provides a rapid fault early warning system for a large-scale power distribution station, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described rapid fault early warning methods for a large-scale power distribution station.

[0085] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0086] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0087] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for rapid fault early warning in large-scale substations, characterized in that, The method includes the following steps: Multiple ultra-high frequency sensors are installed on the switchgear under test in a large-scale substation. The electromagnetic wave signal, its maximum amplitude and phase are collected from each ultra-high frequency sensor in each power frequency cycle. The ultra-high frequency sensor is denoted as sensor. The difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in each sensor within each power frequency cycle and the preset first phase and preset second phase is analyzed, and the interference coefficient of the electromagnetic wave signal in each sensor is determined in combination with the maximum amplitude. Under each power frequency cycle, compare the difference in the maximum amplitude between the electromagnetic wave signals of any two sensors, and combine the mean interference coefficient of the electromagnetic wave signals in all sensors to determine the amplitude deviation between the electromagnetic wave signals of any two sensors under each power frequency cycle. By analyzing the distance between any two sensors and combining it with the amplitude deviation, the comprehensive deviation of each power frequency cycle is determined, so as to select the target cycle from all power frequency cycles. The maximum amplitude of electromagnetic wave signals in all sensors within each target cycle is compared, and the maximum partial discharge signal within each target cycle is selected from the electromagnetic wave signals. The frequency domain of the maximum partial discharge signal is divided into multiple frequency intervals. By analyzing the energy of the maximum partial discharge signal in each frequency interval and the dispersion of the maximum amplitude of the electromagnetic wave signal in all sensors in each target period, the partial discharge energy of each target period is determined. Based on the partial discharge energy of all target cycles and the proportion of the number of all target cycles in the total number of power frequency cycles, the partial discharge index of the switchgear under test is determined, and fault early warning is provided for the switchgear under test in large-scale substations.

2. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The expression for the interference coefficient of the electromagnetic wave signal in each sensor is as follows: In the formula, F k min represents the interference coefficient of the electromagnetic wave signal in sensor k; k,t This represents the minimum difference between the phase corresponding to the maximum amplitude of the electromagnetic wave signal in sensor k under a power frequency period t and the preset first phase and preset second phase, respectively; A k,t represents the maximum amplitude of the electromagnetic wave signal in sensor k under power frequency cycle t; T represents the number of all power frequency cycles; norm[] represents the normalization function; γ represents a preset constant greater than 1.

3. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The expression for the amplitude deviation between the electromagnetic wave signals of any two sensors under each power frequency cycle is: In the formula, L represents the amplitude deviation between the electromagnetic wave signals of sensor i and sensor j within the power frequency cycle t; t This represents the average interference coefficient of electromagnetic wave signals in all sensors within a power frequency period t. This represents the difference in the maximum amplitude of the electromagnetic wave signal between sensor i and sensor j within the power frequency cycle t.

4. The method for rapid fault early warning in a large-scale substation as described in claim 3, characterized in that, The method for determining the comprehensive deviation of each power frequency cycle is as follows: Calculate the product of the amplitude deviation between the electromagnetic wave signals of any two sensors within each power frequency cycle and the distance between the corresponding sensors. The sum of the product results between all sensors within each power frequency cycle is taken as the comprehensive deviation for each power frequency cycle.

5. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The method for determining the target period is as follows: Calculate the mean of the comprehensive deviations of all power frequency cycles, and denot it as the mean deviation. The power frequency cycle corresponding to the comprehensive deviation being greater than or equal to the mean deviation is taken as the target cycle.

6. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The maximum partial discharge signal within each target period is the electromagnetic wave signal corresponding to the maximum value of the largest amplitude among all electromagnetic wave signals within each target period.

7. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The expression for the partial discharge energy of each target cycle is: H z Represents the partial discharge energy of the target period z; CV z This indicates the degree of dispersion of the maximum amplitude of all electromagnetic wave signals within the target period z; w z,n This represents the preset weight of the maximum partial discharge signal within the target period z in the frequency interval n, where w z,1 +w z,2 +w z,3 +w z,4 =1; E z,n N represents the energy of the maximum partial discharge signal within the frequency range during the target period z; z This represents the number of all frequency ranges of the maximum partial discharge signal within the target period z; ε represents a preset constant greater than 0.

8. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The method for determining the partial discharge index of the switchgear under test is as follows: Calculate the sum of the partial discharge energy of all target cycles, and multiply the product of the proportion of all target cycles in the total number of power frequency cycles and the sum as the partial discharge index of the switchgear under test.

9. The method for rapid fault early warning in a large-scale substation as described in claim 1, characterized in that, The method for providing fault early warning for switchgear under test in large-scale substations includes: According to the method for obtaining the partial discharge index, the partial discharge index of a preset number of switchgear without insulation faults is obtained. The maximum value among the partial discharge indices is recorded as the absolute fault threshold. If the partial discharge index of the switchgear under test is greater than the absolute fault threshold, a fault warning is issued for the large-scale substation under test; otherwise, no fault warning is issued.

10. A rapid fault early warning system for a large-scale substation, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for rapid fault early warning of a large-scale substation as described in any one of claims 1-9.

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