A detection method, device and system based on overvoltage influencing factors

Abstract

The application provides a detection method, device and system based on an overvoltage influencing factor, comprising: acquiring an actual overvoltage amplitude of a capacitor bank and a duration corresponding to the actual overvoltage amplitude; determining an influencing factor corresponding to the actual overvoltage amplitude according to the actual overvoltage amplitude, the duration and a preset factor prediction model, wherein the influencing factor is an influencing factor of generating the actual overvoltage amplitude; and outputting the influencing factor if a difference between the actual overvoltage amplitude and a target overvoltage amplitude is less than or equal to a preset difference threshold. The actual overvoltage amplitude and the duration are input into the preset factor prediction model, so that the influencing factor corresponding to the actual overvoltage amplitude is determined, and thus the influencing factor of generating the overvoltage can be accurately determined.

Description

Technical Field

[0001] This application relates to the technical field of detection methods for influencing factors, specifically to a detection method, device, and system based on overvoltage influencing factors. Background Technology

[0002] The increasing prevalence of clean energy generation, distributed power sources, and microgrids has increased the reactive power fluctuations in distribution network operation. To ensure the balance of reactive power in the system, frequent switching of reactive power equipment is required. Vacuum circuit breakers, with their excellent arc-extinguishing performance and high reliability, are suitable for frequent operation and are therefore widely used in 10kV power systems. However, due to the current-cutting phenomenon of vacuum circuit breakers, overvoltages generated when disconnecting parallel reactors can cause faults such as reactor phase-to-phase short circuits, reactor inter-turn insulation damage, and bus phase-to-phase short circuits. However, current technology cannot detect the factors affecting overvoltages, making it impossible for operators to perform corresponding maintenance, thus leading to the aforementioned faults such as reactor phase-to-phase short circuits, reactor inter-turn insulation damage, and bus phase-to-phase short circuits. Summary of the Invention

[0003] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a method, apparatus, and system for detecting overvoltage influencing factors, solving the problem in the prior art that it is impossible to detect factors affecting overvoltage.

[0004] According to one aspect of this application, a method for detecting overvoltage influencing factors is provided, comprising: acquiring the actual overvoltage amplitude of a capacitor bank and the duration corresponding to the actual overvoltage amplitude; determining the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, the duration, and a preset factor prediction model; wherein the influencing factors are those that generate the actual overvoltage amplitude; and outputting the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold.

[0005] In one embodiment, the method for establishing the preset factor prediction model includes: acquiring multiple detection sets and influencing factor sets; wherein, the detection sets include detected overvoltage amplitude and the duration corresponding to the detected overvoltage amplitude; calculating a cumulative contribution rate based on the detection sets and the influencing factor sets; if the cumulative contribution rate is greater than or equal to a preset contribution rate threshold, determining the influencing factor corresponding to the cumulative contribution rate as the influencing factor that generates the detected overvoltage amplitude; and establishing the preset factor prediction model based on the multiple detection sets and the influencing factors corresponding to each detection set.

[0006] In one embodiment, calculating the cumulative contribution rate based on the detection set and the influencing factor set includes: establishing a matrix set based on the matrix corresponding to the detection set and the matrix corresponding to the influencing factor set; wherein the matrix set includes the correspondence between each influencing factor in the influencing factor set and each detected overvoltage amplitude in the detection set and the duration corresponding to the detected overvoltage amplitude; standardizing the matrix set to obtain data results; calculating the covariance matrix of the matrix set; calculating a permutation matrix based on the covariance matrix and the eigenvectors corresponding to the matrix set; and calculating the cumulative contribution rate based on the permutation matrix and the data results.

[0007] In one embodiment, calculating the permutation matrix based on the covariance matrix and the eigenvectors corresponding to the matrix set includes: calculating eigenvalues ​​based on the covariance matrix; and arranging the eigenvectors corresponding to the matrix set according to the magnitude of the eigenvalues ​​to obtain the permutation matrix.

[0008] According to another aspect of this application, a detection device based on overvoltage influencing factors is provided, comprising: an acquisition module for acquiring the actual overvoltage amplitude of a capacitor bank and the duration corresponding to the actual overvoltage amplitude; a determination module for determining the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, the duration, and a preset factor prediction model; wherein the influencing factors are the factors that generate the actual overvoltage amplitude; and an output module for outputting the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold.

[0009] According to one aspect of this application, a detection system based on overvoltage influencing factors is provided, comprising: a capacitor bank including a plurality of first capacitors connected in parallel; a reactor bank including a plurality of reactors, each reactor electrically connected to each of the first capacitors; a parallel assembly including a resistor and a second capacitor connected in parallel to form the parallel assembly; a protection device connected in series with the parallel assembly to form a series assembly; wherein each of the series assemblies is connected in parallel with each reactor and each of the series assemblies is connected in series with each of the first capacitors, and the protection device is used to protect the capacitor bank; a switching assembly connected in series with each of the first capacitors; and a controller connected to the parallel assembly and connected in series with the capacitor bank, the controller being used to execute any of the above-described detection methods based on overvoltage influencing factors.

[0010] In one embodiment, the detection system based on overvoltage influencing factors further includes a fuse connected in parallel with the parallel component.

[0011] In one embodiment, the detection system based on overvoltage influencing factors further includes a zinc oxide device connected in series with the fuse and connected in parallel with the parallel assembly.

[0012] In one embodiment, the detection system based on overvoltage influencing factors further includes a driving component electrically connected to the capacitor bank, which receives the overvoltage when the capacitor bank generates an overvoltage.

[0013] In one embodiment, the detection system based on overvoltage influencing factors further includes a fan electrically connected to the drive component, the drive component being used to drive the fan to rotate.

[0014] According to another aspect of this application, a computer-readable storage medium is provided, the storage medium storing a computer program for performing any of the above-described detection methods based on overvoltage influencing factors.

[0015] According to another aspect of this application, an electronic device is provided, the electronic device comprising: a processor; a memory for storing processor-executable instructions; the processor being configured to perform any of the above-described detection methods based on overvoltage influencing factors.

[0016] This application provides a detection method, apparatus, and system based on overvoltage influencing factors, comprising: acquiring the actual overvoltage amplitude of a capacitor bank and the corresponding duration of the actual overvoltage amplitude; determining the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, duration, and a preset factor prediction model; wherein the influencing factors are those that generate the actual overvoltage amplitude; and outputting the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold. By inputting the actual overvoltage amplitude and duration into the preset factor prediction model, the influencing factors corresponding to the actual overvoltage amplitude are determined, thereby accurately identifying the influencing factors that generate overvoltage. Attached Figure Description

[0017] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0018] Figure 1 This is a schematic flowchart of a detection method based on overvoltage influencing factors provided in an exemplary embodiment of this application.

[0019] Figure 2 This is a flowchart illustrating a method for establishing a preset factor prediction model provided in an exemplary embodiment of this application.

[0020] Figure 3 This is a schematic diagram of the structure of a detection device based on overvoltage influencing factors provided in an exemplary embodiment of this application.

[0021] Figure 4 This is a schematic diagram of the structure of a detection device based on overvoltage influencing factors provided in another exemplary embodiment of this application.

[0022] Figure 5 This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in an exemplary embodiment of this application.

[0023] Figure 6 This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in another exemplary embodiment of this application.

[0024] Figure 7 This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in another exemplary embodiment of this application.

[0025] Figure 8 This is a structural diagram of an electronic device provided in an exemplary embodiment of this application. Detailed Implementation

[0026] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0027] Figure 1 This is a schematic flowchart of a detection method based on overvoltage influencing factors provided in an exemplary embodiment of this application. Figure 1 As shown, the detection methods based on overvoltage influencing factors include:

[0028] Step 110: Obtain the actual overvoltage amplitude of the capacitor bank and the duration corresponding to the actual overvoltage amplitude.

[0029] When the actual overvoltage amplitude generated by the capacitor bank is detected, the actual overvoltage amplitude and the duration of the actual overvoltage amplitude are collected.

[0030] Step 120: Based on the actual overvoltage amplitude, duration, and preset factor prediction model, determine the influencing factors corresponding to the actual overvoltage amplitude, where the influencing factors are the factors that generate the actual overvoltage amplitude.

[0031] The actual overvoltage amplitude and duration are input into a preset factor prediction model to obtain the influencing factors corresponding to both the actual overvoltage amplitude and its duration. These influencing factors are the main factors that cause the actual overvoltage amplitude, i.e., the factors that lead to its occurrence. These influencing factors include current throttling during vacuum circuit breaker interruption, reignition effect, resonance between the reactor and stray capacitance, system parameters, and reactor parameters. When a vacuum circuit breaker disconnects a reactor, an overvoltage phenomenon occurs between the contacts at the instant the arc of the circuit breaker is extinguished. This is known as the Transient Recovery Voltage (TRV). If the TRV is greater than the insulation voltage between the contacts, the vacuum gap will break down, causing reignition. This results in a high-frequency current flowing through the circuit breaker. When the high-frequency current crosses zero, the TRV will reappear. When the TRV is higher than the insulation voltage [16,18], reignition will occur again. This phenomenon will repeat repeatedly. During this process, as the distance between the vacuum circuit breaker contacts increases, the insulation voltage between the contacts also gradually increases, eventually making the insulation voltage greater than the TRV, extinguishing the arc, and disconnecting the circuit breaker. This process can be seen as a game between the TRV and the insulation voltage between the contacts: when the TRV is greater than the insulation voltage, the arc reignites, and an increase in the number of reignitions may lead to a higher overvoltage; conversely, the arc extinguishes.

[0032] Step 130: If the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to the preset difference threshold, then output the influencing factors.

[0033] If the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is small, it indicates that the actual overvoltage amplitude is generated by the influencing factor identified above, and therefore the influencing factor is directly output. If the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is large, it indicates that the actual overvoltage amplitude is not generated by the influencing factor, and therefore the actual overvoltage amplitude should be input into the preset factor prediction model to re-determine the influencing factor.

[0034] This application provides a detection method based on overvoltage influencing factors, comprising: acquiring the actual overvoltage amplitude of a capacitor bank and the corresponding duration of the actual overvoltage amplitude; determining the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, duration, and a preset factor prediction model; wherein the influencing factors are those that generate the actual overvoltage amplitude; and outputting the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold. By inputting the actual overvoltage amplitude and duration into the preset factor prediction model, the influencing factors corresponding to the actual overvoltage amplitude are determined, thereby accurately identifying the influencing factors that generate overvoltage.

[0035] Figure 2 This is a flowchart illustrating a method for establishing a preset factor prediction model provided in an exemplary embodiment of this application. Figure 2 As shown, the methods for establishing a pre-defined factor prediction model may include:

[0036] Step 140: Obtain multiple detection sets and influencing factor sets, wherein the detection sets include the detected overvoltage amplitude and the duration corresponding to the detected overvoltage amplitude.

[0037] Assuming there are m factors affecting the amplitude and duration of overvoltage, the matrix representing these influencing factors is defined as O(V,T)=[F1,F2,......F m ], where V and T represent the overvoltage multiple and the corresponding duration, respectively; F i (i = 1, 2, ... N) indicates the column vector of the i-th influencing factor, with a length of N.

[0038] The relationships among the aforementioned influencing factors are analyzed to ensure their independence. This can be achieved through cluster analysis to test independence. If the influencing factors are mutually independent, prediction can be made; otherwise, correlation elimination is required. Once the factors are independent, principal component analysis can be used to identify the principal factors among the numerous influencing factors.

[0039] Among them, F nm In this context, n represents n samples and m represents m influencing factors.

[0040] Step 150: Calculate the cumulative contribution rate based on the detection set and the influencing factor set.

[0041] Based on the detection set and the set of influencing factors, the cumulative contribution rate is calculated. The main influencing factors corresponding to the detected overvoltage amplitude are then determined using the cumulative contribution rate.

[0042] Step 160: If the cumulative contribution rate is greater than or equal to the preset contribution rate threshold, then the influencing factor corresponding to the cumulative contribution rate is determined to be the influencing factor that generates the detected overvoltage amplitude.

[0043] If the cumulative contribution rate is greater than or equal to the preset contribution rate threshold, which can be set to 85%, then the influencing factors corresponding to the cumulative contribution rate are the influencing factors that generate the detected overvoltage amplitude.

[0044] Step 170: Based on the multiple detection sets and the influencing factors corresponding to each detection set, establish a preset factor prediction model.

[0045] A pre-defined factor prediction model can be established based on the correspondence between multiple detection sets and the influencing factors corresponding to each detection set. Alternatively, a pre-defined factor prediction model can be established based on multiple detection sets, the correspondence between the influencing factors corresponding to each detection set, and an artificial neural network. An artificial neural network (ANN) can mimic the structure and function of biological neural networks to predict specific problems with unpredictable functional expressions. Its computational principle is that the neural network consists of three parts: an input layer, hidden layers, and an output layer. Each layer is composed of numerous interconnected nodes, each representing a specific output function. Data is input from the input layer, processed by the nodes, and the result is then used as the input to the next layer and propagated through the nodes. The nodes mimic the function of biological signals propagating in neurons, ultimately outputting a predicted value. The predicted value is compared with a set threshold, and the deviation between the predicted value and the set threshold is defined as a loss function. The magnitude and sign of the loss function are used to adjust the simulated neuron nodes, adjusting the power-saving function of the neural network. Combined with gradient descent or conjugate descent methods, a global search is performed on the prediction results to achieve the prediction result with the minimum prediction deviation.

[0046] In one embodiment, after establishing a preset factor prediction model, the method for establishing the preset factor prediction model may include: obtaining training samples, generating verification results based on the training samples and the preset factor prediction model, and determining that the preset factor prediction model has been successfully established if the verification results match the target results.

[0047] In addition to evaluating the accuracy of the prediction results using relative error, the effectiveness of the prediction results can also be evaluated: based on the simulation values, an effectiveness evaluation index e of the prediction model is constructed. i as follows:

[0048]

[0049] In the formula, This is the predicted overvoltage value, V. i T ie represents the simulated values ​​(i.e., training samples). Vi ,e Ti The indicator mainly represents the deviation of the prediction results; the smaller the value, the more accurate the prediction.

[0050] In one embodiment, step 150 is specifically implemented as follows: based on the matrix corresponding to the detection set and the matrix corresponding to the influencing factor set, a matrix set is established, wherein the matrix set includes the correspondence between each influencing factor in the influencing factor set and each detected overvoltage amplitude in the detection set or in which the detected overvoltage amplitude is located, as well as the duration corresponding to the detected overvoltage amplitude; the matrix set is standardized to obtain data results; the covariance matrix of the matrix set is calculated; based on the covariance matrix and the eigenvector corresponding to the matrix set, a permutation matrix is ​​obtained; and based on the permutation matrix and the data results, the cumulative contribution rate is calculated.

[0051] Assuming there are m factors affecting the amplitude and duration of overvoltage, then F is defined as the matrix of influencing factors.

[0052] O(V,T)=[F1,F2,......F m ];

[0053] In the formula, V and T represent the overvoltage multiple and the corresponding duration, respectively; F i (i = 1, 2, ... N) indicates the column vector of the i-th influencing factor, with a length of N.

[0054] The relationships among the aforementioned influencing factors are analyzed to ensure their independence. This can be achieved through cluster analysis to test independence. If the influencing factors are mutually independent, prediction can be made; otherwise, correlation elimination is required. Once the factors are independent, principal component analysis can be used to identify the principal factors among the numerous influencing factors.

[0055] Among them, F nm In this context, n represents n samples and m represents m influencing factors.

[0056] The matrix set is standardized to obtain a data result, the goal of which is to reduce the mean of the matrix set to zero. The covariance matrix of the matrix set is calculated. Based on the covariance matrix and the corresponding eigenvectors of the matrix set, the permutation matrix is ​​obtained. Then, the cumulative contribution rate is calculated using the permutation matrix and the contribution rate formula. Specifically, the contribution rate α of each eigenvalue is calculated using the following formula. i and cumulative contribution rate β i :

[0057]

[0058] Where, λi Eigenvalues.

[0059] In one embodiment, step 150 is specifically implemented as follows: calculating eigenvalues ​​based on the covariance matrix; and arranging the eigenvectors corresponding to the matrix set according to the magnitude of the eigenvalues ​​to obtain an arrangement matrix.

[0060] Based on the covariance matrix, the eigenvalue λ is calculated. i The eigenvectors are arranged according to the magnitude of their eigenvalues ​​to obtain a permutation matrix. Then, based on the permutation matrix and the data results, the dimensionality-reduced data is calculated.

[0061] The resulting data is then normalized to form a factor matrix, and the principal components Z after PCA (principal component analysis) are:

[0062]

[0063] Z = {Z1, Z2, ... Z} p} represents p (p≤m) principal components, y ij Let be the coefficient of the j-th factor in the i-th principal component.

[0064] Figure 3 This is a schematic diagram of the structure of a detection device based on overvoltage influencing factors provided in an exemplary embodiment of this application. Figure 3 As shown, the detection device 20 based on overvoltage influencing factors includes: an acquisition module 201, used to acquire the actual overvoltage amplitude of the capacitor bank and the duration corresponding to the actual overvoltage amplitude; a determination module 202, used to determine the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, duration and a preset factor prediction model, wherein the influencing factors are the factors that generate the actual overvoltage amplitude; and an output module 203, used to output the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold.

[0065] This application provides a detection device based on overvoltage influencing factors, comprising: an acquisition module 201 acquiring the actual overvoltage amplitude of a capacitor bank and the corresponding duration of the actual overvoltage amplitude; a determination module 202 determining the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, duration, and a preset factor prediction model, wherein the influencing factors are those that generate the actual overvoltage amplitude; and an output module 203 outputting the influencing factors if the difference between the actual overvoltage amplitude and the target overvoltage amplitude is less than or equal to a preset difference threshold. By inputting the actual overvoltage amplitude and duration into the preset factor prediction model, the influencing factors corresponding to the actual overvoltage amplitude are determined, thereby accurately identifying the influencing factors that generate overvoltage.

[0066] Figure 4 This is a schematic diagram of the structure of a detection device based on overvoltage influencing factors provided in another exemplary embodiment of this application. Figure 4 As shown, the detection device 20 based on overvoltage influencing factors may include: a set acquisition unit 204, used to acquire multiple detection sets and influencing factor sets, wherein the detection sets include the detected overvoltage amplitude and the duration corresponding to the detected overvoltage amplitude; a calculation unit 205, used to calculate the cumulative contribution rate based on the detection sets and the influencing factor sets; a determination unit 206, used to determine the influencing factor corresponding to the cumulative contribution rate as the influencing factor that generates the detected overvoltage amplitude if the cumulative contribution rate is greater than or equal to a preset contribution rate threshold; and an establishment unit 207, used to establish the preset factor prediction model based on the multiple detection sets and the influencing factors corresponding to each detection set.

[0067] In one embodiment, the calculation unit 205 may be specifically configured to: establish a matrix set based on the matrix corresponding to the detection set and the matrix corresponding to the influencing factor set; wherein the matrix set includes the correspondence between each influencing factor in the influencing factor set and each detected overvoltage amplitude in the detection set and the duration corresponding to the detected overvoltage amplitude; perform data standardization on the matrix set to obtain data results; calculate the covariance matrix of the matrix set; obtain a permutation matrix based on the covariance matrix and the eigenvector corresponding to the matrix set; and calculate the cumulative contribution rate based on the permutation matrix and the data results.

[0068] In one embodiment, the calculation unit 205 may be specifically configured to: calculate eigenvalues ​​based on the covariance matrix; and arrange the eigenvectors corresponding to the matrix set according to the magnitude of the eigenvalues ​​to obtain the permutation matrix.

[0069] Figure 5 This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in an exemplary embodiment of this application. Figure 5As shown, the overvoltage-based detection system includes: a capacitor bank 11, a reactor bank 12, a parallel assembly 13, a protection device 14, a switching assembly 15, and a controller 16. The capacitor bank 11 includes multiple first capacitors 111 connected in parallel. The reactor bank 12 includes multiple reactors 121, each reactor 121 electrically connected to each first capacitor 111. The parallel assembly 13 includes a resistor 131 and a second capacitor 132 connected in parallel to form a parallel connection. The parallel assembly 13 and the protection device 14 are connected in series to form a series assembly, wherein each series assembly is connected in parallel with each reactor 121 and each series assembly is connected in series with each first capacitor 111. The protection device 14 is used to protect the capacitor bank 11. The switching assembly 15 is connected in series with each first capacitor 111. The controller 16 is connected to the first parallel assembly 13. The controller 16 is connected in series with each capacitor bank 11. The controller 16 is used to execute any of the above-mentioned detection methods based on overvoltage influence factors.

[0070] This application provides a detection system based on overvoltage influencing factors, comprising: a capacitor bank, a reactor bank, a parallel assembly, a protection device, a switching assembly, and a controller. The capacitor bank includes multiple first capacitors connected in parallel. The reactor bank includes multiple reactors, each electrically connected to each first capacitor. The parallel assembly includes a resistor and a second capacitor connected in parallel to form the parallel assembly. The protection device is connected in series with the parallel assembly to form a series assembly. Each series assembly is connected in parallel with each reactor, and each series assembly is connected in series with each first capacitor. The protection device protects the capacitor bank. The switching assembly is connected in series with each first capacitor. The controller is connected to the first parallel assembly and also connected in series with the capacitor bank. The controller executes any of the above-described detection methods based on overvoltage influencing factors. By inputting the actual overvoltage amplitude and duration into a preset factor prediction model, the influencing factors corresponding to the actual overvoltage amplitude are determined, thereby accurately identifying the influencing factors that cause overvoltage.

[0071] Figure 6 This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in another exemplary embodiment of this application. Figure 6 As shown, the detection system based on overvoltage influencing factors may also include a fuse 17, which is connected in parallel with the parallel component 13.

[0072] When an overvoltage occurs in the capacitor bank, the overvoltage first flows to the protection device 14. If the protection device 14 fails, it can absorb energy through the fuse 17 to protect the capacitor bank.

[0073] Figure 7This is a schematic diagram of the structure of a detection system based on overvoltage influencing factors provided in another exemplary embodiment of this application. Figure 7 As shown, the detection system based on overvoltage influencing factors may also include a zinc oxide device 18, which is connected in series with the fuse 17 and in parallel with the parallel component 13.

[0074] If the fuse 17 is also unable to protect the capacitor bank, the energy can be absorbed by the zinc oxide device 18.

[0075] In one embodiment, the detection system based on overvoltage influencing factors may further include a driving component electrically connected to the capacitor bank, which receives the overvoltage when the capacitor bank generates an overvoltage.

[0076] The driving component can be a motor, etc.

[0077] In one embodiment, the detection system based on overvoltage influencing factors may further include a fan, which is electrically connected to a drive component, which drives the fan to rotate.

[0078] Figure 8 A block diagram of an electronic device according to an embodiment of this application is illustrated.

[0079] like Figure 8 As shown, the electronic device 10 includes one or more processors 11 and memory 12.

[0080] The processor 11 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0081] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may execute the program instructions to implement the overvoltage-based detection method and / or other desired functions described in the various embodiments of this application above. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0082] In one example, the electronic device 10 may also include an input device 13 and an output device 14, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0083] When the electronic device is a standalone device, the input device 13 can be a communication network connector for receiving the collected input signals from the first device and the second device.

[0084] In addition, the input device 13 may also include, for example, a keyboard, a mouse, etc.

[0085] The output device 14 can output various information to the outside, including determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0086] Of course, for the sake of simplicity, Figure 8 Only some of the components of the electronic device 10 relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 10 may include any other suitable components depending on the specific application.

[0087] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0088] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A detection method based on overvoltage influencing factors, characterized in that, include: Obtain the actual overvoltage amplitude of the capacitor bank and the duration corresponding to the actual overvoltage amplitude; Based on the actual overvoltage amplitude, the duration, and a preset factor prediction model, the influencing factors corresponding to the actual overvoltage amplitude are determined; wherein, the influencing factors are those that generate the actual overvoltage amplitude; the method for establishing the preset factor prediction model includes: Multiple detection sets and influencing factor sets are obtained; wherein, the detection set includes the detected overvoltage amplitude and the duration corresponding to the detected overvoltage amplitude; The cumulative contribution rate is calculated based on the detection set and the influencing factor set. If the cumulative contribution rate is greater than or equal to a preset contribution rate threshold, then the influencing factor corresponding to the cumulative contribution rate is determined to be the influencing factor that generates the detected overvoltage amplitude; and Based on the multiple detection sets and the influencing factors corresponding to each detection set, a preset factor prediction model is established; and If the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is less than or equal to a preset difference threshold, then the influencing factor is output. If the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is greater than a preset difference threshold, the actual overvoltage amplitude and the duration are input into the preset factor prediction model to determine the influencing factor again.

2. The detection method based on overvoltage influencing factors according to claim 1, characterized in that, The calculation of the cumulative contribution rate based on the detection set and the influencing factor set includes: A matrix set is established based on the matrix corresponding to the detection set and the matrix corresponding to the influencing factor set; wherein, the matrix set includes the correspondence between each influencing factor in the influencing factor set and each detected overvoltage amplitude in the detection set and the duration corresponding to the detected overvoltage amplitude; The matrix set is standardized to obtain the data results; Calculate the covariance matrix of the matrix set; The permutation matrix is ​​calculated based on the covariance matrix and the eigenvectors corresponding to the matrix set; and The cumulative contribution rate is calculated based on the permutation matrix and the data results.

3. The detection method based on overvoltage influencing factors according to claim 2, characterized in that, The step of calculating the permutation matrix based on the covariance matrix and the eigenvectors corresponding to the matrix set includes: Based on the covariance matrix, the eigenvalues ​​are calculated; and The eigenvectors corresponding to the matrix set are arranged according to the magnitude of the eigenvalues ​​to obtain the permutation matrix.

4. A detection device based on overvoltage influencing factors, characterized in that, include: The acquisition module is used to acquire the actual overvoltage amplitude of the capacitor bank and the duration corresponding to the actual overvoltage amplitude; A determination module is used to determine the influencing factors corresponding to the actual overvoltage amplitude based on the actual overvoltage amplitude, the duration, and a preset factor prediction model; wherein the influencing factors are those that generate the actual overvoltage amplitude; the method for establishing the preset factor prediction model includes: acquiring multiple detection sets and influencing factor sets; wherein the detection sets include detected overvoltage amplitudes and the durations corresponding to the detected overvoltage amplitudes; calculating a cumulative contribution rate based on the detection sets and the influencing factor sets; if the cumulative contribution rate is greater than or equal to a preset contribution rate threshold, then determining the influencing factor corresponding to the cumulative contribution rate as an influencing factor that generates the detected overvoltage amplitude; and establishing the preset factor prediction model based on the multiple detection sets and the influencing factors corresponding to each detection set; and The output module is used to output the influencing factor if the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is less than or equal to a preset difference threshold. The detection device is also used to input the actual overvoltage amplitude and the duration into the preset factor prediction model if the difference between the actual overvoltage amplitude and the target overvoltage amplitude corresponding to the influencing factor is greater than a preset difference threshold, and to determine the influencing factor again.

5. A detection system based on overvoltage influencing factors, characterized in that, include: A capacitor bank, the capacitor bank comprising a plurality of first capacitors, each of the first capacitors being connected in parallel; A reactor bank, the reactor bank comprising a plurality of reactors, each reactor being electrically connected to each of the first capacitors; a parallel assembly, the parallel assembly comprising a resistor and a second capacitor, the resistor and the second capacitor being connected in parallel to form the parallel assembly; A protection device is connected in series with the parallel assembly to form a series assembly; wherein each of the series assemblies is connected in parallel with each reactor and each of the series assemblies is connected in series with each first capacitor, and the protection device is used to protect the capacitor bank; a switching assembly is connected in series with each first capacitor; The controller is connected to the parallel component and is connected in series with the capacitor bank. The controller is used to execute the detection method based on overvoltage influencing factors as described in any one of claims 1-3.

6. The detection system based on overvoltage influencing factors according to claim 5 further includes a fuse, wherein the fuse is connected in parallel with the parallel component.

7. The detection system based on overvoltage influencing factors according to claim 6 further includes a zinc oxide device, wherein the zinc oxide device is connected in series with the fuse and the zinc oxide device is connected in parallel with the parallel assembly.

8. The detection system based on overvoltage influencing factors according to claim 7 further includes a driving component, the driving component being electrically connected to the capacitor bank, and the driving component receiving the overvoltage when the capacitor bank generates an overvoltage.

9. The detection system based on overvoltage influencing factors according to claim 8 further includes a fan, the fan being electrically connected to the driving component, the driving component being used to drive the fan to rotate.

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