Method and system for detecting closing resistance of circuit breaker in switching state of AC filter group

Abstract

The present invention provides a method and system for detecting the switching state of the closing resistor of an AC filter group circuit breaker, which belongs to the technical field of high-voltage AC circuit breakers. The method comprises: loading the closing current recording data of the filter group circuit breaker switching process; performing wavelet decomposition on the closing current recording data of the circuit breaker, obtaining the singular points in the closing current recording data of each layer of the circuit breaker as the starting points of each transient process during the closing resistor switching process of the circuit breaker; performing TLS-ESPRIT decomposition on the recording data of each transient process to obtain the amplitude and attenuation factor of the DC mode, and establishing a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor; fitting two amplitude-resistance curves and two attenuation factor-resistance curves according to the corresponding relationship, as well as the curve function and inverse function of each curve; substituting the amplitude and attenuation factor into the inverse function of the corresponding DC component to calculate the resistance value, and further calculating the number of flashover resistors based on the average resistance value, so as to understand whether a flashover fault occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of high-voltage AC circuit breakers, and in particular to a method and system for detecting closing resistance of an AC filter group circuit breaker in a switched state. Background Art

[0002] In HVDC transmission systems, nonlinear components such as converter valves in converter stations consume significant amounts of reactive power during operation, accounting for 30% to 60% of the DC transmission power. Furthermore, in AC systems, these power consumption also generates a series of harmonics, distorting the voltage and current waveforms of the AC system. Therefore, converter stations are equipped with large-capacity AC filter banks to filter harmonics and compensate for reactive power. The filter bank circuit breakers are opened and closed in real time according to system operating conditions, enabling and disabling the filter bank.

[0003] Compared to conventional line circuit breakers, filter bank circuit breakers operate more frequently and are subject to the unique operating conditions of superimposed AC and DC surge voltages during operation. After interrupting the load current, a capacitive DC voltage is applied to one side of the filter bank breaker, while the AC bus voltage is applied to the other. In the most demanding cases, the voltages on both sides are at peak values ​​and have opposite polarities. Currently, most filter bank breakers incorporate a closing resistor to limit overvoltages and inrush currents caused by the filter bank switching. During the circuit breaker's opening and closing operations, the insulating rod simultaneously actuates the moving contacts of the main and resistor switches. The closing resistor dampens the electromagnetic transients caused by switching the filter bank. Due to the frequent switching of filter bank breaker circuit breakers and their long-term operation under harsh operating conditions, the combined electrical and thermal stresses of the closing resistor often lead to cracking, damage, and explosion. Frequent failures of AC filter bank breaker circuit breakers can trigger protective device activation at best, or even cause widespread power outages, resulting in significant economic losses. Therefore, it is necessary to monitor the status of the filter bank breaker's closing resistor in real time during the switching process.

[0004] When a filter group circuit breaker with a closing resistor is closed, the busbar voltage and current waveform data will reflect at least two transient processes: ① The filter group circuit breaker resistor contacts close, connecting the closing resistor to the system and causing the first closing transient; ② The filter group circuit breaker main contacts close, short-circuiting the closing resistor and removing it from the system, causing the second closing transient. If the closing resistor of the filter group circuit breaker fails during the commissioning phase, such as a flashover failure in the closing resistor string, a new transient process will be superimposed on the first transient process. The starting times of different transient processes do not overlap in the time series. At the same time, the starting times of transient processes are reflected in the filter group busbar voltage and current waveform data as singular points. Depending on the severity of the transient process, the corresponding singular points in the waveform change will vary in the degree of waveform abruptness.

[0005] Research on the operating status of filter bank circuit breaker closing resistors is limited. Currently, most methods rely on manual analysis of closing current and closing voltage waveforms after filter station protection is activated, combined with X-ray detection methods to perform on-site testing of filter bank circuit breaker closing resistors. In these cases, closing resistor device failures can gradually develop into more serious faults over long-term operation, preventing real-time monitoring of the circuit breaker closing resistor status. Furthermore, existing methods are labor-intensive, inefficient, and time-sensitive. Summary of the Invention

[0006] In view of this, the present invention provides a method and system for detecting the closing resistance of an AC filter group circuit breaker in the switching state, which solves the problems of poor real-time performance, low detection efficiency and high labor cost in traditional filter group circuit breaker closing resistance detection.

[0007] The technical solution adopted by the embodiment of the present invention to solve the technical problem is:

[0008] A method for detecting closing resistance of a circuit breaker in a switched state of an AC filter group, characterized by comprising:

[0009] Step S1, loading the closing current recording data of the filter bank circuit breaker switching process;

[0010] Step S2, performing wavelet decomposition on the circuit breaker closing current recording data to obtain singular points in the circuit breaker closing current recording data of each layer as starting points of each transient process during the circuit breaker closing resistance input process;

[0011] Step S3, performing TLS-ESPRIT decomposition on the recorded data of each transient process to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and establishing a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process;

[0012] Step S4, fitting amplitude-resistance curves corresponding to the two DC components and attenuation factor-resistance curves corresponding to the two DC components based on the corresponding relationship between the amplitude, attenuation factor, and the actual resistance value of the closing resistor actually put into the system during the transient process, and further fitting a curve function and a corresponding inverse function of each curve;

[0013] Step S5, when performing closing resistance detection in the circuit breaker switching state, the amplitude and attenuation factor of the DC mode are analyzed in real time based on the circuit breaker closing current data, the amplitude and attenuation factor are substituted into the inverse function of the corresponding DC component to calculate the resistance value, and the number of flashover resistors during the closing resistance switching process is further calculated based on the average resistance value, so as to understand whether a flashover fault occurs in the resistor during operation.

[0014] Preferably, the step S2 of performing wavelet decomposition on the circuit breaker closing current recording data to obtain singular points in each layer of current recording data as starting points of each transient process during the circuit breaker closing resistance input process includes:

[0015] Step S21, defining a decomposition low-pass filter h, a decomposition high-pass filter g, a decomposition layer number J and a threshold T;

[0016] Step S22, using wavelet basis function to perform J-layer wavelet decomposition on the circuit breaker closing current recording data {f[n]}, and obtain the wavelet coefficients of each layer k is the j-th level index;

[0017] Step S23, further processing the wavelet decomposition coefficients obtained in step S22 with a threshold value, that is, for those that meet of make

[0018] Step S24: for the wavelet decomposition detail coefficients J≥2, a hard threshold of 1e is adopted. -4 The modulus maximum detection method is used to obtain the singular point in the current recording data and detect The modulus maximum point, the modulus maximum point criterion is:

[0019]

[0020] and

[0021] Preferably, step S3 performs TLS-ESPRIT decomposition on the recorded data of each transient process to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and establishes a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process, including:

[0022] In step S31, the TLS-ESPRIT algorithm is used to decompose the model to the order P. The signal model x(n) of the current signal waveform at the nth sampling moment is expressed as:

[0023]

[0024] Where: T s is the sampling period. Since the sampled signal is a real signal, the model order P is twice the real sinusoidal component signal actually contained in the signal; a p represents the amplitude of the pth frequency component; φ p represents the initial phase of the pth frequency component; ω p represents the angular frequency of the pth frequency component; σ p Represents the attenuation factor of the pth frequency component; ω(n) represents Gaussian white noise with zero mean;

[0025] Step S32, define c p and signal pole z p , simplified model x(n):

[0026]

[0027] Step S33, the discrete data of the circuit breaker closing current recording data is combined into X N×M The HANKEL matrix is:

[0028]

[0029] Wherein: L is the signal length of the circuit breaker closing current recording data, N is the length of the window function, M is the width of the window function, L>P; M>P; L+M-1=N; L×1 / 4≤M≤L×1 / 3;

[0030] Step S34, perform singular value decomposition on the matrix X and rearrange the matrix in descending order of singular values ​​to obtain the expression:

[0031]

[0032] Where U is a left singular matrix; the Σ matrix is ​​a diagonal matrix, and the diagonal elements of Σ are the singular values ​​q1, q2, q3, ...q of the matrix X. p ,…q max , and the singular values ​​are arranged in descending order, V is a right singular matrix, and the superscript H represents the conjugate transpose; Σ s is a diagonal matrix consisting of the largest P singular values ​​of the matrix X. The threshold for determining the largest P singular values ​​is taken as 1e -4 , the model order is P, Σ n It is the diagonal matrix composed of the remaining singular values ​​of matrix X; U s is the matrix U divided according to the largest P singular values, U n is the matrix composed of the remaining column vectors of matrix U, V H is the conjugate transpose of the right singular matrix V; V s is the matrix V divided according to the largest P singular values, is the matrix V s The conjugate transposed matrix, V n is the matrix composed of the remaining column vectors of matrix V, V n H is the matrix V n The conjugate transpose of

[0033] Step S35, let V1 and V2 represent V sDelete the last row and the first row of the matrix to get a new matrix; construct the matrix [V1, V2], and perform singular value decomposition on [V1, V2] to get matrices R, A, and Q:

[0034] [V1,V2]=RAQ H

[0035] Where R is the left singular matrix; A is the diagonal matrix; Q is the right singular matrix, Q H is the conjugate transposed matrix of matrix Q;

[0036] Decompose the Q matrix into 4 P×P order matrices Q 11 , Q 12 , Q 21 , Q 22 :

[0037]

[0038] Then the rotation operator φ=-Q 12 Q 22 -1 ;

[0039] By rotating the eigenvalue λ of the operator φ p (p=1,2,…,P) Estimate the frequency ω of each component in the signal p , attenuation factor σ p :

[0040]

[0041] Where, for N-point sampling signals, the sampling signal sequence is x(n), and we have:

[0042]

[0043] Using the least squares method, we can solve the vector c=(λ T λ) -1 λ T Y, and then find the amplitude a of each component in the signal p and phase φ p :

[0044] a p =2|c p |,(p=1,2,...,P)

[0045] φ p =arg(c p ),(p=1,2,...,P).

[0046] Preferably, the step S4 includes:

[0047] Step S41, select the amplitude a corresponding to the two DC components p and the attenuation factor σ p According to the corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor in the transient process, the resistance value is the horizontal axis and the amplitude a is the p and the attenuation factor σ p As the vertical axis, draw the amplitude-resistance relationship point diagram and the attenuation factor-resistance relationship point diagram respectively, and then further fit the amplitude-resistance curve function f corresponding to the DC component 1 A1 And attenuation factor-resistance curve function f Σ1 , and the amplitude-resistance curve function f corresponding to the DC component 2 A2 And attenuation factor-resistance curve function f Σ2 ;

[0048] Step S42, find out the function f A1 、Function f Σ1 、Function f A2 and function f Σ2 The inverse function of function function and function

[0049] Preferably, step S5 includes:

[0050] Step S51, when performing closing resistance detection during the circuit breaker switching process, the amplitudes a1 and a2 and attenuation factors σ1 and σ2 corresponding to the two DC components are analyzed in real time based on the circuit breaker closing current data;

[0051] Step S52: Substitute a1, a2, σ1, and σ2 into the corresponding inverse functions to calculate the corresponding resistance value and the average resistance value R:

[0052]

[0053]

[0054] R=(R A1 +R Σ1 +R A2 +R Σ2 )×1 / 4

[0055] Step S53, calculating the number K of flashover resistors in the closing resistance during the current circuit breaker switching process according to the resistance mean R:

[0056]

[0057] Where R0 is the closing resistance, r is the resistance of the single-chip resistor, and K is obtained by rounding down.

[0058] Among them, when K is less than 1, the closing resistance is normal; when K is greater than or equal to 1 and less than 3, the closing resistance is abnormal; when K is greater than or equal to 3, a flashover fault occurs in the closing resistance.

[0059] The present invention also provides a system for detecting closing resistance of an AC filter group circuit breaker in a switched state, which is used to execute the aforementioned method for detecting closing resistance of an AC filter group circuit breaker in a switched state.

[0060] As can be seen from the above technical solution, the method and system for detecting the closing resistance of the circuit breaker in the switching state of the AC filter group provided by the embodiment of the present invention first loads the closing current recording data of the filter group circuit breaker switching process; performs wavelet decomposition on the closing current recording data of the circuit breaker, obtains the singular points in the closing current recording data of each layer of the circuit breaker as the starting points of each transient process during the circuit breaker closing resistance switching process; performs TLS-ESPRIT decomposition on the recording data of each transient process, obtains the amplitude and attenuation factor of the DC mode in the decomposition result, and establishes a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistance actually switched into the system during the transient process; according to The corresponding relationship between the amplitude, attenuation factor, and the actual resistance of the closing resistor in the transient process is calculated, and the amplitude-resistance curves corresponding to the two DC components and the attenuation factor-resistance curves corresponding to the two DC components are fitted, and the curve function and the corresponding inverse function of each curve are further fitted. When performing closing resistance detection in the circuit breaker switching state, the amplitude and attenuation factor of the DC mode are analyzed in real time based on the circuit breaker closing current data, and the amplitude and attenuation factor are substituted into the inverse function of the corresponding DC component to calculate the resistance. The number of flashover resistors during the closing resistance switching process is further calculated based on the average resistance value, thereby understanding whether the resistor has a flashover fault during operation. The solution of the present invention solves the problems of poor real-time performance, low detection efficiency, and high labor cost of closing resistance detection of traditional filter group circuit breakers. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a flow chart of the method for detecting the closing resistance of an AC filter group circuit breaker in the switched state of the present invention.

[0062] Figure 2 An example of the results of the Dmey wavelet 5-layer decomposition of the bus current of the filter group.

[0063] Figure 3 This is an example diagram of the interface for detecting singular points in transient waveforms of circuit breaker using a filter bank based on the maximum modulus of wavelet decomposition.

[0064] Figure 4 Schematic diagram of the TLS-ESPRIT decomposition process for filter bank circuit breaker current transient data.

[0065] Figure 5 The curve of the DC component attenuation factor change under different closing resistance values ​​is shown in the figure.

[0066] Figure 6 The curve of the DC component amplitude change under different closing resistance values ​​is shown in the figure.

[0067] Figure 7 This is a schematic diagram of the equipment structure of the hardware operating environment of the AC filter group circuit breaker switching state closing resistance detection equipment. DETAILED DESCRIPTION

[0068] The technical solutions and technical effects of the present invention are further described in detail below with reference to the accompanying drawings of the present invention.

[0069] The present invention designs different resistance values ​​according to the factory value R0 of the closing resistor in a simulation environment, simulates the closing current during the switching process, obtains the recorded wave data, and performs analysis based on the recorded wave. Figure 1 As shown, the present invention provides a method for detecting the closing resistance of an AC filter group circuit breaker in a switched state, the steps comprising:

[0070] Step S1, loading the closing current recording data of the filter bank circuit breaker switching process;

[0071] Step S2, performing wavelet decomposition on the breaker closing current recording data, obtaining the singular points in the breaker closing current recording data of each layer as the starting points of each transient process during the circuit breaker closing resistance input process;

[0072] Step S3, performing TLS-ESPRIT decomposition on the recorded data of each transient process to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and establishing a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process;

[0073] Step S4, fitting amplitude-resistance curves corresponding to the two DC components and attenuation factor-resistance curves corresponding to the two DC components based on the corresponding relationship between the amplitude, attenuation factor, and the actual resistance value of the closing resistor actually put into the system during the transient process, and further fitting a curve function and a corresponding inverse function of each curve;

[0074] Step S5, when performing closing resistance detection in the circuit breaker switching state, the amplitude and attenuation factor of the DC mode are analyzed in real time based on the circuit breaker closing current data, the amplitude and attenuation factor are substituted into the inverse function of the corresponding DC component to calculate the resistance value, and the number of flashover resistors during the closing resistance switching process is further calculated based on the average resistance value, so as to understand whether a flashover fault occurs in the resistor during operation.

[0075] Among them, for the closing voltage and current signals of the filter group circuit breaker, the rate of change of the function is very large when the closing resistor is turned on, off, or a fault occurs (at the singular points of the signal), and the wavelet transform will have extreme values ​​at these points. Step S2 performs wavelet decomposition on the circuit breaker closing current recording data to obtain the singular points in each layer of current recording data as the starting points of each transient process during the circuit breaker closing resistor input process, including:

[0076] Step S21, defining a decomposition low-pass filter h, a decomposition high-pass filter g, a decomposition layer number J and a threshold T;

[0077] Step S22, using wavelet basis function to perform J-layer wavelet decomposition on the circuit breaker closing current recording data {f[n]}, and obtain the wavelet coefficients of each layer k is the j-th layer index; as an implementation method, Dmey wavelet can be selected as the wavelet basis function;

[0078] Step S23, further process the wavelet decomposition coefficients obtained in step S22 using a threshold value, that is, for those that meet of make

[0079] Step S24: for the wavelet decomposition detail coefficients J≥2, a hard threshold of 1e is adopted. -4 The modulus maximum detection method is used to obtain the singular point in the current recording data and detect The modulus maximum point, the modulus maximum point criterion is:

[0080]

[0081] The 5-layer wavelet decomposition coefficients are as follows Figure 2 The singular point detection process of the transient waveform of the circuit breaker based on the filter bank of the wavelet decomposition modulus maximum is shown in the figure. Figure 3 shown.

[0082] Preferably, refer to Figure 4 In step S3, the recorded data of each transient process is decomposed using TLS-ESPRIT to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process is established.

[0083] In step S31, the TLS-ESPRIT algorithm is used to decompose the model to the order P. The signal model x(n) of the current signal waveform at the nth sampling moment is expressed as:

[0084]

[0085] Where: T sis the sampling period. Since the sampled signal is a real signal, the model order P is twice the real sinusoidal component signal actually contained in the signal; a p represents the amplitude of the pth frequency component; φ p represents the initial phase of the pth frequency component; ω p represents the angular frequency of the pth frequency component; σ p Represents the attenuation factor of the pth frequency component; ω (n) represents Gaussian white noise with zero mean;

[0086] Step S32, define c p and signal pole z p , simplified model x(n):

[0087]

[0088] Step S33, the discrete data of the circuit breaker closing current recording data is combined into X N×M The HANKEL matrix is:

[0089]

[0090] Wherein: L is the signal length of the circuit breaker closing current recording data, N is the length of the window function, M is the width of the window function, L>P; M>P; L+M-1=N; L×1 / 4≤M≤L×1 / 3; in this embodiment, the width M of the window function is 1 / 3 of the signal length;

[0091] Step S34, perform singular value decomposition on the matrix X and rearrange the matrix in descending order of singular values ​​to obtain the expression:

[0092]

[0093] Where U is a left singular matrix; the Σ matrix is ​​a diagonal matrix, and the diagonal elements of Σ are the singular values ​​q1, q2, q3, ...q of the matrix X. p ,…q max , and the singular values ​​are arranged in descending order, V is a right singular matrix, and the superscript H represents the conjugate transpose; Σ s is a diagonal matrix consisting of the largest P singular values ​​of the matrix X. The threshold for determining the largest P singular values ​​is taken as 1e -4 , the model order is P, Σ n It is the diagonal matrix composed of the remaining singular values ​​of matrix X; U s is the matrix U divided according to the largest P singular values, U n is the matrix composed of the remaining column vectors of matrix U, V H is the conjugate transpose of the right singular matrix V; V s is the matrix V divided according to the largest P singular values, Vs H is the matrix V s The conjugate transposed matrix, V n is the matrix composed of the remaining column vectors of matrix V, V n H is the matrix V n In this embodiment, the threshold value for determining the singular value P is taken as 1e -4 , the singular value P is taken as 14;

[0094] Step S35, let V1 and V2 represent V s Delete the last row and the first row of the matrix to get a new matrix; construct the matrix [V1, V2], and perform singular value decomposition on [V1, V2] to get matrices R, A, and Q:

[0095] [V1,V2]=RAQ H (8)

[0096] Where R is the left singular matrix; A is the diagonal matrix; Q is the right singular matrix, Q H is the conjugate transposed matrix of matrix Q;

[0097] Decompose the Q matrix into 4 P×P order matrices Q 11 , Q 12 , Q 21 , Q 22 :

[0098]

[0099] Then the rotation operator φ=-Q 12 Q 22 -1 ;

[0100] By rotating the eigenvalue λ of the operator φ p (p=1,2,…,P) Estimate the frequency ω of each component in the signal p , attenuation factor σ p :

[0101]

[0102] Where, T s is the sampling interval of the circuit breaker closing current recording data. For N-point sampling signals, the sampling signal sequence is x(n), and we have:

[0103]

[0104] Using the least squares method, we can solve the vector c=(λ T λ) -1 λ TY, and then find the amplitude a of each component in the signal p and phase φ p :

[0105] a p =2|c p |,(p=1,2,...,P) (12)

[0106] φ p =arg(c p ),(p=1,2,...,P) (13)

[0107] By decomposing the current waveform data, we can determine the frequency, attenuation factor, amplitude, and phase of each modal component. This data is then compared to the normal closing resistor data. When a surface flashover fault occurs in the closing resistor, the actual operating closing resistor value will decrease by a corresponding amount. Among the current modal components, the DC component is significantly affected by the closing resistor value and can be used as a basis for determining the actual operating closing resistor value.

[0108] Preferably, step S4 includes:

[0109] Step S41, select the amplitude a corresponding to the two DC components p and the attenuation factor σ p According to the corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor in the transient process, the resistance value is the horizontal axis and the amplitude a is the p and the attenuation factor σ p As the vertical axis, draw the amplitude-resistance relationship point diagram and the attenuation factor-resistance relationship point diagram respectively, and then further fit the amplitude-resistance curve function f corresponding to the DC component 1 A1 And attenuation factor-resistance curve function f Σ1 , and the amplitude-resistance curve function f corresponding to the DC component 2 A2 And attenuation factor-resistance curve function f Σ2 ; can be referred to together Figure 5 and Figure 6 As shown;

[0110] Step S42, find out the function f A1 、Function f Σ1 、Function f A2 and function f Σ2 The inverse function of function function and function

[0111] Preferably, step S5 includes:

[0112] Step S51, when performing closing resistance detection during the circuit breaker switching process, the amplitudes a1 and a2 and attenuation factors σ1 and σ2 corresponding to the two DC components are analyzed in real time based on the circuit breaker closing current data;

[0113] Step S52: Substitute a1, a2, σ1, and σ2 into the corresponding inverse functions to calculate the corresponding resistance value and the average resistance value R:

[0114]

[0115] R=(R A1 +R Σ1 +R A2 +R Σ2 )×1 / 4 (18)

[0116] Step S53, calculating the number K of flashover resistors in the closing resistance during the current circuit breaker switching process according to the average resistance value R:

[0117]

[0118] Where R0 is the closing resistance, r is the resistance of the single-chip resistor, and K is obtained by rounding down.

[0119] Among them, when K is less than 1, the closing resistance is normal; when K is greater than or equal to 1 and less than 3, the closing resistance is abnormal; when K is greater than or equal to 3, a flashover fault occurs in the closing resistance.

[0120] The present invention also provides a closing resistance detection system for the switching state of the AC filter group circuit breaker, which is used to perform Figure 1 The method for detecting the closing resistance of the circuit breaker in the switching state of the AC filter group.

[0121] The actual system resistance of the filter bank circuit breaker closing resistor during switching is determined based on the DC component attenuation factor and amplitude. Based on this, the TLS-ESPRIT decomposition results can be used to determine whether a flashover fault has occurred in the closing resistor. A specific implementation example is provided below. The closing resistor is a product from Morgan, UK. The closing resistance R0 totals 1500Ω and consists of 105 resistors connected in series. The resistance r of each resistor is 14.28Ω. The HP24 / 36 filter bank switching current signal is decomposed to obtain the amplitude and attenuation factor of the DC component of the closing transient current during this stage. The functional relationship between the DC component amplitude and attenuation factor and the closing resistance value is shown in the following equation.

[0122]

[0123] R=(R A1 +R Σ1 +R A2 +R Σ2)×1 / 4 (24)

[0124]

[0125] In the above formula, R A1 、R Σ1 、R A2 、R Σ2 The independent variables of the function are the DC component 1 amplitude a1, DC component 1 attenuation factor σ1, DC component 2 amplitude a2 and DC component 2 attenuation factor σ2, and then R A1 、R Σ1 、R A2 、R Σ2 The arithmetic mean is taken to obtain the actual operational resistance value R. Compare this with the design value of the closing resistor R0 and divide it by the resistance value r of each closing resistor to obtain the number k of resistors that flash over during the closing resistor switching process.

[0126] The present invention proposes a method for detecting the closing resistance of an AC filter group circuit breaker in the switching state, which aims to detect the closing resistance value actually put into the system during the closing process of the circuit breaker and determine the operating state of the closing resistance. This method can accurately and real-timely identify the singular points of the recorded data corresponding to the transient process caused by the switching on and off of the closing resistance, and decompose the voltage and current waveforms of each transient process to obtain the parameters of the modal components of different frequencies. Based on the amplitude and attenuation factor of the DC component in the current decomposition result, this patent can effectively identify the closing resistance value actually put into the system during the transient process of the closing resistance and determine whether a flashover fault has occurred in the closing resistance. This technology has important theoretical significance and engineering value for the long-term stable operation and online monitoring of the closing resistance of the filter group circuit breaker.

[0127] The above disclosure is only a preferred embodiment of the present invention, and it is certainly not intended to limit the scope of the present invention. A person skilled in the art can understand that all or part of the processes of the above embodiment and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

[0128] Reference Figure 7 , Figure 7 It is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present application.

[0129] like Figure 7As shown, the device for detecting closing resistance of a circuit breaker in the switching state of an AC filter bank may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. Communication bus 1002 is used to enable communication between processor 1001 and memory 1005. Memory 1005 may be a high-speed RAM memory or a non-volatile memory, such as a disk drive. Memory 1005 may also optionally be a storage device independent of processor 1001.

[0130] Optionally, the AC filter bank circuit breaker switching state closing resistance detection device may further include a rectangular user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. The rectangular user interface may include a display and an input submodule such as a keyboard. Optionally, the rectangular user interface may also include a standard wired interface and a wireless interface. The network interface may optionally include a standard wired interface and a wireless interface (such as a WiFi interface).

[0131] Those skilled in the art will understand that Figure 7 The structure of the AC filter group circuit breaker switching state closing resistance detection device shown in does not constitute a limitation of the AC filter group circuit breaker switching state closing resistance detection device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0132] like Figure 7 As shown, memory 1005, a computer storage medium, may include an operating system, a network communication module, and a program for detecting the closing resistance of an AC filter bank circuit breaker in the switched state. The operating system manages and controls the hardware and software resources of the AC filter bank circuit breaker switching state detection device, supporting the execution of the program and other software and / or programs. The network communication module facilitates communication between components within memory 1005, as well as with other hardware and software within the system.

[0133] exist Figure 7 In the device for detecting the closing resistance of the circuit breaker in the switching state of an AC filter group shown, the processor 1001 is used to execute the program of the method for detecting the closing resistance of the circuit breaker in the switching state of an AC filter group stored in the memory 1005 to implement the steps of any of the above-mentioned methods for detecting the closing resistance of the circuit breaker in the switching state of an AC filter group.

[0134] The specific implementation of the device for detecting closing resistance of the circuit breaker in the switching state of the AC filter group in the present application is basically the same as the embodiments of the method for detecting closing resistance of the circuit breaker in the switching state of the AC filter group described above, and will not be repeated here.

Claims

1. A method for detecting the closing resistance of an AC filter group circuit breaker in the switched state, characterized in that: include: Step S1, loading the closing current recording data of the filter bank circuit breaker switching process; Step S2, performing wavelet decomposition on the circuit breaker closing current recording data to obtain singular points in the circuit breaker closing current recording data of each layer as starting points of each transient process during the circuit breaker closing resistance input process; Step S3, performing TLS-ESPRIT decomposition on the recorded data of each transient process to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and establishing a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process; Step S4, fitting amplitude-resistance curves corresponding to the two DC components and attenuation factor-resistance curves corresponding to the two DC components based on the corresponding relationship between the amplitude, attenuation factor, and the actual resistance value of the closing resistor actually put into the system during the transient process, and further fitting a curve function and a corresponding inverse function of each curve; Step S5, when performing closing resistance detection in the circuit breaker switching state, the amplitude and attenuation factor of the DC mode are analyzed in real time based on the circuit breaker closing current data, the amplitude and attenuation factor are substituted into the inverse function of the corresponding DC component to calculate the resistance value, and the number of flashover resistors during the closing resistance switching process is further calculated based on the average resistance value, so as to understand whether a flashover fault occurs in the resistor during operation.

2. The method for detecting closing resistance of a circuit breaker in the switching state of an AC filter group according to claim 1, characterized in that: The step S2 performs wavelet decomposition on the circuit breaker closing current recording data to obtain singular points in each layer of current recording data as starting points of each transient process during the circuit breaker closing resistance input process, including: Step S21, defining a decomposition low-pass filter h, a decomposition high-pass filter g, a decomposition layer number J and a threshold T; Step S22, using wavelet basis function to perform J-layer wavelet decomposition on the circuit breaker closing current recording data {f[n]}, and obtain the wavelet coefficients of each layer k is the j-th level index; Step S23, further processing the wavelet coefficients obtained in step S22 with a threshold, that is, for those that meet of make Step S24: For wavelet coefficients with J≥2, a hard threshold of 1e is used. -4 The modulus maximum detection method is used to obtain the singular point in the current recording data and detect The modulus maximum point, the modulus maximum point criterion is: and 3. The method for detecting closing resistance of a circuit breaker in the switching state of an AC filter group according to claim 2, characterized in that: The step S3 performs TLS-ESPRIT decomposition on the recorded data of each transient process to obtain the amplitude and attenuation factor of the DC mode in the decomposition result, and establishes a corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor actually put into the system during the transient process, including: In step S31, the TLS-ESPRIT algorithm is used to decompose the model to the order P. The signal model x(n) of the current signal waveform at the nth sampling moment is expressed as: Where: T s is the sampling period. Since the sampled signal is a real signal, the model order P is twice the real sinusoidal component signal actually contained in the signal; a p represents the amplitude of the pth frequency component; φ p represents the initial phase of the pth frequency component; ω p represents the angular frequency of the pth frequency component; σ p represents the attenuation factor of the pth frequency component; ω(n) represents Gaussian white noise with zero mean; Step S32, define c p and signal pole z p , simplified model x(n): Step S33, the discrete data of the circuit breaker closing current recording data is combined into X N×M The HANKEL matrix is: Wherein: L is the signal length of the circuit breaker closing current recording data, N is the length of the window function, M is the width of the window function, L>P; M>P; L+M-1=N; L×1 / 4≤M≤L×1 / 3; Step S34, perform singular value decomposition on the matrix X and rearrange the matrix in descending order of singular values ​​to obtain the expression: Where U is a left singular matrix; the Σ matrix is ​​a diagonal matrix, and the diagonal elements of Σ are the singular values ​​q1, q2, q3, ...q of the matrix X. p ,…q max , and the singular values ​​are arranged in descending order, V is a right singular matrix, and the superscript H represents the conjugate transpose; Σ s is a diagonal matrix consisting of the largest P singular values ​​of the matrix X. The threshold for determining the largest P singular values ​​is taken as 1e -4 , the model order is P, Σ n It is the diagonal matrix composed of the remaining singular values ​​of matrix X; U s is the matrix U divided according to the largest P singular values, U n is the matrix composed of the remaining column vectors of matrix U, V H is the conjugate transpose of the right singular matrix V; V s is the matrix V divided according to the largest P singular values, V s H is the matrix V s The conjugate transposed matrix, V n is the matrix composed of the remaining column vectors of matrix V, V n H is the matrix V n The conjugate transpose of Step S35, let V1 and V2 represent V s Delete the last row and the first row of the matrix to get a new matrix; construct the matrix [V1, V2], and perform singular value decomposition on [V1, V2] to get matrices R, A, and Q: <h2 style=";text-align:left;direction:ltr">[V1,V2]=RAQ<h2 style=";text-align:left;direction:ltr"> H Where R is the left singular matrix; A is the diagonal matrix; Q is the right singular matrix, Q H is the conjugate transposed matrix of matrix Q; Decompose the Q matrix into 4 P×P order matrices Q 11 , Q 12 , Q 21 , Q 22 : Then the rotation operator φ=-Q 12 Q 22 -1 ; By rotating the eigenvalue λ of the operator φ p (p=1,2,…,P) Estimate the frequency ω of each component in the signal p , attenuation factor σ p : Where, for N-point sampling signals, the sampling signal sequence is x(n), and we have: Using the least squares method, we can solve the vector c=(λ T λ) -1 λ T Y, and then find the amplitude a of each component in the signal p and phase φ p : a p =2|c p |,(p=1,2,...,P) φ p =arg(c p ),(p=1,2,...,P)。 4. The method for detecting closing resistance of a circuit breaker in the switching state of an AC filter group according to claim 3, characterized in that: The step S4 comprises: Step S41, select the amplitude a corresponding to the two DC components p and the attenuation factor σ p According to the corresponding relationship between the amplitude, attenuation factor and the actual resistance value of the closing resistor in the transient process, the resistance value is the horizontal axis and the amplitude a is the p and the attenuation factor σ p As the vertical axis, draw the amplitude-resistance relationship point diagram and the attenuation factor-resistance relationship point diagram respectively, and then further fit the amplitude-resistance curve function f corresponding to the DC component 1 A1 And attenuation factor-resistance curve function f Σ1 , and the amplitude-resistance curve function f corresponding to the DC component 2 A2 And attenuation factor-resistance curve function f Σ2 ; Step S42, find out the function f A1 、Function f Σ1 、Function f A2 and function f Σ2 The inverse function of function function and function 5. The method for detecting closing resistance of a circuit breaker in a switched state of an AC filter group according to claim 4, characterized in that: Step S5 includes: Step S51, when performing closing resistance detection during the circuit breaker switching process, the amplitudes a1 and a2 and attenuation factors σ1 and σ2 corresponding to the two DC components are analyzed in real time based on the circuit breaker closing current data; Step S52: Substitute a1, a2, σ1, and σ2 into the corresponding inverse functions to calculate the corresponding resistance value and the average resistance value R: R=(R A1 +R Σ1 +R A2 +R Σ2 )×1 / 4 Step S53, calculating the number K of flashover resistors in the closing resistance during the current circuit breaker switching process according to the resistance mean R: Where R0 is the closing resistance, r is the resistance of the single-chip resistor, and K is obtained by rounding down. Among them, when K is less than 1, the closing resistance is normal; when K is greater than or equal to 1 and less than 3, the closing resistance is abnormal; when K is greater than or equal to 3, a flashover fault occurs in the closing resistance.

6. A system for detecting closing resistance of a circuit breaker in switching state of an AC filter group, characterized in that: Used to execute the method for detecting closing resistance of a circuit breaker in the switching state of an AC filter group as described in any one of claims 1-5.

7. A device for detecting closing resistance of a circuit breaker in the switching state of an AC filter group, characterized in that: include: A memory, a processor, and a program stored in the memory for implementing the method for detecting the closing resistance of the circuit breaker in the switched state of the AC filter group, wherein the memory is used to store the program for implementing the method for detecting the closing resistance of the circuit breaker in the switched state of the AC filter group; The processor is used to execute a program for implementing a method for detecting closing resistance of an AC filter group circuit breaker in a switched state, so as to implement the steps of the method for detecting closing resistance of an AC filter group circuit breaker in a switched state as claimed in any one of claims 1 to 5.

8. A readable storage medium, characterized in that: The readable storage medium stores a program for implementing a method for detecting the closing resistance of an AC filter group circuit breaker in the switched state. The program for implementing the method for detecting the closing resistance of an AC filter group circuit breaker in the switched state is executed by a processor to implement the steps of the method for detecting the closing resistance of an AC filter group circuit breaker in the switched state as claimed in any one of claims 1 to 5.

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