Fault detection method and system of high-voltage direct-current power transmission system and readable storage medium

Abstract

The invention relates to the technical field of relay protection, in particular to a fault detection method and system of a high-voltage direct-current power transmission system and a readable storage medium. The method comprises the following steps: when a fault signal is detected, collecting polar line fault voltage data and determining projection coordinates of the polar line fault voltage data in an empirical orthogonal function clustering space; the Euclidean distance between the projection coordinate and each clustering center in the empirical orthogonal function clustering space is calculated, the types of the clustering centers comprise a plurality of first clustering centers and a single second clustering center, the number of the first clustering centers is multiple, and the number of the second clustering center is single; the minimum Euclidean distance in the Euclidean distances is determined; and according to the projection coordinates, the minimum Euclidean distance and the type of the clustering center corresponding to the minimum Euclidean distance, determining the fault type of the high-voltage direct-current power transmission system. The objective of the invention is to solve the problem of how to accurately detect the fault type of the high-voltage direct-current power transmission system.

Description

Technical Field

[0001] The present application relates to the field of relay protection technology, and in particular to a fault detection method, system and readable storage medium for a high voltage direct current transmission system. Background Art

[0002] In recent years, with the shortage of fossil energy brought about by global economic growth and the increasingly prominent problems of global environmental climate change, the utilization and development of energy has been moving towards a safe, efficient, green and low-carbon direction. Green development has become the trend of global development today. However, my country's energy resources are mainly distributed in the western region. In addition, due to the lack of cross-regional transportation and dispatching capabilities and the flexible operation capabilities of the power grid, my country has long had a problem of mismatch between energy supply and demand. High Voltage Direct Current (HVDC) transmission technology is currently an effective technical means to solve the problem of inverse distribution of electric energy and load demand.

[0003] In related technical solutions, high-voltage direct current transmission systems often use traveling wave protection as the main protection for DC lines, and longitudinal differential protection as the backup protection.

[0004] However, the applicant discovered during the process of conceiving and implementing the present application that: when a high-resistance fault occurs, the traveling wave protection is not sensitive to the high-resistance fault, and the longitudinal differential protection has a time delay defect, so the traveling wave protection will refuse to operate, and the longitudinal differential protection delay is too long, resulting in a large trigger angle, causing the system to lock. In view of this, a method is needed to accurately detect the fault type of the high-voltage direct current transmission system, so that the rectifier station can call different system protection strategies according to different faults. Summary of the invention

[0005] The main purpose of the present application is to provide a fault detection method for a high voltage direct current transmission system, aiming to solve the problem of how to accurately detect the fault type of the high voltage direct current transmission system.

[0006] To achieve the above object, the present application provides a fault detection method for a high voltage direct current transmission system, the method comprising the following steps:

[0007] When a fault signal is detected, collecting pole line fault voltage data and determining the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space;

[0008] Calculating the Euclidean distance between the projection coordinates and each cluster center in the empirical orthogonal function clustering space, wherein the types of the cluster centers include a first cluster center and a second cluster center, the first cluster center is multiple, and the second cluster center is single;

[0009] Determine the minimum Euclidean distance among the Euclidean distances;

[0010] The fault type of the high-voltage direct current power transmission system is determined according to the projection coordinates, the minimum Euclidean distance, and the type of the cluster center corresponding to the minimum Euclidean distance.

[0011] Optionally, the process of constructing the empirical orthogonal function clustering space includes:

[0012] Collecting fault sample data of the high voltage direct current transmission system and centrally processing the fault sample data;

[0013] Extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function, and establishing an empirical orthogonal function clustering space according to the characteristic information;

[0014] Dividing the empirical orthogonal function clustering space into a line fault area, an external fault area and a fuzzy area, wherein the area between the line fault area and the external fault area is the fuzzy area;

[0015] Cluster centers are respectively set in the line fault area and the external fault area, wherein the cluster center in the line fault area is the first cluster center, and the cluster center in the external fault area is the second cluster center.

[0016] Optionally, the step of extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function, and establishing an empirical orthogonal function clustering space according to the characteristic information includes:

[0017] Collect n fault sample data collected at m time points at the measurement end, and construct an m×n dimensional fault sample data matrix;

[0018] Determine the covariance matrix corresponding to the fault sample data matrix, similarly diagonalize the covariance matrix to obtain an eigenvalue matrix;

[0019] Arrange the eigenvalues ​​in the eigenvalue matrix in descending order, and use the largest eigenvalue as the first-order empirical orthogonal function;

[0020] Starting from the first-order empirical orthogonal function, sequentially selecting the empirical orthogonal functions of the next order backward to form an empirical orthogonal function feature set, and calculating the contribution rate of each empirical orthogonal function in the empirical orthogonal function feature set;

[0021] When the cumulative value of each contribution rate in the empirical orthogonal function feature set is greater than a preset contribution rate threshold, the current empirical orthogonal function feature set is used as feature information in the fault sample data;

[0022] The empirical orthogonal function clustering space is established based on the feature information.

[0023] Optionally, the first cluster centers are set to 4, and the second cluster centers are set to 1;

[0024] Among them, let the projection coordinates of the four first cluster centers on the empirical orthogonal function clustering plane be C 1 (x 1 ,y 1 ), C 2 (x 2 ,y 2 ), C 3 (x 3 ,y 3 ), C 4 (x 4 ,y 4 ), the projection coordinates of the second cluster center on the empirical orthogonal function clustering plane are C 5 (x 5 ,y 5 ), the projection coordinate expression of each cluster center is:

[0025]

[0026] Optionally, the step of determining the fault type of the high-voltage direct current power transmission system according to the minimum Euclidean distance and the type of the cluster center corresponding to the minimum Euclidean distance includes:

[0027] When the type of the cluster center corresponding to the minimum Euclidean distance is a first cluster center, and the abscissa of the projection coordinate is less than or equal to the maximum abscissa value of each of the first cluster centers, the fault type is determined to be a line fault;

[0028] When the type of the cluster center corresponding to the minimum Euclidean distance is a second cluster center, and the horizontal coordinate of the projection coordinate is greater than or equal to the horizontal coordinate of each of the second cluster centers, the fault type is determined to be an external fault;

[0029] When the abscissa of the projection coordinate is greater than the maximum abscissa value in the first cluster center and less than the abscissa value in the second cluster center, it is determined that the fault type is a fuzzy area fault.

[0030] Optionally, the fault type includes a line fault, an external fault and a fuzzy area fault, and after the step of determining the fault type of the high voltage direct current transmission system according to the projection coordinates, the minimum Euclidean distance, and the type of the cluster center corresponding to the minimum Euclidean distance, the method further includes:

[0031] When it is determined that the fault type is a line fault, calling a first protection strategy;

[0032] The first protection strategy is characterized by: forcing the trigger angle of the rectifier station to shift to 120° to 160°, and restarting the fault pole of the high-voltage DC system after the fault is cleared;

[0033] When it is determined that the fault type is an external fault, calling a second protection strategy;

[0034] The second protection strategy is characterized as follows: the trigger angle of the rectifier station is forced to shift to 120° to 160°, the differential protection strategy in the inverter station is started and a blocking signal is sent to the rectifier station, so that the rectifier station performs a blocking action after receiving the blocking signal;

[0035] When it is determined that the fault type is a fuzzy area fault, calling a third protection strategy;

[0036] The third protection strategy is characterized as follows: when a fault occurs in the inverter station, the second protection strategy is called; when a fault occurs at the end of the transmission line, the first protection strategy is called.

[0037] Optionally, before the step of collecting the pole line fault voltage data and determining the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space, the step further includes:

[0038] Collect the DC voltage at the converter station exit of the transmission system;

[0039] Calculating a voltage change rate according to the DC voltage;

[0040] When the voltage change rate is greater than a preset threshold, a fault signal is generated.

[0041] In addition, to achieve the above purpose, the present application also provides a fault detection system, the fault detection system comprising:

[0042] Memory;

[0043] processor; and,

[0044] A fault detection program for a high-voltage direct current transmission system is stored in the memory and can be run on the processor. When the fault detection program for the high-voltage direct current transmission system is executed by the processor, the steps of the fault detection method for the high-voltage direct current transmission system as described above are implemented.

[0045] In addition, to achieve the above-mentioned purpose, the present application also provides a computer-readable storage medium, characterized in that a fault detection program of a high-voltage direct current transmission system is stored on the computer-readable storage medium, and when the fault detection program of the high-voltage direct current transmission system is executed by a processor, the steps of the fault detection method of the high-voltage direct current transmission system as described above are implemented.

[0046] This application has at least the following beneficial effects:

[0047] The fault voltage information of the HVDC transmission system is extracted by using the empirical orthogonal functions (EOF), and the Euclidean distance is used as the protection criterion to judge the fault type of the HVDC transmission system, replacing the traditional complex setting calculation, thereby improving the reliability of protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of the architecture of the hardware operating environment of the fault detection system involved in the embodiment of the present application;

[0049] Figure 2 A schematic diagram of a simulation model of a hybrid cascaded direct current power transmission system according to the first embodiment of the present application;

[0050] Figure 3 A schematic flow chart of a first embodiment of a fault detection method for a high voltage direct current transmission system of the present application;

[0051] Figure 4 A schematic flow chart of a second embodiment of a fault detection method for a high voltage direct current transmission system of the present application;

[0052] Figure 5 A schematic flow chart of a third embodiment of a fault detection method for a high voltage direct current transmission system of the present application;

[0053] Figure 6 This is a flow chart of a fourth embodiment of a fault detection method for a high voltage direct current transmission system of the present application.

[0054] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0055] In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0056] As an implementation plan, Figure 1 This is a schematic diagram of the architecture of the hardware operating environment of the fault detection system involved in the embodiment of the present application.

[0057] like Figure 1As shown, the fault detection system may include: a processor 1001, such as a CPU, a memory 1005, a user interface 1003, a network interface 1004, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0058] Those skilled in the art will understand that Figure 1 The fault detection system architecture shown in the figure does not constitute a limitation on the fault detection system, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0059] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a fault detection program of a high-voltage direct current transmission system. The operating system is a program for managing and controlling the hardware and software resources of the fault detection system, the operation of the fault detection program of the high-voltage direct current transmission system, and other software or programs.

[0060] exist Figure 1 In the fault detection system shown, the user interface 1003 is mainly used to connect to the terminal and communicate data with the terminal; the network interface 1004 is mainly used for the background server and communicates data with the background server; the processor 1001 can be used to call the fault detection program of the high-voltage direct current transmission system stored in the memory 1005.

[0061] In this embodiment, the fault detection system includes: a memory 1005, a processor 1001, and a fault detection program for a high-voltage direct current transmission system stored in the memory and executable on the processor, wherein:

[0062] When the processor 1001 calls the fault detection program of the high voltage direct current transmission system stored in the memory 1005, the following operations are performed:

[0063] When a fault signal is detected, collecting pole line fault voltage data and determining the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space;

[0064] Calculating the Euclidean distance between the projection coordinates and each cluster center in the empirical orthogonal function clustering space, wherein the types of the cluster centers include a first cluster center and a second cluster center, the first cluster center is multiple, and the second cluster center is single;

[0065] Determine the minimum Euclidean distance among the Euclidean distances;

[0066] The fault type of the high-voltage direct current power transmission system is determined according to the projection coordinates, the minimum Euclidean distance, and the type of the cluster center corresponding to the minimum Euclidean distance.

[0067] When the processor 1001 calls the fault detection program of the high voltage direct current transmission system stored in the memory 1005, the following operations are performed:

[0068] Collecting fault sample data of the high voltage direct current transmission system and centrally processing the fault sample data;

[0069] Extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function, and establishing an empirical orthogonal function clustering space according to the characteristic information;

[0070] Dividing the empirical orthogonal function clustering space into a line fault area, an external fault area and a fuzzy area, wherein the area between the line fault area and the external fault area is the fuzzy area;

[0071] Cluster centers are respectively set in the line fault area and the external fault area, wherein the cluster center in the line fault area is the first cluster center, and the cluster center in the external fault area is the second cluster center.

[0072] When the processor 1001 calls the fault detection program of the high voltage direct current transmission system stored in the memory 1005, the following operations are performed:

[0073] Collect n fault sample data collected at m time points at the measurement end, and construct an m×n dimensional fault sample data matrix;

[0074] Determine the covariance matrix corresponding to the fault sample data matrix, similarly diagonalize the covariance matrix to obtain an eigenvalue matrix;

[0075] Arrange the eigenvalues ​​in the eigenvalue matrix in descending order, and use the largest eigenvalue as the first-order empirical orthogonal function;

[0076] Starting from the first-order empirical orthogonal function, sequentially selecting the empirical orthogonal functions of the next order backward to form an empirical orthogonal function feature set, and calculating the contribution rate of each empirical orthogonal function in the empirical orthogonal function feature set;

[0077] When the cumulative value of each contribution rate in the empirical orthogonal function feature set is greater than a preset contribution rate threshold, the current empirical orthogonal function feature set is used as feature information in the fault sample data;

[0078] The empirical orthogonal function clustering space is established based on the characteristic information. When the processor 1001 calls the fault detection program of the high-voltage direct current transmission system stored in the memory 1005, the following operations are performed:

[0079] When the type of the cluster center corresponding to the minimum Euclidean distance is a first cluster center, and the abscissa of the projection coordinate is less than or equal to the maximum abscissa value of each of the first cluster centers, the fault type is determined to be a line fault;

[0080] When the type of the cluster center corresponding to the minimum Euclidean distance is a second cluster center, and the horizontal coordinate of the projection coordinate is greater than or equal to the horizontal coordinate of each of the second cluster centers, the fault type is determined to be an external fault;

[0081] When the abscissa of the projection coordinate is greater than the maximum abscissa value in the first cluster center and less than the abscissa value in the second cluster center, it is determined that the fault type is a fuzzy area fault.

[0082] The empirical orthogonal function clustering space is established based on the characteristic information. When the processor 1001 calls the fault detection program of the high-voltage direct current transmission system stored in the memory 1005, the following operations are performed:

[0083] When it is determined that the fault type is a line fault, calling a first protection strategy;

[0084] The first protection strategy is characterized by: forcing the trigger angle of the rectifier station to shift to 120° to 160°, and restarting the fault pole of the high-voltage DC system after the fault is cleared;

[0085] When it is determined that the fault type is an external fault, calling a second protection strategy;

[0086] The second protection strategy is characterized as follows: the trigger angle of the rectifier station is forced to shift to 120° to 160°, the differential protection strategy in the inverter station is started and a blocking signal is sent to the rectifier station, so that the rectifier station performs a blocking action after receiving the blocking signal;

[0087] When it is determined that the fault type is a fuzzy area fault, calling a third protection strategy;

[0088] The third protection strategy is characterized as follows: when a fault occurs in the inverter station, the second protection strategy is called; when a fault occurs at the end of the transmission line, the first protection strategy is called.

[0089] Based on the hardware architecture of the fault detection system of the above-mentioned relay protection technology, an embodiment of the fault detection method of the high-voltage direct current transmission system of the present application is proposed.

[0090] First embodiment

[0091] In this embodiment, refer to Figure 2 The schematic diagram of the simulation model of the hybrid cascade DC transmission system built on PSCAD / EMTDC is shown. The sending end adopts a grid-commutated converter (LCC), and the positive and negative poles are both 12-pulse converters composed of two 6-pulse converters connected in series. The receiving end adopts a multi-terminal hybrid cascade DC transmission system composed of LCC and modular multilevel converter (MMC) cascaded. The total length of the DC transmission line is 2000km.

[0092] Reference Figure 3 In this embodiment, the fault detection method of the high voltage direct current transmission system comprises the following steps:

[0093] Step S10, when a fault signal is detected, collecting polar line fault voltage data and determining the projection coordinates of the polar line fault voltage data in the empirical orthogonal function clustering space;

[0094] Step S20, calculating the Euclidean distance between the projection coordinates and each cluster center in the empirical orthogonal function clustering space;

[0095] Step S30, determining the minimum Euclidean distance among the Euclidean distances;

[0096] Step S40: determining the fault type of the high voltage direct current power transmission system according to the projection coordinates, the minimum Euclidean distance, and the type of the cluster center corresponding to the minimum Euclidean distance.

[0097] In this embodiment, when a fault signal is detected, the pole line fault voltage data is collected and the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space are determined.

[0098] Optionally, in this system, as to how to detect a fault signal, the DC voltage at the outlet of the transmission system converter station is collected, and the voltage change rate is calculated according to the DC voltage. When the voltage change rate is greater than a preset threshold, a fault signal is generated.

[0099] Exemplarily, the criterion for generating the fault signal is as follows:

[0100] |du dc / dt|>Uset

[0101] In the formula, u dc is the DC voltage measured at the converter station exit; t is the sampling time, U set The preset threshold for the start criterion.

[0102] In this embodiment, the empirical orthogonal functions (EOF) clustering space is a clustering space constructed by collecting fault voltage sample data and extracting characteristic information from the fault voltage sample data.

[0103] When a fault signal is detected, the pole line fault voltage data is collected and its projection coordinates in the empirical orthogonal function clustering space are calculated. According to the Euclidean distance between the projection coordinates and each clustering center in the space, it is calculated to which clustering center the collected pole line fault voltage data is close. Based on the type corresponding to the closest clustering center, the fault type of the high-voltage direct current transmission system is comprehensively judged.

[0104] It should be noted that the first cluster center represents the fault voltage data characteristics corresponding to the presence of a line fault in the HVDC transmission system, and the second cluster center represents the fault voltage data characteristics corresponding to the presence of an external fault in the HVDC transmission system. Therefore, the closer the projection coordinates in the collected polar line fault voltage data are to a certain type of cluster center, the greater the probability that the HVDC transmission system is in the fault type corresponding to that type of cluster center.

[0105] In addition, since there are multiple fault voltage data characteristics corresponding to line fault problems, including but not limited to rectifier side converter outlet fault and rectifier side AC system fault, inverter side converter outlet fault and inverter side AC system fault, etc., the first cluster center is set to multiple in this embodiment; and line fault problems that do not belong to the internal system are regarded as external faults, so the second cluster center is set to one.

[0106] In the technical solution provided in this embodiment, empirical orthogonal functions (EOF) are used to extract fault voltage information of the high-voltage direct current transmission system, and Euclidean distance is used as a protection criterion to realize the judgment of the fault type of the high-voltage direct current transmission system, replacing the traditional complex setting calculation, thereby improving the reliability of protection.

[0107] Second embodiment

[0108] As an optional embodiment, refer to Figure 4 Based on the first embodiment, in this embodiment, the construction process of the empirical orthogonal function clustering space includes:

[0109] Step S21, collecting fault sample data of the high voltage direct current transmission system, and centrally processing the fault sample data;

[0110] Specifically and optionally, in this embodiment, in some specific implementations, the specific centralized processing process may be as follows:

[0111] First, for external faults, rectifier-side converter outlet faults and rectifier-side AC system faults, inverter-side converter outlet faults and inverter-side AC system faults are taken into account. A total of 8 typical external faults are set. For line faults, a metallic grounding fault is set every 5 km along the entire length of the DC line. A total of 400 faults are set along the entire length of the line from near to far, with a sampling frequency of 10 kHz.

[0112] Next, 3 sampling points before the DC voltage fault and 7 sampling points after the fault, a total of 10 sampling points, are selected as fault sample data and normalized. The calculation process of normalizing the fault sample data is as follows:

[0113]

[0114] In the formula, x i * is the per-unit value of the fault sample data; x i is the unprocessed fault sample data; x N is the rated voltage of the HVDC transmission system.

[0115] Next, the normalized fault sample data is centralized. The calculation process of the centralization is as follows:

[0116]

[0117] In the formula, x i ' is the fault sample data after centralization; μ is the mean of the fault sample data; σ is the standard deviation of the fault sample data.

[0118] Step S22, extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function, and establishing an empirical orthogonal function clustering space according to the characteristic information;

[0119] After processing the data set, the characteristic information in the fault sample data after the centralization processing is extracted through the empirical orthogonal function, and the empirical orthogonal function clustering space is established according to the characteristic information.

[0120] Specifically and optionally, the steps are as follows:

[0121] Step S221, collecting n fault sample data collected at m time points at the measuring end, and constructing an m×n dimensional fault sample data matrix;

[0122] For example, the m×n dimensional fault sample data matrix is ​​as follows:

[0123]

[0124] Step S222, determining the covariance matrix corresponding to the fault sample data matrix, similarity-diagonalizing the covariance matrix to obtain an eigenvalue matrix;

[0125] Exemplarily, the calculation expression of the covariance matrix C of the fault sample data matrix X is as follows:

[0126]

[0127] Where, X T is the transpose of the fault sample data matrix X.

[0128] The calculation expression for similar diagonalization of the covariance matrix C is as follows:

[0129] CV=VΛ

[0130] Where V is the eigenvector matrix of C and Λ is the eigenvalue matrix of C.

[0131] Step S223, arranging the eigenvalues ​​in the eigenvalue matrix in descending order, and taking the largest eigenvalue as the first-order empirical orthogonal function;

[0132] For example, the eigenvalues ​​in Λ are arranged in descending order to obtain:

[0133] Λ'=[λ 1 ',λ 2 ', ..., λ n ']

[0134] Among them, the eigenvector matrix V' corresponding to Λ' has the largest eigenvalue λ 1 'The corresponding eigenvector is called the first-order EOF 1 , that is, the first-order empirical orthogonal function, and the second-order EOF is obtained in the same way 2 , and the p-th order EOF p .

[0135] Step S224, starting from the first-order empirical orthogonal function, sequentially select the empirical orthogonal functions of the next order to form an empirical orthogonal function feature set, and calculate the contribution rate of each empirical orthogonal function in the empirical orthogonal function feature set;

[0136] For example, the contribution rate of each order of empirical orthogonal function is calculated as follows:

[0137]

[0138] Step S225, when the cumulative value of each contribution rate in the empirical orthogonal function feature set is greater than a preset contribution rate threshold, the current empirical orthogonal function feature set is used as feature information in the fault sample data;

[0139] For example, assuming that the preset contribution rate threshold is 80%, the calculation expression of the cumulative value of the contribution rate is:

[0140]

[0141] Step S226: establishing the empirical orthogonal function clustering space based on the feature information.

[0142] Exemplarily, the empirical orthogonal function feature set composed of the first p-order empirical orthogonal function features is constructed into a matrix V', and the expression of the empirical orthogonal function clustering space Y is obtained as follows:

[0143] Y=V″X

[0144] Step S23, dividing the empirical orthogonal function clustering space into a line fault area, an external fault area and a fuzzy area, wherein the area between the line fault area and the external fault area is the fuzzy area;

[0145] In this embodiment, after obtaining the empirical orthogonal function clustering space, the empirical orthogonal function clustering space is divided into a line fault area, an external fault area and a fuzzy area. Specifically, the line fault area and the external fault area are first divided, and then the area between the line fault area and the external fault area is used as the fuzzy area.

[0146] Step S24, setting cluster centers in the line fault area and the external fault area respectively, wherein the cluster center in the line fault area is the first cluster center, and the cluster center in the external fault area is the second cluster center.

[0147] Further and optionally, in this embodiment, the first cluster center may be set to 4, and the second cluster center may be set to 1;

[0148] Among them, let the projection coordinates of the four first cluster centers on the empirical orthogonal function clustering plane be C 1 (x 1 ,y 1 ), C 2 (x 2 ,y 2 ), C 3 (x 3 ,y 3 ), C 4 (x 4 ,y 4), the projection coordinates of the second cluster center on the empirical orthogonal function clustering plane are C 5 (x 5 ,y 5 ), the projection coordinate expression of each cluster center is:

[0149]

[0150] For example, in some specific implementations, the calculated projection coordinates of the cluster centers on the EOF cluster plane are shown in Table 1 below:

[0151] Table 1. Coordinates of cluster centers on the EOF clustering plane

[0152]

[0153]

[0154] Third embodiment

[0155] As an optional embodiment, based on the first or second embodiment, in this embodiment, referring to Figure 5 , step S40 specifically includes:

[0156] Step S41: when the type of the cluster center corresponding to the minimum Euclidean distance is a first cluster center, and the abscissa of the projection coordinate is less than or equal to the maximum abscissa of each of the first cluster centers, it is determined that the fault type is a line fault;

[0157] Step S42: when the type of the cluster center corresponding to the minimum Euclidean distance is a second cluster center, and the abscissa of the projection coordinate is greater than or equal to the abscissa of each of the second cluster centers, it is determined that the fault type is an external fault;

[0158] Step S43: when the abscissa of the projection coordinate is greater than the maximum abscissa value in the first cluster center and less than the abscissa value in the second cluster center, it is determined that the fault type is a fuzzy area fault.

[0159] In this embodiment, referring to the second embodiment, it is assumed that the first cluster centers can be set to 4, the second cluster center can be set to 1, and the projection coordinates of the four first cluster centers on the empirical orthogonal function clustering plane are C 1 (x 1 ,y 1 ), C 2 (x 2 ,y 2 ), C 3 (x 3 ,y 3 ), C 4 (x4 ,y 4 ), the projection coordinates of the second cluster center on the empirical orthogonal function clustering plane are C 5 (x 5 ,y 5 ).

[0160] Among them, x5>x4>x3>x2>x1.

[0161] Calculate the Euclidean distance d between the projection U(x, y) of the test data and each cluster center, and record it as d 1 , d 2 , …, d 5 , take the minimum value among them and record it as d min , the calculation process of Euclidean distance is as follows:

[0162]

[0163] If d min =d i ,i≤4 and U x ≤x 4 , that is, the type of the cluster center corresponding to the minimum Euclidean distance is the first cluster center, and the abscissa of the projection coordinate is less than or equal to the maximum abscissa of each of the first cluster centers, then it is a direct current transmission system line fault;

[0164] If d min =d i ,i=5 and U x ≥x 5 , that is, the type of the cluster center corresponding to the minimum Euclidean distance is the second cluster center, and the abscissa of the projection coordinate is greater than or equal to the abscissa of each of the second cluster centers, then it is a direct current transmission external fault;

[0165] If d min =d i , and x 4 <U x <x 5 , that is, the horizontal coordinate is greater than the maximum horizontal coordinate in the first cluster center and less than the horizontal coordinate in the second cluster center, which is a fuzzy area fault.

[0166] Fourth embodiment

[0167] As an optional embodiment, refer to Figure 6 Based on any of the foregoing embodiments, in this embodiment, after step S40, the method further includes:

[0168] Step S51, when it is determined that the fault type is a line fault, calling a first protection strategy;

[0169] The first protection strategy is characterized by: forcing the trigger angle of the rectifier station to shift to 120° to 160°, and restarting the fault pole of the high-voltage DC system after the fault is cleared;

[0170] In this embodiment, for line faults, the protection strategy of the rectifier station is to force the trigger angle on the rectifier side to shift to 120°~160°, so that the rectifier station operates as an inverter station in a short period of time, allowing the energy of the DC transmission system to be quickly sent back to the AC system. After the fault is cleared, the DC system fault pole restart strategy is executed.

[0171] Step S52, when it is determined that the fault type is an external fault, calling a second protection strategy;

[0172] The second protection strategy is characterized as follows: the trigger angle of the rectifier station is forced to shift to 120° to 160°, the differential protection strategy in the inverter station is started and a blocking signal is sent to the rectifier station, so that the rectifier station performs a blocking action after receiving the blocking signal;

[0173] In this embodiment, for external faults, the protection strategy of the rectifier station is to force the trigger angle on the rectifier side to shift to 120°~160°, but at this time the station differential protection of the inverter station is activated and sends a locking signal to the rectifier station. After the rectifier station receives the locking signal, it stops executing the forced phase shift strategy and instead executes the locking strategy.

[0174] Step S53, when it is determined that the fault type is a fuzzy area fault, calling a third protection strategy;

[0175] The third protection strategy is characterized as follows: when a fault occurs in the inverter station, the second protection strategy is called; when a fault occurs at the end of the transmission line, the first protection strategy is called.

[0176] In this embodiment, for fuzzy area faults, different protection strategies are called according to the fault location:

[0177] When a fault occurs in the inverter station, the protection strategy of the rectifier station is the same as the second protection strategy, that is, the protection strategy of the rectifier station is to force the trigger angle on the rectifier side to shift to 120°~160°, but at this time the station differential protection of the inverter station is activated and sends a locking signal to the rectifier station. After the rectifier station receives the locking signal, it stops executing the forced phase shift strategy and instead executes the locking strategy.

[0178] When the fault occurs at the end of the transmission line, it is the same as the first protection strategy, that is, the protection strategy of the rectifier station is to force the trigger angle on the rectifier side to shift to 120°~160°. Since the differential protection in the inverter station will not operate at this time, no locking signal will be sent to the rectifier station. Since the rectifier station does not receive the locking signal, the locking strategy will not be executed. After the fault is cleared, the DC system fault pole restart strategy will be executed.

[0179] For example, the system protection strategies corresponding to different fault types are shown in Table 2 below:

[0180] Table 2. System protection strategies for different fault types

[0181]

[0182] For example, assume that a positive metallic ground fault occurs at a DC line 1000 km away from the rectifier side, and the fault voltage data of the test sample is measured at the rectifier side measurement end, and its projection value in the EOF cluster space is calculated to be U(-0.840, -0.367). The Euclidean distance between U and each cluster center is calculated, and the calculation result is d 1 =0.878; d 2 =0.344; d 3 =0.056; d 4 =0.098; d 5 =0.509; then d min =d 3 , and U x <x 4 Therefore, the judgment result is line fault, and the protection strategy of the rectifier station is the first protection strategy.

[0183] For example, assuming that a positive ground fault occurs on the inverter bus, the fault voltage data of the test sample is measured at the rectifier side measurement end, and its projection value in the EOF cluster space is calculated to be U(-0.322, -0.119). The Euclidean distance between U and each cluster center is calculated, and the calculation result is d 1 =1.449;d 2 =0.911; d 3 =0.605; d 4 =0.480; d 5 =0.070; then d min =d 5 ,U x >x 5 , so the judgment result is external fault. At this time, the protection strategy of the rectifier station is the second protection strategy.

[0184] In addition, it can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the fault detection system to implement the process steps of the embodiment of the above method.

[0185] Therefore, the present application also provides a computer-readable storage medium, which stores a fault detection program for a high-voltage direct current transmission system. When the fault detection program for the high-voltage direct current transmission system is executed by a processor, the various steps of the fault detection method for the high-voltage direct current transmission system described in the above embodiment are implemented.

[0186] The computer-readable storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which may store program codes.

[0187] It should be noted that since the storage medium provided in the embodiment of the present application is the storage medium used to implement the method of the embodiment of the present application, based on the method introduced in the embodiment of the present application, the person skilled in the art can understand the specific structure and deformation of the storage medium, so it is not repeated here. All storage media used in the method of the embodiment of the present application belong to the scope of protection of this application.

[0188] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0189] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0190] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0191] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0192] It should be noted that in the claims, any reference signs placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The present application may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0193] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0194] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A fault detection method for a high voltage direct current transmission system, characterized in that: The method comprises the following steps: When a fault signal is detected, collecting pole line fault voltage data and determining the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space; Calculating the Euclidean distance between the projection coordinates and each cluster center in the empirical orthogonal function clustering space, wherein the types of the cluster centers include a first cluster center and a second cluster center, the first cluster center is multiple, and the second cluster center is single; Determine the minimum Euclidean distance among the Euclidean distances; The fault type of the high-voltage direct current power transmission system is determined according to the projection coordinates, the minimum Euclidean distance, and the type of the cluster center corresponding to the minimum Euclidean distance.

2. The method according to claim 1, characterized in that The construction process of the empirical orthogonal function clustering space includes: Collecting fault sample data of the high voltage direct current transmission system and centrally processing the fault sample data; Extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function, and establishing an empirical orthogonal function clustering space according to the characteristic information; Dividing the empirical orthogonal function clustering space into a line fault area, an external fault area and a fuzzy area, wherein the area between the line fault area and the external fault area is the fuzzy area; Cluster centers are respectively set in the line fault area and the external fault area, wherein the cluster center in the line fault area is the first cluster center, and the cluster center in the external fault area is the second cluster center.

3. The method according to claim 2, characterized in that The step of extracting characteristic information from the fault sample data after centralization through an empirical orthogonal function and establishing an empirical orthogonal function clustering space according to the characteristic information comprises: Collect n fault sample data collected at m time points at the measurement end, and construct an m×n dimensional fault sample data matrix; Determine the covariance matrix corresponding to the fault sample data matrix, similarly diagonalize the covariance matrix to obtain an eigenvalue matrix; Arrange the eigenvalues ​​in the eigenvalue matrix in descending order, and use the largest eigenvalue as the first-order empirical orthogonal function; Starting from the first-order empirical orthogonal function, sequentially selecting the empirical orthogonal functions of the next order backward to form an empirical orthogonal function feature set, and calculating the contribution rate of each empirical orthogonal function in the empirical orthogonal function feature set; When the cumulative value of each contribution rate in the empirical orthogonal function feature set is greater than a preset contribution rate threshold, the current empirical orthogonal function feature set is used as feature information in the fault sample data; The empirical orthogonal function clustering space is established based on the feature information.

4. The method according to claim 1, characterized in that The first cluster centers are set to 4, and the second cluster centers are set to 1; Among them, the projection coordinates of the four first cluster centers on the empirical orthogonal function clustering plane are assumed to be C1(x1, y1), C2(x2, y2), C3(x3, y3), and C4(x4, y4), and the projection coordinates of the second cluster center on the empirical orthogonal function clustering plane are assumed to be C5(x5, y5). The projection coordinate expressions of each cluster center are as follows:

5. The method according to claim 1, characterized in that The step of determining the fault type of the high-voltage direct current power transmission system according to the minimum Euclidean distance and the type of the cluster center corresponding to the minimum Euclidean distance comprises: When the type of the cluster center corresponding to the minimum Euclidean distance is a first cluster center, and the abscissa of the projection coordinate is less than or equal to the maximum abscissa value of each of the first cluster centers, the fault type is determined to be a line fault; When the type of the cluster center corresponding to the minimum Euclidean distance is a second cluster center, and the horizontal coordinate of the projection coordinate is greater than or equal to the horizontal coordinate of each of the second cluster centers, the fault type is determined to be an external fault; When the abscissa of the projection coordinate is greater than the maximum abscissa value in the first cluster center and less than the abscissa value in the second cluster center, it is determined that the fault type is a fuzzy area fault.

6. The method according to any one of claims 1 to 5, characterized in that: The fault types include line faults, external faults and fuzzy area faults. After the step of determining the fault type of the high-voltage direct current transmission system according to the projection coordinates, the minimum Euclidean distance, and the type of cluster center corresponding to the minimum Euclidean distance, the step further includes: When it is determined that the fault type is a line fault, calling a first protection strategy; The first protection strategy is characterized as follows: forcibly shifting the trigger angle of the rectifier station to 120° to 160°, and restarting the fault pole of the high-voltage DC system after the fault is cleared; When it is determined that the fault type is an external fault, calling a second protection strategy; The second protection strategy is characterized as follows: the trigger angle of the rectifier station is forced to shift to 120° to 160°, the differential protection strategy in the inverter station is started and a blocking signal is sent to the rectifier station, so that the rectifier station performs a blocking action after receiving the blocking signal; When it is determined that the fault type is a fuzzy area fault, calling a third protection strategy; The third protection strategy is characterized as follows: when a fault occurs in the inverter station, the second protection strategy is called; when a fault occurs at the end of the transmission line, the first protection strategy is called.

7. The method according to claim 1, characterized in that Before the step of collecting the pole line fault voltage data and determining the projection coordinates of the pole line fault voltage data in the empirical orthogonal function clustering space, the method further includes: Collect the DC voltage at the converter station exit of the transmission system; Calculating a voltage change rate according to the DC voltage; When the voltage change rate is greater than a preset threshold, a fault signal is generated.

8. A fault detection system, characterized in that: The fault detection system comprises: Memory; processor; and, A fault detection program for a high-voltage direct current transmission system stored in the memory and executable on the processor, wherein when the fault detection program for the high-voltage direct current transmission system is executed by the processor, the steps of the fault detection method for a high-voltage direct current transmission system as claimed in any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a fault detection program for a high-voltage direct current transmission system, and when the fault detection program for the high-voltage direct current transmission system is executed by the processor, the steps of the fault detection method for a high-voltage direct current transmission system according to any one of claims 1 to 7 are implemented.

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