A Fault Identification Method and Device for Flexible DC Transmission Equipment

Abstract

The present invention provides a method and device for fault identification of flexible DC transmission equipment. Fault characteristic parameters of each sub-module are determined through information in the sub-module; a spatial autocorrelation index of the fault characteristic parameters is calculated; fault identification of each sub-module is performed based on the spatial autocorrelation index; the fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module. The present invention synthesizes the topological structure and electrical characteristics of the flexible DC transmission equipment, realizes online identification of faults in the flexible DC transmission equipment, and improves the accuracy of the identification result; it is not restricted by electrical quantity measurement signals, does not require extraction of all fault characteristic parameters of each component, takes a short time, greatly saves labor costs, and improves the identification efficiency; when performing fault identification of the flexible DC transmission equipment, the flexible DC transmission equipment does not need to be taken out of the operating state, and does not affect the normal operation of the high-voltage DC system.

Description

Technical Field

[0001] The present invention relates to the technical field of on-line monitoring of DC equipment, and particularly relates to a method and device for identifying faults of flexible DC transmission equipment. Background Art

[0002] The topology structure design of flexible DC transmission equipment devices is relatively complex, and the large number of power electronic devices applied increases the vulnerability of equipment operation. The on-line identification and location of flexible DC transmission equipment faults can assist operation and maintenance personnel in quickly discovering and capturing early defects of equipment, provide a scientific basis for formulating the state maintenance plan of flexible DC equipment, reduce unnecessary power outage maintenance and preventive tests of equipment, and is of great significance for ensuring the safe and reliable operation of flexible DC equipment.

[0003] At present, most of the research on fault feature identification of flexible DC transmission equipment focuses on the failure mechanism, simulation analysis of fault characteristic parameters, and selection and management of electronic components of power electronic devices or modules, mainly limited to the post-fault detection and processing of key components such as IGBT modules and metal oxide film capacitors, and fault identification by simulating and calculating according to the implementation principle of equipment components by selecting electrical quantity measurement information.

[0004] The existing fault feature identification of flexible DC transmission equipment focuses on the research of fault mechanism and determination of fault points after the fault occurs, cannot give early warning of the faults occurring in flexible DC transmission equipment, and cannot prevent the further expansion of local faults. The post-fault detection and processing of key components can accurately locate the position and severity of the fault, but the search and location of the fault take a long time and the labor cost is high, and the flexible DC transmission equipment itself must be taken out of the operating state, affecting the normal operation of the high-voltage DC system; the fault feature identification method of flexible DC transmission equipment using simulation calculation needs to be based on comprehensive, complete and correct electrical quantity measurement information, otherwise it may cause inaccurate judgment results, and the structure between the components of each subsystem of flexible DC transmission equipment is complex, it is difficult to comprehensively extract and accurately measure the characteristic parameters of each component, the measurement error is large, it is greatly restricted by electrical quantity measurement information, the obtained identification result accuracy is low, and on-line identification of flexible DC transmission equipment cannot be realized. Summary of the Invention

[0005] In order to overcome the deficiencies in the above-mentioned prior art that on-line identification cannot be realized and the accuracy of the identification result is relatively low, the present invention provides a method for identifying faults of flexible DC transmission equipment, including:

[0006] Determine the fault characteristic parameters of each sub-module through the information in the sub-module;

[0007] Calculate the spatial autocorrelation index of the fault characteristic parameters;

[0008] Fault identification is performed on each sub-module based on the spatial autocorrelation index;

[0009] The fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

[0010] Determining the fault characteristic parameters of each sub-module through the information in the sub-module includes:

[0011] Collecting the temperature of the sub-module through the temperature sensor in the sub-module, and collecting the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through the high-potential board card in the sub-module;

[0012] Determining the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determining the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

[0013] Calculating the spatial autocorrelation index of the fault characteristic parameters includes:

[0014] Calculating the local Moran index of spatial association of the fault characteristic parameters based on the real-time values of the fault characteristic parameters of the sub-module. The local Moran index of spatial association is the Moran index, which belongs to a type of spatial autocorrelation coefficient and is used to determine whether there is spatial autocorrelation.

[0015] Calculating the spatial autocorrelation index of the fault characteristic parameters based on the local Moran index of spatial association.

[0016] Identifying the faults of each sub-module based on the spatial autocorrelation index includes:

[0017] Identifying the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment;

[0018] Identifying the faults of each sub-module based on the identification results of the fault characteristic parameters.

[0019] Identifying the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment includes:

[0020] Determining the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment;

[0021] Based on the confidence level, determining the acceptance region of the spatial autocorrelation index in combination with the statistical distribution type of the fault characteristic parameters;

[0022] Judging whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determining that the fault characteristic parameters are in a normal state; otherwise, determining that the fault characteristic parameters are in an abnormal state.

[0023] Identifying the faults of each sub-module based on the recognition result of the fault characteristic parameters includes:

[0024] When all the fault characteristic parameters of the sub-module are in the normal state, it is determined that the sub-module is in the normal operation state;

[0025] When any one of the fault characteristic parameters of the sub-module is in the abnormal state and the delay time of the fault characteristic parameter in the abnormal state satisfies the preset relationship with the inverse time constant, it is determined that the sub-module is in the fault state.

[0026] The preset relationship is determined by the following formula:

[0027]

[0028] In the formula, t i is the delay time when the fault characteristic parameter of the i-th sub-module is in the abnormal state, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance ability of the sub-module to the fault characteristic parameter.

[0029] The local Moran index of the spatial association of the fault characteristic parameters is calculated by the following formula:

[0030]

[0031] In the formula, S 2 is the variance of the fault characteristic parameter, n is the number of sub-modules, x i is the real-time value of the fault characteristic parameter of sub-module i, x is the average value of the fault characteristic parameter, x j is the real-time value of the fault characteristic parameter of sub-module j, ω ij is the spatial proximity weight coefficient between sub-module i and sub-module j, and d ij is the distance between sub-module i and sub-module j, and ε is the non-linear attenuation coefficient of the fault characteristic parameter.

[0032] The spatial autocorrelation index of the fault characteristic parameter is determined by the following formula:

[0033]

[0034] In the formula, Z i is the spatial autocorrelation index of the fault characteristic parameter of the i-th sub-module, E(I i ) is the expectation of I i , VAR(I i ) is the variance of I i .

[0035] The capacitance value of the voltage-sharing capacitor is determined according to the following formula:

[0036]

[0037] In the formula, C is the capacitance value of the voltage-sharing capacitor, and Δv c is the ripple voltage of the voltage-sharing capacitor, and i c is the ripple current of the voltage-sharing capacitor;

[0038] The voltage-sharing ratio of the sub-module is determined according to the following formula:

[0039]

[0040] In the formula, η i is the voltage-sharing ratio of the i-th sub-module, v i is the voltage of the i-th sub-module, and n is the number of sub-modules.

[0041] On the other hand, the present invention also provides a fault identification device for a flexible DC transmission equipment, including:

[0042] A data processing module, configured to determine the fault characteristic parameters of each sub-module through the information in the sub-module;

[0043] A calculation module, configured to calculate the spatial autocorrelation index of the fault characteristic parameters by using a spatial local estimation method;

[0044] An identification module, configured to perform fault identification on each sub-module based on the spatial autocorrelation index;

[0045] The fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

[0046] The data processing module is specifically configured to:

[0047] An acquisition module, configured to acquire the temperature of the sub-module through a temperature sensor in the sub-module, and acquire the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through a high-potential board card in the sub-module;

[0048] A processing unit, configured to determine the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determine the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

[0049] The calculation module includes:

[0050] A first calculation unit, configured to calculate the spatial association local Moran index of the fault characteristic parameters based on the real-time value of the fault characteristic parameters of the sub-module;

[0051] A second calculation unit, configured to calculate the spatial autocorrelation index of the fault characteristic parameters based on the spatial association local Moran index.

[0052] The recognition module is specifically configured to:

[0053] A parameter recognition unit, configured to recognize the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment;

[0054] A fault recognition unit, configured to recognize the faults of each sub-module based on the recognition result of the fault characteristic parameters.

[0055] The parameter recognition unit is specifically configured to:

[0056] Determine the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment;

[0057] Based on the confidence level, determine the acceptance region of the spatial autocorrelation index in combination with the statistical distribution type of the fault characteristic parameters;

[0058] Judge whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determine that the fault characteristic parameters are in a normal state; otherwise, determine that the fault characteristic parameters are in an abnormal state.

[0059] The fault recognition unit is specifically configured to:

[0060] When all the fault characteristic parameters of the sub-module are in a normal state, determine that the sub-module is in a normal operation state;

[0061] When any one of the fault characteristic parameters of the sub-module is in an abnormal state and the delay time of the fault characteristic parameter in the abnormal state satisfies a preset relationship with the inverse time constant, determine that the sub-module is in a fault state.

[0062] The fault recognition unit determines the preset relationship according to the following formula:

[0063]

[0064] In the formula, t i is the delay time when the fault characteristic parameter of the i-th sub-module is in an abnormal state, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance ability of the sub-module to the fault characteristic parameter.

[0065] The first calculation unit calculates the spatial association local Moran index of the fault characteristic parameter according to the following formula:

[0066]

[0067] In the formula, S 2 is the variance of the fault characteristic parameter, n is the number of sub - modules, and x i is the real - time value of the fault characteristic parameter of sub - module i, is the average value of the fault characteristic parameters, and x j is the real - time value of the fault characteristic parameter of sub - module j, and ω ij is the spatial proximity weight coefficient between sub - module i and sub - module j, and d ij is the distance between sub - module i and sub - module j, and ε is the non - linear attenuation coefficient of the fault characteristic parameter.

[0068] The second calculation unit calculates the spatial autocorrelation index of the fault characteristic parameter according to the following formula:

[0069]

[0070] In the formula, Z i is the spatial autocorrelation index of the fault characteristic parameter of the i - th sub - module, E(I i ) is the expectation of I i and VAR(I i ) is the variance of I i .

[0071] The processing unit determines the capacitance value of the voltage - equalizing capacitor according to the following formula:

[0072]

[0073] In the formula, C is the capacitance value of the voltage - equalizing capacitor, Δv c is the ripple voltage of the voltage - equalizing capacitor, and i c is the ripple current of the voltage - equalizing capacitor;

[0074] The processing unit determines the voltage - equalizing ratio of the sub - module according to the following formula:

[0075]

[0076] In the formula, η i is the voltage - equalizing ratio of the i - th sub - module, v i is the voltage of the i - th sub - module, and n is the number of sub - modules.

[0077] The technical solution provided by the present invention has the following beneficial effects:

[0078] In the fault identification method of the flexible DC transmission equipment provided by the present invention, the fault characteristic parameters of each sub - module are determined through the information in the sub - module; the spatial autocorrelation index of the fault characteristic parameter is calculated; the fault of each sub - module is identified based on the spatial autocorrelation index; the fault characteristic parameters include the capacitance value of the voltage - equalizing capacitor in the sub - module, the temperature of the sub - module, and the voltage - equalizing ratio of the sub - module, realizing the on - line identification of the fault of the flexible DC transmission equipment and improving the accuracy of the identification result;

[0079] The technical solution provided by the present invention not only considers the fault characteristic parameters of the flexible DC transmission equipment, but also considers the correlation relationship between different sub-modules, that is, the topological structure of the flexible DC transmission equipment is integrated, providing a basis for the fault identification of the sub-modules in the flexible DC transmission equipment;

[0080] The technical solution provided by the present invention is not restricted by the electrical quantity measurement signals, does not need to extract all the fault characteristic parameters of each component, takes a short time, and greatly saves the labor cost and improves the identification efficiency;

[0081] When the technical solution provided by the present invention is used for fault identification of the flexible DC transmission equipment, the flexible DC transmission equipment does not need to exit the operating state, and does not affect the normal operation of the high-voltage DC system;

[0082] The technical solution provided by the present invention can assist the operation and maintenance personnel to quickly discover and capture the early defects of the equipment, provide a scientific basis for formulating the state maintenance plan of the flexible DC equipment, reduce the unnecessary power outage maintenance and preventive tests of the equipment, and provide a reliable basis for ensuring the safe and reliable operation of the flexible DC equipment. Brief Description of the Drawings

[0083] Figure 1 is the flowchart of the fault identification method for the flexible DC transmission equipment in the embodiment of the present invention;

[0084] Figure 2 is the structural diagram of the fault identification device for the flexible DC transmission equipment in the embodiment of the present invention. Detailed Embodiments

[0085] The present invention will be further described in detail below with reference to the drawings.

[0086] Embodiment 1

[0087] Embodiment 1 of the present invention provides a fault identification method for flexible DC transmission equipment. The specific flowchart is as Figure 1 shown, and the specific process is as follows:

[0088] S101: Determine the fault characteristic parameters of each sub-module through the information in the sub-module;

[0089] S102: Calculate the spatial autocorrelation index of the fault characteristic parameters;

[0090] S103: Perform fault identification on each sub-module based on the spatial autocorrelation index;

[0091] Among them, the fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

[0092] In S101, the fault characteristic parameters of each sub-module are determined through the information in the sub-module, including:

[0093] Collect the temperature of the sub-module through the temperature sensor in the sub-module, and collect the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through the high-potential board card in the sub-module;

[0094] Determine the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determine the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

[0095] Among them, the capacitance value of the voltage-sharing capacitor is determined according to the following formula:

[0096]

[0097] In the formula, C is the capacitance value of the voltage-sharing capacitor, Δv c is the ripple voltage of the voltage-sharing capacitor, i c is the ripple current of the voltage-sharing capacitor;

[0098] Among them, the voltage-sharing ratio of the sub-module is determined according to the following formula:

[0099]

[0100] In the formula, η i is the voltage-sharing ratio of the i-th sub-module, v i is the voltage of the i-th sub-module, and n is the number of sub-modules.

[0101] There is a certain correlation relationship among the fault characteristic parameters of each sub-module when the equipment is designed. Inside the valve tower of the equipment, the change trends of the fault characteristic parameters of the sub-modules generally tend to be the same, but there are slight differences according to different equipment structure designs.

[0102] Therefore, the embodiment of the present invention adopts a spatial local estimation method to calculate the spatial autocorrelation index of the fault characteristic parameters, including:

[0103] Calculate the local Moran index of spatial association of the fault characteristic parameters based on the real-time values of the fault characteristic parameters of the sub-module; specifically, the local Moran index of spatial association of the fault characteristic parameters is calculated according to the following formula:

[0104]

[0105] In the formula, S 2 is the variance of the fault characteristic parameters, n is the number of sub-modules, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, x is the average value of the fault characteristic parameter, x j is the real-time value of the fault characteristic parameter of the j-th sub-module, ω ijis the spatial proximity weight coefficient between sub-module i and sub-module j, and d ij is the distance between sub-module i and sub-module j, and ε is the non-linear attenuation coefficient of the fault feature parameter.

[0106] Based on the spatial association local Moran index, calculate the spatial autocorrelation index of the fault feature parameter. Specifically, the spatial autocorrelation index of the fault feature parameter is determined by the following formula:

[0107]

[0108] In the formula, Z i is the spatial autocorrelation index of the fault feature parameter of the i-th sub-module, E(I i ) is the expectation of I i , VAR(I i ) is the variance of I i , and n is the number of sub-modules, is the average value of the spatial association local Moran indices of the fault feature parameters of all sub-modules.

[0109] Based on the spatial autocorrelation index, identify the faults of each sub-module, including:

[0110] Identify the fault feature parameter according to the design requirements of the flexible DC transmission equipment;

[0111] Based on the identification result of the fault feature parameter, identify the faults of each sub-module.

[0112] Among them, identifying the fault feature parameter according to the design requirements of the flexible DC transmission equipment includes:

[0113] Determine the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment;

[0114] Based on the confidence level, combine the statistical distribution type of the fault feature parameter to determine the acceptance region of the spatial autocorrelation index;

[0115] Judge whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determine that the fault feature parameter is in the normal state; otherwise, determine that the fault feature parameter is in the abnormal state.

[0116] The statistical distribution type followed by the fault feature parameter is determined according to the design requirements of the flexible DC transmission equipment. In the embodiment of the present invention, the statistical distribution type followed by the fault feature parameter is the normal distribution. For the normal distribution, the relationship between the confidence level α and the acceptance region of the spatial autocorrelation index Z i of the fault feature parameter is shown in Table 1:

[0117] Table 1

[0118] Confidence level α <![CDATA[Acceptance region of statistic Z i > 0.1 <![CDATA[-1.64 < Z i <1.64]]> 0.05 <![CDATA[-1.96 < Z i <1.96]]> 0.01 <![CDATA[-2.57 < Z i <2.57]]>

[0119] Spatial autocorrelation index Z of fault characteristic parameters i In the acceptance region, the change of the fault characteristic parameters of the sub-module i corresponding to the surface is not significant in the set of all sub-module temperatures; otherwise, it indicates that the change of the fault characteristic parameters of the sub-module i is significant.

[0120] Among them, the faults of each sub-module are identified based on the identification results of the fault characteristic parameters, including:

[0121] 1) When all the fault characteristic parameters of the sub-module are in the normal state, it is determined that the sub-module is in the normal operation state;

[0122] 2) When any one of the fault characteristic parameters of the sub-module is in the abnormal state and the delay time of the fault characteristic parameter in the abnormal state and the inverse time constant satisfy the preset relationship, it is determined that the sub-module is in the fault state;

[0123] Among them, the preset relationship is determined according to the following formula:

[0124]

[0125] In the formula, t i is the delay time when the fault characteristic parameter of the i-th sub-module is in the abnormal state, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, and x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance ability of the sub-module to the fault characteristic parameter.

[0126] Embodiment 2

[0127] Based on the same inventive concept, Embodiment 2 of the present invention further provides a fault identification device for a flexible DC transmission device, as Figure 2 shown, and the functions of each component will be described in detail below:

[0128] The data processing module is used to determine the fault characteristic parameters of each sub-module through the information in the sub-module;

[0129] The calculation module is used to calculate the spatial autocorrelation index of the fault characteristic parameters;

[0130] The identification module is used to identify the faults of each sub-module based on the spatial autocorrelation index;

[0131] The fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

[0132] The data processing module is specifically used for:

[0133] The acquisition module is used to collect the temperature of the sub-module through the temperature sensor in the sub-module, and collect the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through the high-potential board card in the sub-module;

[0134] The processing unit is used to determine the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determine the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

[0135] The calculation module includes:

[0136] The first calculation unit is used to calculate the spatial association local Moran index of the fault characteristic parameters based on the real-time value of the fault characteristic parameters of the sub-module;

[0137] The second calculation unit is used to calculate the spatial autocorrelation index of the fault characteristic parameters based on the spatial association local Moran index.

[0138] The identification module is specifically used for:

[0139] The parameter identification unit is used to identify the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment;

[0140] The fault identification unit is used to identify the faults of each sub-module based on the identification results of the fault characteristic parameters.

[0141] The parameter identification unit is specifically used for:

[0142] Determine the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment;

[0143] Based on the confidence level, combine the statistical distribution type of the fault characteristic parameters to determine the acceptance region of the spatial autocorrelation index;

[0144] Judge whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determine that the fault characteristic parameters are in the normal state; otherwise, determine that the fault characteristic parameters are in the abnormal state.

[0145] The fault identification unit is specifically used for:

[0146] When all the fault characteristic parameters of the sub-module are in the normal state, determine that the sub-module is in the normal operation state;

[0147] When any one of the fault characteristic parameters of the sub-module is in the abnormal state and the delay time of the fault characteristic parameter in the abnormal state and the inverse time constant satisfy the preset relationship, determine that the sub-module is in the fault state.

[0148] The fault identification unit determines the preset relationship according to the following formula:

[0149]

[0150] where t i is the delay time when the fault characteristic parameter of the i-th sub-module is in an abnormal state, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, and x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance of the sub-module to the fault characteristic parameter.

[0151] The first calculation unit calculates the spatial association local Moran index of the fault characteristic parameter according to the following formula:

[0152]

[0153] where S 2 is the variance of the fault characteristic parameter, n is the number of sub-modules, x i is the real-time value of the fault characteristic parameter of sub-module i, is the average value of the fault characteristic parameter, x j is the real-time value of the fault characteristic parameter of sub-module j, ω ij is the spatial proximity weight coefficient between sub-module i and sub-module j, and d ij is the distance between sub-module i and sub-module j, and ε is the non-linear attenuation coefficient of the fault characteristic parameter.

[0154] The second calculation unit calculates the spatial autocorrelation index of the fault characteristic parameter according to the following formula:

[0155]

[0156] where Z i is the spatial autocorrelation index of the fault characteristic parameter of the i-th sub-module, E(I i ) is the expectation of I i , and VAR(I i ) is the variance of I i .

[0157] The processing unit determines the capacitance value of the voltage-sharing capacitor according to the following formula:

[0158]

[0159] where C is the capacitance value of the voltage-sharing capacitor, Δv c is the ripple voltage of the voltage-sharing capacitor, and i c is the ripple current of the voltage-sharing capacitor;

[0160] The processing unit determines the voltage-sharing ratio of the sub-module according to the following formula:

[0161]

[0162] where η iis the voltage equalization ratio of the i-th sub-module, v i is the voltage of the i-th sub-module, and n is the number of sub-modules.

[0163] For the convenience of description, each part of the above device is described separately as various modules or units according to its functions. Of course, when implementing the present application, the functions of each module or unit can be implemented in the same or multiple software or hardware.

[0164] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take 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.

[0165] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0166] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0167] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0168] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Those of ordinary skill in the art can still modify or equivalently replace the specific implementation manners of the present invention with reference to the above embodiments. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention is within the protection scope of the present invention pending approval of the application.

Claims

1. A method for identifying faults in a flexible DC transmission device, characterized in that, Including: Determine the fault characteristic parameters of each sub-module through the information in the sub-module; Calculate the spatial autocorrelation index of the fault characteristic parameters; Based on the spatial autocorrelation index, conduct fault identification for each sub-module, including: Identify the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment, including: Determine the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment; Based on the confidence level, combine the statistical distribution type of the fault characteristic parameters to determine the acceptance region of the spatial autocorrelation index; Judge whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determine that the fault characteristic parameters are in a normal state; otherwise, determine that the fault characteristic parameters are in an abnormal state; Based on the identification results of the fault characteristic parameters, conduct fault identification for each sub-module, including: When all the fault characteristic parameters of the sub-module are in a normal state, determine that the sub-module is in a normal operation state; When any one of the fault characteristic parameters of the sub-module is in an abnormal state and the delay time of the fault characteristic parameter in the abnormal state satisfies a preset relationship with the inverse time constant, determine that the sub-module is in a fault state; The preset relationship is determined according to the following formula: where t i is the delay time when the fault characteristic parameter of the i-th sub-module is in an abnormal state, x i is the real-time value of the fault characteristic parameter of the i-th sub-module, and x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance of the sub-module to the fault characteristic parameter; The fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

2. The fault identification method for flexible DC transmission equipment according to claim 1, characterized in that The determination of the fault characteristic parameters of each sub-module through the information in the sub-module includes: Collect the temperature of the sub-module through the temperature sensor in the sub-module, and collect the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through the high-potential board in the sub-module; Determine the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determine the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

3. The fault identification method for flexible DC transmission equipment according to claim 1, characterized in that The calculation of the spatial autocorrelation index of the fault characteristic parameters includes: Calculate the spatial association local Moran index of the fault characteristic parameters based on the real-time values of the fault characteristic parameters of the sub-module; Calculate the spatial autocorrelation index of the fault characteristic parameters based on the spatial association local Moran index.

4. The fault identification method for flexible DC transmission equipment according to claim 3, characterized in that The spatial association local Moran index of the fault characteristic parameters is calculated according to the following formula: Where S 2 is the variance of the fault feature parameter, n is the number of sub - modules, x i is the real - time value of the fault feature parameter of sub - module i, is the average value of the fault feature parameter, x j is the real - time value of the fault feature parameter of sub - module j, ω ij is the spatial proximity weight coefficient between sub - module i and sub - module j, and d ij is the distance between sub - module i and sub - module j, and ε is the non - linear attenuation coefficient of the fault feature parameter.

5. The fault identification method for flexible DC transmission equipment according to claim 4, wherein The spatial autocorrelation index of the fault characteristic parameters is determined according to the following formula: where Z i is the spatial autocorrelation index of the fault feature parameter of the i-th sub-module, E(I i ) is the expectation of I i , and VAR(I i ) is the variance of I i .

6. The method for identifying a flexible DC transmission equipment fault according to claim 2, wherein The capacitance value of the voltage-sharing capacitor is determined according to the following formula: where C is the capacitance value of the voltage-sharing capacitor, and Δv c is the ripple voltage of the voltage-sharing capacitor, and i c is the ripple current of the voltage-sharing capacitor; The voltage-sharing ratio of the sub-module is determined according to the following formula: Where η i is the voltage equalization ratio of the i-th sub-module, v i is the voltage of the i-th sub-module, and n is the number of sub-modules.

7. A fault identification device for a flexible DC transmission equipment, characterized in that, Including: A data processing module for determining the fault characteristic parameters of each sub-module through the information in the sub-module; A calculation module for calculating the spatial autocorrelation index of the fault characteristic parameters; An identification module for conducting fault identification for each sub-module based on the spatial autocorrelation index, including: Identify the fault characteristic parameters according to the design requirements of the flexible DC transmission equipment, including: Determine the confidence level of the spatial autocorrelation index according to the design requirements of the flexible DC transmission equipment; Based on the confidence level, combine the statistical distribution type of the fault characteristic parameters to determine the acceptance region of the spatial autocorrelation index; Judge whether the calculated spatial autocorrelation index belongs to the acceptance region. If so, determine that the fault characteristic parameters are in a normal state; otherwise, determine that the fault characteristic parameters are in an abnormal state; Identifying the faults of each sub-module based on the recognition result of the fault characteristic parameters, including: When all the fault characteristic parameters of the sub-module are in the normal state, it is determined that the sub-module is in the normal operation state; When any one of the fault characteristic parameters of the sub-module is in the abnormal state and the delay time of the fault characteristic parameter in the abnormal state satisfies a preset relationship with the inverse time constant, it is determined that the sub-module is in the fault state; The preset relationship is determined according to the following formula: Where t i is the delay time when the fault characteristic parameter of the i-th sub-module is in an abnormal state, and x i is the real-time value of the fault characteristic parameter of the i-th sub-module, x0 is the reference value of the fault characteristic parameter of the sub-module; c is the inverse time constant, which is determined based on the tolerance of the sub-module to the fault characteristic parameter; The fault characteristic parameters include the capacitance value of the voltage-sharing capacitor in the sub-module, the temperature of the sub-module, and the voltage-sharing ratio of the sub-module.

8. The fault identification device for flexible DC transmission equipment according to claim 7, characterized in that, The data processing module is specifically used for: The acquisition module is used to collect the temperature of the sub-module through the temperature sensor in the sub-module, and collect the voltage of the sub-module, the ripple voltage and ripple current of the voltage-sharing capacitor through the high-potential board card in the sub-module; The processing unit is used to determine the voltage-sharing ratio of the sub-module based on the voltage of the sub-module, and determine the capacitance value of the voltage-sharing capacitor based on the ripple voltage and ripple current.

9. The fault identification device for flexible DC transmission equipment according to claim 7, characterized in that, The calculation module includes: The first calculation unit is used to calculate the spatial association local Moran index of the fault characteristic parameters based on the real-time value of the fault characteristic parameters of the sub-module; The second calculation unit is used to calculate the spatial autocorrelation index of the fault characteristic parameters based on the spatial association local Moran index.

10. The fault identification device for flexible DC power transmission equipment according to claim 9, wherein The first calculation unit calculates the spatial association local Moran index of the fault characteristic parameters according to the following formula: Where S 2 is the variance of the fault characteristic parameter, n is the number of sub-modules, x i is the real-time value of the fault characteristic parameter of sub-module i, is the average value of the fault characteristic parameter, x j is the real-time value of the fault characteristic parameter of sub-module j, ω ij is the spatial proximity weight coefficient between sub-module i and sub-module j, and d ij is the distance between sub-module i and sub-module j, and ε is the non-linear attenuation coefficient of the fault characteristic parameter.

11. The fault identification device for flexible DC transmission equipment according to claim 10, characterized in that, The second calculation unit calculates the spatial autocorrelation index of the fault characteristic parameters according to the following formula: where Z i is the spatial autocorrelation index of the fault feature parameters of the i-th sub-module, and E(I i ) is the expectation of I i , and VAR(I i ) is the variance of I i .

12. The fault identification device for flexible DC transmission equipment according to claim 8, characterized in that, The processing unit determines the capacitance value of the voltage-sharing capacitor according to the following formula: Where C is the capacitance value of the voltage-sharing capacitor, and Δv c is the ripple voltage of the voltage-sharing capacitor, and i c is the ripple current of the voltage-sharing capacitor; The processing unit determines the voltage-sharing ratio of the sub-module according to the following formula: Where η i is the voltage equalization ratio of the i-th sub-module, v i is the voltage of the i-th sub-module, and n is the number of sub-modules.

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