Fault studying and judging method and device of transformer substation, computer equipment and storage medium

Abstract

The invention is suitable for the technical field of power systems, and provides a fault studying and judging method and device of a transformer substation, computer equipment and a storage medium, and the fault studying and judging method of the transformer substation comprises the steps: obtaining standard model information sent by at least one measurement and control device, and determining an edge calculation result based on the standard model information, a signal incidence matrix is constructed based on an edge calculation result, and fault research and judgment are performed based on the signal incidence matrix, so that fault research and judgment can be performed automatically, quickly and accurately.

Description

Technical Field

[0001] The present application belongs to the technical field of power systems, and in particular, relates to a fault analysis method, device, computer equipment and storage medium for a substation. Background Art

[0002] As an important data collection and control equipment in substations, measurement and control devices are not only huge in number and require intensive information collection and transmission, but also quite complex to maintain. At present, the troubleshooting of substation measurement and control devices mainly relies on on-site inspection and manual analysis by operation and maintenance personnel, and the operation and maintenance efficiency is still not accurate. Summary of the invention

[0003] The embodiments of the present application provide a substation fault analysis method, device, computer equipment and storage medium, which can solve the technical problems in the prior art that the fault detection of substation measurement and control devices mainly relies on on-site inspection and manual analysis by operation and maintenance personnel, and the operation and maintenance efficiency is inaccurate.

[0004] In a first aspect, an embodiment of the present application provides a fault analysis method for a substation, comprising:

[0005] Obtaining standard model information sent by at least one measurement and control device;

[0006] Determine an edge computing result based on the standard model information;

[0007] Constructing a signal correlation matrix based on the edge computing results;

[0008] Fault analysis is performed based on the signal correlation matrix.

[0009] In a possible implementation manner of the first aspect, the standard model information includes at least one of the following:

[0011] The first standard model signal associated with the full station network;

[0012] The second standard model signal associated with the timing anomaly;

[0013] A third standard model signal related to the state of the electric device.

[0014] In a possible implementation manner of the first aspect, determining the edge computing result based on the standard model information includes:

[0015] If the target standard model information sent by the target measurement and control device contains the first standard model signal, the power equipment associated with the target measurement and control device is obtained, and the first edge computing result of the associated power equipment is obtained; wherein the target measurement and control device and the associated power equipment are in the same network;

[0016] If the target standard model information sent by the target measurement and control device contains the second standard model signal, obtaining a second edge computing result of the target measurement and control device;

[0017] If the third standard model signal exists in the target standard model information sent by the target measurement and control device, the third edge computing result of the target measurement and control device is obtained.

[0018] In a possible implementation manner of the first aspect, the acquiring the electric power equipment associated with the target measurement and control device includes:

[0019] Based on the pre-built substation network topology, the power equipment associated with the target measurement and control device is obtained; wherein the substation network topology is a plant SV and GOOSE network topology built based on a virtual switch.

[0020] In a possible implementation manner of the first aspect, constructing a signal correlation matrix based on the edge computing result includes:

[0021] Constructing a plant-level signal network association matrix based on the first edge computing result;

[0022] Constructing a network-free plant-level signal correlation matrix based on the second edge computing result;

[0023] A device-level signal correlation matrix is ​​constructed based on the third edge computing result.

[0024] In a possible implementation manner of the first aspect, the performing fault analysis based on the signal correlation matrix includes:

[0025] Constructing a graph database based on the signal association matrix;

[0026] Fault analysis is performed based on the graph database.

[0027] In a possible implementation manner of the first aspect, constructing a signal correlation matrix based on the edge computing result includes:

[0028] If the second edge computing result and the third edge computing result exist at the same time, the plant-level signal network association matrix is ​​constructed based on the second edge computing result and the third edge computing result.

[0029] In a second aspect, an embodiment of the present application provides a fault analysis device for a substation, including:

[0030] An acquisition module, used to acquire standard model information sent by at least one measurement and control device;

[0031] A determination module, configured to determine an edge computing result based on the standard model information;

[0032] A construction module, used to construct a signal correlation matrix based on the edge computing result;

[0033] The analysis module is used to perform fault analysis based on the signal correlation matrix.

[0034] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the substation fault analysis method described in any one of the first aspects above is implemented.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the substation fault analysis method described in any one of the first aspects above is implemented.

[0036] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a computer device, the computer device executes the substation fault analysis method described in any one of the above-mentioned first aspects.

[0037] In an embodiment of the present application, standard model information sent by at least one measurement and control device is obtained, edge computing results are determined based on the standard model information, a signal correlation matrix is ​​constructed based on the edge computing results, and fault analysis is performed based on the signal correlation matrix, so that fault analysis can be performed automatically, quickly and accurately.

[0038] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 It is a schematic diagram of an application environment provided by an embodiment of the present application;

[0041] Figure 2 It is a flowchart of a fault analysis method for a substation provided by an embodiment of the present application;

[0042] Figure 3It is a schematic diagram of the circuit structure of an open loop provided in an embodiment of the present application;

[0043] Figure 4 It is a schematic diagram of a graph database for fault analysis provided by an embodiment of the present application;

[0044] Figure 5 It is a structural schematic diagram of a fault analysis device for a substation provided in an embodiment of the present application;

[0045] Figure 6 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0047] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0048] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0049] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0050] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0051] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0052] The present application provides a fault analysis method for a substation, which can be applied to Figure 1 In the application environment shown, the measurement and control device 101 sends the standard model information to the main station 102, and the main station 102 performs fault analysis based on the standard model information to obtain the fault type or fault location.

[0053] Figure 2 A schematic flow chart of a fault analysis method for a substation provided in the present application is shown.

[0054] S201, obtaining standard model information sent by at least one measurement and control device.

[0055] The measurement and control device is placed in the secondary room of the substation as the data source. It can collect data and provide fault diagnosis services. Optionally, the measurement and control device adopts the standard model of the intelligent electronic device capability description file (IEDCapability Description, ICD) in the specification without changing the original signal point.

[0056] The measurement and control device supports three data (i.e. standard model information) uploading methods. Specifically:

[0057] Trigger upload: A data upload mechanism based on changes. When the measurement value or its quality changes, the latest standard model information is automatically sent.

[0058] General move uploading: data uploading method of response command. When receiving the general move instruction from the master station, the current standard model information is reported.

[0059] Periodic upload: scheduled data upload service, which sends standard model information regularly according to the time interval set by the master station.

[0060] The above three uploading methods can be executed in parallel, that is, the three standard model information uploaded based on the three above methods can be uploaded in parallel.

[0061] Among them, the standard model information is information defined based on the current state grid enterprise standards and power industry standards, and is a conventional power system measurement value.

[0062] Standard Model information is based on Figure 1 DL / T860 report service is uploaded.

[0063] In an optional embodiment, the standard model information includes at least one of the following: a first standard model signal related to the entire station network (also referred to as a network-related standard DL / T860 model measurement value); a second standard model signal related to timing anomalies (also referred to as a timing anomaly-related standard DL / T860 model measurement value); a third standard model signal related to the state of the power equipment (also referred to as a standard DL / T860 model measurement value related to the state of the power equipment).

[0064] Among them, the third standard model signal related to the state of the power equipment can be used to reflect the operating state and potential problems of the power equipment, such as PT disconnection (Potential Transformer open circuit) and CT disconnection (Current Transformer open circuit), which are the third standard model signals.

[0065] In an optional embodiment, the first standard model signal includes at least one of the following: GOOSE general alarm, SV general alarm, station control layer GOOSE communication interruption, process layer GOOSE communication interruption, SV out of step; the second standard model signal includes at least one of the following: timing signal status, timing service status, time jump frame status; the third standard model signal includes at least one of the following: PT line break, CT line break.

[0066] S202: Determine edge computing results based on the standard model information.

[0067] Among them, edge computing refers to providing computing and other services close to the data source. The measurement and control device serves as the data source, and the fault diagnosis service it provides is the edge computing of fault diagnosis. Based on this service, each measurement and control device can obtain the corresponding edge computing results.

[0068] In an embodiment of the present application, the standard model information is first uploaded as described above, and after determining that the edge computing results are required based on the standard model information, the measurement and control device is called upon to upload the edge computing results.

[0069] In an optional embodiment, as described above, the standard model information is first uploaded, and after determining that the edge computing results are needed based on the standard model information, the measurement and control device is called upon to upload the edge computing results and custom measurement values. Based on the custom measurement values, the standard model information can be enriched to make the analysis and judgment results more accurate.

[0070] Among them, the custom measurement value is a data point that has positive significance for fault diagnosis, but it is not established through the DL / T860 model. This data point supports user extension. Typical custom measurement values ​​include abnormal recovery of the first board card and abnormal AD self-test.

[0071] Custom measurement values ​​and edge computing results are stored in files, uploaded based on the DL / T860 file service, written in CIM / E text format, and encoded in UTF-8.

[0072] Among them, custom measurement values ​​can also be uploaded regularly.

[0073] In an optional embodiment, if the first standard model signal exists in the target standard model information sent by the target measurement and control device, the power equipment associated with the target measurement and control device is obtained, and the first edge computing result of the associated power equipment is obtained; wherein the target measurement and control device and the associated power equipment are in the same network;

[0074] If the target standard model information sent by the target measurement and control device contains the second standard model signal, obtaining a second edge computing result of the target measurement and control device;

[0075] If the third standard model signal exists in the target standard model information sent by the target measurement and control device, the third edge computing result of the target measurement and control device is obtained.

[0076] The target measurement and control device is one of the at least one measurement and control device. The target standard model information is one of the at least one standard model information.

[0077] In the embodiment of the present application, as described above, the standard model information includes at least one of the following: GOOSE general alarm, SV general alarm, station control layer GOOSE communication interruption, process layer GOOSE communication interruption, SV desynchronization, timing signal status, timing service status, time jump frame status, PT disconnection, CT disconnection. After receiving the standard model information, the master station analyzes it. The specific analysis is as follows:

[0078] In the first case, if any of the following conditions exists in the standard model information A1: GOOSE general alarm, SV general alarm, station control layer GOOSE communication interruption, process layer GOOSE communication interruption, and SV desynchronization (equivalent to the existence of the first standard model signal in the standard model information), the standard model information A1 is determined as the target standard model information. The standard model information usually includes an identifier of the measurement and control device to identify which measurement and control device sent the standard model information. Based on the identifier, the target measurement and control device corresponding to the target standard model information is determined. Based on the target measurement and control device, the first edge computing result of the associated power equipment is obtained.

[0079] Among them, the target measurement and control device and the associated power equipment are in the same network.

[0080] Optionally, the first edge computing result is only an edge computing result of the associated power equipment, or may be an edge computing result including the target measurement and control device and the associated power equipment.

[0081] Among them, the power equipment can also be called network equipment.

[0082] Among them, based on custom rules, the edge computing results are stored in the measurement and control device in the form of files, and the master station can call them through the DL / T860 protocol.

[0083] Among them, the custom rules adopt a flat logic calculation method based on common state extraction. The specific implementation process is: classify faults based on engineering maintenance and failure analysis records. For each type of fault, establish a hierarchical equipment state from top to bottom according to the scope of its impact, including: device layer state, board layer state, and chip layer state. Sort out all non-bottom-level device states and extract public attributes for them (that is, find out the common points between them and extract these common state attributes). Based on the above extracted attributes, establish a public state logic from bottom to top. Finally, form a flat edge computing logic for each fault classification. This logic only contains the bottom-level state and the public state. In this way, the flat logic presented to the user reduces repeated calculations and facilitates user understanding and rule formulation.

[0084] In an optional embodiment, during edge computing, the process is: trigger edge computing through alarm signals (GOOSE general alarm, SV general alarm, station control layer GOOSE communication interruption, process layer GOOSE communication interruption, SV out of step, timing signal status, timing service status, time jump frame status, PT disconnection, CT disconnection), typically device failure, SV alarm, GOOSE alarm; read custom rules to directly obtain the bottom-level status, and calculate the corresponding public status through public status logic; traverse all fault categories, and implement fault logic analysis based on the bottom-level status and public status.

[0085] When some faults are difficult to accurately judge based on existing equipment, the requirements of edge computing can be met by upgrading the software and hardware. For example, for the export loop, a method for judging the export status is designed based on the external remote control triggering the internal complex programmable logic device (CPLD). Figure 3 As shown in the open circuit, each export circuit corresponds to a status recovery circuit. The circuit contains CPLD input and output signals, export relays, transistors, and resistors. When there is a remote control export outside, the CPLD exports the signal and triggers the export status information collection at the same time, and performs logical AND judgment on it. If the export status is inconsistent with the recovery status within a certain period of time, it is judged that there is a hardware abnormality in the circuit, otherwise it is judged that the circuit is normal.

[0086] In an optional embodiment, obtaining the electric power equipment associated with the target measurement and control device includes:

[0087] Based on a pre-built substation network topology, the power equipment associated with the target measurement and control device is obtained; wherein the substation network topology is a plant sampled value (Sampled Values, SV) and a generic object oriented substation event (Generic Object Oriented Substation Event, GOOSE) network topology constructed based on a virtual switch.

[0088] In actual power plants, the network physical devices of SV and GOOSE include merging units / intelligent terminals, switches, and measurement and control devices. However, the conventional substation configuration description (SCD) file mainly includes the association between the merging unit and the measurement and control device, or includes the association between the intelligent terminal and the measurement and control device, and there is no switch information. To this end, a method for establishing SV and GOOSE network topology based on virtual switches is proposed. Specifically: use the eXtensible Markup Language (XML) parsing library (such as Python's lxml library) to load and parse the SCD file, extract the connection information of the virtual circuit (i.e., virtual circuit information), including the merging unit, the intelligent terminal, and the connection relationship between them and the measurement and control device; according to the extracted virtual circuit information, identify the network devices that need to be connected, such as the merging unit, the intelligent terminal, and the measurement and control device; according to the identified network devices and their connection relationship, establish the network connection between the merging unit / intelligent terminal and the measurement and control device. Then, determine the name and purpose of the two virtual switches to be created, such as VSwitch_A and VSwitch_B according to the keywords A and B respectively. Create two virtual switches. Parse the naming keywords of the merging unit / intelligent terminal, for example, search for keyword A or B. Divide the network devices into two groups according to the keywords, one group is associated with VSwitch_A, and the other group is associated with VSwitch_B. For each group of network devices, configure its network connection properties to connect it to the corresponding virtual switch. The substation network topology can be constructed in the above way.

[0089] In an embodiment of the present application, based on a pre-constructed substation network topology, all power equipment in the network is traversed with a virtual switch as the center, and the power equipment associated with the target measurement and control device is matched.

[0090] S203: construct a signal correlation matrix based on the edge computing result.

[0091] In an embodiment of the present application, a plant-level signal network association matrix is ​​constructed based on the first edge computing result; a plant-level signal association matrix without a network is constructed based on the second edge computing result; and a device-level signal association matrix is ​​constructed based on the third edge computing result.

[0092] In an embodiment of the present application, if the first standard model signal exists in the target standard model information sent by the target measurement and control device, the power equipment associated with the target measurement and control device is obtained, and the first edge computing result of the associated power equipment is obtained, and a plant-level signal network association matrix is ​​constructed based on the first edge computing result. If the second standard model signal exists in the target standard model information sent by the target measurement and control device, the second edge computing result of the target measurement and control device is obtained, and a plant-level signal association matrix without a network is constructed based on the second edge computing result. If the third standard model signal exists in the target standard model information sent by the target measurement and control device, the third edge computing result of the target measurement and control device is obtained, and a device-level signal association matrix is ​​constructed based on the third edge computing result.

[0093] Wherein, constructing a device-level signal correlation matrix based on the third edge computing result includes:

[0094] For the third standard model signal sent by DL / T860, the internal signal correlation equation of the device is established based on the public rules of the master station; for the information sent by edge computing (this information is the local analysis result of the device, that is, the third edge computing result), since the fault analysis result has been formed, it can be directly established as a one-to-one correlation equation between the alarm signal (that is, the third standard model signal, such as PT line break) and the fault result.

[0095] Among them, the device-level signal correlation matrix is ​​as follows:

[0096]

[0097] Among them, establishing the device internal level signal correlation equation based on the master station public rule means that the device internal signal correlation matrix can be configured at the master station using a public configuration method, that is, the same type of equipment uses the same rule.

[0098] Among them, the above-mentioned fault results refer to the final results, which refer to the final analysis results formed by the master station side based on the master station public rules and the edge computing results of the call.

[0099] Among them, the device in the above device internal level signal correlation equation can also be called a measurement and control device.

[0100] Wherein, constructing a plant-level signal correlation matrix without a network based on the second edge computing result (i.e., constructing a signal correlation matrix independent of the network architecture) includes:

[0101] For the second standard model signal sent by DL / T860, it is divided into intersection signals and non-intersection signals (intersection signals refer to the same type of signals generated when multiple devices share signal inputs, such as time jump signals, synchronization service status, CT disconnection, PT disconnection, etc., and non-intersection refers to the signal input unique to the device, such as the service status of the object under test), and the intersection signal association equation of the whole station device level is established, that is, all the same alarm signals of the plant and station are formed or logically associated, and the initial weight of each alarm signal participating in the logic is the same, which supports weight adjustment according to the actual wiring situation; the equation is used as a row in the association matrix; for the second standard model signal sent by DL / T860 and the edge computing results, the association equation is established by referring to the method of constructing the device-level signal association matrix based on the third edge computing results, and the association equations of these three types of equations (device internal level signal association equations, one-to-one corresponding association equations between alarm signals and fault results, and whole station device-level intersection signal association equations) are established to form a plant-level signal association matrix without a network.

[0102] Among them, the plant-level signal correlation matrix without network is as follows:

[0103]

[0104] Among them, from left to right are the signal state matrix, weight matrix, and device matrix.

[0105] Wherein, constructing a plant-level signal network association matrix based on the first edge computing result includes:

[0106] The pre-built substation network topology filters out the merging units, intelligent terminals, measurement and control devices, and switches belonging to this network; for the measurement and control equipment of this network, establish its SV or GOOSE intersection signal association equation; at the same time, for the first standard model signal sent by DL / T860 and the edge computing results, refer to the method of constructing the device-level signal association matrix based on the third edge computing result to establish the association equation.

[0107] Among them, the plant-level signal network association matrix is ​​as follows:

[0108]

[0109] For ease of understanding, here we use Figure 4Take 1 as an example. Associate the node "Measurement and Control X GOOSE General Alarm" with the node "Switch X Associated Device Status", "Measurement and Control X Edge Computing Result" with "Device Network Port Abnormality or Switch Failure", "Device Network Port Abnormality or Switch Failure" with "Switch X Status", "Switch X Associated Device Status" with "Switch X Status", and "Switch X Status" with "Switch 1 Failure" to complete the graph construction. Secondly, when the measurement and control 1 GOOSE general alarm signal is triggered, the operation and maintenance master station retrieves the GOOSE general alarm information of other measurement and control devices, and simultaneously calls up the edge computing results of each measurement and control. Finally, retrieve the nodes related to the GOOSE general alarm signal in the graph database to form a graph. According to the status results of each signal, eliminate the non-fault results, and obtain the final possible cause of the fault as the failure of switch 1.

[0110] In an optional embodiment, if the second edge computing result and the third edge computing result exist at the same time, the plant-level signal network association matrix is ​​constructed based on the second edge computing result and the third edge computing result.

[0111] Specifically: If the first standard model signal (i.e., any one of the GOOSE general alarm, SV general alarm, GOOSE communication interruption at the station control layer, GOOSE communication interruption at the process layer, and SV out of sync) and the second standard model signal (any one of the timing signal status, timing service status, and time jump frame status) both exist at the same time, if this occurs, the first standard model signal logic will be used for processing, and the second standard model signal (the existence of the second standard model signal indicates that there is an equipment abnormality) is only a part of the plant-level signal network association matrix involved in the judgment, that is, the second standard model signal is summarized in the plant-level signal association matrix.

[0112] S204: Perform fault analysis based on the signal correlation matrix.

[0113] Specifically, a graph database is constructed based on the signal correlation matrix, and fault analysis is performed based on the graph database.

[0114] In an embodiment of the present application, a graph database is constructed based on a signal association matrix, and the fault cause corresponding to the alarm signal (i.e., the specific signal in the standard model signal above) is retrieved based on the graph database. At the same time, the fault analysis result (i.e., the final analysis result formed above) is calculated based on the association matrix, and the fault analysis result includes the fault type and fault probability (weight).

[0115] In addition to the real-time status analysis results, the fault analysis results of time-space coupling relationship are also available. The time-space coupling relationship fault analysis results can facilitate users to check the trend of fault occurrence, and can improve the fault analysis rules according to the trend to make it more accurate.

[0116] For the fault analysis results of the time-space coupling relationship, the signal association matrix in the graph database is used to retrieve the signal status information in the history library. The fault analysis results and their distribution probability at the historical moment are calculated based on the signal status information, and the fault occurrence trajectory in the entire historical process is drawn to obtain the fault analysis results of the time-space coupling relationship.

[0117] Among them, the signal status information mainly refers to the signal value sent by the standard model and the fault analysis results stored historically.

[0118] In an optional embodiment, the fault analysis result can be modified, including adding analysis rules, eliminating erroneous results, modifying the proportion of analysis results, etc.

[0119] In the embodiment of the present application, firstly, the data related to the fault analysis of the measurement and control device are sorted out, and for the uploading part that cannot be based on the report service of the standard DL / T860 model, that is, the custom measurement value, modeling and data collection are realized in the form of files; secondly, the fault analysis knowledge graph of the measurement and control device is constructed based on the custom measurement value; thirdly, when the alarm event is triggered (that is, the first standard model signal, the second standard model signal, or the third standard model signal is detected), the measurement and control device completes the edge calculation on this side, obtains the edge calculation result, realizes the local fault analysis, and obtains the local fault analysis result of the measurement and control device side (based on the fault analysis of the measurement and control device). At the same time, the host simultaneously obtains the standard model information sent by the standard DLT / 860 model (based on the first standard model signal sent by the report service, the second standard model signal sent by the file service, and the third standard model signal sent by the file service) to form the fault analysis result of the host side knowledge graph; finally, the main station simultaneously displays the fault analysis result of the host side knowledge graph and the on-site fault analysis result of the measurement and control device side), performs operation and maintenance analysis, judgment and output based on the displayed data, and can also update the entity association relationship and the weight of each fault analysis node in the knowledge graph according to the judgment result, so as to continuously improve the diagnosis accuracy.

[0120] In addition, in the prior art, due to the limited number of channels sent by the measurement and control device, and the model standardization work adopted in some regions, when using the knowledge graph for fault analysis based on the existing data, problems such as small number of entities and poor accuracy of analysis will be faced. Therefore, it is considered to realize the edge computing function on the measurement and control device side, that is, to conduct edge-side fault analysis based on its own real-time information, obtain the local fault analysis result on the measurement and control device side (that is, the edge computing result mentioned above), and synchronize the edge computing result as the data source of the knowledge graph on the host side. At the same time, in view of the problem of the small number of knowledge graphs, a method of expansion in the form of files is proposed, so that the signals sent by the non-compliant reporting service can be sent to the main station to improve the accuracy of the analysis.

[0121] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0122] Corresponding to the fault analysis method of the substation described in the above embodiment, Figure 5 A structural block diagram of a fault analysis device for a substation provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0123] Reference Figure 5 , the fault analysis device of the substation includes:

[0124] An acquisition module, used to acquire standard model information sent by at least one measurement and control device;

[0125] A determination module, configured to determine an edge computing result based on the standard model information;

[0126] A construction module, used to construct a signal correlation matrix based on the edge computing result;

[0127] The analysis module is used to perform fault analysis based on the signal correlation matrix.

[0128] In a possible implementation manner, the standard model information includes at least one of the following:

[0129] The first standard model signal associated with the full station network;

[0130] The second standard model signal associated with the timing anomaly;

[0131] A third standard model signal related to the state of the electric device.

[0132] In a possible implementation, the determination module is used to:

[0133] If the target standard model information sent by the target measurement and control device contains the first standard model signal, the power equipment associated with the target measurement and control device is obtained, and the first edge computing result of the associated power equipment is obtained; wherein the target measurement and control device and the associated power equipment are in the same network;

[0134] If the target standard model information sent by the target measurement and control device contains the second standard model signal, obtaining a second edge computing result of the target measurement and control device;

[0135] If the third standard model signal exists in the target standard model information sent by the target measurement and control device, the third edge computing result of the target measurement and control device is obtained.

[0136] In a possible implementation, the determination module is used to:

[0137] Based on the pre-built substation network topology, the power equipment associated with the target measurement and control device is obtained; wherein the substation network topology is a plant SV and GOOSE network topology built based on a virtual switch.

[0138] In one possible implementation, the building blocks are used to:

[0139] Constructing a plant-level signal network association matrix based on the first edge computing result;

[0140] Constructing a network-free plant-level signal correlation matrix based on the second edge computing result;

[0141] A device-level signal correlation matrix is ​​constructed based on the third edge computing result.

[0142] In one possible implementation, the building blocks are used to:

[0143] If the second edge computing result and the third edge computing result exist at the same time, the plant-level signal network association matrix is ​​constructed based on the second edge computing result and the third edge computing result.

[0144] In a possible implementation, the analysis and judgment module is used to:

[0145] Constructing a graph database based on the signal association matrix;

[0146] Fault analysis is performed based on the graph database.

[0147] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0148] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0149] An embodiment of the present application also provides a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps in any of the above-mentioned method embodiments when executing the computer program.

[0150] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0151] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0152] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0153] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0154] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0155] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0156] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0157] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

[0158] Figure 6 This is a schematic diagram of the structure of a computer device provided in one embodiment of the present application. Figure 6 As shown, the computer device of this embodiment includes: at least one processor 20 ( Figure 6 Only one is shown), a memory 21 and a computer program 22 stored in the memory 21 and executable on the at least one processor 20, wherein the processor 20 implements the steps in any of the above-mentioned embodiments of the fault analysis method for each substation when executing the computer program 22.

[0159] The computer device may include, but is not limited to, a processor 20 and a memory 21. Those skilled in the art will appreciate that Figure 6 It is only an example of a computer device and does not constitute a limitation of the computer device. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0160] The processor 20 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0161] In some embodiments, the memory 21 may be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory 21 may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device. Further, the memory 21 may also include both an internal storage unit of the computer device and an external storage device. The memory 21 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 21 may also be used to temporarily store data that has been output or is to be output.

[0162] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A fault analysis method for a substation, characterized in that: include: Obtaining standard model information sent by at least one measurement and control device; Determine an edge computing result based on the standard model information; Constructing a signal correlation matrix based on the edge computing results; Fault analysis is performed based on the signal correlation matrix.

2. The fault analysis method of a substation according to claim 1, characterized in that: The standard model information includes at least one of the following: The first standard model signal associated with the full station network; The second standard model signal associated with the timing anomaly; A third standard model signal related to the state of the electric device.

3. The fault analysis method of a substation according to claim 2, characterized in that: The determining the edge computing result based on the standard model information includes: If the target standard model information sent by the target measurement and control device contains the first standard model signal, the power equipment associated with the target measurement and control device is obtained, and the first edge computing result of the associated power equipment is obtained; wherein the target measurement and control device and the associated power equipment are in the same network; If the target standard model information sent by the target measurement and control device contains the second standard model signal, obtaining a second edge computing result of the target measurement and control device; If the third standard model signal exists in the target standard model information sent by the target measurement and control device, the third edge computing result of the target measurement and control device is obtained.

4. The fault analysis method of a substation according to claim 3, characterized in that: The obtaining of the electric power equipment associated with the target measurement and control device comprises: Based on the pre-built substation network topology, the power equipment associated with the target measurement and control device is obtained; wherein the substation network topology is a plant SV and GOOSE network topology built based on a virtual switch.

5. The fault analysis method for a substation according to claim 3 or 4, characterized in that: The constructing a signal correlation matrix based on the edge computing result includes: Constructing a plant-level signal network association matrix based on the first edge computing result; Constructing a network-free plant-level signal correlation matrix based on the second edge computing result; A device-level signal correlation matrix is ​​constructed based on the third edge computing result.

6. The fault analysis method of a substation according to claim 5, characterized in that: The performing fault analysis based on the signal correlation matrix includes: Constructing a graph database based on the signal association matrix; Fault analysis is performed based on the graph database.

7. The fault analysis method of a substation according to claim 5, characterized in that: The constructing a signal correlation matrix based on the edge computing result includes: If the second edge computing result and the third edge computing result exist at the same time, the plant-level signal network association matrix is ​​constructed based on the second edge computing result and the third edge computing result.

8. A fault analysis device for a substation, characterized in that: include: An acquisition module, used to acquire standard model information sent by at least one measurement and control device; A determination module, configured to determine an edge computing result based on the standard model information; A construction module, used to construct a signal correlation matrix based on the edge computing result; The analysis module is used to perform fault analysis based on the signal correlation matrix.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

Images