A signal assisted analysis and decision method and system for monitoring services

Abstract

The application discloses a signal auxiliary analysis and decision method and system for monitoring services, first acquires a mapping relationship of primary equipment and secondary signals, and constitutes an original data relationship chain; collects secondary signals in a time interval before and after a fault, forms a fault data evidence chain from the collected secondary signals; compares the fault data evidence chain with the original data relationship chain to obtain a preliminary fault diagnosis result; triggers the same fault through a power system simulation engine according to the preliminary fault diagnosis result to obtain corresponding triggered secondary signals; matches the triggered secondary signals with the fault data evidence chain to obtain a matching degree; judges whether the preliminary fault diagnosis result is verified according to the matching degree, and takes the verified preliminary fault diagnosis result as a final fault diagnosis result. The analysis result is presented to a monitor through a man-machine interface, which helps the monitor to quickly and accurately analyze signals and locate a fault type.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of power dispatching application, and particularly relates to a signal auxiliary analysis and decision method for monitoring business, and further relates to a signal auxiliary analysis and decision system for monitoring business, which is used for assisting dispatching and control operation personnel to quickly and accurately locate, analyze and process various faults and abnormalities. BACKGROUND

[0002] The adoption of the "dispatching-integrated" operation management mode makes the entire power grid dispatching change towards the "big operation" target mode of integrated dispatching, monitoring and operation, intensification and lean management, and makes the existing power grid dispatching and equipment operation monitoring functions integrated, accelerates the integration of power grid dispatching and operation monitoring functions, and establishes an intensive power grid operation management mode with the power grid dispatching and control center as the hub.

[0003] The number of access stations has increased sharply, and the types of devices and the number of signals that need to be mastered are very large, and most of the monitoring personnel do not have the experience of mastering so many substation device conditions at the same time.

[0004] The various signals monitored by the dispatching and control center frequently act, especially when the power grid fails, a large number of signals make the monitoring personnel dazzled and confused, and important signals are easily missed, delaying accident handling. The signals uploaded by the substation have problems: the secondary signal naming is not standardized, the false and refused reports of the alarm information, the repeated alarm, and the lack of correlation between the alarm information.

[0005] At present, the monitoring personnel mainly analyze and handle the monitoring alarm signals by checking the monitoring alarm signals through the SCADA monitoring system. The SCADA monitoring system is used to monitor the monitoring signals uploaded by each substation. Although the monitoring system classifies the signals according to accidents, abnormalities, and notifications, the monitoring personnel still need to sort out and analyze a large number of monitoring alarm signals.

[0006] Therefore, a signal auxiliary analysis and decision system for monitoring business is established to solve the problem that the monitoring personnel cannot easily analyze and decide in the face of complex monitoring signals, which has important positive significance for realizing the fast and efficient handling of faults and abnormalities by the dispatching and control center. SUMMARY

[0007] The present application aims to overcome the deficiencies in the prior art, and provides a signal auxiliary analysis and decision method and system for monitoring business, which solves the technical problem that the real-time faults of dispatching cannot be analyzed and decided in the prior art.

[0008] In a first aspect, the present application provides a signal auxiliary analysis and decision method for monitoring business, which includes the following processes:

[0009] Obtaining a mapping relationship of primary and secondary devices and secondary signals, and constructing an original data relationship chain;

[0010] Collecting secondary signals in a time interval before and after the fault, and forming the collected secondary signals into a fault data evidence chain;

[0011] Comparing the fault data evidence chain with the original data relationship chain to obtain a preliminary fault diagnosis result;

[0012] Triggering a fault same as the preliminary fault diagnosis result through a power system simulation engine to obtain corresponding triggered secondary signals;

[0013] Matching the triggered secondary signals with the fault data evidence chain to obtain a matching degree;

[0014] Determining whether the preliminary fault diagnosis result passes the verification according to the matching degree, and taking the preliminary fault diagnosis result passing the verification as a final fault diagnosis result.

[0015] In combination with the first aspect, further, the obtaining of the mapping relationship of the primary and secondary devices and the secondary signals comprises:

[0016] Obtaining all primary and secondary devices and remote signaling data in the substation, and arranging and modeling the primary and secondary devices according to the dependency relationship;

[0017] Associating the secondary signals in each interval with the primary and secondary devices configured in the interval to form the mapping relationship.

[0018] In combination with the first aspect, further, the constructing of the original data relationship chain comprises:

[0019] Arranging typical fault types of the primary devices and the secondary signals in each typical fault according to the power system relay protection theory;

[0020] Grouping displacement signals, accident action signals and abnormal alarm information in the secondary signals to form the original data relationship chain.

[0021] In combination with the first aspect, further, the forming of the fault data evidence chain from the collected secondary signals comprises:

[0022] Classifying the collected secondary signals, grouping displacement signals and accident action signals into a group and sorting them according to the time of signal occurrence, grouping other abnormal alarm information into a group to form the fault data evidence chain of the fault secondary signals.

[0023] In combination with the first aspect, further, the matching of the triggered secondary signals with the fault data evidence chain comprises:

[0024] Matching the triggered secondary signals with physical numbers of displacement switches and accident action signals in the fault data evidence chain.

[0025] In a second aspect, the application provides a signal-assisted analysis and decision system for monitoring services, comprising an original data relationship chain establishment module, a fault data evidence chain establishment module, a preliminary fault diagnosis module, a fault simulation triggering module, a fault signal matching module, and a final fault diagnosis module, wherein:

[0026] The original data relationship chain establishment module is configured to obtain a mapping relationship between primary equipment and secondary signals, and to form an original data relationship chain.

[0027] The fault data evidence chain establishment module is configured to collect secondary signals within a time interval before and after a fault, and to form a fault data evidence chain from the collected secondary signals.

[0028] The preliminary fault diagnosis module is configured to compare the fault data evidence chain with the original data relationship chain, and to obtain a preliminary fault diagnosis result.

[0029] The fault simulation triggering module is configured to trigger a fault identical to the preliminary fault diagnosis result through a power system simulation engine, and to obtain corresponding triggered secondary signals.

[0030] The fault signal matching module is configured to match the triggered secondary signals with the fault data evidence chain, and to obtain a matching degree.

[0031] The final fault diagnosis module is configured to determine whether the preliminary fault diagnosis result is verified according to the matching degree, and to take the verified preliminary fault diagnosis result as a final fault diagnosis result.

[0032] In combination with the second aspect, further, in the fault data evidence chain establishment module, the formation of the fault data evidence chain from the collected secondary signals comprises:

[0033] The collected secondary signals are classified, the displacement signals and the incident action signals are coded into a group and sorted according to the time of signal occurrence, and other abnormal alarm information is coded into a group to form a fault data evidence chain of fault secondary signals.

[0034] In combination with the second aspect, further, in the fault signal matching module, the matching of the triggered secondary signals with the fault data evidence chain comprises:

[0035] The triggered secondary signals are matched with the physical numbers of the displacement switches and the incident action signals in the fault data evidence chain.

[0036] Compared with the prior art, the present application has the advantages that: the method and system of the present application collect SCADA system fault information, process the information through an expert system to form an evidence chain, and send the preliminary diagnosis result to a power system simulation engine, simulate the fault on the simulation system, send the fault information from the simulation system to the expert system for final diagnosis, and present the analysis result to the monitor through a man-machine interface, and show the accident evolution process to the control operation personnel through the visualization of the theme window and the decision tree, which greatly helps the monitor to quickly and accurately analyze the signal and locate the fault type, and provides the monitor with an accident treatment reference scheme. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 Fig. 1 is a structural block diagram of the intelligent power grid monitoring system of the present application;

[0038] Figure 2 Fig. 4 is a schematic diagram of the correlation relationship between the equipment and the signal;

[0039] Figure 3 Fig. 5 is a schematic diagram of the mapping relationship between the primary and secondary equipment and the secondary signal;

[0040] Figure 4 Fig. 6 is a flowchart of the modeling of the equipment and the signal;

[0041] Figure 5 Fig. 7 is a schematic diagram of the original data relationship of the typical fault and abnormal information;

[0042] Figure 6 Fig. 8 is a flowchart of the signal auxiliary analysis and decision method of the present application. DETAILED DESCRIPTION

[0043] The present application will be further described below in conjunction with the drawings. The following examples are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0044] The inventive concept of the present application is that: the SCADA monitoring system built by the power regulation center can collect telemetry and telesignalling data in normal and fault conditions in real time, and the power system simulation engine is a one-to-one simulation of the SCADA monitoring system, which can simulate the changes of power flow and telemetry and telesignalling in normal and fault conditions. On this basis, by analyzing the device and signal data exported by the basic database of the smart grid dispatching technical support system, a mapping relationship between primary and secondary devices and signals is established to form an expert system original data relationship chain. Real-time fault information is collected from the dispatching area SCADA system, including real-time information such as telemetry, primary device telesignalling, secondary monitoring signal, SOE, etc., which is transmitted to the expert system. Then, the collected information is compared and traced by the original data relationship chain for preliminary judgment of the fault and abnormal type and transmission to the power system simulation engine. The power system simulation engine triggers the fault, and the fault information from the power system simulation engine is transmitted to the expert system and compared with the real-time fault information collected from the dispatching area SCADA system to form a final diagnosis result to help the monitor to quickly and accurately analyze the fault phenomenon.

[0045] The expert system, the SCADA system and the power system simulation system interact with each other to form a monitoring signal auxiliary analysis and decision system.

[0046] The smart grid monitoring system of the present application is shown in Figure 1 The monitoring system is divided into an application layer, an engine layer, a model layer and a platform layer. Based on this system, the present application proposes a signal auxiliary analysis and decision method for monitoring business, as shown in Figure 6 The method comprises the following steps:

[0047] Step 1: Obtain the mapping relationship between primary and secondary devices and secondary signals to form an expert system original data relationship chain.

[0048] The method comprises the following steps:

[0049] 1) Substation device and signal modeling;

[0050] The smart grid dispatching technical support system basic platform establishes the correlation between substation secondary signal measurement and devices and intervals to realize the telesignalling function of substation devices and secondary systems, as shown in Figure 4 The substation device and signal modeling comprises the following steps:

[0051] All substation primary and secondary devices and telesignalling signal data are exported from the platform database to form a cime format document. The cime file format is as follows:

[0052]

Area

[0053] Area name Area ID

[0054] Plant

[0055] Plant name Plant ID Belonged region ID

[0056]

Interval

[0057] Interval name Interval ID Belonged plant ID

[0058]

Device

[0059] Device name Device ID Belonged plant ID Belonged interval ID

[0060]

Remote signal

[0061] Remote signal name Remote signal ID Belonged plant ID Belonged interval ID

[0062] The data in the cime document is classified and arranged according to the ownership relationship among remote signals, devices, intervals, plants and regions, forming a tree structure, as shown in Figure 2 , arranged in order of region, plant, interval, device and signal. Each plant has one branch of data, and each interval is deployed with multiple primary devices.

[0063] Modeling of primary and secondary devices for each plant: according to the device account and monitoring signal analysis, the configuration of primary and secondary devices is analyzed, and corresponding secondary devices are configured for each primary device. The format is as follows:

[0064] Plant ID Primary device name Primary device ID Secondary device name Secondary device number

[0065] Thus, the mapping relationship between primary and secondary devices is established. Primary devices include transformers, busbars, lines, and capacitors, and secondary device types include main transformer protection, busbar protection, line protection, circuit breaker protection, capacitive protection, measurement and control, operation box, and automatic device.

[0066] Each secondary signal in the interval is associated with the primary and secondary devices configured in the interval to form a mapping relationship, as shown in Figure 3 . The primary device under the plant is configured with two secondary devices, and the secondary device corresponds to multiple secondary device signals.

[0067] 2) Establishing the original data relationship chain

[0068] The above step establishes a mapping relationship of primary equipment, secondary equipment and secondary signals. According to the power system relay protection theory, typical fault types of substation main transformer, bus, line, circuit breaker, and capacitive reactance are summarized, as shown in Table 1, and the secondary signals in each typical fault are sorted out, and the displacement signals, accident action signals and abnormal alarm information in the secondary signals are grouped, the displacement signals and the accident action signals are grouped into a group, the abnormal alarm information is grouped into a group, and the strong correlation abnormal alarm information is analyzed, such as the low SF6 gas pressure alarm of the circuit breaker, the control loop disconnection, the PT disconnection and the device abnormality are strong correlation secondary signals, and the expert system is built to establish the original data relationship chain of typical faults and abnormal information. Figure 5

[0069]

[0070] Step 2, fault analysis and diagnosis.

[0071] The method comprises the following steps:

[0072] 1) Information collection

[0073] The expert system collects the secondary signals in a certain time interval before and after the disturbance of a SCADA system, i.e. the secondary signals triggered in the fault condition. The collection rule is set to actively send the secondary signals in a certain time interval before and after the accident tripping of a SCADA system to the expert system, and the specific time interval can be set artificially.

[0074] 2) Establishing a fault data evidence chain of secondary signals in a fault condition

[0075] The expert system classifies the collected secondary signals, groups the displacement signals and the accident action signals and sorts them according to the time of signal occurrence, groups the other abnormal alarm information, and forms a fault data evidence chain of fault secondary signals.

[0076] 3) Information diagnosis

[0077] The expert system engine compares the fault data evidence chain established in step 2) with the original data relationship chain of typical faults and abnormal information established in step 1), and obtains a preliminary fault diagnosis result. For example, if there is switch displacement information and protection action information, the switch displacement signal is compared first, if the switch displacement signal is the same, the fault data evidence chain and the accident action signal in the original data relationship chain are further compared, if the accident action signal is also the same, the action behavior is evaluated, and the fault equipment and fault type are diagnosed; if there is no circuit breaker displacement information and protection action information in the alarm information, but there is device abnormal alarm information, the abnormal type can be diagnosed through the comparison of the abnormal alarm information.

[0078] ​4) Information diagnosis result verification

[0079] After the power system simulation engine receives the preliminary fault diagnosis result, the same fault or abnormality is triggered, and the corresponding triggered secondary signal is obtained. The triggered secondary signal of the power system simulation engine is transmitted to the expert system and matched with the established fault data evidence chain, and the matching degree is given. The matching method is mainly: matching according to the physical number of the displacement switch and the accident action signal (each switch and remote signal in the first area SCADA system has a unique physical number, and is completely consistent with the power simulation engine).

[0080] If the matching degree is greater than the preset threshold value, such as 90%, it is considered that the preliminary diagnosis result passes the verification, and is identified as the final fault diagnosis result; if the matching degree is less than the threshold value, it is considered that the fault diagnosis fails, and the signal needs to be analyzed by the monitor.

[0081] Step 3, application function expansion.

[0082] After the system is established, the fault and abnormal evolution process and the information diagnosis process can be displayed to the operation and control personnel through the visual means of the theme window and the decision tree, and an alarm is given, which helps the monitor to quickly and accurately analyze the secondary signal and diagnose the fault type.

[0083] Compared with the prior art, the method collects SCADA system fault information, processes the information through the expert system to form an evidence chain, and sends the preliminary diagnosis result to the power system simulation engine. The fault is simulated on the simulation system, and the fault information sent by the simulation system is transmitted to the expert system for final diagnosis. The analysis result is presented to the monitor through the man-machine interface. At the same time, the evolution process of the accident is displayed to the operation and control personnel through the visual means of the theme window and the decision tree, which greatly helps the monitor to quickly and accurately analyze the signal and locate the fault type, and can provide the monitor with an accident handling reference scheme.

[0084] The application also provides a signal auxiliary analysis and decision system for monitoring business, which comprises an original data relationship chain establishment module, a fault data evidence chain establishment module, a preliminary fault diagnosis module, a fault simulation triggering module, a fault signal matching module and a final fault diagnosis module.

[0085] The original data relationship chain establishment module is mainly used for obtaining the mapping relationship of primary and secondary equipment and secondary signals, and forming an original data relationship chain. The original data relationship chain provides a basis for subsequent fault judgment.

[0086] The fault data evidence chain establishing module is mainly used for collecting secondary signals in a time interval before and after the fault, and forming the fault data evidence chain of the collected secondary signals. Specifically, the collected secondary signals are classified, the displacement signals and the accident action signals are coded into a group and sorted according to the time of signal generation, and other abnormal alarm information is coded into a group, thereby forming the fault data evidence chain of the fault secondary signals.

[0087] The preliminary fault diagnosis module is mainly used for comparing the fault data evidence chain with the original data relationship chain, comparing the displacement signals and the accident action signals in sequence, finding the specific fault type and fault information from the original data relationship chain, and taking the specific fault type and fault information as the preliminary fault diagnosis result.

[0088] The fault simulation triggering module is mainly used for triggering the same fault as the preliminary fault diagnosis result through the power system simulation engine, and obtaining the corresponding triggered secondary signals.

[0089] The fault signal matching module is mainly used for determining whether the fault of the preliminary diagnosis can trigger the same or similar secondary signals, matching the triggered secondary signals of the fault simulation triggering module with the fault data evidence chain, specifically matching the physical numbers of the displacement switches and the accident action signals of the triggered secondary signals and the fault data evidence chain, obtaining the matching degree, and the more the same physical numbers, the higher the matching degree.

[0090] The final fault diagnosis module is used for judging whether the preliminary fault diagnosis result passes the verification according to the matching degree, taking the preliminary fault diagnosis result that passes the verification as the final fault diagnosis result, and analyzing the signals by the monitor if the preliminary fault diagnosis result fails the verification.

[0091] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product in the form of one or more computer usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer usable program codes.

[0092] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. 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 produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1apparatuses that implement the functions specified in the flowchart or flowcharts and / or blocks. Figure 1

[0093] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flowchart or flowcharts and / or blocks. Figure 1 Figure 1

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart or flowcharts and / or blocks. Figure 1 Figure 1

[0095] The above description is only preferred embodiments of the present application. It should be pointed out that, for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.​​​​​

Claims

1. A signal-assisted analysis and decision-making method for monitoring operations, characterized in that, Includes the following processes: Obtain the mapping relationship between primary and secondary devices and secondary signals to form the original data relationship chain; Secondary signals are collected within a certain time interval before and after the fault, and the collected secondary signals are used to form a fault data evidence chain. By comparing the chain of evidence in the fault data with the chain of relationships in the original data, a preliminary fault diagnosis result is obtained. By triggering a fault that matches the initial fault diagnosis result through a power system simulation engine, the corresponding secondary trigger signal is obtained. The secondary signal is matched with the fault data evidence chain to obtain the matching degree; The preliminary fault diagnosis result is determined based on the matching degree. If the preliminary fault diagnosis result passes the verification, it is taken as the final fault diagnosis result. The acquisition of the mapping relationship between primary and secondary devices and secondary signals includes: Acquire all primary and secondary equipment and remote signaling data within the substation, and organize and model the primary and secondary equipment according to their hierarchical relationships; The secondary signals within each interval are associated with the primary and secondary devices configured in that interval to form a mapping relationship; The original data relationship chain includes: Based on the power system relay protection theory, we have compiled typical fault types of primary equipment and secondary signals for each typical fault. The displacement signals, accident action signals, and abnormal alarm information in the secondary signals are grouped to form the original data relationship chain.

2. The signal-assisted analysis and decision-making method for monitoring services according to claim 1, characterized in that, The process of forming a fault data evidence chain from the collected secondary signals includes: The collected secondary signals are classified, and the displacement signals and accident action signals are grouped together and sorted according to the time of occurrence. Other abnormal alarm information is grouped together to form a fault data evidence chain of secondary fault signals.

3. The signal-assisted analysis and decision-making method for monitoring services according to claim 1, characterized in that, The step of matching the triggered secondary signal with the fault data evidence chain includes: The secondary trigger signal will be matched with the physical numbers of the position changer and accident action signal in the fault data evidence chain.

4. A signal-assisted analysis and decision-making system for monitoring operations, characterized in that, It includes a raw data relationship chain establishment module, a fault data evidence chain establishment module, a preliminary fault diagnosis module, a fault simulation triggering module, a fault signal matching module, and a final fault diagnosis module, among which: The original data relationship chain establishment module is used to obtain the mapping relationship between primary and secondary devices and secondary signals to form the original data relationship chain; The fault data evidence chain establishment module is used to collect secondary signals within a certain time interval before and after the fault, and to form a fault data evidence chain from the collected secondary signals. The preliminary fault diagnosis module is used to compare the fault data evidence chain with the original data relationship chain to obtain preliminary fault diagnosis results. The fault simulation triggering module is used to trigger a fault that is the same as the initial fault diagnosis result through the power system simulation engine and obtain the corresponding triggering secondary signal. The fault signal matching module is used to match the triggered secondary signal with the fault data evidence chain to obtain the matching degree; The final fault diagnosis module is used to determine whether the preliminary fault diagnosis result passes the verification based on the matching degree, and the preliminary fault diagnosis result that passes the verification is used as the final fault diagnosis result. The original data relationship chain establishment module is specifically used for: Acquire all primary and secondary equipment and remote signaling data within the substation, and organize and model the primary and secondary equipment according to their hierarchical relationships; The secondary signals within each interval are associated with the primary and secondary devices configured in that interval to form a mapping relationship; Based on the power system relay protection theory, we have compiled typical fault types of primary equipment and secondary signals for each typical fault. The displacement signals, accident action signals, and abnormal alarm information in the secondary signals are grouped to form the original data relationship chain.

5. A signal-assisted analysis and decision-making system for monitoring services according to claim 4, characterized in that, In the fault data evidence chain establishment module, the step of forming a fault data evidence chain from the collected secondary signals includes: The collected secondary signals are classified, and the displacement signals and accident action signals are grouped together and sorted according to the time of occurrence. Other abnormal alarm information is grouped together to form a fault data evidence chain of secondary fault signals.

6. A signal-assisted analysis and decision-making system for monitoring services according to claim 4, characterized in that, In the fault signal matching module, the step of matching the triggered secondary signal with the fault data evidence chain includes: The secondary trigger signal will be matched with the physical numbers of the position changer and accident action signal in the fault data evidence chain.

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