CN117543840A - An intelligent analysis and auxiliary decision-making system based on centralized monitoring data of substations - Google Patents

Abstract

The invention discloses an intelligent analysis and auxiliary decision-making system based on substation centralized monitoring data, which belongs to the technical field of electric power, and can carry out intelligent analysis and auxiliary decision-making of data when the monitoring data of a subsequent substation arrives by constructing an accident analysis and decision-making module, an abnormality analysis and decision-making module and a monitoring information intelligent grading module, thereby meeting the actual requirement of the substation centralized monitoring operation, assisting a monitor to rapidly and correctly carry out fault and abnormality treatment, providing risk early warning, realizing automatic generation of a monitoring fault tripping report, reducing the workload of the monitor and improving the monitoring work efficiency.

Description

An intelligent analysis and auxiliary decision-making system based on centralized monitoring data of substations

Technical field

The invention belongs to the field of electric power technology, and specifically relates to an intelligent analysis and auxiliary decision-making system based on centralized monitoring data of a substation.

Background technique

The existing power grid accident anomaly analysis method relies on the information processing function of the dispatch control system and lacks analysis of the correlation between equipment faults, abnormalities and other signals. Therefore, it has the following shortcomings: 1. A large number of signals will be sent to the monitoring alarm window. Failure analysis relies heavily on the experience and skill level of the monitor and takes a lot of time. 2. The comprehensive intelligent alarm for dispatching business can only locate faulty equipment, but cannot analyze the cause and development process of the fault, and the comprehensive intelligent alarm does not have the function of analyzing abnormal information. 3. Most comprehensive intelligent alarms only collect power system operation data, do not provide processing and analysis functions, and have a low level of practicality. 4. Currently, monitors use manual entry to filter and record relevant fault messages on the monitoring system one by one, find the protection configuration of on-site equipment and equipment type and other ledger information, and then manually fill in the corresponding equipment trip report template. , in order to form a complete trip report, there are problems such as heavy workload, long time consumption and low work efficiency.

Contents of the invention

The present invention provides an intelligent analysis and auxiliary decision-making system based on centralized monitoring data of a substation to solve the problem that the existing technology cannot perform intelligent analysis and auxiliary decision-making on the substation monitoring data.

An intelligent analysis and auxiliary decision-making system based on centralized monitoring data of substations, including: an accident analysis and decision-making module, an anomaly analysis and decision-making module, and a monitoring information intelligent classification module;

The accident analysis and decision-making module is used to obtain a substation accident data set from a specified data source, and obtain an accident knowledge representation based on the substation accident data set; wherein the accident knowledge representation includes accident data and accident decisions corresponding to the accident data;

The accident analysis and decision-making module is also used to obtain the accident information to be analyzed, and match the accident knowledge representation according to the accident information to be analyzed, to obtain the target accident knowledge representation corresponding to the accident information to be analyzed, and display it;

The anomaly analysis and decision-making module is used to obtain anomaly monitoring alarm signals from specified data sources, and obtain anomaly knowledge representations based on anomaly monitoring alarm signals; wherein the anomalous knowledge representation includes anomaly monitoring alarm signals and anomaly decisions corresponding to the anomaly monitoring alarm signals. ;

The anomaly analysis and decision-making module is also used to obtain the anomaly information to be analyzed, and match the anomaly knowledge representation according to the anomaly information to be analyzed, to obtain the target anomaly knowledge representation corresponding to the anomaly information to be analyzed, and display it;

The monitoring information intelligent classification module is used to obtain monitoring information alarms of the substation, perform secondary classification on the monitoring information alarms, obtain secondary analysis results, and store the secondary analysis results.

Further, the substation accident data set includes equipment type, priority, displacement keyword, protection keyword, equipment status or remote signaling value, accident analysis results and disposal suggestions;

Among them, the accident analysis results and disposal suggestions jointly serve as the accident decision-making corresponding to the accident data.

Further, the accident knowledge obtained according to the substation accident data set is expressed as: IF<equipment type>AND<priority>AND<displacement keyword>AND<protection keyword>AND<equipment status or remote signaling value>THEN<accident analysis Results, disposal recommendations>.

Further, the accident information to be analyzed is obtained, and the accident knowledge representation is matched according to the accident information to be analyzed, and the target accident knowledge representation corresponding to the accident information to be analyzed is obtained, including:

When the source equipment corresponding to the accident information to be analyzed is the busbar, main transformer or 500kV line, the accident information to be analyzed is obtained. The accident information to be analyzed includes accident trip equipment type, displacement keyword, protection keyword, equipment status, remote signal value and/or voltage level;

In the accident analysis and decision-making module, the accident knowledge representation with the highest similarity to the accident information to be analyzed is matched to obtain the target accident knowledge representation corresponding to the accident information to be analyzed.

Further, the accident information to be analyzed is obtained, and the accident knowledge representation is matched according to the accident information to be analyzed, and the target accident knowledge representation corresponding to the accident information to be analyzed is obtained, including:

When the source equipment corresponding to the accident information to be analyzed is a switch, 220kV line, capacitor, reactance or station transformer, the accident information to be analyzed is obtained. The accident information to be analyzed includes the accident tripping equipment type, voltage level field, and displacement keyword. , protection keywords, device status, remote signaling value and/or voltage level;

First, combine the equipment type and voltage level fields to assign the accident knowledge representation corresponding to the switch, 220kV line, capacitor, reactance or station transformer equipment;

Based on the accident knowledge representation corresponding to the assigned switch, 220kV line, capacitance, reactance or station transformer equipment, through accident tripping equipment type, displacement keyword, protection keyword, equipment status, remote signaling value and/or voltage level matching The accident knowledge representation with the highest similarity to the accident information to be analyzed is used to obtain the target accident knowledge representation corresponding to the accident information to be analyzed.

Further, the abnormal monitoring alarm signal includes multi-level equipment alarm information, causes, risk analysis and disposal suggestions. The multi-level equipment includes a device layer, a component layer in the device layer, and a single component layer in the component layer;

Among them, the equipment layer includes lines, main transformers, busbars, capacitors, reactors, station transformers and public equipment. Causes, risk analysis and disposal suggestions are jointly used as abnormal decisions corresponding to abnormal monitoring alarm signals.

Further, the abnormal knowledge representation includes alarm knowledge of a single event and alarm knowledge of associated events;

The alarm knowledge of a single event is: IF<Alarm Signal>THEN<Cause, Risk Analysis, Disposal Suggestions>, and the alarm knowledge of associated events is: IF<Alarm Signal>and…and<Alarm Signal n>THEN<Cause, Risk Analysis and Disposal recommendations>.

Further, obtain the abnormal information to be analyzed, and match the abnormal knowledge representation according to the abnormal information to be analyzed, and obtain the target abnormal knowledge representation corresponding to the abnormal information to be analyzed, including:

Obtain the abnormal signal to be analyzed and determine whether the abnormal signal to be analyzed has not returned. If so, determine that the abnormal information to be analyzed is the abnormal signal to be analyzed. Otherwise, determine that the abnormal information to be analyzed is empty, and end the analysis process of the abnormal information to be analyzed;

Obtain the keywords in the abnormal information to be analyzed, and match the abnormal knowledge representation with the highest similarity with the keywords in the abnormal information to be analyzed, to obtain the target abnormal knowledge representation corresponding to the abnormal information to be analyzed.

Further, the monitoring information alarm is accident information, abnormal information, limit violation information, displacement information or notification information.

Further, the monitoring information alarms of the substation are obtained, and the monitoring information alarms are classified twice to obtain secondary analysis results, including:

Construct preset expert library rules based on the device status and information attributes when the information is sent;

Obtain the monitoring information alarms of the substation, and use the preset expert database rules to classify the monitoring information alarms twice to obtain the secondary analysis results.

The invention provides an intelligent analysis and auxiliary decision-making system based on centralized substation monitoring data. By constructing an accident analysis and decision-making module, an abnormality analysis and decision-making module and a monitoring information intelligent classification module, it can perform data processing when subsequent substation monitoring data arrives. Intelligent analysis and auxiliary decision-making meet the actual needs of centralized monitoring and operation of substations. It can assist monitors to handle faults and abnormalities quickly and correctly, provide risk warnings, realize automatic generation of monitoring fault trip reports, and reduce the workload of monitors. Improve monitoring efficiency.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description serve to explain the principles of the invention.

Figure 1 is a schematic structural diagram of an intelligent analysis and auxiliary decision-making system based on centralized monitoring data of substations provided by an embodiment of the present invention.

Specific embodiments of the present invention have been shown in the above-mentioned drawings and will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate the concept of the present invention to those skilled in the art with reference to specific embodiments.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the appended claims.

The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

As shown in Figure 1, an intelligent analysis and auxiliary decision-making system based on centralized monitoring data of substations includes: accident analysis and decision-making module, anomaly analysis and decision-making module, and monitoring information intelligent classification module;

The accident analysis and decision-making module is used to obtain a substation accident data set from a specified data source, and obtain an accident knowledge representation based on the substation accident data set; wherein the accident knowledge representation includes accident data and accident decisions corresponding to the accident data;

The accident analysis and decision-making module is also used to obtain the accident information to be analyzed, and match the accident knowledge representation according to the accident information to be analyzed, to obtain the target accident knowledge representation corresponding to the accident information to be analyzed, and display it.

The accident analysis and decision-making module identification method adopts the sequential method retrieval, and uses priority matching results. The identification method is divided into two types. The first method is through keywords (accident tripping equipment type, displacement keyword, protection keyword, equipment status or remote signaling value, voltage level) to obtain the analysis results, and then match the equipment type, equipment voltage level and equipment topology relationship module data in the analysis results to obtain the final result. The equipment using method 1 includes busbars, main transformers and 500kV lines. The second method is to first use the equipment that tripped in the accident, combined with the equipment type and voltage level fields, to match the switch, line, capacitor, reactance and station transformer equipment information (original priority: switch > line > capacitor > reactance > station transformer , when a high-priority device is matched, it will no longer match a low-priority device. Just use keyword matching), and then pass the keyword (device type, variable keyword, protection keyword, device status or remote signaling value, voltage level) to get the final result. The equipment using method one includes switches, 220kV lines, capacitors, reactances and station transformers. Among them, method one takes precedence over method two.

The anomaly analysis and decision-making module is used to obtain anomaly monitoring alarm signals from specified data sources, and obtain anomaly knowledge representations based on anomaly monitoring alarm signals; wherein the anomalous knowledge representation includes anomaly monitoring alarm signals and anomaly decisions corresponding to the anomaly monitoring alarm signals. ;

The anomaly analysis and decision-making module is also used to obtain the anomaly information to be analyzed, and match the anomaly knowledge representation according to the anomaly information to be analyzed, to obtain the target anomaly knowledge representation corresponding to the anomaly information to be analyzed, and display it;

The monitoring information intelligent classification module is used to obtain monitoring information alarms of the substation, perform secondary classification on the monitoring information alarms, obtain secondary analysis results, and store the secondary analysis results.

The invention provides an intelligent analysis and auxiliary decision-making system based on centralized substation monitoring data. By constructing an accident analysis and decision-making module, an abnormality analysis and decision-making module and a monitoring information intelligent classification module, it can perform data processing when subsequent substation monitoring data arrives. Intelligent analysis and auxiliary decision-making meet the actual needs of centralized monitoring and operation of substations. It can assist monitors to handle faults and abnormalities quickly and correctly, provide risk warnings, realize automatic generation of monitoring fault trip reports, and reduce the workload of monitors. Improve monitoring efficiency.

In this embodiment, the substation accident data set includes equipment type, priority, displacement keyword, protection keyword, equipment status or remote signaling value, accident analysis results and disposal suggestions;

Among them, the accident analysis results and disposal suggestions jointly serve as the accident decision-making corresponding to the accident data.

According to the type of equipment, it can be divided into line fault, busbar fault, main transformer fault, capacitor fault, reactor fault and station transformer fault.

According to the complexity of faults, they can be divided into "simple faults" and "combination faults". A simple fault refers to a type of fault that occurs in a piece of equipment, such as: "line fault tripping, reclosing failed". Combined failure refers to the occurrence of two or more related accidents in equipment, and these accidents have a logical causal relationship. A combined fault can be seen as a fault set composed of multiple simple faults and their associated signals, such as "line fault tripping, switch refusal to operate, failure protection starting bus differential, tripping other switches on the bus where this line is located".

The substation fault sets are classified according to equipment and fault properties and then stored in the knowledge base. The knowledge in the knowledge base covers all fault types as much as possible, and an index table is established to improve the fault tolerance and efficiency of knowledge retrieval during the reasoning process.

In this embodiment, the accident knowledge obtained according to the substation accident data set is expressed as: IF<equipment type>AND<priority>AND<displacement keyword>AND<protection keyword>AND<equipment status or remote signaling value>THEN <Accident analysis results, disposal suggestions>.

When the equipment trips in an accident, the system collects displacement keywords, protection keywords, equipment status after tripping and remote signaling values, and automatically matches the accident tripping expert library based on the priority sorting algorithm, and performs accident analysis and reasoning to determine the accident. Analyze the results and provide targeted disposal suggestions based on the analysis results.

Therefore, the accident knowledge representation can be: IF<equipment type>AND<priority>AND<displacement keyword>AND<protection keyword>AND<equipment status or remote signaling value>THEN<accident analysis results, disposal suggestions>.

In this embodiment, the accident information to be analyzed is obtained, and the accident knowledge representation is matched according to the accident information to be analyzed, and the target accident knowledge representation corresponding to the accident information to be analyzed is obtained, including:

When the source equipment corresponding to the accident information to be analyzed is a busbar, main transformer or 500kV line, the accident information to be analyzed is obtained. The accident information to be analyzed includes accident trip equipment type, displacement keyword, protection keyword, equipment status, remote signal value and/or voltage level;

In the accident analysis and decision-making module, the accident knowledge representation with the highest similarity to the accident information to be analyzed is matched to obtain the target accident knowledge representation corresponding to the accident information to be analyzed.

In this embodiment, the accident information to be analyzed is obtained, and the accident knowledge representation is matched according to the accident information to be analyzed, and the target accident knowledge representation corresponding to the accident information to be analyzed is obtained, including:

When the source equipment corresponding to the accident information to be analyzed is a switch, 220kV line, capacitor, reactance or station transformer, the accident information to be analyzed is obtained. The accident information to be analyzed includes the accident tripping equipment type, voltage level field, and displacement keyword. , protection keywords, device status, remote signaling value and/or voltage level;

First, combine the equipment type and voltage level fields to allocate the accident knowledge representation corresponding to the switch, 220kV line, capacitor, reactance or station transformer equipment; among them, the original priority: switch > line > capacitor > reactance > station transformer;

Based on the accident knowledge representation corresponding to the allocated switch, 220kV line, capacitance, reactance or station transformer equipment, through accident tripping equipment type, displacement keyword, protection keyword, equipment status, remote signaling value and/or voltage level matching The accident knowledge representation with the highest similarity to the accident information to be analyzed is used to obtain the target accident knowledge representation corresponding to the accident information to be analyzed.

In this embodiment, the abnormal monitoring alarm signal includes multi-level equipment alarm information, causes, risk analysis and disposal suggestions. The multi-level equipment includes a device layer, a component layer in the device layer, and a single component layer in the component layer. ;

Among them, the equipment layer includes lines, main transformers, busbars, capacitors, reactors, station transformers and public equipment. Causes, risk analysis and disposal suggestions are jointly used as abnormal decisions corresponding to abnormal monitoring alarm signals.

Optionally, monitoring alarm signals corresponding to common abnormalities in substations can be divided into the following types by device:

(1) Line;

For double busbar wiring, it can include switching mechanism, line protection and line measurement and control signals; for 3/2 wiring, it can include side (middle) switching mechanism, switch protection, switch measurement and control, line protection and line measurement and control signals;

(2) Main transformer, which can include three-sided switch mechanism, switch measurement and control, main transformer cooler and its power supply, main transformer non-electricity, main transformer protection and main transformer measurement and control signals;

(3) Busbar;

According to the voltage level, connect the switching mechanism, switch protection, switch measurement and control and bus differential protection signals of all switches on the bus;

(4) Capacitor (reactor), capacitor (reactor) switching mechanism, capacitor (reactor) protection and measurement and control signals;

(5) Station transformer, which may include station transformer switching mechanism, station transformer protection, and station transformer measurement and control signals;

(6) Public equipment, which may include DC systems, fault recorders, stability control devices and other public signals.

The signals contained in various equipment can be further divided. For example, the switch mechanism signals in the line are again divided into SF6 air pressure, control loop, spring mechanism, hydraulic mechanism and air pressure mechanism signals. SF6 air pressure is further divided into SF6 air pressure low alarm, SF6 air pressure low locking signal. After various equipment signals are classified layer by layer, corresponding sub-knowledge bases are established, and the knowledge of the same signals is stored in the same sub-knowledge base. When querying relevant knowledge, a knowledge index table is established for the knowledge base to connect all relatively independent sub-knowledge bases. The system uses the knowledge index table to quickly find the sub-knowledge base where the signal is located, and determines the alarm signal based on the device to which it belongs. Faulty or abnormal equipment. When the last level in the index table is the same, it points to the same sub-knowledge base, which stores all the knowledge related to the device.

If there is no correlation between the monitoring alarm signals received by the system within a time interval, it means that each alarm signal represents an event. Therefore, it is necessary to design a single alarm signal event knowledge base for various devices according to the index table for non-correlation. Abnormal reasoning for alarm information.

For the alarm knowledge of a single event, the abnormal knowledge representation can be: IF<alarm signal>THEN<cause, risk analysis, disposal suggestions>.

Generally, a fault or anomaly will generate a series of monitoring alarm signals, and these signals are related. Therefore, it is necessary to design a knowledge base of associated event alarm information and apply it to the alarm reasoning of associated events.

For the alarm knowledge of related event reasoning, the abnormal knowledge is expressed as: IF<alarm signal>and…and<alarm signal n>THEN<cause, risk analysis and disposal suggestions>.

In this embodiment, the abnormal information to be analyzed is obtained, and the abnormal knowledge representation is matched according to the abnormal information to be analyzed, and the target abnormal knowledge representation corresponding to the abnormal information to be analyzed is obtained, including:

Obtain the abnormal signal to be analyzed and determine whether the abnormal signal to be analyzed has not returned. If so, determine that the abnormal information to be analyzed is the abnormal signal to be analyzed. Otherwise, determine that the abnormal information to be analyzed is empty, and end the analysis process of the abnormal information to be analyzed;

Obtain the keywords in the abnormal information to be analyzed, and match the abnormal knowledge representation with the highest similarity with the keywords in the abnormal information to be analyzed, to obtain the target abnormal knowledge representation corresponding to the abnormal information to be analyzed.

This embodiment provides an example of abnormal analysis and identification, as follows.

Judgment premise: the abnormal signal has not returned;

Fields include: signal name, other associated signals, cause analysis, risk analysis, disposal recommendations, priority, update time, and whether it is a single signal.

Signal name: Match the keywords in the abnormal signal. "%" is an inclusive relationship and is used in the main identification content of the signal. For example: "Protect%Collect%MergeUnit%SV%Exception" means protect ××collection××merge unit. ××SV×× abnormal content, in which special existence such as "[Active power P telemetry data]", "[Reactive power Q telemetry data]", "[Power factor cosφ telemetry data]" means the active power P under the line respectively Telemetry data, reactive power Q telemetry data, power factor cosφ telemetry data information display to facilitate abnormal analysis

Other related signals: A single signal is empty by default. The modified field is used to assemble a single signal. The "+" character is a union relationship, the "||" character is an OR relationship, and the "%" character matches an inclusion relationship.

In this embodiment, the monitoring information alarm is accident information, abnormal information, limit violation information, displacement information or notification information.

Monitoring information alarms are alarm clauses that appear in the alarm window after the dispatch control system processes equipment monitoring information. They are the main focus of monitoring operations. According to the "Substation Equipment Monitoring Information Specifications",

Monitoring information alarms are divided into five levels according to the priority of their impact on the power grid and equipment: accident, abnormality, limit violation, displacement and notification. Among them, accident, abnormality, limit violation, and displacement information are information that require real-time monitoring and immediate or timely processing by the monitor, while notification information is general information that reflects the operation status of the power grid equipment. This type of information is handled by the operation and maintenance unit, and the monitor Only regular queries are required, no real-time monitoring is required. Monitoring information at all levels is sent to different alarm windows on the dispatch control system, triggering different alarm sounds to remind the monitor to handle the situation in accordance with regulations.

Under normal circumstances, a signal represents an event, and the impact of the event needs to be determined by the actual situation. Therefore, it is necessary to design an intelligent hierarchical knowledge base for monitoring information, and provide secondary information based on the equipment status, information attributes, etc. when the information is sent. Hierarchical reasoning results.

The system automatically matches expert database rules directly based on equipment type and information keywords, and obtains hierarchical adjustment results. Sometimes it is necessary to share the analysis results with other modules. For example, whether a disconnection of a switch control loop is accompanied by a signal requires calling the results of the system's intelligent abnormality analysis module; Whether signals are sent frequently requires calling the results of the system monitoring information statistics module.

In this embodiment, the monitoring information alarms of the substation are obtained, and the monitoring information alarms are classified twice to obtain secondary analysis results, including:

Construct preset expert library rules based on the device status and information attributes when the information is sent;

Obtain the monitoring information alarms of the substation, and use the preset expert database rules to classify the monitoring information alarms twice to obtain the secondary analysis results.

Optionally, use preset expert database rules to perform secondary classification of monitoring information alarms, which may include:

A1. Obtain the monitoring information alarm of the substation, and determine whether there is an alarm suppression indication in the monitoring information alarm. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is notification information, otherwise proceed to step A2;

A2. Determine whether there is a maintenance tag indication in the monitoring information alarm. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is notification information; otherwise, proceed to step A3;

A3. Determine whether there is an OMS defect record in the monitoring information alarm. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is notification information. Otherwise, proceed to step A4;

A4. Determine whether the monitoring information alarm is accident information. If so, directly determine that the secondary analysis result corresponding to the monitoring information alarm is accident information. Otherwise, proceed to step A5;

A5. Determine whether the monitoring information alarm is abnormal information. If so, proceed to step A6; otherwise, proceed to step A17;

A6. Determine whether the number of occurrences of the abnormal information in step A5 exceeds the preset threshold. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information; otherwise, proceed to step A7;

A7. Determine whether the abnormal information in step A5 is the abnormal information corresponding to the disconnection of the control loop. If so, proceed to step A8, otherwise proceed to step A11;

A8. Determine whether the signal corresponding to the abnormal information in step A5 returns within the preset time. If so, proceed to step A9, otherwise proceed to step A10;

A9. Determine whether the abnormal information in step A5 also contains corresponding switch displacement information. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is notification information. Otherwise, determine that the secondary analysis result corresponding to the monitoring information alarm is abnormal information. ;

A10. Determine whether the switch corresponding to the signal corresponding to the abnormal information in step A5 is in the closed position or there is flow in any phase. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information, otherwise proceed to step A11;

A11. Determine whether the abnormal information in step A5 is abnormal information corresponding to a measurement and control device failure or communication interruption. If so, proceed to step A12, otherwise proceed to step A14;

A12. Determine whether the device corresponding to the exception information in step A5 is in a running state. If so, proceed to step A13; otherwise, proceed to step A14;

A13. Determine whether the measurement and control device corresponding to the abnormal information in step A5 is put in. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information, otherwise proceed to step A14;

A14. Determine whether the abnormal information in step A5 is abnormal information corresponding to the protection device failure. If so, proceed to step A15. Otherwise, determine that the secondary analysis result corresponding to the monitoring information alarm is abnormal information;

A15. Determine whether the device corresponding to the abnormal information in step A5 is in a running state. If so, proceed to step A16. Otherwise, determine that the secondary analysis result corresponding to the monitoring information alarm is abnormal information;

A16. Determine whether the protection device corresponding to the abnormal information in step A5 is engaged. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information; otherwise, determine that the secondary analysis result corresponding to the monitoring information alarm is abnormal information;

A17. Determine whether the monitoring information alarm is out-of-limit information. If so, proceed to step A18, otherwise proceed to subsidy A19;

A18. Determine whether the out-of-limit information in step A17 is an accident out-of-limit information. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information; otherwise, determine that the secondary analysis result corresponding to the monitoring information alarm is out-of-limit information;

A19. Determine whether the monitoring information alarm is displacement information. If so, proceed to step A20; otherwise, proceed to step A25;

A20. Determine whether the number of occurrences of the displacement information in step A19 exceeds the preset threshold. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information, otherwise proceed to step A21;

A21. Based on the displacement information in step A19, determine whether there is accident information for the whole station accident at the same time. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information, otherwise proceed to step A22;

A22. Determine whether the device corresponding to the displacement information in step A19 is operated by remote control. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is displacement information, otherwise proceed to step A23;

A23. Determine whether the equipment corresponding to the displacement information in step A19 is AVC automatic control. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is displacement information, otherwise proceed to step A24;

A24. Determine whether the equipment corresponding to the displacement information in step A19 has an OMS transfer on-site operation record. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is displacement information. Otherwise, determine the secondary analysis corresponding to the monitoring information alarm. The result is accident information;

A25. Determine that the monitoring information alarm is notification information, and determine whether the number of times the notification information is generated exceeds the preset threshold. If so, determine that the secondary analysis result corresponding to the monitoring information alarm is accident information. Otherwise, determine the secondary analysis result corresponding to the monitoring information alarm. The analysis results are informative.

The information without maintenance mark means that there is no maintenance mark in the information attribute. When the supervisor puts the maintenance tag on the bay or equipment, the information of the corresponding bay or equipment will have the maintenance mark;

If the information does not have an alarm suppression mark, it means that there is no alarm suppression mark in the information attributes. When the monitor performs alarm suppression operations on the information, the information will all have a suppression mark;

Information OMS defect-free record means that there are no false alarms or frequent defects of this information in the monitoring defect records of the OMS system. Locate related devices through information keyword identification and device topology analysis, and then match them with OMS defect records to obtain the results.

Other embodiments of the invention will be readily apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary technical means in the technical field that are not disclosed in the invention. . It is to be understood that the present invention is not limited to the precise construction described above and illustrated in the accompanying drawings, and that various modifications and changes may be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims (10)

1. Intelligent analysis and auxiliary decision-making system based on centralized monitoring data of transformer substation is characterized by comprising: the system comprises an accident analysis and decision module, an abnormality analysis and decision module and a monitoring information intelligent grading module;

the accident analysis and decision module is used for acquiring a substation accident data set of a designated data source and acquiring an accident knowledge representation according to the substation accident data set; the accident knowledge representation comprises accident data and accident decisions corresponding to the accident data;

the accident analysis and decision module is also used for acquiring the accident information to be analyzed, matching the accident knowledge representation according to the accident information to be analyzed, obtaining a target accident knowledge representation corresponding to the accident information to be analyzed, and displaying;

the abnormality analysis and decision module is used for acquiring an abnormality monitoring alarm signal of the designated data source and acquiring an abnormality knowledge representation according to the abnormality monitoring alarm signal; the abnormal knowledge representation comprises abnormal decision corresponding to the abnormal monitoring alarm signal;

the anomaly analysis and decision module is further used for acquiring anomaly information to be analyzed, matching the anomaly knowledge representation according to the anomaly information to be analyzed, obtaining a target anomaly knowledge representation corresponding to the anomaly information to be analyzed, and displaying the target anomaly knowledge representation;

the intelligent classification module of the monitoring information is used for acquiring the monitoring information alarm of the transformer substation, secondarily classifying the monitoring information alarm to obtain a secondary analysis result, and storing the secondary analysis result.

2. The intelligent analysis and decision-making system based on centralized monitoring data of a transformer substation according to claim 1, wherein the transformer substation accident data set comprises equipment type, priority, shift key, protection key, equipment status or remote signaling value, accident analysis result and treatment suggestion;

the accident analysis result and the treatment suggestion are used as accident decisions corresponding to the accident data.

3. The intelligent analysis and decision-making system based on substation centralized monitoring data according to claim 2, wherein the acquisition of the accident knowledge from the substation accident data set is expressed as: IF < device type > AND < priority > AND < shift key > AND < protect key > AND < device status or remote signaling value > THEN < incident analysis result, handling advice >.

4. The intelligent analysis and decision-making system based on centralized monitoring data of a transformer substation according to claim 3, wherein obtaining accident information to be analyzed, and matching the accident knowledge representation according to the accident information to be analyzed, to obtain a target accident knowledge representation corresponding to the accident information to be analyzed, comprises:

when source equipment corresponding to accident information to be analyzed is a bus, a main transformer or a 500kV line, acquiring the accident information to be analyzed, wherein the accident information to be analyzed comprises an accident tripping equipment type, a deflection keyword, a protection keyword, an equipment state, a remote signaling value and/or a voltage level;

and matching the accident knowledge representation with the highest similarity with the accident information to be analyzed in the accident analysis and decision module to obtain the target accident knowledge representation corresponding to the accident information to be analyzed.

5. The intelligent analysis and decision-making system based on centralized monitoring data of a transformer substation according to claim 3, wherein obtaining accident information to be analyzed, and matching the accident knowledge representation according to the accident information to be analyzed, to obtain a target accident knowledge representation corresponding to the accident information to be analyzed, comprises:

when source equipment corresponding to accident information to be analyzed is a switch, a 220kV line, a capacitor, a reactance or a station transformer, acquiring the accident information to be analyzed, wherein the accident information to be analyzed comprises an accident tripping equipment type, a voltage class field, a deflection keyword, a protection keyword, an equipment state, a remote signaling value and/or a voltage class;

firstly, combining equipment type and voltage class fields to be matched with a switch, a 220kV line, a capacitor, a reactance or accident knowledge representation corresponding to station transformer equipment;

and obtaining a target accident knowledge representation corresponding to the accident information to be analyzed by matching the accident tripping equipment type, the deflection key word, the protection key word, the equipment state, the remote signaling value and/or the voltage class with the accident knowledge representation with the highest similarity to the accident information to be analyzed based on the accident knowledge representation corresponding to the matched switch, 220kV line, capacitor, reactance or station transformer equipment.

6. The substation centralized monitoring data-based intelligent analysis and decision-making aid system according to claim 1, wherein the anomaly monitoring alert signal includes multi-level device alert information, cause, risk analysis, and treatment advice, the multi-level device including a device layer, a component layer in the device layer, and a single component layer in the component layer;

the equipment layer comprises a line, a main transformer, a bus, a capacitor, a reactor, a station transformer and public equipment, and reasons, risk analysis and treatment suggestions are used as abnormal decisions corresponding to abnormal monitoring alarm signals.

7. The intelligent analysis and decision-making aid system based on centralized monitoring data of a transformer substation according to claim 6, wherein the abnormal knowledge representation comprises alarm knowledge of individual events and alarm knowledge of associated events;

the alarm knowledge of a single event is: IF < alert > THEN < cause, risk analysis, treatment advice >, alert knowledge of the associated event is: IF < alert signal > and … and < alert signal n > THEN < cause, risk analysis and treatment advice >.

8. The intelligent analysis and decision-making system based on substation centralized monitoring data according to claim 7, wherein the acquiring the anomaly information to be analyzed, and the matching the anomaly knowledge representation according to the anomaly information to be analyzed, to obtain the target anomaly knowledge representation corresponding to the anomaly information to be analyzed, comprises:

acquiring an abnormal signal to be analyzed, judging whether the abnormal signal to be analyzed is not reset, if so, determining that the abnormal information to be analyzed is the abnormal signal to be analyzed, otherwise, determining that the abnormal information to be analyzed is empty, and ending the analysis flow of the abnormal information to be analyzed;

and obtaining the keywords in the abnormal information to be analyzed, and matching the abnormal knowledge representation with the highest similarity with the keywords in the abnormal information to be analyzed to obtain the target abnormal knowledge representation corresponding to the abnormal information to be analyzed.

9. The intelligent analysis and decision-making system based on centralized monitoring data of a transformer substation according to claim 1, wherein the monitoring information alarm is accident information, abnormal information, out-of-limit information, shift information or notification information.

10. The intelligent analysis and decision-making system based on centralized monitoring data of a transformer substation according to claim 9, wherein the steps of obtaining the monitoring information alarm of the transformer substation, and performing secondary classification on the monitoring information alarm to obtain a secondary analysis result comprise:

constructing a preset expert database rule according to the equipment state and the information attribute when the information is sent;

and acquiring monitoring information alarms of the transformer substation, and carrying out secondary classification on the monitoring information alarms by adopting preset expert database rules to obtain a secondary analysis result.