CN113535685B - Method for constructing event knowledge base of intelligent power grid dispatching - Google Patents
Method for constructing event knowledge base of intelligent power grid dispatching Download PDFInfo
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Abstract
The invention discloses an event knowledge base construction method for intelligent power grid dispatching, which comprises the following steps: determining data to be stored, and establishing a data entry module; the invention constructs a sub knowledge base, a standard knowledge base and an experience knowledge base with the sub knowledge base architecture model, and forms an intelligent power grid dispatching event knowledge base together, so that the knowledge base can be well matched with a power grid dispatching system for use, further, the power grid dispatching system is simpler and more convenient in the processes of fault positioning, analysis, elimination and the like in the actual operation process, the operation and maintenance cost is greatly reduced, the working efficiency of the system is greatly improved, and in addition, the knowledge base has depth and breadth expansion technology and larger coverage range, and can be well put into practical use.
Description
Technical Field
The invention relates to the technical field of intelligent power grid dispatching, in particular to an event knowledge base construction method for intelligent power grid dispatching.
Background
In the prior art, the power grid dispatching comprises operation basic knowledge, power generation equipment basic knowledge, power grid structure and power system communication basic knowledge, power grid regulation and control, power grid operation, power grid abnormity processing and power grid accident handling, along with the rapid development of a domestic power system, large-scale trans-regional power transmission is more and more common, the structure of the power grid is more complex, the operation of the power system faces the risk of unsafe and stable, the dispatching of the power grid is required to be rapid and accurate, the intelligent dispatching technology of the power grid is further researched, the current difficulty of power access of various energy sources can be effectively solved, meanwhile, the operation efficiency and the safety of the power grid are further improved, the intelligent dispatching technology of the power grid is researched, the development and the application of the intelligent dispatching system of the power grid are researched on the basis, the intelligent dispatching of the power grid is researched, the information of the power grid is required to be processed, and the process of the information of the power grid comprises the following items in the process of processing the information of the power grid: researching a power grid event information objectification modeling and event feature extraction technology; research on an eventing knowledge base construction technology; a study event reasoning algorithm, a control strategy algorithm and a power grid scheduling event auxiliary decision technique; and the method realizes the eventuality of the power grid information and analysis, early warning and event auxiliary decision after the power grid faults.
The construction technology of the event knowledge base is a more important item, but in the prior art, the construction technology of the event knowledge base is thinner, so that the constructed event knowledge base cannot be well matched with a power grid dispatching system to be used, the processes of positioning, analyzing, removing and the like of faults become extremely complex and long in the actual operation process of the power grid dispatching system, the operation and maintenance cost is further improved, the working efficiency of the system is reduced, and meanwhile, the event knowledge base constructed by the prior construction technology does not have depth and breadth expansion technology, has smaller coverage range and cannot be well put into actual use.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an event knowledge base construction method for intelligent power grid dispatching so as to solve the problems in the background technology.
In order to solve the technical problems, the invention adopts the technical scheme that: the utility model provides a method for constructing an event knowledge base for intelligent power grid dispatching, which comprises the following steps:
step S10, original data and new data to be stored are determined, the original data and the new data are received through a data input module, and the original data are divided into standard data and experience data;
Step S11, searching a data type corresponding to the data input by the data input module in a knowledge base through an established information type searching module, selecting a sub-knowledge base architecture model corresponding to the data type, and classifying the input data into the corresponding sub-knowledge base architecture model, wherein the sub-knowledge base architecture model comprises: element class knowledge base architecture model, list class knowledge base architecture model, concept class knowledge base architecture model and FAQ class knowledge base architecture model;
Step S12, a standard knowledge base is constructed according to standard data in the original data, corresponding standard data types in the standard knowledge base are searched according to an information type searching module, and the standard original data and standard newly-built data matched with the standard knowledge base are classified into the standard knowledge base;
And S13, constructing an experience knowledge base according to experience data in the original data, searching corresponding experience data types in the standard knowledge base according to the information type searching module, and classifying the experience original data and the experience newly-built data matched with the experience data into the experience knowledge base.
Preferably, in step S10, further comprising: and establishing a data input module according to the original data and the new data by using an operating system supporting DBMS operation through an SQL language, wherein the input module comprises an original data input module and a new data input module, the original data input module is used for receiving the input of the original information, and the new data input module is used for receiving the input of the new information.
Preferably, in the step S10:
The source of the original data is original operation basic knowledge data, power generation equipment basic knowledge data, power grid structure data, power system communication basic knowledge data, power grid regulation and control data, power grid operation data, power grid abnormal processing data and power grid accident processing data which are possessed by the power grid dispatching; the new data are new power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data generated in the power grid dispatching process;
in the original data, data having a certain common attribute or characteristic is merged together by data classification, and the data is discriminated by the attribute or characteristic of its class, so that standard data and experience data are obtained.
Preferably, in the step S11, further includes:
And establishing an information type searching module according to data in the system through SQL language by using an operating system supporting DBMS to run.
Preferably, the step S11 further includes:
And the sub knowledge base architecture models of each class merge together the power grid dispatching data with certain common attribute or characteristic through data classification, distinguish the data through the attribute or characteristic of the class, and store the distinguished power grid dispatching information in a classified mode.
Preferably, in the step S11, further includes:
Creating an element knowledge set by using the element knowledge base architecture model, wherein the element knowledge set comprises power grid problem triggering scene information and a plurality of element question-answering groups corresponding to the power grid problem triggering scene information, each element question-answering group comprises a specific occurrence problem, an occurrence reason and a solution, and the solution comprises element attributes and element information corresponding to the element attributes;
Creating a list class knowledge set by using the list class knowledge base architecture model, wherein the list class knowledge set comprises a list class question-answer group and a list element set, and the list class question-answer group comprises a positive solution, a negative solution, a standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem;
Creating a concept knowledge set by using the concept knowledge base architecture model, wherein the concept knowledge set comprises a concept question-answer group, and the concept question-answer group comprises a solution, a standard occurrence problem and more than one concept expansion set problem corresponding to the standard occurrence problem;
And creating an FAQ class knowledge set by using the FAQ class knowledge base architecture model, wherein the FAQ class knowledge set comprises an FAQ class question-answering group, and the FAQ class question-answering group solution, one standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem.
Preferably, the step S12 further includes:
step S121, standard original data and standard newly-built data are received, standard original data and standard newly-built data content are classified through an intelligent scheduling technology analysis engine of a power grid, variances of all features of the two data are calculated at the same time, and then features with variances larger than a threshold are selected according to the threshold to obtain standard feature items; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
step S122, arranging the standard feature items to generate corresponding file numbers, and generating a corresponding relation table according to the file numbers and the data of the standard feature items to obtain a forward arrangement table.
Preferably, the step S13 further includes:
Step S131, receiving the experience original data and the experience newly-built data, classifying the experience original data and the experience newly-built data through an intelligent scheduling technology analysis engine of the power grid, simultaneously calculating variances of all features of the two data, and then selecting features with variances larger than a threshold according to the threshold to obtain an original feature item; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
and S132, arranging the original characteristic items to generate corresponding archive numbers, and generating a corresponding relation table according to the archive numbers and the data of the original characteristic items to obtain a forward arrangement table.
Preferably, the method further comprises:
and forming an intelligent scheduling event knowledge base of the power grid together according to the sub knowledge base, the standard knowledge base and the experience knowledge base.
The implementation of the invention has the following beneficial effects:
the invention provides an event knowledge base construction method for intelligent power grid dispatching, which constructs an intelligent power grid dispatching event knowledge base by constructing a sub knowledge base with a sub knowledge base architecture model, a standard knowledge base and an experience knowledge base, so that the knowledge base can be well matched with a power grid dispatching system for use, further the positioning, analysis, removal and other processes of faults of the power grid dispatching system in the actual operation process are simpler and more convenient, the operation and maintenance cost is greatly reduced, the working efficiency of the system is greatly improved, and in addition, the knowledge base has a depth and breadth expansion technology and a larger coverage range, so that the system can be well put into practical use.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are required in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that it is within the scope of the invention to one skilled in the art to obtain other drawings from these drawings without inventive faculty.
Fig. 1 is a schematic flow chart of an embodiment of a method for constructing an eventing knowledge base for intelligent power grid dispatching.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
In the description of the present invention, it should be noted that the positional or positional relationship indicated by the terms such as "upper", "lower", "inner", "outer", "top/bottom", etc. are based on the positional or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "configured to," "engaged with," "connected to," and the like are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Fig. 1 is a schematic flow chart of an embodiment of a method for constructing an eventing knowledge base for intelligent dispatching of a power grid. In this embodiment, the method includes the steps of:
Step S10, original data and new data to be stored are determined, the original data and the new data are received through a data input module, and the original data are divided into standard data and experience data; specifically, the original data and the newly-built data are stored in a computer and a storage device, and an operating system for supporting the DBMS to run is arranged in the computer and the storage device and used for defining, inserting, modifying and deleting the original data and the newly-built data;
more specifically, in one example, in step S10, further includes: and establishing a data input module according to the original data and the new data by using an operating system supporting DBMS operation through an SQL language, wherein the input module comprises an original data input module and a new data input module, the original data input module is used for receiving the input of the original information, and the new data input module is used for receiving the input of the new information.
In a specific example, in the step S10:
The source of the original data is original operation basic knowledge data, power generation equipment basic knowledge data, power grid structure data, power system communication basic knowledge data, power grid regulation and control data, power grid operation data, power grid abnormal processing data and power grid accident processing data which are possessed by the power grid dispatching; the new data are new power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data generated in the power grid dispatching process;
In the original data, data having a certain common attribute or characteristic is merged together by data classification, and the data is discriminated by the attribute or characteristic of its class, so that standard data and experience data are obtained. More specifically, the standard data is data output after the obtained intelligent script of the power grid dispatching operates the body structure corresponding to the power grid dispatching system, the standard data comprises basic knowledge data, basic knowledge data of power generation equipment, power grid structure data and basic knowledge data of power system communication, the experience data is experience statistical data obtained after an operator performs statistics according to actual operation steps and information in the operation process of the power grid dispatching system, the experience data comprises power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data, and the new data is new power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data generated in the power grid dispatching process, so that the data to be stored can be well determined.
Step S11, searching a data type corresponding to the data input by the data input module in a knowledge base through an established information type searching module, selecting a sub-knowledge base architecture model corresponding to the data type, and classifying the input data into the corresponding sub-knowledge base architecture model, wherein the sub-knowledge base architecture model comprises: element class knowledge base architecture model, list class knowledge base architecture model, concept class knowledge base architecture model and FAQ class knowledge base architecture model;
in a specific example, in the step S11, further includes:
And establishing an information type searching module according to data in the system through SQL language by using an operating system supporting DBMS to run.
In a specific example, the step S11 further includes:
And the sub knowledge base architecture models of each class merge together the power grid dispatching data with certain common attribute or characteristic through data classification, distinguish the data through the attribute or characteristic of the class, and store the distinguished power grid dispatching information in a classified mode.
In a specific example, in the step S11, further includes:
Creating an element knowledge set by using the element knowledge base architecture model, wherein the element knowledge set comprises power grid problem triggering scene information and N element question-answering groups corresponding to the power grid problem triggering scene information, each element question-answering group comprises a specific occurrence problem, an occurrence reason and a solution, the solution comprises element attributes and element information corresponding to the element attributes, and N is a positive integer not less than 1;
Creating a list class knowledge set by using the list class knowledge base architecture model, wherein the list class knowledge set comprises a list class question-answer group and a list element set, and the list class question-answer group comprises a positive solution, a negative solution, a standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem;
Creating a concept knowledge set by using the concept knowledge base architecture model, wherein the concept knowledge set comprises a concept question-answer group, and the concept question-answer group comprises a solution, a standard occurrence problem and more than one concept expansion set problem corresponding to the standard occurrence problem;
And creating an FAQ class knowledge set by using the FAQ class knowledge base architecture model, wherein the FAQ class knowledge set comprises an FAQ class question-answering group, and the FAQ class question-answering group solution, one standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem.
Step S12, a standard knowledge base is constructed according to standard data in the original data, corresponding standard data types in the standard knowledge base are searched according to an information type searching module, and the standard original data and standard newly-built data matched with the standard knowledge base are classified into the standard knowledge base;
In a specific example, the step S12 further includes:
step S121, standard original data and standard newly-built data are received, standard original data and standard newly-built data content are classified through an intelligent scheduling technology analysis engine of a power grid, variances of all features of the two data are calculated at the same time, and then features with variances larger than a threshold are selected according to the threshold to obtain standard feature items; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
step S122, arranging the standard feature items to generate corresponding file numbers, and generating a corresponding relation table according to the file numbers and the data of the standard feature items to obtain a forward arrangement table.
And S13, constructing an experience knowledge base according to experience data in the original data, searching corresponding experience data types in the standard knowledge base according to the information type searching module, and classifying the experience original data and the experience newly-built data matched with the experience data into the experience knowledge base.
In a specific example, the step S13 further includes:
Step S131, receiving the experience original data and the experience newly-built data, classifying the experience original data and the experience newly-built data through an intelligent scheduling technology analysis engine of the power grid, simultaneously calculating variances of all features of the two data, and then selecting features with variances larger than a threshold according to the threshold to obtain an original feature item; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
and S132, arranging the original characteristic items to generate corresponding archive numbers, and generating a corresponding relation table according to the archive numbers and the data of the original characteristic items to obtain a forward arrangement table.
In a specific example, the method further comprises:
and forming an intelligent scheduling event knowledge base of the power grid together according to the sub knowledge base, the standard knowledge base and the experience knowledge base.
It can be understood that in the actual operation, firstly, determining the data to be stored, and establishing a data entry module, wherein the data to be stored comprises original data and new data, the original data and the new data are stored in a computer and a storage device, an operating system for supporting the DBMS to run is arranged in the computer and the storage device and used for defining, inserting, modifying and deleting the original data and the new data, the original data are original operation basic knowledge data, power generation equipment basic knowledge data, power grid structure data, power system communication basic knowledge data, power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data, the original data are obtained by merging the data with a certain common attribute or characteristic through data classification, the data are distinguished through the attribute or characteristic of the category of the original data, so that standard data and experience data are obtained, an operating system supporting the DBMS to run is provided with a data entry module through SQL language according to the original data and the new data, the original data entry module comprises an original data entry module and a new data entry module, and the original data entry module is used for receiving the input of original information, and the new data entry module is used for receiving the input of new information; then an operating system supporting DBMS operation establishes an information type searching module according to data in the system through SQL language, and searches a sub-knowledge base architecture model corresponding to data with certain common attribute or characteristic of the data types input by the data input module in a knowledge base through DML operation data in the DBMS, the sub-knowledge base architecture model merges together power grid dispatching data with certain common attribute or characteristic through data classification, distinguishes the data according to the attribute or characteristic of the category, and classifies and stores distinguished power grid dispatching information, and the sub-knowledge base architecture model is classified into an element knowledge base architecture model, a list knowledge base architecture model, a concept knowledge base architecture model and an FAQ knowledge base architecture model according to the power grid dispatching information; constructing a standard knowledge base according to standard data in original data, wherein the standard knowledge base is used for storing standard data, the corresponding standard data types in the standard knowledge base are searched by a searching module according to the information types through DML operation data provided by a DBMS, the standard original data and standard newly-built data matched with the standard knowledge base are classified by the searching module, the standard original data and the standard newly-built data are accepted, the standard original data and the standard newly-built data are analyzed by a power grid intelligent scheduling technology analysis engine, the power grid intelligent scheduling technology analysis engine is a VisualRules rule engine, the standard original data and the standard newly-built data are classified, variances of all features of the two data are calculated simultaneously by a variance selection method, then features with variances larger than a threshold are selected according to a threshold, standard feature items are obtained, corresponding file numbers are generated for arranging the standard feature items, and a corresponding relation table, namely a forward arrangement table is generated according to the file numbers and the data of the standard feature items; an experience knowledge base is built according to experience data in the original data, the experience knowledge base is used for storing the experience data, corresponding experience data types in the standard knowledge base are searched according to an information type searching module, the experience original data and experience newly-built data matched with the experience data types are classified, the experience original data and the experience newly-built data are received, the experience original data and the experience newly-built data are analyzed through a power grid intelligent scheduling technology analysis engine which is a VisualRules rule engine, the experience original data and the experience newly-built data are classified, variances of all features of the two types of data are calculated simultaneously through a variance selection valve, then features with variances larger than a threshold are selected according to a threshold value to obtain an original feature item, corresponding file numbers are generated for arranging the original feature item, and a corresponding relation table, namely a forward arrangement table, is generated according to the file numbers and the data of the original feature item; meanwhile, the sub knowledge base, the standard knowledge base and the experience knowledge base together form an intelligent scheduling event knowledge base of the power grid.
The implementation of the invention has the following beneficial effects:
the invention provides an event knowledge base construction method for intelligent power grid dispatching, which constructs an intelligent power grid dispatching event knowledge base by constructing a sub knowledge base with a sub knowledge base architecture model, a standard knowledge base and an experience knowledge base, so that the knowledge base can be well matched with a power grid dispatching system for use, further the positioning, analysis, removal and other processes of faults of the power grid dispatching system in the actual operation process are simpler and more convenient, the operation and maintenance cost is greatly reduced, the working efficiency of the system is greatly improved, and in addition, the knowledge base has a depth and breadth expansion technology and a larger coverage range, so that the system can be well put into practical use.
The above disclosure is only a preferred embodiment of the present invention, and it is needless to say that the scope of the invention is not limited thereto, and therefore, the equivalent changes according to the claims of the present invention still fall within the scope of the present invention.
Claims (7)
1. The method for constructing the eventing knowledge base for intelligent power grid dispatching is characterized by comprising the following steps of:
step S10, original data and new data to be stored are determined, the original data and the new data are received through a data input module, and the original data are divided into standard data and experience data;
Step S11, searching a data type corresponding to the data input by the data input module in a knowledge base through an established information type searching module, selecting a sub-knowledge base architecture model corresponding to the data type, and classifying the input data into the corresponding sub-knowledge base architecture model, wherein the sub-knowledge base architecture model comprises: element class knowledge base architecture model, list class knowledge base architecture model, concept class knowledge base architecture model and FAQ class knowledge base architecture model;
Step S12, a standard knowledge base is constructed according to standard data in the original data, corresponding standard data types in the standard knowledge base are searched according to an information type searching module, and the standard original data and standard newly-built data matched with the standard knowledge base are classified into the standard knowledge base;
step S13, an experience knowledge base is constructed according to experience data in the original data, corresponding experience data types in the standard knowledge base are searched according to an information type searching module, and the experience original data and experience newly-built data matched with the experience knowledge base are classified into the experience knowledge base;
Wherein, in the step S10:
The source of the original data is original operation basic knowledge data, power generation equipment basic knowledge data, power grid structure data, power system communication basic knowledge data, power grid regulation and control data, power grid operation data, power grid abnormal processing data and power grid accident processing data which are possessed by the power grid dispatching; the new data are new power grid regulation data, power grid operation data, power grid abnormal processing data and power grid accident processing data generated in the power grid dispatching process;
In the original data, merging data with certain common attribute or characteristic through data classification, and distinguishing the data through the attribute or characteristic of the class to obtain standard data and experience data;
The step S12 further includes:
step S121, standard original data and standard newly-built data are received, standard original data and standard newly-built data content are classified through an intelligent scheduling technology analysis engine of a power grid, variances of all features of the two data are calculated at the same time, and then features with variances larger than a threshold are selected according to the threshold to obtain standard feature items; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
step S122, arranging the standard feature items to generate corresponding file numbers, and generating a corresponding relation table according to the file numbers and the data of the standard feature items to obtain a forward arrangement table.
2. The method according to claim 1, characterized in that in step S10 it further comprises: and establishing a data input module according to the original data and the new data by using an operating system supporting DBMS operation through an SQL language, wherein the input module comprises an original data input module and a new data input module, the original data input module is used for receiving the input of the original information, and the new data input module is used for receiving the input of the new information.
3. The method according to claim 2, characterized in that in said step S11, further comprising:
And establishing an information type searching module according to data in the system through SQL language by using an operating system supporting DBMS to run.
4. A method according to claim 3, wherein in step S11, further comprising:
The power grid dispatching data with certain common attribute or characteristic are merged together by each sub knowledge base architecture model through data classification, the data are distinguished through the attribute or characteristic of the category, and the distinguished power grid dispatching information is classified and stored.
5. The method according to claim 4, further comprising, in the step S11:
Creating an element knowledge set by using the element knowledge base architecture model, wherein the element knowledge set comprises power grid problem triggering scene information and a plurality of element question-answering groups corresponding to the power grid problem triggering scene information, each element question-answering group comprises a specific occurrence problem, an occurrence reason and a solution, and the solution comprises element attributes and element information corresponding to the element attributes;
Creating a list class knowledge set by using the list class knowledge base architecture model, wherein the list class knowledge set comprises a list class question-answer group and a list element set, and the list class question-answer group comprises a positive solution, a negative solution, a standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem;
Creating a concept knowledge set by using the concept knowledge base architecture model, wherein the concept knowledge set comprises a concept question-answer group, and the concept question-answer group comprises a solution, a standard occurrence problem and more than one concept expansion set problem corresponding to the standard occurrence problem;
And creating an FAQ class knowledge set by using the FAQ class knowledge base architecture model, wherein the FAQ class knowledge set comprises an FAQ class question-answering group, and the FAQ class question-answering group solution, one standard occurrence problem and more than one expansion occurrence problem corresponding to the standard occurrence problem.
6. The method according to any one of claims 1 to 5, wherein the step S13 further comprises:
Step S131, receiving the experience original data and the experience newly-built data, classifying the experience original data and the experience newly-built data through an intelligent scheduling technology analysis engine of the power grid, simultaneously calculating variances of all features of the two data, and then selecting features with variances larger than a threshold according to the threshold to obtain an original feature item; wherein the intelligent scheduling technology analysis engine of the power grid is VisualRules rule engine;
and S132, arranging the original characteristic items to generate corresponding archive numbers, and generating a corresponding relation table according to the archive numbers and the data of the original characteristic items to obtain a forward arrangement table.
7. The method according to any one of claims 1 to 5, further comprising:
and forming an intelligent scheduling event knowledge base of the power grid together according to the sub knowledge base, the standard knowledge base and the experience knowledge base.
Priority Applications (1)
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