CN111368387B - Electric power system simulation data textualization method - Google Patents

Electric power system simulation data textualization method Download PDF

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CN111368387B
CN111368387B CN201811588838.1A CN201811588838A CN111368387B CN 111368387 B CN111368387 B CN 111368387B CN 201811588838 A CN201811588838 A CN 201811588838A CN 111368387 B CN111368387 B CN 111368387B
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textualization
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黄彦浩
李炳男
李文臣
孙世杰
雷富强
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China Electric Power Research Institute Co Ltd CEPRI
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Abstract

The invention relates to a method for textualizing simulation data of a power system, which comprises the following steps: step S1, constructing a conceptual model generated by the text; step S2, performing data text preparation on the simulation calculation data; step S3, a data textualization task is performed. The invention can convert massive calculation data which has complex structure and is difficult to be directly observed into a knowledge text with clear and definite natural language characters as contents in a universal and convenient way; in the field of power flow simulation analysis, calculation data is converted into texts, customized data reading and analysis rules are performed for the calculation data conversion, and template languages for supporting rule operation are formulated and analyzed.

Description

Electric power system simulation data textualization method
[ technical field ] A method for producing a semiconductor device
The invention belongs to the technical field of electric power automation, and particularly relates to a method for textualizing simulation data of an electric power system.
[ background of the invention ]
The simulation calculation of the power system can generate a large amount of operation real-time data and result data, and the structure of the data has certain complexity and is difficult to directly observe to draw a conclusion. In the conventional simulation calculation analysis of the power system, a professional analyst analyzes and summarizes the data to generate a conclusion opinion. Most of the analysts will first perform some general statistical calculations on the result data, and then find out important information from the intermediate results according to different analysis strategies or angles and by means of professional experiences of the analysts. It can be seen that there is a lot of repetitive work in the simulation analysis process, and the essence of this repetitive work is the lack of extraction of data information. There is a need for a system that can parse simulation data having a special structure, extract and concentrate knowledge information from the parsed data, and express the information in the form of a natural language text. Meanwhile, in order to support applications such as text mining, it is also considered to construct a data structure supporting text mining. The invention can convert massive calculation data which has complex structure and is difficult to directly observe into a knowledge text which takes clear and definite natural language characters as contents in a universal, convenient and fast way; in the field of power flow simulation analysis, calculation data is subjected to textualization, customized data reading and analysis rules are performed for the textualization of the calculation data, and template languages for supporting the operation of the rules are formulated and analyzed.
[ summary of the invention ]
In order to solve the above problems in the prior art, the present invention provides a method for textualizing simulation data of an electric power system, the method comprising:
step S1, constructing a conceptual model generated by the text;
step S2, performing data text preparation on the simulation calculation data;
step S3, a data textualization task is executed.
Further, the step S1 is specifically: and setting the corresponding relation among the data reading template, the data analysis template and the text template based on the concept object, the relation and the logic relation among the entities.
Further, the step S2 is specifically: and performing specific setting of a data reading template, a data analysis template and a text template.
Further, the step S3 is specifically: reading an original simulation data file, reading the original simulation data file based on a data reading template, analyzing the read data based on a data analyzing file, and filling a textual information file according to a textual template.
Furthermore, the attributes in the concept object, the relationship between the attributes and the like and the relationship between the template items are constructed by setting the corresponding relationship among the data reading template, the data analysis template and the text template.
Further, the step S1 specifically includes the following steps:
step S11: constructing a concept object;
step S12: constructing a horizontal relation between concept objects;
step S13: entity construction of a data textualization task;
step S14: and generating a data text information file.
Further, the step S11 is specifically: and setting a conceptual object for the electric appliance component aimed by the power system simulation data, constructing a data reading template based on the conceptual object, and taking the data reading template as a carrier of the conceptual object.
Further, the step S12 is specifically: and selecting the referred concept object, performing relation analysis on the concept object, and filling a data analysis template based on a relation analysis result.
Further, the step S13 is specifically: and carrying out entity construction according to the attribute of the data textualization task, and correspondingly constructing a textualization template.
Further, the step S14 is specifically: initializing a data text information file, and storing data text related information based on a text template in the subsequent text process.
The beneficial effects of the invention include: the method can convert massive calculation data which are complex in structure and difficult to directly observe into a knowledge text with clear and definite natural language characters as contents in a universal and convenient manner; in the field of power flow simulation analysis, calculation data is subjected to textualization, customized data reading and analysis rules are performed for the textualization of the calculation data, and template languages for supporting the operation of the rules are formulated and analyzed.
[ description of the drawings ]
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, are not intended to limit the invention, and:
FIG. 1 is a schematic diagram of a data parsing template according to the present invention.
FIG. 2 is a schematic diagram of a data reading template of the present invention.
FIG. 3 is a timing diagram illustrating the textual task execution process of the present invention.
FIG. 4 is a diagram illustrating call relations during execution of a texting task according to the present invention.
[ detailed description ] embodiments
The present invention will now be described in detail with reference to the drawings and specific embodiments, wherein the exemplary embodiments and descriptions are only intended to illustrate the present invention, but not to limit the present invention.
As shown in fig. 1, a detailed description is given of a power system simulation data text method applied in the present invention;
performing the execution of the simulation data textualization based on the concept object, the relationship and the logic relationship among the entities; regarding the data textualization task as an entity called E, and setting the existence of the entity; the entity is composed of a plurality of facts (Fact) which are obtained by prior judgment or logical reasoning; there is no relationship between facts, a fact is just a description or listing;
facts are made up of conceptual objects and relationships between conceptual objects; the conceptual object contains one or more conceptual object properties; conceptual objects can span facts and become components of different facts, but cannot be used to directly constitute entities, and exist only based on facts; attributes are used to describe the state of a conceptual object;
a fact is a collection of one or more conceptual objects, the collection of facts constituting an entity, the facts being noted as:
E={Fact1{O1,O2,O3...},Fact2{O1,O2,O3...}...} (1);
preferably, the following components: the relationship is a horizontal relationship between conceptual objects; the horizontal relation comprises a logical operation relation, a numerical operation relation, a self-defined function relation and the like; suppose a conceptual object is x n N is a positive integer greater than 1, then with respect to x n The horizontal relational expression of (c) can be written as:
Figure BDA0001919755270000041
Figure BDA0001919755270000042
for example: for the text of the load flow calculation data, one text task of the load flow calculation data is an entity; the textualization tasks will exist natively, regardless of the content of the entity; only the fact statement, i.e. the statement whose logic value (including probabilistic true value) in the horizontal relation is true, is output from the entity; the sentence is the basis of the fact, is a regular expression set by a system user and accords with formal logic; for the textualization of load flow calculation data, due to the large data volume and the complex structure, a concept object needs to be constructed by using a data reading template;
preferably, the following components: fusing expert experience in the construction of the horizontal relationship, converting numerical data into a knowledge text, and constructing the horizontal relationship by using a data analysis template;
firstly, a textual model is required to be constructed for a textual task, and the model is maintained by software design to operate; the method comprises the following steps of taking a textual template as a carrier of an entity in a textual model; the data analysis template is used as a carrier of the fact, and a horizontal relation can be set in the data analysis template; for the simulation data of the power system, the key for constructing the textual model is to construct a textual template, a data analysis template, a data reading template and the like;
the electric power system simulation data textualization method specifically comprises the following steps of:
step S1, constructing a conceptual model generated by the text; setting corresponding relations of the data reading template, the data analysis template and the textualization template based on the concept objects, the relations and the logic relations among the entities;
the method comprises the steps that the corresponding relations among a data reading template, a data analyzing template and a text template are set, the relations among attributes and the like in a concept object and the relations among template items are established, and then in the process of performing the text processing on a specific simulation data file, the instantiation setting of the template file is required to be performed according to the characteristics of the simulation data file;
step S11: constructing a concept object, specifically: setting a conceptual object for an electric appliance component aimed by power system simulation data, constructing a data reading template based on the conceptual object, and taking the data reading template as a carrier of the conceptual object; it can be seen that the purpose of constructing a concept object is achieved by constructing a data reading template;
preferably, the following components: the data reading template comprises a plurality of key items, and the key items correspond to a plurality of attributes of the concept object;
in the process of data textualization, a data textualization task is an entity, the entity consists of a plurality of facts (Fact), and the facts are obtained by prior judgment or logical reasoning; there is no relationship between facts, a fact is just a description or listing;
preferably: the concept objects to be constructed include: electrical components such as a bus, an alternating current line, a direct current line, a generator, a transformer, a load and the like;
preferably, the following components: the attributes of the conceptual object include: the method comprises the following steps of row and column of electric element related data, read data set, unique identification of the data set, data cross-row reading and data association reading;
preferably, the following components: setting a plurality of template items in the data reading template corresponding to the conceptual object attributes according to the characteristics of the conceptual object model; the specific corresponding relationship is shown in the following table;
template item A Concept object name Concept object attributes Concept object name
Template item B Result set Concept object Properties Set of data read
Template item C Main key Concept object attributes Unique identification of data sets
Template item D Read step size Concept object attributes Data cross-row reading
Template item E External connection Concept object attributes Data associative reading
Step S12: constructing a horizontal relation between concept objects; the method comprises the following specific steps: selecting the referred concept object, performing relation analysis of the concept object, and filling a data analysis template based on a relation analysis result;
the horizontal relation construction is the extraction of data knowledge, and the knowledge in the data mainly exists in the incidence relation among the data, so the horizontal relation comprises the extraction of numerical value relation, logic relation, equation relation or custom relation among the data;
preferably: the analysis experience of experts on the data relationship is fused, data mining is carried out on the knowledge text formed according to the horizontal relationship, and the data mining result is used for constructing the horizontal relationship;
preferably: the horizontal relationship between conceptual objects includes: logical operational relationships (HRL), numerical operational relationships (HRN), custom functional relationships (HRF), etc.;
preferably: a plurality of horizontal relations can be set in one analysis template, and concept objects are called in the horizontal relations;
the corresponding relation between the template items and a plurality of items of the horizontal relation is shown in the following table;
Figure BDA0001919755270000061
Figure BDA0001919755270000071
step S13: the entity construction of the data textualization task specifically comprises the following steps: entity construction is carried out according to the attribute of the data textualization task, and a textualization template is correspondingly constructed;
the entity construction is carried out according to the attribute of the data text task, and specifically comprises the following steps: setting a set of facts contained by a corresponding entity of the data textualization task; namely, a set formed by a set of conceptual objects and horizontal relations between the conceptual objects; constructing corresponding relations among template items, user-defined information and horizontal relations of the textual template based on the entities; the purpose of outputting the textual report is achieved by constructing a textual template;
the entity is the whole content of the report document, the construction of the entity model is to determine the content set output by the document, and the content set is to output the truth items of all horizontal relations according to the design of the text model; the design of mockups tends to report on the flexibility of the documents and the ease with which a set of relationships can be defined; and the solid model includes: self-defining information and calling a horizontal relation;
preferably: the text template comprises custom information of a text entity and horizontal relation call;
the textual template item corresponds to a plurality of entries of the entity model as a table below;
Figure BDA0001919755270000072
step S14: generating a data text information file; the method specifically comprises the following steps: initializing a data textualization information file, and storing data textualization related information based on a textualization template in the subsequent textualization process;
the initialization data is a textual information file, which specifically includes: creating a new text information file, and setting the size of the text information file according to the size of the original simulation data file;
the data textualization information file is a data structure data file which is provided by a data textualization prototype system and supports text mining; in order to support text mining, a data structure of an information file records all associated information when each fact statement is generated in the next textual task; meanwhile, a storage form taking the fact statement as a unit is provided so as to facilitate searching taking the fact statement as a dimension;
step S2, performing data text preparation on the simulation calculation data; the method specifically comprises the following steps: performing specific setting of a data reading template, a data analysis template and a text template;
the data text preparation of the simulation calculation data comprises the following steps: the method comprises the following steps:
step S21: setting names of the horizontal relation groups and names of concept objects quoted in the horizontal relations in a data analysis template;
preferably, the following components: the horizontal relation group name and the quoted concept object name are English characters;
step S22: setting a horizontal relation name in a data analysis template;
preferably, the following components: the horizontal relationship name is English character;
step S23: setting a horizontal relation description in a data analysis template;
preferably, the following components: the horizontal relation description can be characters such as Chinese characters, English characters, numbers and the like;
step S24: setting a horizontal relation expression in a data analysis template;
preferably: the horizontal relational expression supports modes such as logic expression and function name. The logic expression supports numerical operation and logic relation operation;
step S215 sets a conceptual object name in the data reading template;
preferably, the following components: the concept object name is English character;
step S26: setting a conceptual object description field in a data reading template;
preferably, the following components: the description content of the concept object can be characters such as Chinese characters, English characters, numbers and the like;
step S27: setting a file name of a concept object data source and a returned result set name in a data reading template;
step S28: setting a concept object data set main key in a data reading template;
preferably, the following components: the main key is the column number of the concept object data file;
step S29: setting associated reading data of the concept object in a data reading template;
preferably, the following components: according to the special structure of the simulation data, the association between the concept objects A, B, the data content of the appointed row and column of the object A and the row sequence number of the object B can be set;
step S210: configuring and calling a set horizontal relation name in a text template, and filling in custom information according to the requirement;
step S3, executing data text task; the method comprises the following specific steps: reading an original simulation data file, reading the original simulation data file based on a data reading template, analyzing the read data based on a data analyzing file, and filling a textual information file according to a textual template;
preferably: the original simulation data file is a load flow simulation calculation data file; the power flow simulation calculation data files are stored in an example folder according to different electrical elements, and the content of a single file is simulation calculation data of one type of electrical elements; the content form of each file is a two-dimensional table, the rows of the two-dimensional table represent simulation data generated by certain physical quantity of the electrical elements in unit simulation time, and the columns of the two-dimensional table represent observable physical quantities of the elements; furthermore, the data form is changed in that it is possible to represent the simulation data of the observable physical quantity and the unit time of the electric element in a plurality of lines;
preferably: the load flow simulation calculation data files have the characteristic of correlation among files, and the data value of a certain row in the first file can be correlated to the data value of a certain row in the second file; the two associated data values are equal; for example: from A electrical element data, a certain row L a C a Is associated with a certain row L in the B electrical element data b C b The data value of (A) can be abbreviated as A (L) a C a )=B(L b C b );
The reading of the original simulation data file based on the data reading template specifically comprises the following steps: according to the characteristics of the conceptual object model, filling template items in the data reading template based on the corresponding relation between the template items and the conceptual object attributes;
after the data reading template is processed, the data textualization task reads all calling functions needed by the template analysis to process the subsequent template analysis;
the analyzing of the read data based on the data analyzing file specifically comprises: circularly calling the template analysis function, wherein in each calling process, the template analysis function analyzes the concept object and the horizontal relation thereof by reading the data analysis file; analyzing all the template items by circularly calling until all the template items are analyzed;
the filling of the textual information file according to the textual template specifically comprises: filling the data analysis result into a text information file according to a text template;
preferably; after the execution of the textualization task is initiated, initializing a textualization information file;
preferably: the text information file is positioned on distributed storage equipment; the method is suitable for a big data environment of simulation calculation of the current power system;
taking the prepared data '36-node arithmetic data' as an original data file, wherein the size of a folder is 2.66M, and the folder comprises data presentation files such as a bus, an alternating current line, a transformer, a direct current line, a generator, a load and the like and data result files; in the data textualization process, after a reading template, a last shift analysis and a textualization template are configured, a scene management is selected on a textualization system interface, a scene operation 2 is newly established, a corresponding template is selected, and an original data file is imported. Clicking and analyzing on the main interface to obtain the analysis result; looking at the local project folder "project pathname" + "resultData", we can see the temporary file generated according to the rule, the size of the temporary file is 50.26 KB;
preferably: the data textualization is considered to be completed by adopting distributed equipment; for example: the system runs in two node machines, and achieves the purpose of testing multi-machine distributed processing; meanwhile, the configurable characteristics of the generation template and the generation process are realized in the text generation process, and meanwhile, a relatively accurate text case can be generated only by using about 2M data, so that the design requirement and the purpose are achieved;
in the embodiments provided in the present invention, it should be understood that the disclosed method and terminal can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
In addition, the technical solutions in the above several embodiments can be combined and replaced with each other without contradiction.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned. Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of modules or means recited in the system claims may also be implemented by one module or means in software or hardware. The terms first, second, etc. are used to denote names, but not to denote any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (4)

1. A power system simulation data textualization method, the method comprising:
step S1, constructing a conceptual model generated by the text;
step S2, performing data text preparation on the simulation calculation data;
step S3, executing data text task;
the step S1 specifically includes the following steps:
step S11: constructing a concept object;
step S12: constructing a horizontal relation between concept objects;
step S13: entity construction of a data textualization task;
step S14: generating a data text information file;
the step S11 specifically includes: setting a concept object for an electric appliance component aimed by power system simulation data, constructing a data reading template based on the concept object, and taking the data reading template as a carrier of the concept object;
the data reading template comprises a plurality of key items, and the key items correspond to a plurality of attributes of the concept object;
the constructed concept objects comprise: the system comprises a bus, an alternating current line, a direct current line, a generator, a transformer and load electrical components;
the attributes of the conceptual object include: the method comprises the following steps of row and column of electric component related data, read data set, unique identification of the data set, data cross-row reading and data association reading;
the step S12 specifically includes: selecting the referred concept object, performing relation analysis of the concept object, and filling a data analysis template based on a relation analysis result;
the horizontal relation construction comprises the following steps: extracting data knowledge;
the analysis experience of the data relation is fused, data mining is carried out on the knowledge text formed according to the horizontal relation, and the result of the data mining is used for constructing the horizontal relation;
the horizontal relationship between conceptual objects includes: a logical operation relationship, a numerical operation relationship and a custom function relationship;
the step S13 specifically includes: entity construction is carried out according to the attribute of the data textualization task, and a textualization template is correspondingly constructed;
the entity construction is carried out according to the attribute of the data text task, and specifically comprises the following steps: setting a set of facts contained in the entity corresponding to the data textualization task; constructing corresponding relations among template items, user-defined information and horizontal relations of the textual templates based on the entities; the purpose of outputting the textual report is achieved by constructing a textual template;
the step S14 specifically includes: initializing a data text information file, and storing data text related information based on a text template in a subsequent text process;
the step S3 specifically includes: reading an original simulation data file, reading the original simulation data file based on a data reading template, analyzing the read data based on a data analyzing file, and filling a textual information file according to a textual template; the original simulation data file is a load flow simulation calculation data file;
the reading of the original simulation data file based on the data reading template specifically comprises the following steps: filling template items in the data reading template based on the corresponding relation between the template items and the concept object attributes according to the characteristics of the concept object model;
after the data reading template is subjected to analysis, the data textualization task reads all calling functions required by the template analysis to perform subsequent template analysis;
the analyzing of the read data based on the data analyzing file specifically comprises the following steps: circularly calling the template analysis function, wherein in each calling process, the template analysis function analyzes the concept object and the horizontal relation thereof by reading the data analysis file; analyzing all the template items by circularly calling until all the template items are analyzed;
the filling of the textual information file according to the textual template specifically comprises: and filling the textual information file according to the data analysis result by a textual template.
2. The power system simulation data textualization method according to claim 1, wherein the step S1 is specifically: and setting the corresponding relation of the data reading template, the data analysis template and the textualization template based on the logical relation among the concept objects, the relation and the entities.
3. The electric power system simulation data textualization method according to claim 2, wherein the step S2 is specifically: and performing specific setting of a data reading template, a data analysis template and a textualization template.
4. The electric power system simulation data textualization method according to claim 1, wherein the attributes in the conceptual object, the relationships between the attributes and the relationships between the template items are constructed by setting the corresponding relationships of the data reading template, the data parsing template and the textualization template.
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