CN113346449A - Protection constant value granulation intelligent checking method based on big data - Google Patents
Protection constant value granulation intelligent checking method based on big data Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
- H02H3/00—Emergency protective circuit arrangements for automatic disconnection directly responsive to an undesired change from normal electric working condition with or without subsequent reconnection ; integrated protection
- H02H3/006—Calibration or setting of parameters
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
- H02H1/00—Details of emergency protective circuit arrangements
- H02H1/0092—Details of emergency protective circuit arrangements concerning the data processing means, e.g. expert systems, neural networks
Abstract
The invention discloses an intelligent checking method for protecting constant value granulation based on big data, which comprises the following steps: and granulating fixed values of the fixed value list, analyzing each fixed value of the fixed value list which is audited by the OMS system through the system to obtain granulated fixed value item information, and using the granulated fixed value item information for subsequent fixed value intelligent audit and statistical analysis, construction of a fixed value audit expert experience base, fixed value intelligent audit and statistical analysis, CT saturation check, transformer neutral point grounding mode check and protection device data unified management. The method has the beneficial effects that: the intelligent checking method for protecting constant value granulation based on big data is suitable for the establishment form of a constant value audit rule expert system base, the constant value audit rule knowledge base is decoupled from the system, the operation of adding, deleting and modifying the constant value audit rule knowledge base is realized without upgrading the system, and the interaction form of the constant value audit rule knowledge base with intuition and strong operability is formed.
Description
Technical Field
The invention relates to a fixed value granulation intelligent checking method, in particular to a fixed value granulation intelligent checking method based on big data, and belongs to the technical field of application of the fixed value granulation intelligent checking method.
Background
The foreign power grid generally takes inverse time-limited current protection as backup protection, is relatively less influenced by an operation mode, has higher fixed value accuracy, has less research on related fixed value on-line check in foreign countries, and does not see related system application at present; relevant reports of engineering practical application; the research on the relay protection fixed value checking technology in China has been carried out for about ten years, some enterprises have developed relay protection fixed value on-line checking systems for main protection and backup protection fixed values on-line checking, the checking of other fixed values of the device mainly depends on manual checking in a fixed value single circulation system, and the research on comprehensive checking of all fixed values of the relay protection device on one platform is not available.
In the aspect of CT saturation checking, a relay protection online checking system or a relay protection constant value setting system is adopted to calculate the bus short-circuit capacity and then manually check the CT saturation condition, in the aspect of checking the transformer neutral point grounding mode, only the transformer neutral point grounding condition of each transformer substation can be manually checked, and the system analysis can not be carried out on the transformer neutral point grounding mode of the whole power grid; because the relay protection constant value online checking system is developed on a domestic operating system, the research on the application functions of the comprehensive constant value checking, the CT checking and the like on the basis of the system has technical difficulty, and all levels of scheduling of a power grid company are not at the beginning in the aspect of power grid relay protection intelligent checking technical research based on the OS2 system, so that the improvement of the intelligent level of the power grid is not facilitated. Therefore, an intelligent checking method for protecting fixed value granulation based on big data is proposed to solve the problems.
Disclosure of Invention
The invention aims to solve the problems and provide an intelligent checking method based on protection fixed value granulation under big data.
The invention achieves the above purposes through the following technical scheme, and a fixed value granulation intelligent checking method is protected based on big data, and comprises the following steps:
step S1, granulation of the fixed value list, wherein each fixed value of the fixed value list audited by the OMS system is analyzed to obtain granular fixed value item information through the system for subsequent intelligent auditing and statistical analysis of the fixed value;
step S2: constructing a constant value auditing expert experience base;
step S3: intelligent auditing and statistical analysis of fixed values, including:
a. designing a protection constant value standard format;
b. analyzing and classifying protection constant value data:
analyzing fixed value information of different protections into a uniform format uniformly, wherein the uniform format consists of a protection device name, a station name, a protected equipment name, a fixed value item and a fixed value, the fixed value item comprises each type of protection fixed value name of each equipment, and the fixed value is a numerical value corresponding to each fixed value item;
c. protection constant value intelligent audit: designing and developing intelligent auditing functions aiming at a constant value standard range, single protection logic, double protection logic, line two-side association and the like;
d. statistical analysis of the fixed-value data:
counting the value distribution rule of the protection constant value according to the historical accumulation of the constant value auditing result, and summarizing the distribution characteristics of the relay protection constant value of the regional power grid;
e. and (3) protecting the visual display of the intelligent audit result of the fixed value:
coloring and displaying the constant values with insufficient audit according to audit requirements, and visually displaying the distribution rule of the constant values in a curve mode;
step S4: and performing CT saturation check, calculating the maximum short-circuit current under the fault condition by adopting a parallel rapid algorithm through the existing power grid real-time operation mode of the relay protection setting value on-line check and risk early warning system based on the OS2 system and the existing power grid model CT transformation ratio data basis, and comparing with the CT selection multiple to realize CT saturation check.
Step S5: checking the grounding mode of the neutral point of the transformer, counting the number, rated capacity and zero sequence reactance value of the neutral point grounding transformer through a data base of the grounding mode of the neutral point of the transformer in the existing real-time operation mode of the power grid of the relay protection fixed value online checking system, analyzing the distribution characteristics of zero sequence current, judging whether the grounding mode is consistent with a set grounding rule or not, and giving an alarm when the grounding mode is not consistent with the set grounding rule;
step S6: the protection device data are managed uniformly, the protection devices are classified according to manufacturers, each protection device model maintains detailed version numbers and check codes, constant value lists, setting descriptions, device use specifications and constant value single-mode boards of different device models are classified and managed uniformly, and quick inquiry and downloading of relevant data can be performed according to different conditions.
Further, in step S1, first, the format of the fixed value list of different device models is studied, and the extraction and recording methods of the names of different fixed value items and the fixed value display positions are analyzed; secondly, designing a man-machine interaction interface and a data storage mode according to the research and analysis result; finally, extracting fixed value single key information according to the analyzed fixed value single format data information of the corresponding device model; and designing a standard format for storing the granular constant value according to various data extracted from the constant value list, wherein the storage file of the granular constant value is an xml or cime format file.
Further, in step S2, a preliminary fixed value audit expert experience base is first formulated according to the relationship between fixed values, and fixed value audit rules are gradually increased with the increase of fixed value items, and the expert experience base can be divided into fixed value range comparison, fixed value size relationship comparison, fixed value consistent relationship comparison, fixed value logic relationship comparison and the like according to different fixed value audit methods, so as to facilitate the operation of adding, deleting and modifying the fixed value audit rule knowledge base, the establishment of the fixed value rule knowledge base can be realized in a file form, and the addition, deletion and modification of the fixed value audit expert experience base are performed according to rules; if the alarm constant value in the constant value auditing result is the set experience value, a regional constant value auditing expert experience base can be finally formed by setting and modifying corresponding rules.
Further, the method for protecting the intelligent audit technology of the fixed value in step S3,
c1. comparing with a standard fixed value range, comparing the analyzed fixed value with the standard fixed value range, judging whether the analyzed fixed value is in the standard range, and giving an alarm prompt if the analyzed fixed value is not in the standard range;
c2. the intelligent examination and verification of a single set of protection constant value items, the check of the single set of protection device constant values is a basic function module of the relay protection constant value intelligent check system, and the main realization functions are as follows: judging a reasonable interval of the value of a single constant value item, and auditing the logical relation of the associated constant value items;
c3. and performing correlation audit on the double protection constant values on the same side by acquiring the two protection device constant values on the same side of the line protection and performing audit on the correlation items of the double protection constant values on the same side. The method can check through the related fixed value items between the two sets of protections, and can alarm by finding out the inconsistent fixed value items of the two sets of protections. The checking between the double sets of protection at the same side comprises auditing and alarming aiming at the same constant value items of the double sets of protection.
c4. And the correlation audit of the protection setting values at two sides of the line is mainly used for checking the consistency of the parameter setting values of basic equipment at two sides of the line, the correlation of line identification codes, the correlation of related control words and the like, so that the checking alarm is carried out on the setting value data to the greatest extent.
Further, in the automatic analysis method for protection fixed value data in step S2, the number of fixed value items of different protection devices is large, the manual establishment of a standard fixed value item template has a large workload of automatic analysis and docking and is prone to errors, the project can be fuzzily matched with a plurality of fixed value item name descriptions through the fixed value items of each standard format, the manually matched fixed value item name descriptions are automatically recorded, and the matching library is intelligently updated, so that more device fixed values can be automatically identified when a new device fixed value list is obtained, and finally, the automatic analysis of protection fixed value data is realized.
Further, in the step S2, the adaptive method for protecting the constant value audit expert base gradually increases the constant value audit rules as the constant value items increase, so as to facilitate the operation of increasing, deleting and modifying the constant value audit rule experience base, the establishment of the constant value rule experience base can be realized in a file form, the increase, deletion and modification of the constant value audit rule experience base are performed according to the rules, and after the constant value rules change, the system program does not need to be updated, so that the constant value audit rule experience base can be decoupled from the system, so that the constant value audit rule experience base can be adaptively increased, deleted and modified, and the operation is easy and more flexible.
Further, the specific steps of protecting the visualization of the intelligent audit result of the fixed value in step S2 are,
e1. early warning is realized through a visual means, and simplified warning information or detailed warning content is selected and displayed according to needs;
e2. the normal state and the abnormal state are colored respectively through visual early warning;
e3. and the visual display in various forms such as lists, curves, vector diagrams, two-dimensional colored diagrams, animations and the like is supported.
Further, the reasonable interval of the value of the single constant value item refers to a reasonable interval determined by experience or requirements of a protection device, basic parameters such as line length, impedance angle and the like can determine the reasonable interval according to experience and voltage level, when device constant value data are located outside the interval, the problem of the constant value can be judged, an alarm is given, and the main function of auditing the reasonable interval of the single constant value is to prevent the error setting of the constant value caused by decimal point errors and the like.
Further, the logical relationship audit of the associated fixed value items refers to the check of the associated fixed value items in the same set of protection device, for example, the phase distance I section should be about 80% of the line positive sequence impedance under normal conditions, so that the line positive sequence impedance can be taken for the associated audit when the fixed value of the phase distance I section is audited, other associated fixed value items including the fixed values of the distance protection sections should be increased from large to small, the time fixed values also have similar relationships, and the mutation current, the differential current and the like are associated with the CT transformation ratio, so that the associated audit can also be carried out.
The invention has the beneficial effects that: the intelligent checking method is suitable for the establishment form of a constant value audit rule expert system base, the constant value audit rule knowledge base is decoupled from the system, the operation of increasing, deleting and changing the constant value audit rule knowledge base is realized without upgrading the system, an intuitive and strong-operability interaction form of the constant value audit rule knowledge base is researched, so that protection workers can establish a set of complete constant value audit rule expert system base according to the needs, the expert experience of relay protection profession is converted from the form of a rule into the process of simulating artificial intelligent audit, the constant value hierarchical classification technology of devices is researched from different angles such as different equipment types, different sides of the same equipment, double sets of the same equipment and constant value data of the device, the distribution rule of data type incidence relation and numerical type multi-item probability is established, and the data mining technology of the big data is utilized, establishing a constant value auditing standard library and a regional library adapted to regional power grid characteristics, realizing intelligent auditing based on a constant value single of a constant value setting device, firstly acquiring a CT transformation ratio primary value and a current transformer type of each device, respectively obtaining primary CT transformation ratio values of different types of protection at each side of a transformer, then obtaining a real-time operation mode of a power grid from an EMS platform, calculating the maximum short-circuit current and the maximum zero-sequence current which pass through each current transformer, finally checking whether the CT is saturated or not through the primary CT transformation ratio and the type of the current transformer, and (3) timely early warning the discovered hidden danger, prompting a scheduling department to timely adjust an operation mode or replace a current transformer, forming a probability distribution function by auditing results, deviation degrees, alarm information and the like of protection fixed value items of different devices of different equipment to obtain a distribution rule, and realizing statistics and visual display of the results.
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In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in the figure, the intelligent checking method for protection fixed value granulation based on big data of the embodiment includes the following steps:
step S1, granulation of the fixed value list, wherein each fixed value of the fixed value list audited by the OMS system is analyzed to obtain granular fixed value item information through the system for subsequent intelligent auditing and statistical analysis of the fixed value;
firstly, researching formats of fixed value lists of different device models, and analyzing extraction and recording methods of names of different fixed value items and fixed value display positions; secondly, designing a man-machine interaction interface and a data storage mode according to the research and analysis result; finally, extracting definite value single key information, such as a definite value single number, a station name, an equipment name, a protection device model, a CT transformation ratio, a PT transformation ratio and the like, and definite value detailed data, such as a definite value item name, a definite value, a unit, an original definite value and the like, according to the analyzed definite value single format data information corresponding to the device model; designing a standard format for storing the granular constant value according to various data extracted from the constant value list, wherein the storage file of the granular constant value is an xml or cime format file;
step S2: the method comprises the steps of establishing a fixed value audit expert experience base, firstly establishing a preliminary fixed value audit expert experience base according to the relation between fixed values, gradually increasing fixed value audit rules along with the increase of fixed value items, dividing the expert experience base into fixed value range comparison, fixed value size relation comparison, fixed value consistent relation comparison, fixed value logic relation comparison and the like according to different fixed value audit methods, achieving the establishment of the fixed value rule knowledge base through files for facilitating the operation of increasing, deleting and modifying the fixed value audit rule knowledge base, and increasing, deleting and modifying the fixed value audit expert experience base according to rules; if the alarm constant value in the constant value auditing result is the set experience value, a regional constant value auditing expert experience base can be finally formed by setting and modifying corresponding rules;
step S3: intelligent auditing and statistical analysis of fixed values,
a. the design of a standard format of a protection constant value requires protection equipment of different manufacturers with different principles in order to ensure the safe and stable operation of the transformer substation; however, because of the non-standard protection design and naming of different manufacturers, certain potential safety hazard exists in the actual operation, so a standardized fixed value library needs to be designed, different fixed value items of different protection manufacturers are unified, fixed values in the system are converted into a standard format, the fixed values are divided into four parts, namely an equipment parameter fixed value, a numerical value fixed value, a control word fixed value and a soft pressing plate fixed value, each fixed value of the fixed value library contains a fixed value item name, a fixed value range, a fixed value unit and the like, and a foundation is laid for the intelligent auditing of subsequent fixed values;
b. analyzing and classifying protection constant value data: the automatic identification function of the fixed value of the protection device is developed, basic data support is provided for intelligent anti-error audit of the fixed value protection, the fixed value items of different types of protection are different, therefore, the fixed value data need to be analyzed and in butt joint with the fixed value name in a standard format to obtain a standard fixed value name, and the condition that the same fixed value item name is not consistent is avoided.
The method comprises the steps of analyzing fixed value information of different protections into a uniform format in a uniform mode, wherein the uniform format mainly comprises a protection device name, a station name, a protected device name, a fixed value item and a fixed value, the fixed value item comprises fixed value names of various types of protection of all devices, and the fixed value is a numerical value corresponding to each fixed value item.
The classified definite value items are subjected to fuzzy matching with definite values in a standard format, completely identical definite value items are automatically matched, incompletely identical definite value items are manually matched, the matching range is subject to analysis definite values, and device-level protection definite value data can be classified according to the following categories so as to facilitate check, statistical analysis and display design of related visual interfaces of the definite value data.
c. Protection constant value intelligent audit: designing and developing intelligent auditing functions aiming at a constant value standard range, single protection logic, double protection logic and association of two sides of a line;
d. statistical analysis of the fixed-value data: and counting the value distribution rule of the protection constant value according to the historical accumulation of the constant value auditing result, and summarizing the distribution characteristics of the relay protection constant value of the regional power grid.
e. Visual display for protecting constant value intelligent audit result
Coloring and displaying the constant values with insufficient audit according to audit requirements, and visually displaying the distribution rule of the constant values in a curve mode;
step S4: and CT saturation checking, namely calculating the maximum short-circuit current under the fault condition by adopting a parallel rapid algorithm through the existing power grid real-time operation mode of the relay protection setting value on-line checking and risk early warning system based on the OS2 system and the existing power grid model CT transformation ratio data basis, and comparing with the CT selection multiple to realize CT saturation checking.
Step S5: checking the grounding mode of the neutral point of the transformer, counting the number, rated capacity and zero sequence reactance value of the neutral point grounding transformer by using a data base of the grounding mode of the neutral point of the transformer in the existing real-time operation mode of a power grid of the relay protection fixed value online checking system, analyzing the distribution characteristics of zero sequence current, judging whether the grounding mode is consistent with a set grounding rule or not, and giving an alarm when the grounding mode is not consistent with the set grounding rule.
Step S6: the protection device data are managed uniformly, the protection devices are classified according to manufacturers, each protection device model maintains detailed version numbers and check codes, constant value lists, setting descriptions, device use specifications and constant value single modules of different device models are classified and managed uniformly, quick inquiry can be carried out according to different conditions, and relevant data can be downloaded.
Further, the granulation method of the standard data format of the fixed value file in step S1 is specifically that most of the fixed value single files are in word or excel format, and the number and content of the fixed value items of different protection devices are different, so that the fixed value file needs to be granulated to realize the intelligent fixed value check. Firstly, the fixed value single content of different device models of a power grid is researched, extraction and recording methods of different fixed value item names and fixed value display positions are analyzed, and then a data storage mode and an application display interface are designed according to the research and analysis results. Finally, extracting definite value single key information (such as definite value single number, station name, equipment name, protection device model, CT transformation ratio, PT transformation ratio and the like) through the analyzed definite value single format data information corresponding to the device model, and extracting definite value detailed data; and finally forming a granular constant value storage file in an xml or cime format which accords with the power line standard interaction specification according to each item of data extracted from the constant value list and a standard format of granular constant value storage.
Further, the method for protecting the intelligent audit technology of the fixed value in step S3 includes:
c1. comparing with a standard fixed value range, comparing the analyzed fixed value with the standard fixed value range, judging whether the analyzed fixed value is in the standard range, and giving an alarm prompt if the analyzed fixed value is not in the standard range;
c2. the intelligent examination and verification of a single set of protection constant value items, the check of the single set of protection device constant values is a basic function module of the relay protection constant value intelligent check system, and the main realization functions are as follows: judging a reasonable interval of the value of a single constant value item, and auditing the logical relation of the associated constant value items;
c3. and performing correlation audit on the double protection constant values on the same side by acquiring the two protection device constant values on the same side of the line protection and performing audit on the correlation items of the double protection constant values on the same side. The method can check through the related fixed value items between the two sets of protections, and can alarm by finding out the inconsistent fixed value items of the two sets of protections. The checking between the double sets of protection at the same side comprises auditing and alarming aiming at the same constant value items of the double sets of protection.
c4. And the correlation audit of the protection setting values at two sides of the line is mainly used for checking the consistency of the parameter setting values of basic equipment at two sides of the line, the correlation of line identification codes, the correlation of related control words and the like, so that the checking alarm is carried out on the setting value data to the greatest extent.
Further, the automatic analysis method of the guard-value data in step S2 includes: the number of the fixed value items of different protection devices is large, the manual establishment of a standard fixed value item template for automatic analysis and butt joint is large in workload and prone to errors, the items are planned to be capable of being matched with a plurality of fixed value item name descriptions in a fuzzy mode through the fixed value items of each standard format, the fixed value item name descriptions matched manually are recorded automatically, a matching library is updated intelligently, so that more device fixed values can be identified automatically when a new device fixed value list is obtained, and finally, automatic analysis of protection fixed value data is achieved.
Further, the adaptive method for protecting the constant value audit expert database in step S2 includes: the fixed value auditing rule is gradually increased along with the increase of the fixed value items, in order to facilitate the operation of increasing, deleting and modifying the fixed value auditing rule experience library, the establishment of the fixed value auditing rule experience library can be realized in a file form, the increase, deletion and modification of the fixed value auditing rule experience library are carried out according to the rules, and after the fixed value rules are changed, the system program does not need to be upgraded, the fixed value auditing rule experience library can be decoupled from the system, so that the fixed value auditing rule experience library can be adaptively increased, deleted and modified, and the operation is easy and more flexible.
Further, the step S2 of protecting the visualization of the intelligent audit result of the fixed value includes the specific steps of,
e1. early warning is realized through a visual means, and simplified warning information or detailed warning content is selected and displayed according to needs;
e2. the normal state and the abnormal state are colored respectively through visual early warning;
e3. and the visual display in various forms such as lists, curves, vector diagrams, two-dimensional colored diagrams, animations and the like is supported.
Further, a reasonable interval of the value of the single constant value item refers to a reasonable interval determined through experience or requirements of a protection device, basic parameters such as line length, impedance angle and the like can determine the reasonable value interval according to experience and voltage level, when device constant value data are located outside the interval, the problem of the constant value can be judged, an alarm is given, and the main function of auditing the reasonable interval of the single constant value is to prevent the error setting of the constant value caused by decimal point errors and the like.
Further, the logical relation audit of the associated fixed value items refers to the check of the associated fixed value items in the same set of protection device, for example, the phase distance I section is about 80% of the line positive sequence impedance under the normal condition, so that the line positive sequence impedance can be taken for the associated audit when the fixed value of the phase distance I section is audited, other associated fixed value items including the fixed value of each section of distance protection are increased from large to small, the time fixed value has a similar relation, and the mutation current, the differential current and the like are associated with the CT transformation ratio, so that the associated audit can be carried out.
The method is suitable for the establishment form of the constant value audit rule expert system base, the constant value audit rule knowledge base is decoupled from the system, the operation of increasing, deleting and modifying the constant value audit rule knowledge base is realized without upgrading the system, and an interactive form of the constant value audit rule knowledge base with intuition and strong operability is researched, so that a protection worker can make a set of complete constant value audit rule expert system base according to the requirement, and the expert experience of relay protection profession is converted into the process of simulating artificial intelligent audit from the form of the rule.
The method is suitable for forming probability distribution functions of audit results, deviation degrees, alarm information and the like of protection fixed value items of different devices of different equipment to obtain a distribution rule and realize statistics and visual display of the results.
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 sign in a claim should not be construed as limiting the claim concerned.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. Protection fixed value granulation intelligent checking method based on big data is characterized in that: the intelligent checking method for the constant value granulation comprises the following steps:
step S1, granulation of the fixed value list, wherein each fixed value of the fixed value list audited by the OMS system is analyzed to obtain granular fixed value item information through the system for subsequent intelligent auditing and statistical analysis of the fixed value;
step S2: constructing a constant value auditing expert experience base;
step S3: intelligent auditing and statistical analysis of fixed values, including:
a. designing a protection constant value standard format;
b. analyzing and classifying protection constant value data: analyzing fixed value information of different protections into a uniform format uniformly, wherein the uniform format consists of a protection device name, a station name, a protected equipment name, a fixed value item and a fixed value, the fixed value item comprises each type of protection fixed value name of each equipment, and the fixed value is a numerical value corresponding to each fixed value item;
c. protection constant value intelligent audit: designing and developing intelligent auditing functions aiming at a constant value standard range, single protection logic, double protection logic and association of two sides of a line;
d. statistical analysis of the fixed-value data: counting the value distribution rule of the protection constant value according to the historical accumulation of the constant value auditing result, and summarizing the distribution characteristics of the relay protection constant value of the regional power grid;
e. and (3) protecting the visual display of the intelligent audit result of the fixed value: coloring and displaying the constant values with insufficient audit according to audit requirements, and visually displaying the distribution rule of the constant values in a curve mode;
step S4: performing CT saturation check, calculating the maximum short-circuit current under the fault condition by adopting a parallel rapid algorithm through the existing power grid real-time operation mode of the relay protection setting value on-line check and risk early warning system based on the OS2 system and the existing power grid model CT transformation ratio data basis, and comparing with the CT selection multiple to realize CT saturation check;
step S5: checking the grounding mode of the neutral point of the transformer, counting the number, rated capacity and zero sequence reactance value of the neutral point grounding transformer through a data base of the grounding mode of the neutral point of the transformer in the existing real-time operation mode of the power grid of the relay protection fixed value online checking system, analyzing the distribution characteristics of zero sequence current, judging whether the grounding mode is consistent with a set grounding rule or not, and giving an alarm when the grounding mode is not consistent with the set grounding rule;
step S6: the protection device data are managed uniformly, the protection devices are classified according to manufacturers, each protection device model maintains detailed version numbers and check codes, constant value lists, setting descriptions, device use specifications and constant value single-mode boards of different device models are classified and managed uniformly, and quick inquiry and downloading of relevant data can be performed according to different conditions.
2. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: in step S1, the format of the fixed value list of different device models is studied first, and the extraction and recording methods of the names of different fixed value items and fixed value display positions are analyzed; secondly, designing a man-machine interaction interface and a data storage mode according to the research and analysis result; finally, extracting fixed value single key information according to the analyzed fixed value single format data information of the corresponding device model; and designing a standard format for storing the granular constant value according to various data extracted from the constant value list, wherein the storage file of the granular constant value is an xml or cime format file.
3. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: in step S2, a preliminary fixed value audit expert experience library is first formulated according to the relationship between fixed values, and fixed value audit rules are gradually increased with the increase of fixed value items, and the expert experience library can be divided into fixed value range comparison, fixed value magnitude relationship comparison, fixed value consistency relationship comparison, and fixed value logic relationship comparison according to different fixed value audit methods.
4. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: the intelligent audit of the protection fixed value in the step S3 includes:
c1. comparing with a standard fixed value range, comparing the analyzed fixed value with the standard fixed value range, judging whether the analyzed fixed value is in the standard range, and giving an alarm prompt if the analyzed fixed value is not in the standard range;
c2. the intelligent examination and verification of a single set of protection constant value items, the check of the single set of protection device constant values is a basic function module of the relay protection constant value intelligent check system, and the main realization functions are as follows: judging a reasonable interval of the value of a single constant value item, and auditing the logical relation of the associated constant value items;
c3. the correlation audit of the same-side double-protection constant values can be realized by acquiring the two protection device constant values at the same side of the line protection and auditing the correlation items of the same-side double-protection constant values, the check can be performed through the correlated constant value items between the double-protection sets, the alarm can be realized by finding out the inconsistent constant value items of the double-protection sets, and the check of the double-protection sets at the same side comprises the audit alarm aiming at the same constant value items of the double-protection sets.
c4. And the correlation audit of the protection setting values at two sides of the line is mainly used for checking the consistency of the parameter setting values of basic equipment at two sides of the line, the correlation of line identification codes, the correlation of related control words and the like, so that the checking alarm is carried out on the setting value data to the greatest extent.
5. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: in the automatic analysis method of the protection fixed value data in step S2, a plurality of fixed value item name descriptions can be fuzzy-matched through each fixed value item in the standard format, and the manually-matched fixed value item name descriptions are automatically recorded, so that the matching library is intelligently updated, so that more device fixed values can be automatically identified when a new device fixed value list is obtained, and finally, the automatic analysis of the protection fixed value data is realized.
6. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: in the step S2, the adaptive method for protecting the constant value audit expert base gradually increases the constant value audit rules as the constant value items increase, so as to facilitate the operation of increasing, deleting and modifying the constant value audit rule experience base, the establishment of the constant value rule experience base can be realized in the form of a file, the increase, deletion and modification of the constant value audit rule experience base are performed, and after the constant value rule is changed, the decoupling of the constant value audit rule experience base and the system can be achieved without upgrading the system program, so that the constant value audit rule experience base can be adaptively increased, deleted and modified.
7. The intelligent checking method for protection fixed value granulation based on big data according to claim 1, characterized in that: in step S2, the steps of protecting the visual display of the fixed value intelligent audit result include:
e1. early warning is realized through a visual means, and simplified warning information or detailed warning content is selected and displayed according to needs;
e2. the normal state and the abnormal state are colored respectively through visual early warning;
e3. and the visual display in various forms such as lists, curves, vector diagrams, two-dimensional colored diagrams, animations and the like is supported.
8. The intelligent checking method for protection fixed value granulation based on big data according to claim 3, characterized in that: the reasonable interval of the value of the single constant value item is a reasonable interval determined by experience or the requirements of a protection device, basic parameters such as line length, impedance angle and the like can determine the reasonable value interval according to experience and voltage level, and when the constant value data of the device is positioned outside the interval, the problem of the constant value can be judged, and an alarm is given.
9. The intelligent checking method for protection fixed value granulation based on big data according to claim 3, characterized in that: the logical relationship examination of the associated fixed value items refers to the examination of the associated fixed value items in the same set of protection device.
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