Power plant protection device constant value comparison optimization method, electronic equipment and storage medium

Abstract

The invention relates to a power plant protection device constant value comparison optimization method, electronic equipment and a storage medium, and the method comprises the steps: collecting and preprocessing the constant value data of a protection device, obtaining a constant value item data set, and generating a constant value item library according to the constant value item data set; obtaining a pre-constructed docking principle training library, and carrying out fixed value docking training on the docking principle training library to obtain a docking training model; the data in the constant value item library are compared and analyzed through the docking training model, and a constant value comparison result of the protection device is obtained.By using the constant value item docking principle library generated based on the training model, the constant value item docking efficiency is improved, and meanwhile the constant value item docking accuracy is also improved.

Description

Technical Field

[0001] The present application relates to the technical field of relay protection, and in particular to a method for optimizing the comparison of fixed value of protection devices in power plants, electronic equipment and storage media. Background Art

[0002] The relay protection system is an indispensable key component for the safe and stable operation of power plants. Its importance is reflected in many aspects and is directly related to the reliable power supply and operating efficiency of power plants and even the entire power system. With the large-scale investment in secondary equipment in power plants, the setting comparison of protection devices has become a task that cannot be ignored. The large number of irregular device setting comparisons has brought great challenges to the operation and maintenance personnel in the plant. At present, most of the setting comparison work is done by manually docking the setting items, which is not only inefficient and labor-intensive, but also may be caused by human errors. Mis-docking and mis-comparison, which in turn affects the comparison results and leads to misjudgment. It can be seen that the traditional manual item-by-item comparison is no longer suitable for the intelligent development requirements of power plants.

[0003] In recent years, with the rapid development of artificial intelligence technology, it has shown significant advantages in data processing. Artificial intelligence technology can process large amounts of data quickly and efficiently, and deeply explore the potential connections and patterns in the data through algorithms such as deep learning and machine learning. In the comparison of protection device setting values, artificial intelligence technology can accurately identify and process abnormal values ​​and outliers in the data to avoid interference with the analysis results.

[0004] However, despite the great potential of artificial intelligence technology in setting value comparison, the existing setting value comparison scheme still lacks an online setting value comparison process after the power plant executes the setting value order. This makes it impossible to confirm whether the setting value executed in the protection device is consistent with the setting value order set in the plant or the setting value order issued by the dispatcher. Therefore, in the event of a fault in the power system, it is impossible to ensure that the relay protection system accurately executes the protection action, thus affecting the safety and stability of the power grid operation. Summary of the invention

[0005] The embodiments of the present application provide a method for optimizing the comparison of fixed value of a power plant protection device, an electronic device and a storage medium, so as to at least solve the problem that the existing fixed value comparison scheme in the related art lacks an online fixed value comparison process after the power plant executes the fixed value order.

[0006] In a first aspect, an embodiment of the present application provides a method for optimizing the comparison of fixed value of a power plant protection device, comprising:

[0007] Collecting and preprocessing the fixed value data of the protection device to obtain a fixed value item data set, and generating a fixed value item library according to the fixed value item data set;

[0008] Obtaining a pre-built docking principle training library, performing fixed-value docking training on the docking principle training library, and obtaining a docking training model;

[0009] The docking training model is used to compare and analyze the data in the fixed value item library to obtain the fixed value comparison result of the protection device.

[0010] In one embodiment, the collecting and preprocessing of the protection device fixed value data to obtain the fixed value item data set includes:

[0011] Collect the data of the currently running set value items of the on-site protection device, as well as the data of the adjusted set value items issued by the factory setting or dispatch;

[0012] The in-operation fixed value item data and the adjusted fixed value item data are subjected to abnormal value processing, missing value processing, and data screening processing to obtain the fixed value item data set.

[0013] In one embodiment, the construction of the docking principle training library includes:

[0014] The set value item name equivalence group C1 is used to indicate the correspondence between the set value item names actually operated on site and the adjusted set value item names;

[0015] The fixed value unit equivalence group C2 is used to express the correspondence between fixed value items of the same physical quantity expressed in different units;

[0016] Protection classification equivalence group C3 is used to indicate the classification correspondence between different protection functions of protection devices;

[0017] Ignore docking fixed value item group C4, used to indicate fixed value items that do not need to be docked during the fixed value comparison process;

[0018] Ignore verification set value group C5 is used to indicate the set values ​​that do not need to be verified in detail during the set value comparison process.

[0019] In one embodiment, the docking principle training library is subjected to fixed-value docking training to obtain a docking training model, including:

[0020] Constructing a total objective function of the fixed value comparison according to the docking principle training library, the in-operation fixed value item data and the adjusted fixed value item data;

[0021] Before comparing the fixed value items, docking training is performed on the in-service fixed value item data and the adjusted fixed value item data according to the equivalent group information in the docking principle training library to obtain the fixed value item association conditions;

[0022] Perform fixed value item comparison training on the related in-operation fixed value item data and adjusted fixed value item data to obtain matching result verification rules;

[0023] The docking training model is obtained by combining the total objective function of the fixed value comparison, the associated conditions of the fixed value items and the matching result verification rules.

[0024] In one embodiment, assuming that the in-operation fixed value item data is A and the adjustment fixed value item data is B, the fixed value item association conditions include:

[0025] Condition 1: If the names of the fixed-value items of A and B are the same or the overlap is higher than the set threshold, then A and B are associated;

[0026] Condition 2: In the docking principle training library, if A and B belong to the same fixed value item name equivalence group C1, then A and B are associated;

[0027] Condition 3: If the units of the fixed-value items of A and B are the same, or if neither A nor B has a unit, then A and B are associated;

[0028] Condition 4: In the docking principle training library, if the units of A and B belong to the same fixed-value unit equivalence group C2, then A and B are associated;

[0029] Condition 5: if A and B belong to the same protection classification equivalence group C3 or the overlap is higher than the set threshold, then A and B are associated;

[0030] Condition 6: If A or B belongs to the docking valued item group C4 ignored in the docking principle training library, then A and B are not associated;

[0031] Condition 7: If A or B belongs to the ignored check constant group C5 in the docking principle training library, then A and B are not associated.

[0032] In one embodiment, the matching result verification rules include:

[0033] Rule 1: If A and B meet condition 6, the verification result of A and B is "ignore the connection";

[0034] Rule 2: If A and B meet condition 7, the verification result of A and B is "ignore verification";

[0035] Rule 3: If the values ​​of A and B are consistent and meet conditions 3 or 4, the verification result of A and B is "consistent";

[0036] Rule 4: If the relationship between A and B does not satisfy Rule 1, Rule 2 or Rule 3, the verification result is "inconsistent".

[0037] In one embodiment, the method of performing a fixed value comparison item by item on the data in the fixed value item library through the docking training model to obtain a fixed value comparison result of the protection device includes:

[0038] Compare and analyze each fixed value in the fixed value item library through the docking training model to obtain a verification result of each fixed value;

[0039] When more than one verification result in the fixed-value item library is "inconsistent", the fixed-value comparison result of the fixed-value item library is different; otherwise, the fixed-value comparison result of the fixed-value item library is no difference.

[0040] In one embodiment, the condition for determining whether the values ​​of A and B are consistent is:

[0041] When A and B are digital data, the difference between A and B is less than a preset threshold; or, when the values ​​of A and B are the data in this article, the values ​​of A and B are completely consistent.

[0042] In a second aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for optimizing the comparison of constant values ​​of protection devices of a power plant as described in the first aspect above is implemented.

[0043] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the power plant protection device constant value comparison optimization method as described in the first aspect above.

[0044] The power plant protection device setting comparison optimization method, electronic device and storage medium provided by the embodiments of the present application have at least the following technical effects:

[0045] The fixed value data of the protection device is collected and preprocessed to obtain a fixed value item data set, and a fixed value item library is generated according to the fixed value item data set; a pre-constructed docking principle training library is obtained, and fixed value docking training is performed on the docking principle training library to obtain a docking training model; the data in the fixed value item library is compared and analyzed by the docking training model to obtain a fixed value comparison result of the protection device. The present application improves the efficiency of fixed value item docking by using a fixed value item docking principle library generated based on the training model, and also improves the accuracy of fixed value item docking.

[0046] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0048] Figure 1 is a flow chart of a method for optimizing the comparison of fixed value of a power plant protection device in one embodiment of the present application;

[0049] Figure 2 is a flow chart of a method for optimizing the comparison of fixed value of a power plant protection device in another embodiment of the present application;

[0050] Figure 3 It is a structural block diagram of an electronic device in one embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0052] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0053] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0054] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0055] In recent years, artificial intelligence technology has become more and more mature, and it has also shown significant advantages in the processing of fixed value comparison data. With the help of advanced algorithms and models, it can process a large amount of data quickly and efficiently. At the same time, through deep learning, machine learning and other algorithms, it is possible to deeply explore the potential associations and patterns in the data. In the fixed value comparison, the abnormal values ​​and outliers in the data can be accurately identified and processed to avoid interference with the analysis results. Therefore, the docking principle training model can be introduced, and the idea of ​​ignoring docking groups and equivalent groups can be proposed, so that the program can intelligently compare fixed values. Inspired by this, a method for optimizing the comparison of fixed values ​​of power plant protection devices based on training models is proposed. A training library for the docking principle of power plants is constructed. Based on this method, the in-operation fixed values ​​and the fixed values ​​issued by the dispatcher or set in the plant are preprocessed, and the comparison results are output through the intelligent comparison function.

[0056] In order to achieve accurate comparison of the set values ​​of power plant protection devices, the present invention proposes a set value comparison optimization method based on a training model to improve the docking accuracy and efficiency of the set value items. At the same time, the output comparison results can also provide auxiliary decision-making for on-site operation and maintenance personnel.

[0057] Based on the above situation, the embodiment of the present application provides a power plant protection device constant value comparison optimization method, electronic device and storage medium. First, a large amount of pre-processed text data reflecting the equipment protection device information, protection classification, and protection constant value items is used as the input of the system to obtain a constant value item data set, and the fixed value item text data is parsed and stored through an artificial intelligence automatic algorithm to obtain a plant protection device constant value item library; the docking principle library is injected to perform constant value docking training to obtain a docking training model; finally, the fixed value is compared item by item through the reaction of the mature docking principle library, and the fixed value comparison result of the protection device is obtained.

[0058] In a first aspect, the present application provides a method for optimizing the comparison of fixed value of a power plant protection device, such as Figure 1 As shown, the method includes the following steps.

[0059] Step S1, collect the protection device fixed value data and perform preprocessing to obtain a fixed value item data set, and generate a fixed value item library according to the fixed value item data set. Specifically, collect the current operating fixed value item data executed by the field protection device and the adjustment fixed value item data set or dispatched by the factory; perform abnormal value processing, missing value processing, and data screening processing on the operating fixed value item data and the adjustment fixed value item data to obtain the fixed value item data set.

[0060] Step S2, obtaining a pre-built docking principle training library, performing fixed-value docking training on the docking principle training library through a large number of fixed-value item data sets, and obtaining a docking training model.

[0061] Specifically, the docking principle training library includes the following equivalence groups: a set value item name equivalence group C1, which is used to indicate the correspondence between the set value item names actually operated on site and the adjusted set value item names; a set value unit equivalence group C2, which is used to indicate the correspondence between the set value items of the same physical quantity expressed in different units; a protection classification equivalence group C3, which is used to indicate the classification correspondence between different protection functions of protection devices; an ignored docking set value item group C4, which is used to indicate the set value items that do not need to be docked during the fixed value comparison process; and an ignored verification set value group C5, which is used to indicate the set values ​​that do not need to be verified in detail during the fixed value comparison process. In this embodiment, the ignore check fixed value group is used to determine whether the fixed value in the fixed value item after docking needs to be ignored during comparison, the fixed value unit equivalence group is used to determine whether the fixed value unit in the fixed value item after docking is consistent during comparison, and the protection classification equivalence group is used to determine whether the protection classification of the fixed value item is consistent during docking; that is, ignore check is for the fixed value, the fixed value unit equivalence group is for the fixed value unit, the protection classification equivalence group is for the protection classification, and the others are for the fixed value items.

[0062] After the docking principle training library is constructed, a total objective function for fixed value comparison is constructed according to the docking principle training library, the in-operation fixed value item data and the adjusted fixed value item data; before performing the fixed value item comparison, docking training is performed on the in-operation fixed value item data and the adjusted fixed value item data according to the equivalent group information in the docking principle training library to obtain the fixed value item association conditions; fixed value item comparison training is performed on the associated in-operation fixed value item data and the adjusted fixed value item data to obtain the matching result verification rules; the total objective function for the fixed value comparison, the fixed value item association conditions and the matching result verification rules are combined to obtain the docking training model.

[0063] During the training process, a large amount of training data needs to be obtained first. These data include the historically collected data of in-operation fixed value items and the number of adjusted fixed value items. Fuzzy matching and manual correction can be performed based on these training data and the docking principle training library. After docking, corresponding data will be automatically generated in the equivalence group to enrich the docking principle training library and achieve the purpose of training the docking model.

[0064] For example, taking the training process of the association condition "some in-operation set value items and adjustment items have a high degree of overlap in name" as an example, in the early training process, the set value items in the set value item data set will be sorted according to [protection classification-set value item name], and automatically docked according to whether the overlap is higher than the set threshold in the order of "protection classification first and then set value item name", and the training accuracy can be affected by modifying the set threshold. Example: protection set value-recombination pressure overcurrent section I set value (set value item A) and protection set value item-recombination pressure overcurrent section I set value (set value item B); after docking is completed, the protection classification equivalence group and set value item name equivalence group rules will be automatically generated in the docking principle training library, that is, protection set value / protection set value item, recombination pressure overcurrent section I set value / recombination pressure overcurrent section I set value. However, if you encounter a fixed value item or protection classification that cannot be automatically connected or the automatic connection is incorrect, you can correct it through manual correction to complete the connection. After the connection is completed, the connection principle training library will still be automatically improved to achieve the purpose of training the model. In the subsequent comparison work, if you encounter a fixed value order of the same equipment type, you can quickly connect and complete the comparison according to the connection model.

[0065] Similarly, C2-C5 can also be processed according to the above docking training method, which will not be described in detail in this application. In addition, the number of fixed value items for ignoring docking and ignoring verification is small, and they can be maintained manually according to experience, and the purpose is also to serve the comparison results.

[0066] In the embodiment of the present application, assuming that the in-operation fixed value item data is A and the adjusted fixed value item data is B, the fixed value item association conditions obtained by training include the following conditions:

[0067] Condition 1: If the names of the fixed-value items of A and B are the same or the overlap is higher than the set threshold, then A and B are associated;

[0068] Condition 2: In the docking principle training library, if A and B belong to the same fixed value item name equivalence group C1, then A and B are associated;

[0069] Condition 3: If the units of the fixed-value items of A and B are the same, or if neither A nor B has a unit, then A and B are associated;

[0070] Condition 4: In the docking principle training library, if the units of A and B belong to the same fixed-value unit equivalence group C2, then A and B are associated;

[0071] Condition 5: if A and B belong to the same protection classification equivalence group C3 or the overlap is higher than the set threshold, then A and B are associated;

[0072] Condition 6: If A or B belongs to the docking valued item group C4 ignored in the docking principle training library, then A and B are not associated;

[0073] Condition 7: If A or B belongs to the ignored check constant group C5 in the docking principle training library, then A and B are not associated.

[0074] In the embodiment of the present application, after determining that A and B are associated, a matching result verification rule is required to determine whether the associated A and B are consistent. Among them, the matching result verification rule trained in the embodiment of the present application includes:

[0075] Rule 1: If A and B meet condition 6, the verification result of A and B is "ignore the connection";

[0076] Rule 2: If A and B meet condition 7, the verification result of A and B is "ignore verification";

[0077] Rule 3: If the values ​​of A and B are consistent and meet conditions 3 or 4, the verification result of A and B is "consistent", where, when A and B are digital data, the difference between A and B is less than a preset threshold; or, when the values ​​of A and B are the data in this article, the values ​​of A and B are completely consistent;

[0078] Rule 4: If the relationship between A and B does not satisfy Rule 1, Rule 2 or Rule 3, the verification result is "inconsistent".

[0079] Step S3, compare and analyze the data in the fixed value item library through the docking training model to obtain the fixed value comparison result of the protection device. Specifically, compare and analyze each fixed value in the fixed value item library through the docking training model to obtain the verification result of each fixed value; when more than one verification result in the fixed value item library is "inconsistent", the fixed value comparison result of the fixed value item library is different; otherwise, the fixed value comparison result of the fixed value item library is no difference.

[0080] The power plant protection device fixed value comparison optimization method of the embodiment of the present application uses artificial intelligence technology to automatically process, screen, and classify the collected on-site protection device information, so that the input raw data is more in line with the fixed value docking format, and the comparison efficiency is improved. And by using the fixed value item docking principle library generated based on the training model, the fixed value item docking efficiency is improved, and the fixed value item docking accuracy is also improved. In addition, the protection device fixed value comparison result output by the method provided by the present application can provide auxiliary decision-making for on-site personnel.

[0081] In another embodiment of the present application, the implementation process of the power plant protection device setting comparison optimization method of the present application refers to Figure 2 .

[0082] A large amount of text data reflecting equipment protection device information, protection classification, and protection setting items in the collected on-site protection devices is used as input data.

[0083] The output data is the comparison result of the protection device setting values, and the results are divided into difference and no difference.

[0084] Specific as Figure 2 As shown, the technical solution of this embodiment is as follows:

[0085] The step S1 comprises:

[0086] Collect the set value data of the on-site protection device in operation and the set value data issued by the factory setting or dispatch as the original data, and pre-process the input raw data. It includes abnormal value processing (setting 0 or ∞ for those exceeding the specified range of the set value item, deleting the set value item displayed by the unit error, etc.), missing value processing (deletion), data sorting (discarding some useless strings to form new data storage), establishing the corresponding set value data set, and participating in the construction of the set value item library of the factory protection device.

[0087] The step S2 comprises:

[0088] Inject the docking principle library, train the fixed value item docking model, and form a mature fixed value docking training model. After the fixed value items are intelligently docked, compare the fixed values ​​item by item and output the comparison results.

[0089] Step S2.1 Definition of total objective function and variables for constant value comparison

[0090] The total objective function is: E=f(A, B, C), where E represents the comparison result of the protection device setting value, A represents the setting value of the protection device in the plant, B represents the setting value in the plant or the setting value issued by the dispatcher, and C represents the docking principle training library.

[0091] In this embodiment, the docking principle training library includes: C1 represents the equivalent group of the fixed value item name; C2 represents the equivalent group of the fixed value unit; C3 represents the equivalent group of the protection classification; C4 represents the ignored docking fixed value item group; C5 represents the ignored verification fixed value group.

[0092] Step S2.2 Docking model training

[0093] When the operating set value items of the plant protection devices are connected with the plant set set value sheets or the set value sheets issued by the dispatcher, there may be inconsistencies in protection classification, inconsistent set value item names, different set value unit descriptions, and missing set value items. To solve this problem, it is necessary to preprocess the input data and perform connection training at the same time, which can be achieved using the following process.

[0094] Before comparing the fixed values, first match each fixed value item in the current fixed value list data with the fixed value item in the factory setting or the fixed value list issued by the dispatcher. The association between fixed value item A and fixed value item B must satisfy one of the following (1) and (3), one of (3) and (4), and (5).

[0095] (1) The names of the fixed value items A and B are consistent (priority) or the overlap degree is higher than the set threshold;

[0096] (2) In the docking principle library, A and B belong to the same fixed value item name equivalence group C1;

[0097] (3) The units of the fixed value items of A and B are consistent, and neither A nor B has a unit, which is considered consistent (priority);

[0098] (4) In the docking principle library, the units of A and B belong to the same fixed value unit equivalence group C2;

[0099] (5) A and B belong to the same protection classification equivalence group C3 or the overlap is higher than the set threshold;

[0100] In addition, when there is no fixed value item that meets the conditions or the fixed value item belongs to the ignored docking fixed value item group C4 in the docking principle library, no association is performed; when the number of fixed value items that meet the conditions is greater than 1, the first data is taken.

[0101] In the present application, it is also possible to supplement through manual docking fixed value items, and after docking, the docking content is automatically supplemented into the docking principle library to achieve the purpose of training the docking principle library model.

[0102] Step S2.3 Fixed value item comparison process

[0103] Objective function: M = bool (A, B), where A represents the operating value of the protection device in the plant, and B represents the set value in the plant or the set value issued by the dispatcher.

[0104] When the on-site operating set value item A is associated with the set value item B set in the factory or issued by the dispatcher, the verification results need to consider the following conditions:

[0105] Rule (1), in the docking principle library, A or B belongs to the ignored docking value item group C4;

[0106] Rule (2), in the docking principle library, A or B belongs to the ignored check value group C5;

[0107] Rule (3): The values ​​of A and B are completely consistent (AB<0.00001 for numerical comparison and A and B are completely consistent for textual comparison); and the units of A and B are completely consistent or belong to the same fixed value unit equivalence group C2 in the docking principle.

[0108] In this embodiment, the following criteria are arranged in order of priority from high to low:

[0109] Case 1: Rule (1) is met and the verification result is "Ignore docking";

[0110] Case 2: Rule (2) is met and the verification result is "ignore verification";

[0111] Case 3: Rule (3) is met and the verification result is "consistent";

[0112] Rule 4: In other cases, the verification result is "inconsistent".

[0113] If the comparison results of A and B are inconsistent, M=false is returned; otherwise, M=true is returned.

[0114] Step S3 includes:

[0115] E=bool(M1, M2, ..., Mn), where M represents the comparison result of a single fixed value item and E represents the comparison result of the fixed value.

[0116] When there is no "inconsistent" result in the comparison results of all the set value items in the set value list, the set value comparison results of the protection device are indifferent, that is, the values ​​of M1~Mn must all be true, as long as one is false, the set value comparison results of the protection device are different.

[0117] In a second aspect, an embodiment of the present application provides an electronic device, Figure 3 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Figure 3 As shown, the electronic device may include a processor 11 and a memory 12 storing computer program instructions.

[0118] Specifically, the processor 11 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0119] Among them, the memory 12 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 12 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 12 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 12 may be inside or outside a data processing device. In a specific embodiment, the memory 12 is a non-volatile memory. In a specific embodiment, the memory 12 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable ProgrammableRead-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable ProgrammableRead-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0120] The memory 12 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 11 .

[0121] The processor 11 reads and executes the computer program instructions stored in the memory 12 to implement any one of the power plant protection device setting comparison optimization methods in the above embodiments.

[0122] In one embodiment, the electronic device may further include a communication interface 13 and a bus 10. Figure 3 As shown, the processor 11, the memory 12, and the communication interface 13 are connected via a bus 10 and communicate with each other.

[0123] The communication interface 13 is used to realize the communication between the modules, devices, units and / or equipment in the embodiment of the present application. The communication port 13 can also realize data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage and image / data processing workstations.

[0124] The bus 10 includes hardware, software or both, and couples the components of the electronic device to each other. The bus 10 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 10 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 10 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0125] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, the power plant protection device constant value comparison optimization method provided in the first aspect is implemented.

[0126] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0127] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of the power plant protection device setting comparison optimization method provided in the first aspect.

[0128] The program code for executing the present invention may be written in any combination of one or more programming languages, and may be executed entirely on a user device, partially on a user device, as an independent software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0129] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for optimizing the comparison of fixed value of protection devices in power plants, characterized in that: include: Collecting and preprocessing the fixed value data of the protection device to obtain a fixed value item data set, and generating a fixed value item library according to the fixed value item data set; Obtaining a pre-built docking principle training library, performing fixed-value docking training on the docking principle training library, and obtaining a docking training model; The docking training model is used to compare and analyze the data in the fixed value item library to obtain the fixed value comparison result of the protection device.

2. The power plant protection device setting comparison optimization method according to claim 1 is characterized in that: The collecting and preprocessing of the protection device fixed value data to obtain the fixed value item data set includes: Collect the data of the currently running set value items of the on-site protection device, as well as the data of the adjusted set value items issued by the factory setting or dispatch; The in-operation fixed value item data and the adjusted fixed value item data are subjected to abnormal value processing, missing value processing, and data screening processing to obtain the fixed value item data set.

3. The power plant protection device setting comparison optimization method according to claim 2 is characterized in that: The construction of the docking principle training library includes: The set value item name equivalence group C1 is used to indicate the correspondence between the set value item names actually operated on site and the adjusted set value item names; The fixed value unit equivalence group C2 is used to express the correspondence between fixed value items of the same physical quantity expressed in different units; Protection classification equivalence group C3 is used to indicate the classification correspondence between different protection functions of protection devices; Ignore docking fixed value item group C4, used to indicate fixed value items that do not need to be docked during the fixed value comparison process; Ignore verification set value group C5 is used to indicate the set values ​​that do not need to be verified in detail during the set value comparison process.

4. The power plant protection device setting comparison optimization method according to claim 2 is characterized in that: Performing fixed-value docking training on the docking principle training library to obtain a docking training model includes: Constructing a total objective function of the fixed value comparison according to the docking principle training library, the in-operation fixed value item data and the adjusted fixed value item data; Before comparing the fixed value items, docking training is performed on the in-service fixed value item data and the adjusted fixed value item data according to the equivalent group information in the docking principle training library to obtain the fixed value item association conditions; Perform fixed value item comparison training on the related in-operation fixed value item data and adjusted fixed value item data to obtain matching result verification rules; The docking training model is obtained by combining the total objective function of the fixed value comparison, the associated conditions of the fixed value items and the matching result verification rules.

5. The power plant protection device setting comparison optimization method according to claim 4 is characterized in that: Assuming that the in-operation fixed value item data is A and the adjustment fixed value item data is B, the fixed value item association conditions include: Condition 1: If the names of the fixed-value items of A and B are the same or the overlap is higher than the set threshold, then A and B are associated; Condition 2: In the docking principle training library, if A and B belong to the same fixed value item name equivalence group C1, then A and B are associated; Condition 3: If the units of the fixed-value items of A and B are the same, or if neither A nor B has a unit, then A and B are associated; Condition 4: In the docking principle training library, if the units of A and B belong to the same fixed-value unit equivalence group C2, then A and B are associated; Condition 5: if A and B belong to the same protection classification equivalence group C3 or the overlap is higher than the set threshold, then A and B are associated; Condition 6: If A or B belongs to the docking valued item group C4 ignored in the docking principle training library, then A and B are not associated; Condition 7: If A or B belongs to the ignored check constant group C5 in the docking principle training library, then A and B are not associated.

6. The power plant protection device setting comparison optimization method according to claim 4 is characterized in that: Matching result verification rules include: Rule 1: If A and B meet condition 6, the verification result of A and B is "ignore the connection"; Rule 2: If A and B meet condition 7, the verification result of A and B is "ignore verification"; Rule 3: If the values ​​of A and B are consistent and meet conditions 3 or 4, the verification result of A and B is "consistent"; Rule 4: If the relationship between A and B does not satisfy Rule 1, Rule 2 or Rule 3, the verification result is "inconsistent".

7. The power plant protection device setting comparison optimization method according to claim 4 is characterized in that: The data in the fixed value item library is compared item by item through the docking training model to obtain the fixed value comparison result of the protection device, including: Compare and analyze each fixed value in the fixed value item library through the docking training model to obtain a verification result of each fixed value; When more than one verification result in the fixed-value item library is "inconsistent", the fixed-value comparison result of the fixed-value item library is different; otherwise, the fixed-value comparison result of the fixed-value item library is no difference.

8. The power plant protection device setting comparison optimization method according to claim 6 is characterized in that: The judgment condition for the values ​​of A and B to be consistent is: When A and B are digital data, the difference between A and B is less than a preset threshold; or, when the values ​​of A and B are the data in this article, the values ​​of A and B are completely consistent.

9. An electronic device, characterized in that: The invention comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the power plant protection device constant value comparison optimization method as described in any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the power plant protection device setting comparison optimization method according to any one of claims 1 to 8 is implemented.

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