CN116894064A - Intelligent integrated power-transformation auxiliary control data system and method - Google Patents
Intelligent integrated power-transformation auxiliary control data system and method Download PDFInfo
- Publication number
- CN116894064A CN116894064A CN202310880871.6A CN202310880871A CN116894064A CN 116894064 A CN116894064 A CN 116894064A CN 202310880871 A CN202310880871 A CN 202310880871A CN 116894064 A CN116894064 A CN 116894064A
- Authority
- CN
- China
- Prior art keywords
- data
- auxiliary control
- entity
- power
- bits
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000012545 processing Methods 0.000 claims abstract description 39
- 238000007418 data mining Methods 0.000 claims abstract description 19
- 230000002452 interceptive effect Effects 0.000 claims abstract description 12
- 230000009466 transformation Effects 0.000 claims description 33
- 238000012544 monitoring process Methods 0.000 claims description 28
- 238000006243 chemical reaction Methods 0.000 claims description 16
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 238000011161 development Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 8
- 239000000178 monomer Substances 0.000 claims description 6
- 230000009977 dual effect Effects 0.000 claims description 5
- 230000006872 improvement Effects 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 4
- 238000010606 normalization Methods 0.000 claims description 4
- 230000006855 networking Effects 0.000 claims description 3
- 238000010801 machine learning Methods 0.000 abstract description 8
- 230000006870 function Effects 0.000 abstract description 5
- 230000003993 interaction Effects 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 description 15
- 238000004891 communication Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 6
- 238000012423 maintenance Methods 0.000 description 6
- 238000003672 processing method Methods 0.000 description 5
- 230000004044 response Effects 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000001186 cumulative effect Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000013499 data model Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000005286 illumination Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
Landscapes
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The application discloses an intelligent integrated power-transformation auxiliary control data system and method, which aim at improving a data system in a data processing mode of directly comparing sensing data with a calibration alarm threshold in a traditional power-transformation auxiliary control system, and convert the existing single and hard non-interactive power-transformation auxiliary control data system into an interactive data system with multi-angle and multi-depth data mining compatibility. The application combines the requirements of carrying out data link interaction and function guiding underderiving iteration on the intelligent integrated power-transformation auxiliary control system, a big data processing platform and a machine learning system, and develops an intelligent integrated power-transformation auxiliary control data system and method with basicity and universality.
Description
Technical Field
The application relates to the technical field of electric power intellectualization and informatization, in particular to a basic data processing system and a related data processing method for intelligent integrated power transformation auxiliary control.
Background
At present, the modern, intelligent and informationized construction of the transformer substation has been widely and deeply developed. In general, an intelligent substation auxiliary control system is based on remote sensing equipment and intelligent processing equipment, comprehensively adopts technical means such as power environment, image monitoring, fire protection, illumination, monitoring, early warning and control, and widely adopts comprehensive technical means based on sensing and information control, such as automation technology, computer technology, network communication technology, video equipment technology and the like, and realizes on-line monitoring and reliable control on power environment, images, fire alarm, fire protection, illumination, heating ventilation, security alarm, access control and the like of a substation; and the data are transmitted to a monitoring center or a dispatching center of the power grid system or a corresponding cloud master control center in an interactive manner according to the requirement or in real time.
According to the latest development trend of an intelligent substation auxiliary control system, on the basis of technologies such as video image monitoring, electrical sensing, communication network, distributed control and the like, the technical application and fusion points of the current cores comprise: (1) the automatic identification of video image elements and the dynamic tracking technology thereof, and the tracked dynamic elements are subjected to automatic generation of spatial data information flow; (2) the high-precision sensor technology is introduced and popularized, so that parameters such as current, voltage, temperature and the like of the substation equipment are monitored more and more accurately in real time; (3) the intelligent substation auxiliary control system can realize remote monitoring, remote operation and remote communication among devices under the support of technologies including the Internet of things, 5G and the like, and simultaneously supports real-time transmission and cloud storage of data; (4) the power grid central control visualization intelligent operation and maintenance technology is used for carrying out real-time data link and interaction with an intelligent substation auxiliary control system and forming a real-time visualization platform, so that the monitoring of the remote operation and maintenance on the equipment state can be realized, and meanwhile, the automatic inspection, maintenance and maintenance of the power transformation equipment are realized through an intelligent operation and maintenance technology system; (5) the data processing and analyzing technology is used for processing and analyzing the monitored data based on big data, artificial intelligence and brand new data means of machine learning on the intelligent substation auxiliary control system equipment, and realizing real-time monitoring, prediction and fault diagnosis of equipment states.
The data processing and analyzing technology based on the big data platform and linked with the artificial intelligent data processing system is developed very rapidly at present, and is the hottest technology improvement trend of the intelligent substation auxiliary control system at present and is also the important foundation for development and realization of other related key technologies.
Disclosure of Invention
The application aims to solve the technical problems that the intelligent integrated power transformation auxiliary control system is combined with the requirements of carrying out data link interaction and function guiding downward derived iteration on a big data processing platform and a machine learning system, and the related development of a data mining algorithm is directly carried out based on an original database of the existing intelligent integrated power transformation auxiliary control system so as to provide an intelligent integrated power transformation auxiliary control data system and method with basicity and universality.
In order to solve the technical problems, the technical scheme adopted by the application is as follows.
An intelligent integrated power transformation auxiliary control data system, wherein a hardware system carries out configuration and configuration based on a plurality of optional subsystems interconnected by networking information, and the plurality of optional subsystems conventionally comprise: the system comprises a network video monitoring platform subsystem, an anti-theft platform subsystem, a fire disaster and fire fighting platform subsystem, an access control platform subsystem and other auxiliary control integrated subsystems; the network video monitoring platform subsystem is a necessary option; the other auxiliary control integrated subsystems carry out selective configuration on various monomer sensing units according to actual auxiliary control requirements, and the monomer sensing units are selected from/purchased from the existing conventional power and electrical industry data signal sensors; aiming at the improvement of a data system in a data processing mode of directly comparing the sensing data with the calibration alarm threshold in the traditional power-transformation auxiliary control system, the existing single and hard non-interactive power-transformation auxiliary control data system is converted into an interactive data system with multi-angle and multi-depth data mining compatibility.
As a preferable technical scheme of the application, the data construction process comprises the following steps: basic data acquisition, exchangeable double-assigned data arrangement and two-dimensional data format standardization.
As a preferred embodiment of the present application, the obtaining of the basic data includes: firstly, maintaining the consistency with the existing power-transformation auxiliary control system for the original space data and basic electric signal data physically acquired by hardware systems such as a video system, a sensing unit and the like, allowing the original data stored by the existing power-transformation auxiliary control system to be directly read under the working condition of system improvement, and directly linking the data port of the hardware system under the working condition of a newly installed system to obtain the original physical and/or space data;
as a preferred technical solution of the present application, the exchangeable dual assigned data arrangement includes: after the storage and reading or direct acquisition of the basic data, the data configuration of the original data is improved by the interactivity and the data mining compatibility of a data system, and the data configuration is realized by the exchangeable double-assigned data arrangement.
As a preferred technical solution of the present application, the two-dimensional data format normalization includes: the original data acquired by the power transformation auxiliary control data system is subjected to exchangeable double-order data arrangement to obtain a basic two-dimensional data array, but the basic two-dimensional data array is not standard, the data extensibility of the entity data V corresponding to any single extension data bit of the entity data H set in the exchangeable double-order data arrangement is different on each single extension data bit of the entity data H, and the non-standard data array obtained after the exchangeable double-order data arrangement is subjected to standardization of a two-dimensional data format based on the actual situation of the extensibility of the entity data V or the actual situation of the space or physical data acquired by monitoring the video subsystem and each electrical sensing subsystem arranged in the power transformation auxiliary control data system.
As a preferred technical solution of the present application, the exchangeable dual-assigned data arrangement specifically includes: (1) in the form of a data structure, setting two mutually orthogonal fillable and extensible empty data bits, setting the intersecting data bits as null to be blank, and then sequentially filling and giving natural sequence numbers along the two orthogonal data bit directions from the null data bit; in this data filling configuration, two sets of orthogonal extensible data bits are compatible to be exchanged along with the orthogonal data bits as long as the data in the two orthogonal directions are always in accordance with the sequence number originally given; the initial sequence number assignment for two orthogonal data is therefore also optional; further, under the exchangeable dual data bit initial architecture, if the basic space of the power transformation auxiliary control and the physical data are obtained by reading from the existing power transformation auxiliary control system under the improved working condition of the system, the data are naturally read according to the data record format of the existing system, and the formats of the existing system and the data record are not limited and preprocessed; the natural sequence number is preferred, but is not limited to a natural sequence number, and any other data sequence is allowed to be adopted for marking the symbol; for two orthogonal extension data bits, two different natural sequence numbers are adopted, namely a digital sequence number and a letter sequence number; (2) in the meaning of the data structure, two mutually orthogonal extensible data bits are interchangeably mapped to corresponding two items of entity data respectively, and are named as (horizontal) entity data H and (vertical) entity data V; exchangeable means that the naming of the two, the form of the data structure and the connotation of the data structure are compatible and mutually exchanged; because the original expandable data are set to be mutually orthogonal, the exchange of the two data is represented as transposed exchange on a data configuration, and compatibility and convenience are brought to the subsequent development of data mining modules with different angles and different depths, wherein the entity data H corresponds to a monitoring object entity of the power conversion auxiliary control data system, and the entity data V corresponds to space or physical entity data obtained by monitoring a physical object corresponding to the entity data H under a video subsystem and each electric sensing subsystem arranged in the power conversion auxiliary control data system.
As a preferable technical scheme of the application, based on connotation setting of entity data on orthogonal exchangeable data bits of the power transformation auxiliary control data system, the entity data H and the entity data V respectively adopt ordinal number data formats and numerical data formats which are optimal; the data phenotype and the numerical value of the vertical entity data V are directly presented as numerical data, such as temperature, pressure, current, power and the like, based on the data connotation of the data.
As a preferable technical scheme of the application, the standardization of the two-dimensional data format specifically comprises the following data processing formula (1): (1) firstly, performing empirical data bit ordering, exchanging and sorting based on the frequency characteristic of data extension on the entity data V; (1) -2 based on this further the length characteristics of the data extensions on the physical data V and multi-attribute data filling of the blank data bits on the other short extensions with the selected long extensions as standard, resulting in a normalized two-dimensional data format.
As a preferred technical scheme of the application, (1) -1, in the current concrete power-transformation auxiliary control task, based on the actual frequency of the occurrence of the space or physical data obtained by monitoring the video subsystem and each electrical sensing subsystem arranged in the power-transformation auxiliary control data system of the corresponding physical object on any extension data bit of the entity data H, the frequency level directly corresponds to the frequency characteristic of the data extension on the entity data V, at the moment, backtracking is performed on the filling giving of natural sequence numbers along the two orthogonal data bit directions in the exchangeable double-order data arrangement process, sequence number adjustment is performed according to the frequency level, and the integrated data carrying exchange of the orthogonal data bits is performed generally by adopting a data mode of high-frequency words and low sequence numbers
As a preferred embodiment of the present application, (1) -2 comprises: (1) -2-1, the selected criteria for standard extensibility simultaneously comprising: omega, the longest data expansion degree is the number of non-empty data expansion bits; the psi condition, namely the most complete data extension degree is provided with all data extension bits on all other entity data V; when there are a plurality of entity data V satisfying ω and ψ conditions at the same time, they are substantially equivalent, and thus are simultaneously selected as extension criteria; when the entity data V which simultaneously meets the omega condition and the psi condition does not exist, selecting the closest one as an extension standard; (1) 2-2, based on the application of the following different possible data mining algorithms, the data population of the blank data bits adopts different norms, for which purpose is set to multi-attribute data population, the multi-attribute comprising null, value 0, non-zero value, infinite value, statement-physical state description, statement-engineering or management description, letters, other symbols; all blank data bits are filled with all selected multi-attribute data in the data phenotype, all the selected multi-attribute data are sequentially combined into a bracket according to the same sequence in the data format, and the different attribute data are separated by commas.
As a preferred technical solution of the present application, the standardization of the two-dimensional data format specifically includes a data processing paradigm (2): and developing a two-dimensional data format automatic specification algorithm based on the data processing essence and the data processing result of the data processing paradigm (1) for automatic generation.
The beneficial effects of adopting above-mentioned technical scheme to produce lie in: compared with the data processing mode based on comparison of sensing data and calibration alarm threshold values in the traditional power-transformation auxiliary control system, the data processing method based on the data processing mode has the advantages that the built global, double-dimensional and normalized dynamic data model and the dynamic database formed based on the data processing mode can adapt to the common data characteristic extraction and data connotation mining algorithm in large data processing platforms and machine learning, and the traditional single and hard non-interactive power-transformation auxiliary control data system is converted into the data system which is interactive and has multi-angle and multi-depth data mining compatibility, so that a basic data mining and analysis processing method is provided for the large data and the artificial intelligence of the intelligent power-transformation auxiliary control system, and a data foundation is laid for the intelligent efficient operation and maintenance of the transformer substation.
Detailed Description
In the following description of embodiments, for purposes of explanation and not limitation, specific details are set forth, such as particular system architectures, techniques, etc. in order to provide a thorough understanding of the embodiments of the application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail. It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]". Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance. Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
Example 1
The hardware system of the intelligent integrated power-transformation auxiliary control system carries out configuration based on a plurality of optional subsystems interconnected by networking information, and the plurality of optional subsystems conventionally comprise: the system comprises a network video monitoring platform subsystem, an anti-theft platform subsystem, a fire disaster and fire fighting platform subsystem, an access control platform subsystem and other auxiliary control integrated subsystems; the network video monitoring platform subsystem is a necessary option; the other auxiliary control integrated subsystems carry out selective configuration on various monomer sensing units according to actual auxiliary control requirements, and each monomer sensing unit is selected from/purchased from the existing conventional power and electrical industry data signal sensors.
Example 2
In combination with the requirements of carrying out data link interaction and function guiding downward deriving iteration on the intelligent integrated power transformation auxiliary control system, a big data processing platform and a machine learning system, the data foundation construction is firstly required to be carried out based on an original database of the existing intelligent integrated power transformation auxiliary control system. Specifically, for the original space data and basic electric signal data physically collected by hardware systems such as a video platform, a sensing unit and the like in the intelligent integrated power-transformation auxiliary control system, the consistency with the existing power-transformation auxiliary control system is maintained, the original data stored by the existing power-transformation auxiliary control system is allowed to be directly read under the improved working condition of the system, and the data ports of the hardware system are directly linked under the working condition of the newly installed system to obtain the original physical and/or space data.
Example 3
Based on the above embodiment, in order to improve a data system according to a data processing manner of directly comparing sensing data with a calibration alarm threshold in a conventional power conversion auxiliary control system, the existing single and hard non-interactive power conversion auxiliary control data system is converted into an interactive data system with multi-angle and multi-depth data mining compatibility, and in the first step, exchangeable dual-order data arrangement is performed: after the storage and reading or direct acquisition of the basic data, the data configuration of the original data is improved by the interactivity and the data mining compatibility of a data system, and the data configuration is realized by the exchangeable double-assigned data arrangement. The exchangeable dual-ordered data arrangement is specifically as follows: (1) in the form of a data structure, setting two mutually orthogonal fillable and extensible empty data bits, setting the intersecting data bits as null to be blank, and then sequentially filling and giving natural sequence numbers along the two orthogonal data bit directions from the null data bit; in this data filling configuration, two sets of orthogonal extensible data bits are compatible to be exchanged along with the orthogonal data bits as long as the data in the two orthogonal directions are always in accordance with the sequence number originally given; the initial sequence number assignment for two orthogonal data is therefore also optional; further, under the exchangeable dual data bit initial architecture, if the basic space of the power transformation auxiliary control and the physical data are obtained by reading from the existing power transformation auxiliary control system under the improved working condition of the system, the data are naturally read according to the data record format of the existing system, and the formats of the existing system and the data record are not limited and preprocessed; the natural sequence number is preferred, but is not limited to the natural sequence number, and any other data sequence is allowed to be adopted for marking the symbol; for two orthogonal extension data bits, two different natural sequence numbers are adopted, namely a digital sequence number and a letter sequence number; (2) in the meaning of the data structure, two mutually orthogonal extensible data bits are interchangeably mapped to corresponding two items of entity data respectively, and are named as (horizontal) entity data H and (vertical) entity data V; exchangeable means that the naming of the two, the form of the data structure and the connotation of the data structure are compatible and mutually exchanged; because the original expandable data are set to be mutually orthogonal, the exchange of the two data is represented as transposed exchange on a data configuration, and compatibility and convenience are brought to the subsequent development of data mining modules with different angles and different depths, wherein the entity data H corresponds to a monitoring object entity of the power conversion auxiliary control data system, and the entity data V corresponds to space or physical entity data obtained by monitoring a physical object corresponding to the entity data H under a video subsystem and each electric sensing subsystem arranged in the power conversion auxiliary control data system. Based on connotation setting of entity data on orthogonal exchangeable data bits of the power-transformation auxiliary control data system, the entity data H and the entity data V are respectively in an ordinal number data format and a numerical data format, and are optimal; the data phenotype and the numerical value of the vertical entity data V are directly presented as numerical data, such as temperature, pressure, current, power and the like, based on the data connotation of the data. In addition, regarding the data phenotype of the vertical entity data V and the numerical value thereof, for the individual special switch-mode data, a numerical value data format is obtained after the data conversion by adopting a 0-1 assignment method or a 0-infinity assignment method, or the non-numerical value data of the vertical entity data V is directly adopted. This step takes care of additional manual marking to prevent the data from being reviewed after execution of the disorder.
Example 4
In order to directly dock with a big data platform and the existing open-source artificial intelligent training system, data normalization processing is further needed to form an intelligent integrated power-transformation auxiliary control data system with basicity and universality. Specifically, the data processing method of the foregoing embodiment and the monitored data characteristic of the intelligent power conversion auxiliary control system are combined to normalize the data format in two dimensions. The original data acquired by the power transformation auxiliary control data system is subjected to exchangeable double-order data arrangement to obtain a basic two-dimensional data array, but the basic two-dimensional data array is not standard, the data extensibility of the entity data V corresponding to any single extension data bit of the entity data H set in the exchangeable double-order data arrangement is different on each single extension data bit of the entity data H, and the non-standard data array obtained after the exchangeable double-order data arrangement is subjected to standardization of a two-dimensional data format based on the actual situation of the extensibility of the entity data V or the actual situation of the space or physical data acquired by monitoring the video subsystem and each electrical sensing subsystem arranged in the power transformation auxiliary control data system.
The standardization of the two-dimensional data format specifically includes the following data processing formula (1): (1) firstly, performing empirical data bit ordering, exchanging and sorting based on the frequency characteristic of data extension on the entity data V; (1) -2 based on this further the length characteristics of the data extensions on the physical data V and multi-attribute data filling of the blank data bits on the other short extensions with the selected long extensions as standard, resulting in a normalized two-dimensional data format. In the step (1) -1, in the current specific power transformation auxiliary control task, based on the actual frequency of the occurrence of the space or physical data obtained by monitoring the video subsystem and each electrical sensing subsystem arranged in the power transformation auxiliary control data system of the corresponding physical object on any extension data bit of the entity data H, the frequency of the video subsystem directly corresponds to the frequency characteristic of data extension on the entity data V, at the moment, the filling giving of natural sequence numbers is sequentially carried out along the two orthogonal data bit directions in the exchangeable double-sequence data arrangement process, sequence number adjustment is carried out according to the frequency, and the integrated data carrying exchange of orthogonal data bits is generally carried out by adopting a data mode of high-frequency words and low sequence numbers; wherein, (1) -2: (1) -2-1, the selected criteria for standard extensibility simultaneously comprising: omega, the longest data expansion degree is the number of non-empty data expansion bits; the psi condition, namely the most complete data extension degree is provided with all data extension bits on all other entity data V; when there are a plurality of entity data V satisfying ω and ψ conditions at the same time, they are substantially equivalent, and thus are simultaneously selected as extension criteria; when the entity data V which simultaneously meets the omega condition and the psi condition does not exist, selecting the closest one as an extension standard; (1) 2-2, based on the application of the following different possible data mining algorithms, the data filling of the blank data bits adopts different norms, and is set to be multi-attribute data filling, wherein the multi-attribute comprises null, value 0, non-zero value, infinite value, statement-physical state description, statement-engineering or management description, letters and other symbols; all blank data bits are filled with all selected multi-attribute data in the data phenotype, all the selected multi-attribute data are sequentially combined into a bracket according to the same sequence in the data format, and the different attribute data are separated by commas.
Example 5
Normalized data processing paradigm (2) of a two-dimensional data format: and developing a two-dimensional data format automatic specification algorithm based on the data processing essence and the data processing result of the data processing paradigm (1) for automatic generation. The (2) data processing paradigm is automatically generated based on a development algorithm of the data processing paradigm (1), and specifically comprises two aspects, (2) -1, the data processing essence of the data processing paradigm (1) is examined, the rectangular sub-data array which is based on real original data and is the largest in the upper left corner of the two-dimensional data array is taken as a first specification, and multi-attribute data filling under unified standards is carried out on blank data bits on the rest data bits; (2) - (2) developing a data algorithm based on the data specification substance to perform an automated data normalization process.
Example 6
In the research, under the requirements of carrying out data link interaction and deriving iteration on an intelligent integrated power transformation auxiliary control system, a big data processing platform and a machine learning system, the related development of a data mining algorithm is carried out based on an original database of the existing intelligent integrated power transformation auxiliary control system, compared with the data processing mode based on comparison of sensing data and a calibration alarm threshold value in the traditional power transformation auxiliary control system, the global, bi-dimensional and normalized dynamic data model constructed by the research and the dynamic database formed based on the model can adapt to the common data feature extraction and data content mining algorithm in the big data processing platform and the machine learning, and the traditional single and hard non-interactive power transformation auxiliary control data system is converted into the data system with multi-angle and multi-depth data mining compatibility, so that a basic data mining and analysis processing method is provided for big data and artificial intelligence of the intelligent power transformation auxiliary control system. If the local dynamic database is based on a big data processing platform, internal relevance analysis is carried out on a local dynamic database under a certain single power-transformation auxiliary control monitoring operation at any moment by constructing determinant absolute value parameters of a two-dimensional canonical data array or a specific subarray thereof (under a model constructed by us, generally rectangular subarray data concentrated in an upper left corner area); and then, based on accumulation of large-scale past data of the transformer substation in the cumulative month or the cumulative year and a fault characteristic database under each data, performing machine learning neural network training on the correlation parameter system based on the determinant absolute value, and realizing automatic fault monitoring of the artificial intelligent collaborative power transformation system based on the correlation data parameters as long as the data precision and the data quantity are high enough.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
In various embodiments, the hardware implementation of the technology may directly employ existing smart devices, including, but not limited to, industrial personal computers, PCs, smartphones, handheld standalone machines, floor stand-alone machines, and the like. The input device is preferably a screen keyboard, the data storage and calculation module adopts an existing memory, a calculator and a controller, the internal communication module adopts an existing communication port and protocol, and the remote communication module adopts an existing gprs network, a universal Internet and the like. It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again. In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms. The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment. The functional units in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units. The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, and the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Acces Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (8)
1. An intelligent integrated power transformation auxiliary control data system, wherein a hardware system carries out configuration and configuration based on a plurality of optional subsystems interconnected by networking information, and the plurality of optional subsystems conventionally comprise: the system comprises a network video monitoring platform subsystem, an anti-theft platform subsystem, a fire disaster and fire fighting platform subsystem, an access control platform subsystem and other auxiliary control integrated subsystems; the network video monitoring platform subsystem is a necessary option; the other auxiliary control integrated subsystems carry out selective configuration on various monomer sensing units according to actual auxiliary control requirements, and the monomer sensing units are selected from/purchased from the existing conventional power and electrical industry data signal sensors; the method is characterized in that: aiming at the improvement of a data system in a data processing mode of directly comparing the sensing data with the calibration alarm threshold in the traditional power-transformation auxiliary control system, the existing single and hard non-interactive power-transformation auxiliary control data system is converted into an interactive data system with multi-angle and multi-depth data mining compatibility.
2. An intelligently integrated power-conversion auxiliary control data system according to claim 1, characterized in that: the data construction process comprises the following steps:
basic data acquisition: firstly, maintaining the consistency with the existing power-transformation auxiliary control system for the original space data and basic electric signal data physically acquired by hardware systems such as a video system, a sensing unit and the like, allowing the original data stored by the existing power-transformation auxiliary control system to be directly read under the working condition of system improvement, and directly linking the data port of the hardware system under the working condition of a newly installed system to obtain the original physical and/or space data;
exchangeable dual ordered data arrangement: after the storage and reading or the direct acquisition of the basic data, the data configuration of the original data is improved by aiming at the interactivity and the data mining compatibility of a data system, and the data configuration is realized by the arrangement of exchangeable double-assigned data;
two-dimensional data format normalization: the original data acquired by the power transformation auxiliary control data system is subjected to exchangeable double-order data arrangement to obtain a basic two-dimensional data array, but the basic two-dimensional data array is not standard, the data extensibility of the entity data V corresponding to any single extension data bit of the entity data H set in the exchangeable double-order data arrangement is different on each single extension data bit of the entity data H, and the non-standard data array obtained after the exchangeable double-order data arrangement is subjected to standardization of a two-dimensional data format based on the actual situation of the extensibility of the entity data V or the actual situation of the space or physical data acquired by monitoring the video subsystem and each electrical sensing subsystem arranged in the power transformation auxiliary control data system.
3. An intelligently integrated power-conversion auxiliary control data system according to claim 2, characterized in that: the exchangeable double assigned data arrangement specifically comprises:
(1) in the form of a data structure, setting two mutually orthogonal fillable and extensible empty data bits, setting the intersecting data bits as null to be blank, and then sequentially filling and giving natural sequence numbers along the two orthogonal data bit directions from the null data bit; in this data filling configuration, two sets of orthogonal extensible data bits are compatible to be exchanged along with the orthogonal data bits as long as the data in the two orthogonal directions are always in accordance with the sequence number originally given; the initial sequence number assignment for two orthogonal data is therefore also optional; further, under the exchangeable dual data bit initial architecture, if the basic space of the power transformation auxiliary control and the physical data are obtained by reading from the existing power transformation auxiliary control system under the improved working condition of the system, the data are naturally read according to the data record format of the existing system, and the formats of the existing system and the data record are not limited and preprocessed; the natural sequence number is preferred, but is not limited to a natural sequence number, and any other data sequence is allowed to be adopted for marking the symbol; for two orthogonal extension data bits, two different natural sequence numbers are adopted, namely a digital sequence number and a letter sequence number;
(2) in the meaning of the data structure, two mutually orthogonal extensible data bits are interchangeably mapped to corresponding two items of entity data respectively, and are named as (horizontal) entity data H and (vertical) entity data V; exchangeable means that the naming of the two, the form of the data structure and the connotation of the data structure are compatible and mutually exchanged; because the original expandable data are set to be mutually orthogonal, the exchange of the two data is represented as transposed exchange on a data configuration, and compatibility and convenience are brought to the subsequent development of data mining modules with different angles and different depths, wherein the entity data H corresponds to a monitoring object entity of the power conversion auxiliary control data system, and the entity data V corresponds to space or physical entity data obtained by monitoring a physical object corresponding to the entity data H under a video subsystem and each electric sensing subsystem arranged in the power conversion auxiliary control data system.
4. An intelligently integrated power-conversion auxiliary control data system according to claim 3, characterized in that: based on connotation setting of entity data on orthogonal exchangeable data bits of the power-transformation auxiliary control data system, the entity data H and the entity data V are respectively in an ordinal number data format and a numerical data format, and are optimal; the data phenotype and the numerical value of the vertical entity data V are directly presented as numerical data, such as temperature, pressure, current, power and the like, based on the data connotation of the data.
5. An intelligently integrated power-conversion auxiliary control data system according to claim 2, characterized in that: the standardization of the two-dimensional data format specifically comprises the following data processing formula (1): (1) firstly, performing empirical data bit ordering, exchanging and sorting based on the frequency characteristic of data extension on the entity data V; (1) -2 based on this further the length characteristics of the data extensions on the physical data V and multi-attribute data filling of the blank data bits on the other short extensions with the selected long extensions as standard, resulting in a normalized two-dimensional data format.
6. The intelligently integrated power-conversion auxiliary control data system according to claim 5, wherein: (1) in the process of carrying out the current specific power transformation auxiliary control task, the sequence number adjustment is carried out according to the frequency, and the integrated data carrying exchange of orthogonal data bits is generally carried out by adopting a data mode of high-frequency words and low sequence numbers.
7. The intelligently integrated power-conversion auxiliary control data system according to claim 5, wherein: (1) -2 comprises:
(1) -2-1, the selected criteria for standard extensibility simultaneously comprising: omega, the longest data expansion degree is the number of non-empty data expansion bits; the psi condition, namely the most complete data extension degree is provided with all data extension bits on all other entity data V; when there are a plurality of entity data V satisfying ω and ψ conditions at the same time, they are substantially equivalent, and thus are simultaneously selected as extension criteria; when the entity data V which simultaneously meets the omega condition and the psi condition does not exist, selecting the closest one as an extension standard;
(1) 2-2, based on the application of the following different possible data mining algorithms, the data population of the blank data bits adopts different norms, for which purpose is set to multi-attribute data population, the multi-attribute comprising null, value 0, non-zero value, infinite value, statement-physical state description, statement-engineering or management description, letters, other symbols; all blank data bits are filled with all selected multi-attribute data in the data phenotype, all the selected multi-attribute data are sequentially combined into a bracket according to the same sequence in the data format, and the different attribute data are separated by commas.
8. A single item data configuration and local or global number dynamic database obtained by the configuration of the single item data configuration and the local or global number dynamic database which is suitable for an intelligent integrated power transformation auxiliary control system, which is characterized in that: the data attribute with the global, bi-dimensional and normative property is constructed by adopting the technical means of the claims 2-7, wherein a dynamic data configuration stream is constructed based on the time sequence variation of single data configuration, a local dynamic database is constructed based on single power transformation auxiliary control monitoring operation and the related monitoring data set, and a global database is constructed based on each local dynamic database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310880871.6A CN116894064B (en) | 2023-07-18 | 2023-07-18 | Intelligent integrated power-transformation auxiliary control data system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310880871.6A CN116894064B (en) | 2023-07-18 | 2023-07-18 | Intelligent integrated power-transformation auxiliary control data system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116894064A true CN116894064A (en) | 2023-10-17 |
| CN116894064B CN116894064B (en) | 2024-04-09 |
Family
ID=88310450
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310880871.6A Active CN116894064B (en) | 2023-07-18 | 2023-07-18 | Intelligent integrated power-transformation auxiliary control data system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116894064B (en) |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070203693A1 (en) * | 2002-05-22 | 2007-08-30 | Estes Timothy W | Knowledge Discovery Agent System and Method |
| CN105158647A (en) * | 2015-10-10 | 2015-12-16 | 国家电网公司 | Single station end fault diagnosis and auxiliary decisionmaking method based on power supply monitoring system |
| US20160012150A1 (en) * | 2014-07-11 | 2016-01-14 | State Grid Corporation Of China | System and method for main distribution network graph/model/data integration based on remote access and information interaction |
| US20160019033A1 (en) * | 2014-07-18 | 2016-01-21 | Braintribe IT - Technologies GmbH | Expressive generic model technology |
| CN110162556A (en) * | 2018-02-11 | 2019-08-23 | 陕西爱尚物联科技有限公司 | A kind of effective method for playing data value |
| US20210342293A1 (en) * | 2020-05-04 | 2021-11-04 | International Business Machines Corporation | Pointer-based dynamic data structures in key-value stores |
| CN113722303A (en) * | 2021-08-16 | 2021-11-30 | 盛隆电气集团有限公司 | Electric energy equipment and information operation and maintenance system based on visualization |
| CN114328506A (en) * | 2021-11-19 | 2022-04-12 | 集美大学 | Intelligent ship automatic control system |
| CN114638728A (en) * | 2022-03-25 | 2022-06-17 | 国网河北省电力有限公司 | Big data-based real-time operation monitoring method for power service center |
| CN115391371A (en) * | 2022-07-21 | 2022-11-25 | 北京理工大学 | Data interactive transformation and visual embedding method for complex table |
| CN115941293A (en) * | 2022-11-18 | 2023-04-07 | 国网河北省电力有限公司电力科学研究院 | Power network security detection and vulnerability protection datamation method |
| CN115982172A (en) * | 2023-02-02 | 2023-04-18 | 青岛农业大学 | Valence phenotype data recombination method of wheat breeding data platform and application thereof |
| CN116029699A (en) * | 2023-01-17 | 2023-04-28 | 国网辽宁省电力有限公司信息通信分公司 | Power information system based on data twinning and operation and maintenance method |
| CN116308883A (en) * | 2023-03-08 | 2023-06-23 | 国网重庆市电力公司 | Regional power grid data overall management system based on big data |
-
2023
- 2023-07-18 CN CN202310880871.6A patent/CN116894064B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070203693A1 (en) * | 2002-05-22 | 2007-08-30 | Estes Timothy W | Knowledge Discovery Agent System and Method |
| US20160012150A1 (en) * | 2014-07-11 | 2016-01-14 | State Grid Corporation Of China | System and method for main distribution network graph/model/data integration based on remote access and information interaction |
| US20160019033A1 (en) * | 2014-07-18 | 2016-01-21 | Braintribe IT - Technologies GmbH | Expressive generic model technology |
| CN105158647A (en) * | 2015-10-10 | 2015-12-16 | 国家电网公司 | Single station end fault diagnosis and auxiliary decisionmaking method based on power supply monitoring system |
| CN110162556A (en) * | 2018-02-11 | 2019-08-23 | 陕西爱尚物联科技有限公司 | A kind of effective method for playing data value |
| US20210342293A1 (en) * | 2020-05-04 | 2021-11-04 | International Business Machines Corporation | Pointer-based dynamic data structures in key-value stores |
| CN113722303A (en) * | 2021-08-16 | 2021-11-30 | 盛隆电气集团有限公司 | Electric energy equipment and information operation and maintenance system based on visualization |
| CN114328506A (en) * | 2021-11-19 | 2022-04-12 | 集美大学 | Intelligent ship automatic control system |
| CN114638728A (en) * | 2022-03-25 | 2022-06-17 | 国网河北省电力有限公司 | Big data-based real-time operation monitoring method for power service center |
| CN115391371A (en) * | 2022-07-21 | 2022-11-25 | 北京理工大学 | Data interactive transformation and visual embedding method for complex table |
| CN115941293A (en) * | 2022-11-18 | 2023-04-07 | 国网河北省电力有限公司电力科学研究院 | Power network security detection and vulnerability protection datamation method |
| CN116029699A (en) * | 2023-01-17 | 2023-04-28 | 国网辽宁省电力有限公司信息通信分公司 | Power information system based on data twinning and operation and maintenance method |
| CN115982172A (en) * | 2023-02-02 | 2023-04-18 | 青岛农业大学 | Valence phenotype data recombination method of wheat breeding data platform and application thereof |
| CN116308883A (en) * | 2023-03-08 | 2023-06-23 | 国网重庆市电力公司 | Regional power grid data overall management system based on big data |
Non-Patent Citations (4)
| Title |
|---|
| 冷喜武;陈国平;蒋宇;张家琪;曹越峰;: "智能电网监控运行大数据分析系统的数据规范和数据处理", 电力系统自动化, no. 19 * |
| 冷喜武;陈国平;蒋宇;张家琪;曹越峰;: "智能电网监控运行大数据分析系统的数据规范和数据处理", 电力系统自动化, no. 19, 10 October 2018 (2018-10-10) * |
| 李鸿奎;程昭龙;周蕾;王曼琪;胡国华;: "智能变电站设备管控大数据分析系统研究", 机械与电子, no. 10, 20 October 2020 (2020-10-20), pages 22 * |
| 李鸿奎;程昭龙;周蕾;王曼琪;胡国华;: "智能变电站设备管控大数据分析系统研究", 机械与电子, no. 10, pages 22 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116894064B (en) | 2024-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116933052B (en) | Substation data online monitoring system and method | |
| CN107730394A (en) | The polynary isomeric data fusion method of panorama power network based on big data | |
| CN117010532B (en) | Comprehensive pipe gallery fire trend prediction method based on multi-mode deep learning | |
| CN112769237A (en) | Transformer substation digital twin system | |
| CN114511718B (en) | Intelligent management method and system for materials for building construction | |
| CN115395646B (en) | Intelligent operation and maintenance system of digital twin traction substation | |
| CN113327136A (en) | Attribution analysis method and device, electronic equipment and storage medium | |
| CN115392937A (en) | User fraud risk identification method and device, electronic equipment and storage medium | |
| CN116894064B (en) | Intelligent integrated power-transformation auxiliary control data system and method | |
| CN108132423A (en) | A kind of method for rapidly positioning based on state transition probability power system monitoring data distortion | |
| CN113159517B (en) | Three-dimensional visual power grid operation data analysis system | |
| CN111159152A (en) | Secondary operation and maintenance data fusion method based on big data processing technology | |
| CN115034278A (en) | Performance index abnormality detection method and device, electronic equipment and storage medium | |
| CN116029116B (en) | Intelligent substation wisdom management and control digital twin system | |
| CN115309871B (en) | Industrial big data processing method and system based on artificial intelligence algorithm | |
| CN116644289A (en) | Slow disk detection method and device | |
| CN111274232A (en) | Digital twinning processing system and method based on multivariate data manufacturing process | |
| CN115828145A (en) | Online monitoring method, system and medium for electronic equipment | |
| CN115601212A (en) | Intelligent dormitory integrated management method based on digital twin and Internet of things technology | |
| CN113268506B (en) | Query method and device of cache database, electronic equipment and readable storage medium | |
| CN113691390A (en) | Cloud-end-coordinated edge node alarm system and method | |
| JP7421260B1 (en) | Vulnerability mining method and system for competitive industrial control systems | |
| CN115328724B (en) | Monitoring method and system based on big data platform | |
| CN117040137B (en) | Ring main unit temperature rise early warning method, system, terminal and medium based on multi-source data | |
| CN117094206B (en) | Simulation data generation system and generation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |