CN112801817B - Electric energy quality data center construction method and system thereof - Google Patents

Electric energy quality data center construction method and system thereof Download PDF

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CN112801817B
CN112801817B CN202110123467.5A CN202110123467A CN112801817B CN 112801817 B CN112801817 B CN 112801817B CN 202110123467 A CN202110123467 A CN 202110123467A CN 112801817 B CN112801817 B CN 112801817B
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data
ledger
ledger data
bhattacharyya
chinese character
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CN112801817A (en
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徐思尧
李妍
程晨
张子瑛
彭明洋
周刚
陈晓科
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Electric Power Research Institute of Guangdong Power Grid Co Ltd
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Electric Power Research Institute of Guangdong Power Grid Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a construction method and a system of an electric energy quality data center, wherein the construction method comprises the following steps: splitting the data of the system into ledger data and production data according to the attribute characteristics; and judging whether the ledger data in each system are the same according to the Bhattacharyya distance and the DTW algorithm so as to integrate the ledger data and load the production data into the integrated ledger data. The invention starts from the characteristics of a power grid system, and provides a fusion algorithm which accords with the characteristic design of the fusion frame and the ledger data of the industry according to the power grid commonality, so that the matching accuracy of single words is improved, the fusion realization of the ledger with different lengths can be solved, and the fusion efficiency of the ledger data is improved.

Description

Electric energy quality data center construction method and system thereof
Technical Field
The present invention relates to the field of power systems, and in particular, to a method and a system for constructing a power quality data center, a computer terminal device, and a readable storage medium.
Background
In recent years, with the rapid development of high-voltage direct-current transmission technology, distributed micro-grid and other technologies, the form of a power grid is greatly changed, and the power quality mechanism of the power grid caused by the novel technologies is more complex and extends to an ultrahigh voltage and a distribution network, so that the power quality problem exists in all links of a modern power system.
In contrast, grid companies have installed very few, very few power quality monitoring devices and mainly cover 10kV and above buses. With the development of the power grid, the power grid production system constructed by the synchronous phasor measurement unit containing the power quality data and other devices makes it possible to acquire the power quality data covering the whole grid.
In view of the complexity and massive nature of the power quality data, how to reasonably design and build a power quality data center is critical to the overall monitoring system. Because the electric energy quality industry always lacks unified data format and specification, and many electric power companies and enterprises can produce monitoring equipment, the monitoring equipment and analysis tools produced by various manufacturers are characterized, the monitoring data emphasis points are different, and the data formats are quite different and mutually incompatible. This is very disadvantageous for information sharing and application integration between applications within and between utility companies.
Disclosure of Invention
The invention aims to provide a construction method of a power quality data center, which provides a fusion algorithm which is designed according with the characteristics of fusion frames and ledger data of the industry according to the power grid commonality, so that the matching accuracy of single characters is improved, the fusion realization of ledger data with different lengths can be solved, and the fusion efficiency of the ledger data is improved.
To achieve the above object, an embodiment of the present invention provides a method for constructing a power quality data center, including:
splitting the data of the system into ledger data and production data according to the attribute characteristics;
judging whether the ledger data in each system are the same according to the Bhattacharyya distance and a DTW algorithm so as to integrate the ledger data;
and hanging the production data in the integrated ledger data.
In one embodiment, the system includes a production management system, a dispatch automation system, a distribution network automation system, a metering automation system, a marketing system, a GIS system, a voltage system, and a power quality system.
In a certain embodiment, before the step of determining whether the ledger data of each system are the same according to the Bhattacharyya distance and the DTW algorithm, the step of dividing the ledger data into subsets according to a management unit is further included.
In one embodiment, the determining whether the ledger data of each system is the same according to the Bhattacharyya distance and the DTW algorithm includes:
obtaining a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
according to a DTW algorithm, sequentially accumulating all the past points Bhattacharyya coefficients, and traversing the ledger data Q in the ledger data a And ledger data C g Chinese characters can be obtained to obtain the accumulated distance gamma (a, g), a represents the standing account Q a Word number of the name of the Chinese ledger, g represents the ledger Q g Number of words of the account name; the calculation formula is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein B (q) a ,c g ) Representing the ledger data Q a Chinese character q a And the ledger data C g Chinese character c g Bhattacharyya coefficients of (C);
judging whether the two pieces of account data are the same or not, wherein a judging formula is as follows:
where r is the number of valid matches of γ (a, g), τ is a preset threshold.
The embodiment of the invention also provides a construction system of the electric energy quality data center, which is applied to the construction method of the electric energy quality data center in any embodiment. Comprising the following steps:
the system data splitting module is used for splitting the system data into ledger data and production data according to the attribute characteristics;
the system comprises a ledger data integration module, a ledger data processing module and a data processing module, wherein the ledger data integration module is used for judging whether the ledger data of each system are the same according to a Bhattacharyya distance and a DTW algorithm so as to integrate the ledger data;
and the production data mounting module is used for mounting the production data in the integrated ledger data.
In a certain embodiment, the system further comprises a ledger data subset dividing module, wherein the ledger data subset dividing module is used for dividing the ledger data into subsets according to a management unit.
In one embodiment, the ledger data integration module includes:
the standing book data single word similarity calculation unit is used for calculating a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
the standing book data accumulation distance calculation unit is used for sequentially accumulating all the past points Bhattacharyya coefficients according to a DTW algorithm and traversing the standing book data Q in the standing book data a And ledger data C g Chinese characters can be obtained to obtain the accumulated distance gamma (a, g), a represents the standing account Q a Word number of the name of the Chinese ledger, g represents the ledger Q g Number of words of the account name; the calculation formula is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein B (q) a ,c g ) Representing the ledger data Q a Chinese character q a And the ledger data C g Chinese characterc g Bhattacharyya coefficients of (C);
the ledger data identity judging unit is used for judging whether the two ledger data are identical or not, and the judging formula is as follows:
where r is the number of valid matches of γ (a, g), τ is a preset threshold.
The embodiment of the invention also provides computer terminal equipment which comprises one or more processors and a memory. A memory coupled to the processor for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the power quality data center building method as described in any of the embodiments above.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for constructing a power quality data center according to any of the above embodiments.
According to the electric energy quality data center construction method and system, from the characteristics of the power grid system, the fusion algorithm which accords with the fusion frame and the ledger data characteristic design of the industry is provided according to the power grid commonality, so that the matching accuracy of single words is improved, the ledger fusion realization of different lengths can be solved, and the ledger data fusion efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for constructing a power quality data center according to an embodiment of the present invention;
FIG. 2 is a block diagram of a method for constructing a power quality data center according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of subset partitioning in a method for constructing a power quality data center according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a result of calculation of a full-pel probability in a method for constructing a power quality data center according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a computer terminal device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the step numbers used herein are for convenience of description only and are not limiting as to the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate 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.
The term "and/or" refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1, an embodiment of the present invention provides a method for constructing a power quality data center, including:
s10, splitting the data of the system into ledger data and production data according to attribute characteristics;
s20, judging whether the ledger data in each system are the same according to the Bhattacharyya distance and a DTW algorithm so as to integrate the ledger data;
s30, the production data are mounted in the integrated ledger data.
Referring to fig. 2, in this embodiment, system data (a production management system, a dispatching automation system, a distribution network automation system, a metering automation system, a marketing system, a GIS system, a voltage system and a power quality system) is split into ledger data and production data, wherein the ledger data is archive information representing a power object, and is composed of a plurality of sub-attributes, and each attribute value is usually fixed, for example, the ledger data of a transformer usually includes a transformer name, a model number, a capacity, an id allocated by the system, etc., while the production data is variable, and the production data represents dynamic operation data of the power object, and is usually related to time, for example: the transformer operation data contains voltage, current, work, reactive power, etc. of each time sequence, and thus the production data is stored depending on the ledger data.
Finding out the commonality of the ledger data of each system is a key for realizing data integration. And obtaining the similarity of the Chinese character full spelling by using the Bhattacharyya distance according to the standing account data, obtaining the standing account similarity by using the improved DTW (Dynamic Time Warping) dynamic time normalization, and then judging the identity. And finally, the production data are mounted in the integrated standing book data, so that the construction of the whole electric energy quality data center is completed. According to the electric network commonality, a fusion framework conforming to the industry is provided, and a fusion algorithm designed according to the standing book data characteristics not only improves the matching accuracy of the single words.
In one embodiment, the system includes a production management system, a dispatch automation system, a distribution network automation system, a metering automation system, a marketing system, a GIS system, a voltage system, and a power quality system.
In a certain embodiment, before the step of determining whether the ledger data of each system are the same according to the Bhattacharyya distance and the DTW algorithm, the step of dividing the ledger data into subsets according to a management unit is further included.
Referring to fig. 3, in the present embodiment, in the ledger integration implementation module, word set division is first performed according to a management unit, so as to reduce ledger repetition and improve fusion efficiency. Ledger names are the naming of power system objects, but may be repeated among systems or in the same system, for example: the power supply bureau of the Zhongshan and the power supply bureau of the bead sea of the voltage monitoring system find that the standing account name is the distribution transformer name of the private transformer of the public security bureau. Therefore, by means of the management relationship of the grid company, the management unit to which the ledger name belongs is judged from top to bottom until a unit directly responsible for the ledger is found. Taking an integrated provincial system as an example, the next stage is a power supply office, the next stage of the power supply office is a county-dividing office, the next stage of the county-dividing office is a power supply office or a transformer substation, and the next stages of the county-dividing offices are sequentially searched downwards. The processing is a classification process, and can improve the integration efficiency of the multi-system ledgers.
In one embodiment, the determining whether the ledger data of each system is the same according to the Bhattacharyya distance and the DTW algorithm includes:
obtaining a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
according to a DTW algorithm, sequentially accumulating all the past points Bhattacharyya coefficients, and traversing the ledger data Q in the ledger data a And ledger data C g Chinese characters can be obtained to obtain the accumulated distance gamma (a, g), a represents the standing account Q a Word number of the name of the Chinese ledger, g represents the ledger Q g Number of words of the account name; the calculation formula is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein B (q) a ,c g ) Representing the ledger data Q a Chinese character q a And the ledger data C g Chinese character c g Bhattacharyya coefficients of (C);
judging whether the two pieces of account data are the same or not, wherein a judging formula is as follows:
where r is the number of valid matches of γ (a, g), τ is a preset threshold.
In this embodiment, the Chinese character full-spelling similarity is obtained according to the Bhattacharyya distance. The Bhattacharyya distance is used to measure the similarity of two discrete or continuous probabilities, defined as: in the same definition field X, the pasteurization distance of two discrete probability distributions p and q is defined as follows:
D B (p,q)＝-ln(B C (p,q)) (1)
and converting the whole spelling of the Chinese characters into a probability histogram, and solving the similarity of any two Chinese characters by using the formula (1) and the formula (2), wherein the higher the similarity is, the closer BC is to 1, and the closer BC is to 0.
Firstly, carrying out probability conversion on Chinese characters, wherein the process is as follows: for any Chinese character y, the whole spelling is sequence H, H= [ H ] 1 ,h 2 ..h r .,h t ]，h r The r-th letter for y full spell, t denotes the full spell length. Numbering according to the alphabet in turn, and taking the numbering as the abscissa of the histogram; counting the total number of phonetic letters a of Chinese character y and the number n of each letter r The duty ratio P (h) of each letter is calculated according to the formula (3) i ) And as a histogram value.
And DTW (Dynamic Time Warping) dynamic time warping to obtain the similarity of the standing accounts. The same object names in each system are mostly different in length, and on the other hand, the power system ledger names are named according to the power supply relationship, so that the power system ledger names are considered to have time sequence, and therefore the DTW is suitable for solving the ledger name similarity.
Please refer to fig. 4, forAny two account names Q a And C g The subscript indicates the number of Chinese characters, and a and g may be different. By solving for the accumulated distance gamma: starting from (0, 0), find Q using Bhattacharyya distance a And C g Similarity of two Chinese characters, e.g. Q a The Chinese character "Tang" is included, and the Chinese character "frame" is included in Cg, and the full spelling probabilities are respectively obtained by using the formula (3). The Bhattacharyya coefficients of the Tang and the box are calculated as 0.67 by the formula (2), all the Bhattacharyya coefficients of the passing points are accumulated in sequence, the accumulated distance gamma is obtained after the end points (a and g) are reached, the solution formula is expressed as the formula (4),
equation (4) is a variation of the existing DTW, modified by: the Bhattacharyya coefficient B () is used for replacing the common Euclidean distance, the maximum value obtained in the searching process is obtained instead of the traditional minimum value, and the Bhattacharyya coefficient characteristic is used for determining, and the calculation formula is as follows:
γ(i,j)＝B(q i ,c j )+max{γ(i-1,j-1),γ(i-1,j),γ(i,j-1)} (4)
q i represents Q a I-th Chinese character, c j Represent C g The j-th Chinese character, and B (q i ,c j ) Then represent and calculate Chinese character q i And c j Bhattacharyya coefficients of (a),
finally, after reaching the heavy end (a, g), the accumulated distance gamma (a, g) is obtained, and the formula is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein B (q) a ,c g ) Representing the ledger data Q a Chinese character q a And the ledger data C g Chinese character c g Bhattacharyya coefficients of (C);
finally, judging whether the two pieces of account data are the same or not through a formula (5), wherein the formula is as follows
r is the effective matching times of gamma (i, j), tau is a preset threshold, when the formula (5) is established, the two ledger data are judged to be identical, and when the formula (5) is not established, the two ledger data are judged to be different.
The embodiment of the invention also provides a construction system of the electric energy quality data center, which is applied to the construction method of the electric energy quality data center in any embodiment. Comprising the following steps:
the system data splitting module is used for splitting the system data into ledger data and production data according to the attribute characteristics;
the system comprises a ledger data integration module, a ledger data processing module and a data processing module, wherein the ledger data integration module is used for judging whether the ledger data of each system are the same according to a Bhattacharyya distance and a DTW algorithm so as to integrate the ledger data;
and the production data mounting module is used for mounting the production data in the integrated ledger data.
In a certain embodiment, the system further comprises a ledger data subset dividing module, wherein the ledger data subset dividing module is used for dividing the ledger data into subsets according to a management unit.
In one embodiment, the ledger data integration module includes:
the standing book data single word similarity calculation unit is used for calculating a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
the standing book data accumulation distance calculation unit is used for sequentially accumulating all the past points Bhattacharyya coefficients according to a DTW algorithm and traversing the standing book data Q in the standing book data a And ledger data C g Chinese characters can be obtained to obtain the accumulated distance gamma (a, g), a represents the standing account Q a Word number of the name of the Chinese ledger, g represents the ledger Q g Number of words of the account name; the calculation formula is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein B (q) a ,c g ) Representing the ledger data Q a Chinese character q a And the ledger data C g Chinese character c g Bhattacharyya coefficients of (C);
the ledger data identity judging unit is used for judging whether the two ledger data are identical or not, and the judging formula is as follows:
where r is the number of valid matches of γ (a, g), τ is a preset threshold.
For specific limitations on the construction system of the power quality data center, reference may be made to the above limitation on the construction method of the power quality data center, and no further description is given here. The modules in the above-described power quality data center building system may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Referring to fig. 5, an embodiment of the present invention provides a computer terminal device including one or more processors and a memory. The memory is coupled to the processor for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the method of constructing a power quality data center as in any of the embodiments described above.
The processor is used for controlling the overall operation of the computer terminal equipment to complete all or part of the steps of the construction method of the power quality data center. The memory is used to store various types of data to support operation at the computer terminal device, which may include, for example, instructions for any application or method operating on the computer terminal device, as well as application-related data. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk or optical disk.
In an exemplary embodiment, the computer terminal device may be implemented by one or more application specific integrated circuits (Application Specific, ntegrated Circuit, abbreviated AS 1C), digital signal processors (Digital Signal Processor, abbreviated DSP), digital signal processing devices (Digital Signal Processing Device, abbreviated DSPD), programmable logic devices (Programmable Logic Device, abbreviated PLD), field programmable gate arrays (Field Programmable Gate Array, abbreviated FPGA), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-described method for constructing a power quality data center, and achieving technical effects consistent with the above-described method.
In another exemplary embodiment, a computer readable storage medium is also provided, comprising program instructions which, when executed by a processor, implement the steps of the method of constructing a power quality data center in any of the above embodiments. For example, the computer readable storage medium may be the above memory including program instructions executable by a processor of the computer terminal device to perform the above method for constructing a power quality data center, and achieve technical effects consistent with the above method.
According to the electric energy quality data center construction method and system, from the characteristics of the power grid system, the fusion algorithm which is designed according with the characteristics of the fusion frame and the ledger data of the industry is provided according to the power grid commonality, so that the matching accuracy of single words is improved, the fusion realization of ledger data with different lengths can be solved, and the fusion efficiency of the ledger data is improved.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.

Claims (5)

1. A method of constructing a power quality data center, comprising:
splitting data in a plurality of systems into ledger data and production data according to attribute characteristics, and dividing the ledger data into subsets according to management units; the ledger data is file information for representing the electric power object, and consists of a plurality of sub-attributes, wherein the attribute value of each sub-attribute is fixed; the production data is dynamic operational data characterizing the power object;
judging whether the ledger data in the systems are the same according to the Bhattacharyya distance and a DTW algorithm so as to integrate the ledger data;
the production data are hung in the integrated ledger data;
judging whether the ledger data in the systems are the same according to the Bhattacharyya distance and the DTW algorithm, wherein the method comprises the following steps:
obtaining a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
according to a DTW algorithm, bhattacharyya coefficients of all passed points are sequentially accumulated, and the ledger data Q in the ledger data are traversed a And ledger data C g The Chinese characters in the table account data Q can be obtained by the accumulated distance gamma (a, g), wherein a represents the table account data Q a Word number of the account name, g represents account data C g Number of words of the account name;
the calculation formula of Bhattacharyya coefficients of all points sequentially accumulated is as follows:
γ(i,j)＝B(q i ,c j )+max{γ(i-1,j-1),γ(i-1,j),γ(i,j-1)}
wherein, gamma (i, j) represents traversing to the ledger data Q according to the DTW algorithm a I-th Chinese character and ledger data C g The cumulative distance at the j-th kanji; q i Representing ledger data Q a I-th Chinese character, c j Representing ledger data C g The j-th Chinese character, and B (q i ,c j ) Then the representation is based on Chinese character q i Hehan dynastyWord c j Chinese character q obtained by calculating Bhattacharyya distance i He Hanzi c j Bhattacharyya coefficients in between;
and, the accumulated distance gamma (a, g) represents the traversed standing book data Q a A Chinese characters and standing account data C g The accumulated distance of g Chinese characters, and the calculation formula of the accumulated distance gamma (a, g) is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein q a Representing ledger data Q a A-th Chinese character, c g Representing ledger data C g G-th Chinese character, B (q) a ,c g ) Representing according to Chinese character q a He Hanzi c g Chinese character q obtained by calculating Bhattacharyya distance a He Hanzi c g Bhattacharyya coefficients in between;
judging whether the two pieces of account data are the same or not, wherein a judging formula is as follows:
and r is the effective matching times of gamma (a, g), tau is a preset threshold value, and when the judging formula is established, the two ledger data are judged to be the same.
2. The method of claim 1, wherein the power quality data center is constructed,
the system comprises a production management system, a dispatching automation system, a distribution network automation system, a metering automation system, a marketing system, a GIS system, a voltage system and a power quality system.
3. A system for constructing a power quality data center, comprising:
the system data splitting module is used for splitting the system data into ledger data and production data according to the attribute characteristics, and carrying out subset division on the ledger data according to the management units; the ledger data is file information for representing the electric power object, and consists of a plurality of sub-attributes, wherein the attribute value of each sub-attribute is fixed; the production data is dynamic operational data characterizing the power object;
the ledger data integration module is used for judging whether the ledger data of each system are the same according to the Bhattacharyya distance and the DTW algorithm so as to integrate the ledger data;
the production data mounting module is used for mounting the production data in the integrated ledger data;
judging whether the ledger data of each system are the same according to the Bhattacharyya distance and the DTW algorithm, comprising:
obtaining a single word Bhattacharyya coefficient in the standing book data according to the Bhattacharyya distance;
according to a DTW algorithm, bhattacharyya coefficients of all passed points are sequentially accumulated, and the ledger data Q in the ledger data are traversed a And ledger data C g The Chinese characters in the table account data Q can be obtained by the accumulated distance gamma (a, g), wherein a represents the table account data Q a Word number of the account name, g represents account data C g Number of words of the account name;
the calculation formula of Bhattacharyya coefficients of all points sequentially accumulated is as follows:
γ(i,j)＝B(q i ,c j )+max{γ(i-1,j-1),γ(i-1,j),γ(i,j-1)}
wherein, gamma (i, j) represents traversing to the ledger data Q according to the DTW algorithm a I-th Chinese character and ledger data C g The cumulative distance at the j-th kanji; q i Representing ledger data Q a I-th Chinese character, c j Representing ledger data C g The j-th Chinese character, and B (q i ,c j ) Then the representation is based on Chinese character q i He Hanzi c j Chinese character q obtained by calculating Bhattacharyya distance i He Hanzi c j Bhattacharyya coefficients in between;
and, the accumulated distance gamma (a, g) represents the traversed standing book data Q a A Chinese characters and standing account data C g The cumulative distance of g Chinese characters, andthe calculation formula of γ (a, g) is as follows:
γ(a,g)＝B(q a ,c g )+max{γ(a-1,g-1),γ(a-1,g),γ(a,g-1)}
wherein q a Representing ledger data Q a A-th Chinese character, c g Representing ledger data C g G-th Chinese character, B (q) a ,c g ) Representing according to Chinese character q a He Hanzi c g Chinese character q obtained by calculating Bhattacharyya distance a He Hanzi c g Bhattacharyya coefficients in between;
judging whether the two pieces of account data are the same or not, wherein a judging formula is as follows:
and r is the effective matching times of gamma (a, g), tau is a preset threshold value, and when the judging formula is established, the two ledger data are judged to be the same.
4. A computer terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of constructing a power quality data center of any of claims 1-2.
5. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements a method of constructing a power quality data center according to any one of claims 1 to 2.
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