CN115494382B - Method, system, equipment and storage medium for judging upper and lower level relation of intelligent switch - Google Patents
Method, system, equipment and storage medium for judging upper and lower level relation of intelligent switch Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
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- G—PHYSICS
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention discloses a method, a system, equipment and a storage medium for judging the upper and lower level relation of intelligent switches. And then the fixed current proportion coefficient is calculated by using a statistical mode, and the high-frequency electric quantity data of the two intelligent switches are synchronously processed, so that the influence of metering errors is effectively eliminated. Finally, counting the magnitude relation between the processed high-frequency electric quantity data, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the electric quantity data of the first intelligent switch is larger than the electric quantity data of the second intelligent switch and the proportion of the electric quantity data of the first intelligent switch exceeds a preset threshold value, so that the upper and lower level relation between the adjacent intelligent switches can be accurately identified.
Description
Technical Field
The present invention relates to the field of a platform area line topology identification technology, and in particular, to a method and system for determining a superior-subordinate relationship of an intelligent switch, an electronic device, and a computer readable storage medium.
Background
The line topology data of the transformer area is the basic data of marketing and operation and maintenance of the electric power system, is also the basis of digitalization and intellectualization of the distribution network transformer area, and finally can form optimal configuration and effective linkage of source, load and storage of the transformer area based on the digitalization of the transformer area. In order to realize the digitalization of the platform area, for the incremental platform area, intelligent switches (also called intelligent circuit breakers) are installed in branch boxes and meter boxes of all nodes at present, and particularly, the intelligent switches are arranged at the wire inlet positions of each branch box and meter box and at each wire outlet position, and have metering functions and edge processing capacity, so that the minute-level data acquisition and edge side data processing of the low-voltage platform area can be realized. Therefore, the identification of the topology of the transformer area line can be realized through the perception identification of the upper and lower level relations between the intelligent switches.
The existing method for identifying the upper and lower level relation between the intelligent switches comprises the following steps: firstly, a load jump matching algorithm based on the starting and stopping of a typical electric appliance is adopted to identify the series connection relation between the intelligent switches, and when the starting and stopping of the typical electric appliance occur, a plurality of intelligent switches on the same series connection link have load change values with the same size, so that a plurality of intelligent switches on the same series connection link can be identified through the characteristic value matching of the starting and stopping of the load; then, based on the law of conservation of electric energy, the data of the electric quantity such as the active power, the voltage and the like of the upper intelligent switch should be larger than that of the lower intelligent switch, so that the switch topological relation between the upper branch node and the lower branch node on the same serial link can be judged. However, since the intelligent switches at the outlet of the upper-stage branch box are connected with the intelligent switches at the inlet of the lower-stage branch box through only one wire, the difference between the data collected by the two intelligent switches is mainly in line loss and metering error, and the two influencing factors have the effects of mutual offset or mutual superposition, so that the electric quantity data collected by the two intelligent switches are equivalent, and therefore, the upper-stage relationship and the lower-stage relationship between the two intelligent switches cannot be accurately identified by the existing identification method.
Disclosure of Invention
The invention provides a method and a system for judging the upper and lower level relation of an intelligent switch, electronic equipment and a computer readable storage medium, which are used for solving the technical problem that the existing identification method cannot accurately identify the upper and lower level relation between the intelligent switch at the outlet of a last-level branch box and the intelligent switch at the inlet of a next-level branch box.
According to one aspect of the present invention, there is provided a method for determining a relationship between upper and lower levels of an intelligent switch, including:
respectively acquiring transient current data acquired by two intelligent switches and generating two transient current curves;
generating a current proportion sequence based on the two transient current curves;
calculating a fixed current proportion coefficient based on the current proportion sequence;
and respectively acquiring high-frequency electrical quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the upper and lower relation between the two intelligent switches according to the counting result.
Further, the process of calculating the fixed current proportionality coefficient based on the current proportionality sequence specifically comprises the following steps:
and counting the occurrence frequency of each value in the current proportion sequence, and calculating the fixed current proportion coefficient between the two intelligent switches by using normal distribution.
Further, the process of synchronously processing the high-frequency electric quantity data by using the fixed current proportionality coefficient and counting the magnitude relation between the processed high-frequency electric quantity data and judging the upper and lower relation between the two intelligent switches according to the counting result specifically comprises the following steps:
constructing an electric quantity matrix based on the high-frequency electric quantity data collected by the two intelligent switches and the fixed current proportionality coefficient;
normalizing the two constructed electric quantity matrixes;
and comparing the magnitude relation of the corresponding electrical quantity data in the two electrical quantity matrixes after normalization processing, and counting the comparison result, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the proportion of the electrical quantity data of the first intelligent switch is larger than that of the second intelligent switch and exceeds a preset threshold value.
Further, the high-frequency electrical quantity data comprises voltage U, power P and electric quantity W, and the two constructed electrical quantity matrixes are respectivelyWherein matrix A represents the electrical quantity matrix of intelligent switch i, matrix B represents the electrical quantity matrix of intelligent switch j, ">W ', P ' and U ' represent the actual measured values of the intelligent switch, < >>Respectively representing the converted electric quantity value, converted electric power value and converted electric voltage value of the intelligent switch i at the time t>Representing a fixed current scaling factor.
Further, the two electrical quantity matrixes after normalization processing are as follows Wherein (1)>
Further, after the electrical quantity matrix normalization processing, the following contents are included:
and carrying out weighted fusion on the three electric quantity data in the electric quantity matrix after normalization processing to form an electric quantity fusion data sequence.
Further, the upper and lower level relation between the two intelligent switches is judged by adopting single electric quantity data based on historical data, the judgment accuracy is counted, and the weight coefficient when the three electric quantity data are weighted and fused is determined based on the judgment accuracy corresponding to each electric quantity data.
In addition, the invention also provides a system for judging the upper and lower level relation of the intelligent switch, which comprises:
the transient current curve generation module is used for respectively acquiring the transient current data acquired by the two intelligent switches and generating two transient current curves;
the current proportion sequence generation module is used for generating a current proportion sequence based on the two transient current curves;
the proportional coefficient calculation module is used for calculating a fixed current proportional coefficient based on the current proportional sequence;
the data processing module is used for respectively acquiring the high-frequency electric quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electric quantity data by utilizing the fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electric quantity data, and judging the upper and lower relation between the two intelligent switches according to the counting result.
In addition, the invention also provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is used for executing the steps of the method by calling the computer program stored in the memory.
In addition, the invention also provides a computer readable storage medium for storing a computer program for judging the upper and lower level relation of the intelligent switch, wherein the computer program executes the steps of the method when running on a computer.
The invention has the following effects:
according to the method for judging the upper and lower level relation of the intelligent switches, the transient current data acquired by the two intelligent switches are acquired respectively, the two transient current curves are generated, and then the current proportion sequence is generated. Then, a fixed current proportion coefficient is obtained by means of statistics based on a current proportion sequence, and then the obtained fixed current proportion coefficient is used for synchronously processing high-frequency electric quantity data collected by the two intelligent switches, so that the influence of metering errors of the intelligent switches is effectively eliminated. Finally, counting the magnitude relation between the processed high-frequency electric quantity data, judging the upper and lower relation between the two intelligent switches according to the counting result, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the electric quantity data of the first intelligent switch is larger than the electric quantity data of the second intelligent switch and exceeds a preset threshold value, so that the upper and lower relation between the intelligent switch at the outlet of the upper-level branch box and the intelligent switch at the inlet of the lower-level branch box can be accurately identified.
In addition, the system for judging the upper and lower level relation of the intelligent switch has the advantages.
In addition to the objects, features and advantages described above, the present invention has other objects, features and advantages. The present invention will be described in further detail with reference to the drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
fig. 1 is a flowchart of a method for determining a relationship between upper and lower levels of an intelligent switch according to a preferred embodiment of the present invention.
FIG. 2 is a schematic diagram of two transient current curves generated in a preferred embodiment of the invention.
Fig. 3 is a schematic diagram of a current ratio curve generated in a preferred embodiment of the present invention.
Fig. 4 is a schematic diagram showing the distribution of current proportion values in a current proportion sequence according to a preferred embodiment of the present invention.
Fig. 5 is a schematic view of the sub-flow of step S4 in fig. 1.
Fig. 6 is a schematic block diagram of a system for determining a relationship between upper and lower levels of an intelligent switch according to another embodiment of the present invention.
Detailed Description
Embodiments of the invention are described in detail below with reference to the attached drawing figures, but the invention can be practiced in a number of different ways, as defined and covered below.
As shown in fig. 1, a preferred embodiment of the present invention provides a method for determining a relationship between upper and lower levels of an intelligent switch, which includes the following steps:
step S1: respectively acquiring transient current data acquired by two intelligent switches and generating two transient current curves;
step S2: generating a current proportion sequence based on the two transient current curves;
step S3: calculating a fixed current proportion coefficient based on the current proportion sequence;
step S4: and respectively acquiring high-frequency electrical quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the upper and lower relation between the two intelligent switches according to the counting result.
It can be understood that in the method for judging the upper and lower level relationship of the intelligent switches in this embodiment, firstly, transient current data collected by two intelligent switches are respectively obtained and two transient current curves are generated, so as to generate a current proportion sequence. Then, a fixed current proportion coefficient is obtained by means of statistics based on a current proportion sequence, and then the obtained fixed current proportion coefficient is used for synchronously processing high-frequency electric quantity data collected by the two intelligent switches, so that the influence of metering errors of the intelligent switches is effectively eliminated. Finally, counting the magnitude relation between the processed high-frequency electric quantity data, judging the upper and lower relation between the two intelligent switches according to the counting result, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the electric quantity data of the first intelligent switch is larger than the electric quantity data of the second intelligent switch and exceeds a preset threshold value, so that the upper and lower relation between the intelligent switch at the outlet of the upper-level branch box and the intelligent switch at the inlet of the lower-level branch box can be accurately identified.
It can be understood that a plurality of intelligent switches on the same serial link can be identified through the existing load jump matching algorithm, and then the topological relation of the upper branch node switch and the lower branch node switch can be obtained by combining the law of conservation of electric energy. For example, since the upper branch node is correspondingly connected with a plurality of lower branch nodes at the same time, the electrical quantity data of the intelligent switches at the inlet of the upper branch node, such as power, voltage, electric quantity and the like, are obviously larger than those of all the intelligent switches at the lower branch node, and meanwhile, for the same branch box, the electrical quantity data of the intelligent switches at the inlet is obviously larger than those of the intelligent switches at each outlet. However, for the intelligent switch at a certain outlet of the upper-stage branch box and the intelligent switch at the inlet of the lower-stage branch box, the two adjacent intelligent switches are connected through only one wire, the difference of the electric quantity data measured by the two adjacent intelligent switches is mainly caused by line loss and measurement error, and the two influencing factors can have the problems of mutual offset or mutual superposition, so that the upper-stage relationship and the lower-stage relationship between the two adjacent intelligent switches cannot be accurately judged. Therefore, the invention focuses on how to identify the upper and lower relationships between two adjacent intelligent switches.
Specifically, in the step S1, since two adjacent intelligent switches belong to a series connection, in theory, the current real-time indication values of the upper node and the lower node should be the same, but the metering data will have a slight difference due to the metering error. Meanwhile, the intelligent switches do not have the capability of measuring the cycle data, so that only the second-level data can be acquired, and a certain time offset error exists between the second-level data acquired by two adjacent intelligent switches. Therefore, the method and the device can effectively eliminate the influence of time offset errors by acquiring the transient current data acquired from the transient occurrence to the transient ending of the adjacent two intelligent switches, forming two transient current curves and then performing time synchronization between the two transient current curves based on the transient occurrence time period, as shown in fig. 2. In fig. 2, the horizontal axis represents time and the vertical axis represents a transient current value.
It can be appreciated that in said step S2, it is assumed that the data sequence of the transient current curve of the first smart switch is i= [ I ] 1 ，i 2 ，...，i n ]The data sequence of the transient current curve of the second intelligent switch is I '= [ I ]' 1 ，i′ 2 ，...，i′ n ]The current ratio sequence is: eta= [ eta ] 1 ,η 2 ,...,η n ]，The resulting current ratio curve is shown in fig. 3. In fig. 3, the horizontal axis represents time, and the vertical axis represents the transient current ratio value.
It can be understood that in the step S3, the process of calculating the fixed current scaling factor based on the current scaling sequence is specifically:
counting the occurrence frequency of each value in the current proportion sequence, and then calculating the fixed current proportion coefficient between two intelligent switches by using normal distributionThe distribution of the resulting current ratio sequence is shown in fig. 4. Wherein the desired value can be selected as a fixed current scaling factor +.>Alternatively, the median or average value of the numerical range with the frequency ratio of 85% may be selected as the constant current ratio coefficient +.>For example, the numerical interval [1.004,1.0057 ] in FIG. 4 is selected]Is used as a fixed current scaling factor.
It can be understood that the data difference between the two intelligent switches is mainly caused by a certain voltage division and energy consumption influence of the line impedance between the two intelligent switches on the premise of not considering the influence of the ammeter, and the combination judgment is performed by long-time electric quantity statistics, instantaneous voltage and active power at the moment according to the following conditionsConservation of energy consumption on the line, W Upper j ＝W Lower i +ε i,j ，U Upper j ＝U Lower i +Ir i,j P Upper j ＝P Lower i +I 2 r i,j Therefore, under the influence of inaccurate metering caused by metering errors and clock deviations of the non-taking-account rate ammeter, the upper-stage intelligent switch is slightly larger than the lower-stage intelligent switch in the aspects of electricity consumption W, power P and voltage U, and the hierarchical relation between the two intelligent ammeter can be judged as a theoretical basis. However, in a practical environment, the magnitude of the impedance between two intelligent switches is related to the wire diameter and the wire length, and when two intelligent switches are adjacent to each other, the impedance has little influence on the electrical quantity in a short time, and therefore, it is difficult to judge the upper and lower relationship between the adjacent two intelligent switches. In the step S4, the invention respectively acquires the high-frequency electrical quantity data acquired by the two intelligent switches, then uses the fixed current proportionality coefficient to synchronously process the high-frequency electrical quantity data, counts the magnitude relation between the processed high-frequency electrical quantity data, and judges the upper and lower relation between the two intelligent switches according to the counted result.
As shown in fig. 5, the process of performing synchronous processing on the high-frequency electrical quantity data by using a fixed current proportionality coefficient and counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the upper and lower relation between the two intelligent switches according to the counted result specifically includes:
step S41: constructing an electric quantity matrix based on the high-frequency electric quantity data collected by the two intelligent switches and the fixed current proportionality coefficient;
step S42: normalizing the two constructed electric quantity matrixes;
step S43: and comparing the magnitude relation of the corresponding electrical quantity data in the two electrical quantity matrixes after normalization processing, and counting the comparison result, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the proportion of the electrical quantity data of the first intelligent switch is larger than that of the second intelligent switch and exceeds a preset threshold value.
Specifically, the high-frequency electrical quantity data includes a voltage U, a power P and an electric quantity W, and is constituted byThe two built electric quantity matrixes are respectivelyWherein matrix A represents the electrical quantity matrix of intelligent switch i, matrix B represents the electrical quantity matrix of intelligent switch j, ">W ', P ' and U ' represent the actual measured values of the intelligent switch, < >> The converted electric power value, and the converted electric voltage value of the intelligent switch i at the time t are respectively shown. The high-frequency electric quantity data collected by the two intelligent switches are synchronously processed through the fixed current proportionality coefficient, so that the influence of metering errors of the intelligent switches can be effectively eliminated.
The two electrical quantity matrixes after normalization are Wherein (1)> Respectively representing t moment intelligent switch i normalizationThe electric energy value, the power value and the voltage value after chemical treatment.
Optionally, the method and the device consider that the accuracy of judging the upper and lower relationship of the adjacent circuit breakers by utilizing the single electric quantity data of voltage, power, electric quantity and the like cannot realize high-accuracy judgment, so the method and the device further comprise the following contents after the electric quantity matrix is normalized:
and carrying out weighted fusion on the three electric quantity data in the electric quantity matrix after normalization processing to form an electric quantity fusion data sequence.
Wherein, the electric quantity fusion data sequence is respectively: ω 1 、ω 2 and omega 3 The weight coefficients of the electric quantity, the power and the voltage are respectively represented, and the judgment is carried out by fusing the three electric quantity data, so that the judgment accuracy is improved.
The specific values of the three weight coefficients can be obtained through calculation according to historical data, specifically, the upper and lower relationships between the two intelligent switches are judged by adopting single electric quantity data based on the historical data, the judgment accuracy is counted, and the weight coefficients when the three electric quantity data are weighted and fused are determined based on the judgment accuracy corresponding to each electric quantity data. For example, for a certain two adjacent intelligent switches, the accuracy of the upper and lower relationship is determined to be 82% by voltage, the accuracy of the upper and lower relationship is determined to be 64% by electric quantity, and the accuracy of the upper and lower relationship is determined to be 40% by power by using 96-point electric quantity freezing curves, when weighting fusion is performed, the weighting coefficient of the voltage is 82/(82+64+40) =0.441, the weighting coefficient of the electric quantity is 64/(82+64+40) =0.344, and the weighting coefficient of the power is 40/(82+64+40) =0.215. Alternatively, 0.82, 0.64 and 0.4 may be directly used as the weight coefficients of voltage, electric quantity and power, respectively.
Finally, the corresponding data items in the two electrical quantity fusion data sequences are compared in size relation, namelyAnd (3) withComparing, if->If the ratio exceeds 50%, the intelligent switch i is considered to be at the upper level of the intelligent switch j, so that the upper-lower level relationship between two adjacent intelligent switches is identified. Of course, in other embodiments of the present invention, the preset threshold may be set to 60%, 70% or 80% or other values, which may be set according to actual needs.
It will be appreciated that in other embodiments of the present invention, one type of electrical quantity data or two types of electrical quantity data may be used for comparison analysis to determine the upper and lower relationships.
In addition, as shown in fig. 6, another embodiment of the present invention further provides a system for determining a relationship between upper and lower levels of an intelligent switch, preferably adopting the method as described above, where the system includes:
the transient current curve generation module is used for respectively acquiring the transient current data acquired by the two intelligent switches and generating two transient current curves;
the current proportion sequence generation module is used for generating a current proportion sequence based on the two transient current curves;
the proportional coefficient calculation module is used for calculating a fixed current proportional coefficient based on the current proportional sequence;
the data processing module is used for respectively acquiring the high-frequency electric quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electric quantity data by utilizing the fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electric quantity data, and judging the upper and lower relation between the two intelligent switches according to the counting result.
It can be understood that, in the system for judging the upper and lower relationships of the intelligent switches of this embodiment, transient current data collected by two intelligent switches are obtained respectively first and two transient current curves are generated, so as to generate a current proportion sequence. Then, a fixed current proportion coefficient is obtained by means of statistics based on a current proportion sequence, and then the obtained fixed current proportion coefficient is used for synchronously processing high-frequency electric quantity data collected by the two intelligent switches, so that the influence of metering errors of the intelligent switches is effectively eliminated. Finally, counting the magnitude relation between the processed high-frequency electric quantity data, judging the upper and lower relation between the two intelligent switches according to the counting result, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the electric quantity data of the first intelligent switch is larger than the electric quantity data of the second intelligent switch and exceeds a preset threshold value, so that the upper and lower relation between the intelligent switch at the outlet of the upper-level branch box and the intelligent switch at the inlet of the lower-level branch box can be accurately identified.
In addition, another embodiment of the present invention also provides an electronic device, including a processor and a memory, where the memory stores a computer program, and the processor is configured to execute the steps of the method described above by calling the computer program stored in the memory.
In addition, another embodiment of the present invention also provides a computer readable storage medium storing a computer program for determining a relationship between upper and lower levels of an intelligent switch, the computer program executing the steps of the method as described above when running on a computer.
Forms of general computer-readable storage media include: a floppy disk (floppy disk), a flexible disk (flexible disk), hard disk, magnetic tape, any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a Random Access Memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a FLASH-erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium from which a computer can read. The instructions may further be transmitted or received over a transmission medium. The term transmission medium may include any tangible or intangible medium that may be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communications signals or their communications with intangible medium that facilitate communication of such instructions. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise a bus for transmitting a computer data signal.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The solutions in the embodiments of the present application may be implemented in various computer languages, for example, object-oriented programming language Java, and an transliterated scripting language JavaScript, etc.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (7)
1. The method for judging the upper and lower level relation of the intelligent switch is characterized by comprising the following steps of:
respectively acquiring transient current data acquired by two intelligent switches and generating two transient current curves;
generating a current proportion sequence based on the two transient current curves;
calculating a fixed current proportion coefficient based on the current proportion sequence;
respectively acquiring high-frequency electric quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electric quantity data by utilizing a fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electric quantity data, and judging the upper-level relation and the lower-level relation between the two intelligent switches according to the counting result;
the process for calculating the fixed current proportionality coefficient based on the current proportionality sequence comprises the following steps:
counting the occurrence frequency of each value in the current proportion sequence, and then calculating the distribution condition of the current proportion sequence obtained by the fixed current proportion coefficient between the two intelligent switches by using normal distribution, wherein the expected value is selected as the fixed current proportion coefficient, or the median value or the average value of a numerical interval with the frequency proportion of 85% is selected as the fixed current proportion coefficient;
the process of synchronously processing the high-frequency electric quantity data by utilizing the fixed current proportionality coefficient and counting the magnitude relation between the processed high-frequency electric quantity data and judging the upper and lower relation between the two intelligent switches according to the counting result comprises the following steps:
constructing an electric quantity matrix based on the high-frequency electric quantity data collected by the two intelligent switches and the fixed current proportionality coefficient;
normalizing the two constructed electric quantity matrixes;
comparing the magnitude relation of the corresponding electrical quantity data in the two electrical quantity matrixes after normalization processing, and counting the comparison result, wherein when the proportion of the electrical quantity data of the first intelligent switch is larger than that of the electrical quantity data of the second intelligent switch and exceeds a preset threshold value, the first intelligent switch is judged to be positioned at the upper level of the second intelligent switch;
the high-frequency electric quantity data comprise voltage U, power P and electric quantity W, and two constructed electric quantityThe gas flow matrixes are respectivelyWherein matrix A represents the electrical quantity matrix of intelligent switch i, matrix B represents the electrical quantity matrix of intelligent switch j, "> W ', P ' and U ' represent the actual measured values of the intelligent switch, < >>Respectively representing the converted electric quantity value, converted electric power value and converted electric voltage value of the intelligent switch i at the time t>Representing a fixed current scaling factor.
2. The method for determining the upper and lower relationships of an intelligent switch as set forth in claim 1, wherein the normalized two electrical quantity matrices are Wherein,
wherein (1)>And respectively representing the electric energy value, the power value and the voltage value of the intelligent switch i after normalization processing at the moment t.
3. The method for determining the upper and lower relationships of an intelligent switch according to claim 2, further comprising the following after normalizing the electrical quantity matrix:
and carrying out weighted fusion on the three electric quantity data in the electric quantity matrix after normalization processing to form an electric quantity fusion data sequence.
4. The method for determining the upper and lower relationships of the intelligent switches according to claim 3, wherein the upper and lower relationships between the two intelligent switches are determined by using single electrical quantity data based on historical data, and the determination accuracy is counted, and the weight coefficients of the three electrical quantity data when weighted fusion is performed are determined based on the determination accuracy corresponding to each electrical quantity data.
5. A system for judging the upper and lower level relation of an intelligent switch, adopting the method as claimed in any one of claims 1 to 4, comprising:
the transient current curve generation module is used for respectively acquiring the transient current data acquired by the two intelligent switches and generating two transient current curves;
the current proportion sequence generation module is used for generating a current proportion sequence based on the two transient current curves;
the proportional coefficient calculation module is used for calculating a fixed current proportional coefficient based on the current proportional sequence;
the data processing module is used for respectively acquiring the high-frequency electric quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electric quantity data by utilizing the fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electric quantity data, and judging the upper and lower relation between the two intelligent switches according to the counting result.
6. An electronic device comprising a processor and a memory, said memory having stored therein a computer program for executing the steps of the method according to any of claims 1-4 by invoking said computer program stored in said memory.
7. A computer readable storage medium storing a computer program for determining the context of an intelligent switch, wherein the computer program when run on a computer performs the steps of the method according to any one of claims 1 to 4.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111289942A (en) * | 2020-01-21 | 2020-06-16 | 北京市腾河电子技术有限公司 | Method and system for analyzing error of measurement domain based on single load jump and storage medium |
| CN111654005A (en) * | 2020-04-20 | 2020-09-11 | 国网福建省电力有限公司 | Method for monitoring, studying and judging low-voltage electric leakage of distribution transformer area and self-healing low-voltage electric leakage of distribution transformer area |
| CN111929483A (en) * | 2020-08-07 | 2020-11-13 | 贵州电网有限责任公司 | Primary and secondary fusion equipment test system and test method thereof |
| CN112098886A (en) * | 2020-08-07 | 2020-12-18 | 国网山东省电力公司青岛供电公司 | Single-phase grounding line selection method and system for low-current grounding system |
| CN112966219A (en) * | 2021-03-01 | 2021-06-15 | 北京市腾河智慧能源科技有限公司 | Method, system, equipment and medium for identifying relationship between household meter and meter box |
| CN114188941A (en) * | 2021-11-30 | 2022-03-15 | 国网湖北省电力有限公司营销服务中心(计量中心) | Intelligent platform area fusion terminal system and application method thereof |
| CN114285170A (en) * | 2021-12-28 | 2022-04-05 | 广东电网有限责任公司 | Low-voltage topology identification method and device and storage medium |
| CN114785441A (en) * | 2022-04-22 | 2022-07-22 | 湖南腾河智慧能源科技有限公司 | Cycle-level power data synchronization method, system, equipment and storage medium |
| WO2022217812A1 (en) * | 2021-04-16 | 2022-10-20 | 西安热工研究院有限公司 | Electromechanical transient modeling method and system, and device and storage medium |
-
2022
- 2022-10-25 CN CN202211309282.4A patent/CN115494382B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111289942A (en) * | 2020-01-21 | 2020-06-16 | 北京市腾河电子技术有限公司 | Method and system for analyzing error of measurement domain based on single load jump and storage medium |
| CN111654005A (en) * | 2020-04-20 | 2020-09-11 | 国网福建省电力有限公司 | Method for monitoring, studying and judging low-voltage electric leakage of distribution transformer area and self-healing low-voltage electric leakage of distribution transformer area |
| CN111929483A (en) * | 2020-08-07 | 2020-11-13 | 贵州电网有限责任公司 | Primary and secondary fusion equipment test system and test method thereof |
| CN112098886A (en) * | 2020-08-07 | 2020-12-18 | 国网山东省电力公司青岛供电公司 | Single-phase grounding line selection method and system for low-current grounding system |
| CN112966219A (en) * | 2021-03-01 | 2021-06-15 | 北京市腾河智慧能源科技有限公司 | Method, system, equipment and medium for identifying relationship between household meter and meter box |
| WO2022217812A1 (en) * | 2021-04-16 | 2022-10-20 | 西安热工研究院有限公司 | Electromechanical transient modeling method and system, and device and storage medium |
| CN114188941A (en) * | 2021-11-30 | 2022-03-15 | 国网湖北省电力有限公司营销服务中心(计量中心) | Intelligent platform area fusion terminal system and application method thereof |
| CN114285170A (en) * | 2021-12-28 | 2022-04-05 | 广东电网有限责任公司 | Low-voltage topology identification method and device and storage medium |
| CN114785441A (en) * | 2022-04-22 | 2022-07-22 | 湖南腾河智慧能源科技有限公司 | Cycle-level power data synchronization method, system, equipment and storage medium |
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