CN115494382A - Method, system, equipment and storage medium for judging superior-inferior relation of intelligent switch - Google Patents
Method, system, equipment and storage medium for judging superior-inferior relation of intelligent switch Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a storage medium for judging the superior-inferior relation of intelligent switches. And then, a fixed current proportion coefficient is calculated by utilizing 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. And finally, counting the magnitude relation between the processed high-frequency electrical quantity data, and when the proportion that the electrical quantity data of the first intelligent switch is larger than the electrical quantity data of the second intelligent switch exceeds a preset threshold value, judging that the first intelligent switch is positioned at the upper level of the second intelligent switch, so that the superior-inferior relation between adjacent intelligent switches can be accurately identified.
Description
Technical Field
The invention relates to the technical field of distribution room line topology identification, in particular to a method and a system for judging the superior-subordinate relation of an intelligent switch, electronic equipment and a computer readable storage medium.
Background
The line topology data of the distribution area is basic data of marketing and operation and maintenance of the power system and is also a basis for digitalization and intellectualization of the distribution network area, and finally, optimal configuration and effective linkage of a source, a load and a storage of the distribution area can be formed on the basis of the digitalization of the distribution area. In order to realize the digitalization of the transformer area, for the incremental transformer area, intelligent switches (also called intelligent circuit breakers) are installed in branch boxes and meter boxes of each node at present, and particularly, the intelligent switches are arranged at the wire inlet and the wire outlet of each branch box and the meter box, have the metering function and the edge processing capacity, and can realize the minute-level data acquisition and the edge-side data processing of the low-voltage transformer area. Therefore, the topology identification of the line in the transformer area can be realized through the perception identification of the superior-inferior relation between the intelligent switches.
The existing method for identifying the superior-inferior relation between intelligent switches comprises the following steps: firstly, identifying the series relation among the intelligent switches by adopting a load jump matching algorithm based on the start and stop of a typical electric appliance, and when the start and stop of the typical electric appliance occur, the plurality of intelligent switches on the same series link have the same load change value, so that the plurality of intelligent switches on the same series link can be identified through the characteristic value matching of the start and stop of the load; then, based on the law of conservation of electric energy, it can be known that the data of electric quantities such as active power, voltage and the like of the upper-level intelligent switch should be larger than that of the lower-level intelligent switch, so that the switching topological relation between the upper-level branch node and the lower-level branch node on the same serial link can be judged. However, since the intelligent switch at the outlet of the upper branch box is connected with the intelligent switch at the inlet of the lower branch box through only one wire, the difference between the data collected by the two intelligent switches mainly lies in the line loss and the metering error, and the two influencing factors can have the effect of mutual cancellation or mutual superposition, so that the electrical quantity data collected by the two intelligent switches are equivalent, and therefore, the existing identification method cannot accurately identify the upper-lower level relation between the two intelligent switches.
Disclosure of Invention
The invention provides a method and a system for judging the superior-inferior relation of an intelligent switch, electronic equipment and a computer readable storage medium, which are used for solving the technical problem that the superior-inferior relation between an intelligent switch at the outlet of a superior branch box and an intelligent switch at the inlet of a inferior branch box cannot be accurately identified by the existing identification method.
According to an aspect of the present invention, a method for determining the relationship between the upper level and the lower level of an intelligent switch is provided, which includes the following steps:
respectively acquiring transient current data acquired by the two intelligent switches and generating two transient current curves;
generating a current proportion sequence based on the two transient current curves;
calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
the method comprises the steps of respectively obtaining high-frequency electrical quantity data collected by two intelligent switches, utilizing a fixed current proportion coefficient to synchronously process the high-frequency electrical quantity data, counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the superior-subordinate relation between the two intelligent switches according to the counting result.
Further, the process of obtaining the fixed current proportion coefficient based on the current proportion sequence calculation specifically comprises:
and counting the frequency of each value in the current proportion sequence, and calculating a fixed current proportion coefficient between the two intelligent switches by utilizing normal distribution.
Further, the step of synchronously processing the high-frequency electrical quantity data by using the fixed current proportionality coefficient, counting the magnitude relation between the processed high-frequency electrical quantity data, and determining the superior-subordinate relation between the two intelligent switches according to the statistical result specifically comprises the following steps:
constructing an electrical quantity matrix based on the high-frequency electrical quantity data acquired by the two intelligent switches and the fixed current proportionality coefficient;
normalizing the two constructed electric quantity matrixes;
and comparing the corresponding electrical quantity data in the two electrical quantity matrixes after normalization processing in a size relationship, counting comparison results, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the ratio of the electrical quantity data of the first intelligent switch to the electrical quantity data of the second intelligent switch exceeds a preset threshold value.
Further, the high-frequency electrical quantity data includes voltage U, power P and electric quantity W, and the two constructed electrical quantity matrices are respectively
Wherein the matrix A represents the matrix of the electrical quantities of the intelligent switch i, the matrix B represents the matrix of the electrical quantities of the intelligent switch j,
w ', P ' and U ' represent the actual measured values of the intelligent switch, W i t 、P i t 、
Respectively representing the converted electric quantity value, the converted power value and the converted voltage value of the intelligent switch i at the moment t,
representing a fixed current scaling factor.
Further, the two electrical quantity matrixes after normalization processing are
Wherein the content of the first and second substances,
further, the following contents are included after the electrical quantity matrix normalization processing:
and performing weighted fusion on the three electrical quantity data in the electrical quantity matrix after normalization processing to form an electrical quantity fusion data sequence.
Further, the upper-level and lower-level relation between the two intelligent switches is judged by respectively 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 subjected to weighting fusion is determined based on the judgment accuracy corresponding to each electric quantity data.
In addition, the invention also provides a system for judging the superior-inferior relation of the intelligent switch, which comprises the following steps:
the transient current curve generation module is used for respectively acquiring 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 proportion coefficient calculation module is used for calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
and the data processing module is used for respectively acquiring the high-frequency electrical quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportion coefficient, counting the size relationship between the processed high-frequency electrical quantity data, and judging the superior-inferior relationship between the two intelligent switches according to the counting result.
In addition, the present 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 superior and inferior relation of the intelligent switch, and the computer program executes the steps of the method when running on a computer.
The invention has the following effects:
the method for judging the relationship between the upper level and the lower level of the intelligent switch comprises the steps of firstly respectively acquiring transient current data acquired by two intelligent switches, generating two transient current curves and further generating a current proportion sequence. Then, a fixed current proportion coefficient is obtained by utilizing a statistical mode based on the current proportion sequence calculation, and then the obtained fixed current proportion coefficient is utilized to synchronously process the high-frequency electrical quantity data collected by the two intelligent switches, so that the influence of the metering error of the intelligent switches is effectively eliminated. And finally, counting the magnitude relation between the processed high-frequency electrical quantity data, judging the superior-inferior 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 proportion of the electrical quantity data of the first intelligent switch which is larger than the electrical quantity data of the second intelligent switch exceeds a preset threshold value, so that the superior-inferior 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 superior-subordinate relationship of the intelligent switch also has the advantages.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for determining the relationship between upper and lower stages 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 present invention.
Fig. 3 is a schematic diagram of a current proportion curve generated in a preferred embodiment of the present invention.
Fig. 4 is a diagram illustrating the distribution of the current proportion values in the current proportion sequence according to the preferred embodiment of the present invention.
Fig. 5 is a schematic view of a sub-flow of step S4 in fig. 1.
Fig. 6 is a schematic block diagram of a system for determining a hierarchical relationship between intelligent switches according to another embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be practiced in many different ways, which are defined and covered by the following.
As shown in fig. 1, a preferred embodiment of the present invention provides a method for determining a relationship between an upper level and a lower level of an intelligent switch, including the following steps:
step S1: respectively acquiring transient current data acquired by the two intelligent switches and generating two transient current curves;
step S2: generating a current proportion sequence based on the two transient current curves;
and step S3: calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
and step S4: the method comprises the steps of respectively obtaining high-frequency electrical quantity data collected by two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportion coefficient, counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the superior-inferior relation between the two intelligent switches according to the counting result.
It can be understood that, in the method for determining the relationship between the upper and lower stages of the intelligent switches of this embodiment, the transient current data collected by the two intelligent switches are respectively obtained and two transient current curves are generated, and then a current proportion sequence is generated. Then, a fixed current proportion coefficient is obtained by utilizing a statistical mode based on the current proportion sequence calculation, and then the obtained fixed current proportion coefficient is utilized to synchronously process the high-frequency electrical quantity data collected by the two intelligent switches, so that the influence of the metering error of the intelligent switches is effectively eliminated. And finally, counting the magnitude relation between the processed high-frequency electrical quantity data, judging the superior-inferior 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 proportion of the electrical quantity data of the first intelligent switch which is larger than the electrical quantity data of the second intelligent switch exceeds a preset threshold value, so that the superior-inferior 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 located on the same serial link can be identified through the existing load jump matching algorithm, and the topological relation of the upper and lower branch node switches can be obtained by combining the law of conservation of electric energy. For example, since the upper-level branch node is correspondingly connected to a plurality of lower-level branch nodes at the same time, the electrical quantity data of the intelligent switch at the wire inlet of the upper-level branch node, such as power, voltage, electrical quantity, etc., is significantly greater than the electrical quantity data of all the intelligent switches at the lower-level branch nodes, and for the same branch box, the electrical quantity data of the intelligent switch at the wire inlet is significantly greater than the electrical quantity data of the intelligent switch at each wire outlet. However, for the intelligent switch at a certain outlet of the upper branch box and the intelligent switch at the inlet of the lower 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 be mutually offset or mutually overlapped, so that the upper and lower level relation between the two adjacent intelligent switches cannot be accurately judged. Therefore, the invention focuses on how to identify the superior-inferior relation between two adjacent intelligent switches.
Specifically, in the step S1, since two adjacent intelligent switches belong to a series relationship, in theory, real-time current indications of upper and lower nodes should be the same, but metering errors may cause some difference in metering data. Meanwhile, because the intelligent switches do not have the cycle level data metering capability, only second level data can be obtained, and a certain time offset error exists between the second level data collected by two adjacent intelligent switches. Therefore, the transient current data acquired in the time period from the transient occurrence to the transient end of the two adjacent intelligent switches are acquired, two transient current curves are formed, and then the time synchronization between the two transient current curves is performed based on the transient occurrence time period, as shown in fig. 2, so that the influence of the time offset error can be effectively eliminated. In fig. 2, the horizontal axis represents time, and the vertical axis represents a transient current value.
It can be understood that, in the step S2, it is assumed that the data sequence of the transient current profile of the first intelligent switch is I = [ I ] 1 ，i 2 ，...，i n ]The data sequence of the transient current profile of the second intelligent switch is I '= [ I' 1 ，i′ 2 ，...，i′ n ]Then the current proportion 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 proportion coefficient based on the current proportion sequence specifically includes:
counting the frequency of each value in the current proportion sequence, and calculating the fixed current proportion coefficient between the two intelligent switches by utilizing normal distribution
The distribution of the resulting sequence of current ratios is shown in fig. 4. Wherein the desired value can be selected as a fixed current proportionality factor
Alternatively, the median or average of the interval of values with a frequency ratio of 85% may be selected as the constant current proportionality factor
For example, the interval of values [1.004,1.0057 ] in FIG. 4 was chosen]The median or average value of (a) is taken as the fixed current scaling factor.
It can be understood that the data difference degree between the two intelligent switches is mainly caused by the fact that line impedance between the two intelligent switches has certain partial pressure and energy consumption influence on the premise of not considering the influence of an ammeter, the judgment is carried out by combining long-time electricity statistics, instantaneous voltage and active power at the moment, and W can be known according to the conservation of energy consumption on the line Upper j ＝W Lower i +ε i,j ，U Upper j ＝U Lower i +Ir i,j And P Upper j ＝P Lower i +I 2 r i,j Therefore, under the influence of inaccurate measurement caused by the measurement error of the electric meters without considering the rate and the clock deviation, the upper-level intelligent switch is slightly larger than the lower-level intelligent switch in the electricity consumption W, the power P and the voltage U, and the hierarchical relationship between the two intelligent electric meters can be judged by taking the upper-level intelligent switch as a theoretical basis. However, in an actual environment, the magnitude of 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, so that it is difficult to determine the superior-inferior relation between two adjacent intelligent switches. In the step S4, the present invention obtains the high-frequency electrical quantity data collected by the two intelligent switches, then synchronously processes the high-frequency electrical quantity data by using the fixed current proportionality coefficient, counts the magnitude relation between the processed high-frequency electrical quantity data, and determines the superior-inferior relation between the two intelligent switches according to the statistical result.
As shown in fig. 5, the step of synchronously processing the high-frequency electrical quantity data by using the fixed current proportionality coefficient, and counting the magnitude relation between the processed high-frequency electrical quantity data, and determining the superior-inferior relation between the two intelligent switches according to the statistical result specifically includes:
step S41: constructing an electrical quantity matrix based on the high-frequency electrical quantity data acquired 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, counting comparison results, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the ratio of the electrical quantity data of the first intelligent switch to the electrical quantity data of the second intelligent switch exceeds a preset threshold value.
Specifically, the high-frequency electrical quantity data comprises a voltage U, a power P and an electric quantity W, and two constructed electrical quantity matrixes are respectively
Wherein the matrix A represents the matrix of the electrical quantities of the intelligent switch i, the matrix B represents the matrix of the electrical quantities of the intelligent switch j,
w ', P ' and U ' represent the actual measured values of the intelligent switch, W i t 、P i t 、
And respectively representing the converted electric quantity value, the converted power value and the converted voltage value of the intelligent switch i at the time t. The high-frequency electrical quantity data collected by the two intelligent switches are synchronously processed through the fixed current proportionality coefficient, so that the influence of the metering error of the intelligent switches can be effectively eliminated.
The two electrical quantity matrixes after normalization processing are
Wherein the content of the first and second substances,
Optionally, in the present invention, it is considered that the accuracy of determining the relationship between the upper level and the lower level of the adjacent circuit breakers by using the single electrical quantity data such as voltage, power, and electric quantity cannot achieve high accuracy determination, and therefore, the following contents are included after the electrical quantity matrix normalization processing:
and performing weighted fusion on the three electrical quantity data in the electrical quantity matrix after normalization processing to form an electrical quantity fusion data sequence.
Wherein, the electric quantity fusion data sequence is respectively:
ω 1 、ω 2 and ω 3 Weight coefficients of electric quantity, power and voltage are respectively represented, and judgment is carried out by fusing three kinds of electric quantity data, so that the judgment accuracy is improved.
Specific values of the three weight coefficients can be obtained through calculation according to historical data, specifically, the upper-level and lower-level relations between the two intelligent switches are judged by respectively adopting single electrical quantity data based on the historical data, the judgment accuracy is counted, and the weight coefficients when the three electrical quantity data are subjected to weighted fusion are determined based on the judgment accuracy corresponding to each electrical quantity data. For example, for a certain two adjacent intelligent switches, by using an electric quantity freezing curve at 96 points a day, the accuracy of the relationship between the upper level and the lower level is determined to be 82% by voltage, the accuracy of the relationship between the upper level and the lower level is determined to be 64% by electric quantity, and the accuracy of the relationship between the upper level and the lower level is determined to be 40% by power, when weighting fusion is performed, the weight coefficient of voltage is 82/(82 +64+ 40) =0.441, the weight coefficient of electric quantity is 64/(82 +64+ 40) =0.344, and the weight coefficient of power is 40/(82 +64+ 40) =0.215. Alternatively, 0.82, 0.64, and 0.4 may be directly used as the weighting coefficients of the voltage, the amount of electricity, and the power, respectively.
Finally, comparing the corresponding data items in the two electrical quantity fusion data sequences in a size relationship manner, namely
And
carry out the comparison if
If the ratio of the number of the intelligent switches exceeds 50%, the intelligent switch i is considered to be at the upper level of the intelligent switch j, so that the upper-level and lower-level relations between two adjacent intelligent switches are identified. Of course, in other embodiments of the present invention, the preset threshold may also be set to other values such as 60%, 70%, or 80%, and may be set according to actual needs.
It is understood that in other embodiments of the present invention, one or two types of electrical quantity data may be used for comparison and analysis to determine the relationship between the upper level and the lower level.
In addition, as shown in fig. 6, another embodiment of the present invention further provides a system for determining a hierarchical relationship between a first level and a second level of an intelligent switch, preferably using the method described above, where the system includes:
the transient current curve generation module is used for respectively acquiring 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 proportion coefficient calculation module is used for calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
and the data processing module is used for respectively acquiring the high-frequency electrical quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportion coefficient, counting the size relationship between the processed high-frequency electrical quantity data, and judging the superior-inferior relationship between the two intelligent switches according to the counting result.
It can be understood that, in the system for determining the relationship between the upper and lower stages of the intelligent switch of this embodiment, the transient current data collected by the two intelligent switches are respectively obtained first, and two transient current curves are generated, and then a current proportion sequence is generated. Then, a fixed current proportion coefficient is obtained by utilizing a statistical mode based on the current proportion sequence calculation, and then the obtained fixed current proportion coefficient is utilized to synchronously process the high-frequency electrical quantity data collected by the two intelligent switches, so that the influence of the metering error of the intelligent switches is effectively eliminated. And finally, counting the magnitude relation between the processed high-frequency electrical quantity data, judging the superior-inferior 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 proportion of the electrical quantity data of the first intelligent switch which is larger than the electrical quantity data of the second intelligent switch exceeds a preset threshold value, so that the superior-inferior 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, which includes a processor and a memory, wherein 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 further provides a computer-readable storage medium for storing a computer program for determining a relationship between an upper level and a lower level of an intelligent switch, where the computer program executes the steps of the method when the computer program runs on a computer.
Typical forms of computer-readable storage media include: floppy disk (floppy disk), flexible disk (flexible disk), hard disk, magnetic tape, any of the other magnetic media, CD-ROM, any of the remaining optical media, punch cards (punch cards), paper tape (paper tape), any of the remaining physical media with patterns of holes, random Access Memory (RAM), programmable Read Only Memory (PROM), erasable Programmable Read Only Memory (EPROM), FLASH erasable programmable read only memory (FLASH-EPROM), any of the remaining memory chips or cartridges, or any of the remaining media readable by a computer. The instructions may further be transmitted or received by a transmission medium. The term transmission medium may include any tangible or intangible medium that is operable to store, encode, or carry instructions for execution by the machine, and includes digital or analog communications signals or intangible medium that facilitates communication of the instructions. Transmission media include 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 a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
As will be appreciated by one skilled in the art, 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 scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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 the 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. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the present application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method for judging the superior-inferior relation of an intelligent switch is characterized by comprising the following steps:
respectively acquiring transient current data acquired by the two intelligent switches and generating two transient current curves;
generating a current proportion sequence based on the two transient current curves;
calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
the method comprises the steps of respectively obtaining high-frequency electrical quantity data collected by two intelligent switches, utilizing a fixed current proportion coefficient to synchronously process the high-frequency electrical quantity data, counting the magnitude relation between the processed high-frequency electrical quantity data, and judging the superior-subordinate relation between the two intelligent switches according to the counting result.
2. The method for determining the context of an intelligent switch as claimed in claim 1, wherein the process of calculating the fixed current scaling factor based on the current scaling sequence specifically comprises:
and counting the occurrence frequency of each value in the current proportion sequence, and calculating a fixed current proportion coefficient between the two intelligent switches by utilizing normal distribution.
3. The method for determining the context of the intelligent switches according to claim 1, wherein the step of synchronously processing the high-frequency electrical data with the fixed current scaling factor and counting the magnitude relationship between the processed high-frequency electrical data comprises the steps of:
constructing an electrical quantity matrix based on the high-frequency electrical quantity data acquired by the two intelligent switches and the fixed current proportionality coefficient;
normalizing the two constructed electric quantity matrixes;
and comparing the corresponding electrical quantity data in the two electrical quantity matrixes after normalization processing in a size relationship, counting comparison results, and judging that the first intelligent switch is positioned at the upper level of the second intelligent switch when the ratio of the electrical quantity data of the first intelligent switch to the electrical quantity data of the second intelligent switch exceeds a preset threshold value.
4. The method for determining the relationship between the upper level and the lower level of the intelligent switch as claimed in claim 3, wherein the high frequency electrical quantity data includes voltage U, power P and electric quantity W, and the two electrical quantity matrices are constructed as
Wherein the matrix A represents the matrix of the electrical quantities of the intelligent switch i, the matrix B represents the matrix of the electrical quantities of the intelligent switch j,
w ', P ' and U ' represent the actual measured values of the intelligent switch,
respectively representing the converted electric quantity value, the converted power value and the converted voltage value of the intelligent switch i at the time t,
representing a fixed current scaling factor.
5. The method for determining the relationship between the upper and lower levels of the intelligent switch as claimed in claim 4, wherein the normalized two electrical quantity matrices are
Wherein the content of the first and second substances,
6. the method for determining the relationship between the upper and lower levels of the intelligent switch according to claim 5, wherein the electrical quantity matrix is normalized and then further comprises the following steps:
and performing weighted fusion on the three electrical quantity data in the electrical quantity matrix after normalization processing to form an electrical quantity fusion data sequence.
7. The method for determining the relationship between the upper and lower levels of the intelligent switches according to claim 6, wherein the relationship between the upper and lower levels of the two intelligent switches is determined by using single electrical quantity data based on historical data, the determination accuracy is counted, and the weighting coefficients for weighted fusion of the three electrical quantity data are determined based on the determination accuracy corresponding to each electrical quantity data.
8. The utility model provides a system for judge superordinate and subordinate's relation on intelligence switch which characterized in that includes:
the transient current curve generation module is used for respectively acquiring 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 proportion coefficient calculation module is used for calculating to obtain a fixed current proportion coefficient based on the current proportion sequence;
and the data processing module is used for respectively acquiring the high-frequency electrical quantity data acquired by the two intelligent switches, synchronously processing the high-frequency electrical quantity data by using a fixed current proportion coefficient, counting the size relationship between the processed high-frequency electrical quantity data, and judging the superior-inferior relationship between the two intelligent switches according to the counting result.
9. An electronic device, characterized in that it comprises a processor and a memory, in which a computer program is stored, said processor being adapted to carry out the steps of the method according to any one of claims 1 to 7 by invoking said computer program stored in said memory.
10. A computer-readable storage medium for storing a computer program for determining a relationship between a level and a level 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 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116628454A (en) * | 2023-07-24 | 2023-08-22 | 北京智芯微电子科技有限公司 | Low-voltage distribution network topology identification method and device based on intelligent switch |
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 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116628454A (en) * | 2023-07-24 | 2023-08-22 | 北京智芯微电子科技有限公司 | Low-voltage distribution network topology identification method and device based on intelligent switch |
| CN116628454B (en) * | 2023-07-24 | 2023-12-08 | 北京智芯微电子科技有限公司 | Low-voltage distribution network topology identification method and device based on intelligent switch |
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|---|---|
| CN115494382B (en) | 2024-04-16 |
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