Space-time correlation analysis method for power quality data based on intelligent fusion terminal

Abstract

The application discloses a power quality data space-time correlation analysis method based on an intelligent fusion terminal and relates to the technical field of power quality operation monitoring. The intelligent fusion terminal is networked, and a power grid topology network is constructed according to the distribution positions of the networked intelligent fusion terminals and the power grids monitored by each intelligent fusion terminal. The spatial correlation between each intelligent fusion terminal is determined based on the constructed power grid topology network, and a power quality data time sequence change graph of the intelligent fusion terminal is constructed according to the spatial correlation. The power quality data time sequence change graph is subjected to power quality data feature extraction, and the time correlation between the intelligent fusion terminals is obtained according to the extracted power quality data features. The spatial correlation and the time correlation between the intelligent fusion terminals are used to determine the risk weight of the intelligent fusion terminal in the power grid topology network, so that the monitoring resources can be conveniently allocated, and the monitoring efficiency of the power grid is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of power quality operation monitoring, and particularly relates to a power quality data space-time correlation analysis method based on an intelligent fusion terminal. BACKGROUND

[0002] In a modern power system, power quality problems are increasingly concerned, which are directly related to the normal operation of power equipment and the power experience of users. As a key device for collecting and transmitting power quality data in the power grid, the intelligent fusion terminal is self-evident in importance.

[0003] Traditional power quality analysis methods often only focus on the data of a single terminal, ignoring the space-time correlation between different intelligent fusion terminal data. However, the power grid is a complex network, and the data collected by intelligent fusion terminals at different positions reflects the operation state of different parts of the power grid. Determining the importance difference of different intelligent fusion terminals in the power grid is crucial for accurately evaluating power quality, and therefore, the power quality data space-time correlation analysis method based on the intelligent fusion terminal is provided. SUMMARY

[0004] The application aims to provide a power quality data space-time correlation analysis method based on an intelligent fusion terminal.

[0005] The application can be achieved by the following technical scheme: a power quality data space-time correlation analysis method based on an intelligent fusion terminal, comprising:

[0006] The intelligent fusion terminal is connected to the network, and a power grid topology network is constructed according to the distribution position of the connected intelligent fusion terminal and the power grid monitored by each intelligent fusion terminal;

[0007] The spatial correlation between each intelligent fusion terminal is determined based on the constructed power grid topology network, and a power quality data time sequence change graph of the intelligent fusion terminal is constructed based on the spatial correlation between the intelligent fusion terminals;

[0008] The power quality data time sequence change graph is subjected to power quality data feature extraction, and the time correlation between the intelligent fusion terminals is obtained according to the extracted power quality data features;

[0009] According to the obtained spatial correlation and time correlation between the intelligent fusion terminals, the risk weight of the intelligent fusion terminal in the power grid topology network is determined.

[0010] Further, the process of constructing the power grid topology network comprises:

[0011] After the intelligent fusion terminal completes the network access, a topology node associated with each intelligent fusion terminal is constructed, and the positioning information of the intelligent fusion terminal and the monitored power grid line information are uploaded, wherein the power grid line information includes line number, line specification and electrical parameter information;

[0012] The positioning information uploaded by the intelligent fusion terminal is associated with the corresponding topology node;

[0013] A plane coordinate system is constructed, and the topology nodes are mapped to the corresponding positions in the plane coordinate system according to the positioning information associated with each topology node;

[0014] According to the power grid line monitored by the intelligent fusion terminal associated with each topology node, a corresponding topology link is generated, and the topology link is set with corresponding link attributes according to the power grid line information, so as to complete the construction of the power grid topology graph.

[0015] Further, the process of determining the spatial correlation between the intelligent fusion terminals based on the constructed power grid topology network includes:

[0016] Any intelligent fusion terminal is selected as a reference terminal, and the line transmission distance between the reference terminal and other intelligent fusion terminals is obtained, and is taken as a spatial correlation coefficient.

[0017] Further, the line transmission distance refers to the shortest power grid line distance required between one intelligent fusion terminal and another intelligent fusion terminal, and if one intelligent fusion terminal cannot be transmitted to another intelligent fusion terminal through the power grid line, there is no line transmission distance between the two intelligent fusion terminals.

[0018] Further, the process of constructing the power quality data time sequence change graph of the intelligent fusion terminal according to the spatial correlation includes:

[0019] Obtain each spatial correlation marker in the power grid topology graph, and obtain the power quality data of the corresponding intelligent fusion terminal;

[0020] Construct a time sequence coordinate system with respect to the power quality data;

[0021] According to the power quality data of the two intelligent fusion terminals corresponding to the spatial correlation marker, a corresponding power quality data change curve is generated, and the power quality data change curves of the two intelligent fusion terminals are mapped into the same time sequence coordinate system, to obtain a power quality data time sequence change graph corresponding to the spatial correlation marker.

[0022] Further, the process of extracting the power quality data features from the constructed power quality data time sequence change graph, and obtaining the time correlation between the intelligent fusion terminals according to the extracted power quality data features includes:

[0023] Set a sampling frequency, generate continuous sampling points in the power quality data time sequence change graph according to the set sampling frequency, obtain the sampling parameters corresponding to each sampling point in the power quality data time sequence change graph, and the sampling parameters include the sampling voltage change rate and the sampling current change rate;

[0024] Set a voltage change rate threshold and a current change rate threshold;

[0025] When the absolute value of the voltage change rate exceeds the voltage change rate threshold, or the absolute value of the current change rate exceeds the current change rate threshold;

[0026] The voltage change rate or the current change rate corresponding to the corresponding sampling point is extracted to obtain the corresponding power quality data characteristics;

[0027] According to the line transmission distance between the two topology nodes, set the influence coefficient between the topology nodes, and match the obtained power quality data characteristics between the two topology nodes, and obtain the time correlation coefficient between the two topology nodes corresponding to the intelligent fusion terminal according to the matching result.

[0028] Further, according to the obtained spatial correlation and time correlation between the intelligent fusion terminals, the process of judging the risk weight of the intelligent fusion terminal in the power grid topology network includes:

[0029] Select any intelligent fusion terminal coordinate to be evaluated, obtain other intelligent fusion terminals having spatial correlation and time correlation with the terminal to be evaluated, thereby obtaining the risk weight coefficient of the intelligent fusion terminal, denoted as Fp, wherein:

[0030] ;

[0031] Wherein is the weight coefficient, a1 and a2 are preset coefficients, is the number of other intelligent fusion terminals passed between the line transmission distance between the intelligent fusion terminal with the mark c and the terminal to be evaluated, represents the spatial correlation coefficient between the intelligent fusion terminal with the mark c and the terminal to be evaluated, is the time correlation coefficient between the intelligent fusion terminal with the mark c and the terminal to be evaluated;

[0032] Sort the obtained risk weight coefficients of each intelligent fusion terminal from high to low, and the earlier the sorting is, the higher the weight of the corresponding intelligent fusion terminal in the power grid topology network, that is, the higher the importance of the position monitored by the corresponding intelligent fusion terminal in the power grid topology network.

[0033] Compared with the prior art, the beneficial effects of the present application are:

[0034] By monitoring the power grid position of the intelligent fusion terminal and the line transmission relationship with other intelligent fusion terminals, the spatial correlation between the intelligent fusion terminals is determined, and based on the spatial correlation, the influence on other intelligent fusion terminals when the monitoring position of an intelligent fusion terminal is abnormal is analyzed, so as to obtain the time correlation between the intelligent fusion terminals. According to the spatial correlation and the time correlation between the intelligent fusion terminal and all other intelligent fusion terminals, the importance of the monitoring position of the intelligent fusion terminal in the power grid is obtained, so as to facilitate the allocation of monitoring resources and improve the monitoring efficiency of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0036] Figure 1 The schematic diagram of the present application. DETAILED DESCRIPTION

[0037] As shown in the power quality data space-time correlation analysis method based on the intelligent fusion terminal, comprising: Figure 1

[0038] The intelligent fusion terminal is connected to the network, and the distribution position of the connected intelligent fusion terminal and the power grid monitored by each intelligent fusion terminal are used to construct a power grid topology network;

[0039] Based on the constructed power grid topology network, the spatial correlation between each intelligent fusion terminal is determined, and the power quality data time sequence change graph of the intelligent fusion terminal is constructed based on the spatial correlation between the intelligent fusion terminals;

[0040] The power quality data time sequence change graph is constructed, and the power quality data features are extracted, and the time correlation between the intelligent fusion terminals is obtained according to the extracted power quality data features;

[0041] According to the obtained spatial correlation and time correlation between the intelligent fusion terminals, the risk weight of the intelligent fusion terminal in the power grid topology network is judged.

[0042] It should be further pointed out that in the specific implementation process, the management personnel connects each intelligent fusion terminal to the network, and each intelligent fusion terminal is associated with a unique device number. The management personnel connects the corresponding intelligent fusion terminal to the network through the device number, so that the corresponding intelligent fusion terminal obtains the permission to upload the monitored data.

[0043] ​It needs to be further explained that in the specific implementation process, the process of constructing the power grid topology network according to the distribution position of the intelligent fusion terminal and the power grid monitored by each intelligent fusion terminal includes:

[0044] After the intelligent fusion terminal completes the network access, the topology node associated with each intelligent fusion terminal is constructed, and the positioning information of the intelligent fusion terminal itself and the monitored power grid line information are uploaded, the power grid line information including line number, line specification and electrical parameter information;

[0045] The positioning information uploaded by the intelligent fusion terminal is associated with the corresponding topology node;

[0046] A plane coordinate system is constructed, and the topology node is mapped to the corresponding position in the plane coordinate system according to the positioning information associated with each topology node;

[0047] According to the power grid line monitored by the intelligent fusion terminal associated with each topology node, the corresponding topology link is generated, and the topology link is set with the corresponding link attribute according to the power grid line information, so as to complete the construction of the power grid topology graph.

[0048] It needs to be further explained that in the specific implementation process, the process of determining the spatial correlation between each intelligent fusion terminal based on the constructed power grid topology network includes:

[0049] Any intelligent fusion terminal is selected as a reference terminal, and the line transmission distance between the reference terminal and other intelligent fusion terminals is obtained; it needs to be explained that the line transmission distance refers to the shortest power grid line distance required between one intelligent fusion terminal and another intelligent fusion terminal, if one intelligent fusion terminal cannot be transmitted to another intelligent fusion terminal through the power grid line, then there is no line transmission distance between the two intelligent fusion terminals;

[0050] According to the existing line transmission distance, the corresponding node pair of the reference terminal and other intelligent fusion terminals is obtained, denoted as [K, c], wherein K corresponds to the reference terminal, and c corresponds to other intelligent fusion terminals;

[0051] According to the generated node pair, the corresponding intelligent fusion terminal is marked with spatial correlation in the power grid topology graph;

[0052] The line transmission distance corresponding to each node pair is recorded as , and is taken as the spatial correlation coefficient.

[0053] It needs to be further explained that in the specific implementation process, the process of constructing the intelligent fusion terminal power quality data time sequence change graph according to the spatial correlation includes:

[0054] Obtaining each spatial correlation marker in the power grid topology map, obtaining the power quality data of the corresponding intelligent fusion terminal, the power quality data including voltage rate of change and current rate of change;

[0055] Constructing a time sequence coordinate system of the power quality data;

[0056] Generating a corresponding power quality data change curve according to the power quality data of the two intelligent fusion terminals corresponding to the spatial correlation marker, and mapping the power quality data change curves of the two intelligent fusion terminals into the same time sequence coordinate system to obtain a power quality data time sequence change graph corresponding to the spatial correlation marker.

[0057] It should be further explained that, in the specific implementation process, the process of extracting the power quality data features from the constructed power quality data time sequence change graph and obtaining the time correlation between the intelligent fusion terminals according to the extracted power quality data features includes:

[0058] Setting a sampling frequency, generating continuous sampling points in the power quality data time sequence change graph according to the set sampling frequency, obtaining the sampling parameters corresponding to each sampling point in the power quality data time sequence change graph, the sampling parameters including the sampling voltage rate of change and the sampling current rate of change;

[0059] Setting a voltage rate of change threshold and a current rate of change threshold;

[0060] When the absolute value of the voltage rate of change exceeds the voltage rate of change threshold, or the absolute value of the current rate of change exceeds the current rate of change threshold;

[0061] The voltage rate of change or the current rate of change corresponding to the sampling point is extracted to obtain the corresponding power quality data feature, the power quality data feature corresponding to the reference terminal in the power quality data time sequence change graph is denoted as , and the power quality data feature corresponding to the intelligent fusion terminal is denoted as ; wherein 、 represents the voltage rate of change or the current rate of change, 、 represents the corresponding time;

[0062] Setting an influence coefficient between the topology nodes according to the line transmission distance between the two topology nodes, denoted as ; It should be noted that the influence coefficient is set by the technician according to the line transmission distance, and is inversely related to the length of the line transmission distance;

[0063] The obtained power quality data features and the power quality data features are matched so as to satisfy It should be noted that and For same-dimensional matching, that is, when When corresponding to the rate of change of voltage, then Also the rate of change of voltage. When corresponding to the rate of change of current, then It is also the rate of change of current;

[0064] Acquisition and The closest moment The time difference between the two is obtained and used as the time correlation coefficient between the intelligent fusion terminals corresponding to the two topology nodes.

[0065] It should be noted that in practice, when the power quality data of the power grid location monitored by the smart fusion terminal changes, other locations that are spatially related to the smart fusion terminal will also be affected accordingly. However, this effect is often time-delayed. By using this time delay, the correlation between the power quality data features extracted by different smart fusion terminals can be found, which facilitates the subsequent assessment of the importance of each smart fusion terminal.

[0066] It should be further explained that, in the specific implementation process, the process of determining the risk weight of the intelligent fusion terminal in the power grid topology based on the obtained spatial and temporal correlations between the intelligent fusion terminals includes:

[0067] Select any intelligent fusion terminal coordinates to evaluate the terminal, obtain other intelligent fusion terminals that have spatial and temporal correlation with the terminal to be evaluated, and label each other intelligent fusion terminal as c, where c = 1, 2, ..., n;

[0068] The risk weight coefficient of the intelligent converged terminal is then obtained, denoted as Fp, where:

[0069] ;

[0070] in , These are weighting coefficients, where a1 and a2 are preset coefficients used to eliminate dimensions and level out orders of magnitude. This represents the number of other smart converged terminals that pass between the smart converged terminal labeled c and the terminal to be evaluated along the transmission distance. Let c be the time correlation coefficient between the intelligent fusion terminal and the terminal to be evaluated.

[0071] The risk weight coefficients of the obtained respective intelligent fusion terminals are sorted from high to low, and the earlier the sorting is, the higher the weight of the corresponding intelligent fusion terminal in the power grid topology network is, that is, the higher the importance of the position monitored by the corresponding intelligent fusion terminal in the power grid topology network is;

[0072] By the line transmission relationship between the position monitored by the intelligent fusion terminal and other intelligent fusion terminals, the spatial correlation between the intelligent fusion terminals is determined, and based on the spatial correlation, the influence on other intelligent fusion terminals when the monitoring position of one intelligent fusion terminal is abnormal is analyzed, so as to obtain the time correlation between the intelligent fusion terminals, and the importance of the monitoring position of the intelligent fusion terminal in the power grid is obtained according to the spatial correlation and the time correlation between the intelligent fusion terminal and all other intelligent fusion terminals.

[0073] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the scope of the technical solution of the present application. Any modification or equivalent replacement of the above embodiments based on the technical essence of the present application is still within the scope of the technical solution of the present application.

Claims

1. A method for spatiotemporal correlation analysis of power quality data based on intelligent fusion terminals, characterized in that, include: The smart converged terminals are connected to the network, and a power grid topology is constructed based on the distribution of the connected smart converged terminals and the power grid monitored by each smart converged terminal. Based on the constructed power grid topology, the spatial correlation between each smart fusion terminal is determined, and based on the spatial correlation between the smart fusion terminals, a time-series variation diagram of the power quality data of the smart fusion terminals is constructed. Power quality data features are extracted from the constructed power quality data time series variation map, and the temporal correlation between smart fusion terminals is obtained based on the extracted power quality data features. Based on the spatial and temporal correlations among the intelligent fusion terminals, the risk weights of the intelligent fusion terminals in the power grid topology are determined. The process of determining the spatial correlation between various smart converged terminals based on the constructed power grid topology includes: If any intelligent converged terminal is selected as the reference terminal, the line transmission distance between the reference terminal and other intelligent converged terminals is obtained and used as the spatial correlation coefficient. The line transmission distance refers to the shortest power grid line distance required for one smart fusion terminal to transmit power to another smart fusion terminal. If one smart fusion terminal cannot transmit power to another smart fusion terminal through the power grid line, then there is no line transmission distance between the two smart fusion terminals. The process of extracting power quality data features from the constructed power quality data time-series variation map and obtaining the temporal correlation between smart fusion terminals based on the extracted power quality data features includes: Set the sampling frequency, generate continuous sampling points in the power quality data time series variation graph according to the set sampling frequency, and obtain the sampling parameters corresponding to each sampling point in the power quality data time series variation graph. The sampling parameters include the sampling voltage change rate and the sampling current change rate. Set the voltage change rate threshold and the current change rate threshold; When the absolute value of the voltage change rate exceeds the voltage change rate threshold, or the absolute value of the current change rate exceeds the current change rate threshold; Then the voltage change rate or current change rate corresponding to the corresponding sampling point is extracted to obtain the corresponding power quality data features; Based on the transmission distance between two topology nodes, an influence coefficient between the topology nodes is set, and the power quality data characteristics between the two topology nodes are matched. Based on the matching results, the time correlation coefficient between the smart fusion terminals corresponding to the two topology nodes is obtained.

2. The method for spatiotemporal correlation analysis of power quality data based on intelligent fusion terminals according to claim 1, characterized in that, The process of constructing a power grid topology includes: After the intelligent fusion terminal completes its network access, it constructs a topology node associated with each intelligent fusion terminal and uploads its own location information and the monitored power grid line information, which includes line number, line specifications and electrical parameter information. Associate the location information uploaded by the intelligent fusion terminal with the corresponding topology node; Construct a planar coordinate system and map the topology nodes to their corresponding positions within the planar coordinate system based on the positioning information associated with each topology node. Based on the power grid lines monitored by the intelligent fusion terminals associated with each topology node, corresponding topology links are generated, and corresponding link attributes are set for the topology links according to the power grid line information, thereby completing the construction of the power grid topology map.

3. The method for spatiotemporal correlation analysis of power quality data based on intelligent fusion terminals according to claim 2, characterized in that, The process of constructing a time-series variation map of power quality data for intelligent fusion terminals based on spatial correlation includes: Obtain each spatial correlation marker within the power grid topology map and acquire the power quality data of the corresponding smart fusion terminal; Construct a time-series coordinate system for power quality data; Based on the power quality data of the two smart fusion terminals corresponding to the spatial correlation marker, corresponding power quality data change curves are generated, and the power quality data change curves of the two smart fusion terminals are mapped to the same time-series coordinate system to obtain the time-series change map of power quality data corresponding to the spatial correlation marker.

4. The method for spatiotemporal correlation analysis of power quality data based on intelligent fusion terminals according to claim 3, characterized in that, The process of determining the risk weight of intelligent fusion terminals in the power grid topology based on the obtained spatial and temporal correlations among intelligent fusion terminals includes: Select any intelligent fusion terminal coordinate to be evaluated, and obtain other intelligent fusion terminals that have spatial and temporal correlation with the terminal to be evaluated. This yields the risk weight coefficient of the intelligent fusion terminal, denoted as Fp, where: ； in , These are the weighting coefficients, where a1 and a2 are preset coefficients. This represents the number of other smart converged terminals that pass between the smart converged terminal labeled c and the terminal to be evaluated along the transmission distance. This represents the spatial correlation coefficient between the intelligent fusion terminal labeled c and the terminal to be evaluated. Let c be the time correlation coefficient between the intelligent fusion terminal and the terminal to be evaluated. The risk weight coefficients of each smart fusion terminal are sorted from high to low. The higher the ranking, the higher the weight of the corresponding smart fusion terminal in the power grid topology, that is, the higher the importance of the location monitored by the corresponding smart fusion terminal in the power grid topology.

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