A distribution network information automatic collection system and method

Abstract

The present invention relates to the technical field of data acquisition and recording, and specifically to a distribution network information automatic acquisition system and method; a load characteristic curve is acquired according to the position characteristics of the upper envelope and the lower envelope of the initial curve of the load data; different load intervals are acquired according to the data change characteristics of the load characteristic curve; a difference characteristic value is acquired according to the data difference characteristics between the upper envelope and the lower envelope at the same time; and an acquisition frequency index of the load interval is acquired according to the data distribution characteristics of the difference characteristic value of the time period where the load interval is located and the data fluctuation characteristics of the load interval. The present invention performs adaptive data acquisition on the initial curve of the load data according to the acquisition frequency index to obtain a load data sampling sequence of the distribution network; and can reduce the data acquisition storage amount without reducing the accuracy of load data analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of data acquisition and recording, and in particular to a distribution network information automatic acquisition system and method. Background Art

[0002] The collection and monitoring of load data in the distribution network is of great significance to ensure the efficient operation and safety of the power grid. Monitoring load data can help technicians adjust the load distribution of different equipment in the power grid, ensure that the equipment operates within a safe range, reduce the risk of equipment damage, and extend the service life of the equipment. Load data needs to be collected before data monitoring and analysis. In the traditional way, a fixed collection frequency needs to be set for the collection of load data, and the collected data needs to be stored in the data analysis module for analysis. However, due to the complexity and large volume of load data, direct storage will result in a large amount of data, making it difficult to quickly determine abnormal load fluctuation data, and at the same time causing too much storage space to be occupied; if all load data are downsampled to reduce the amount of collected data, the load fluctuation characteristics cannot be accurately analyzed, resulting in inaccurate monitoring and analysis results, affecting the stability and safety of the distribution network operation. Summary of the invention

[0003] In order to solve the problems in the background technology, the purpose of the present invention is to provide a distribution network information automatic collection system and method, and the technical solutions adopted are as follows:

[0004] Obtaining the initial curve of load data of the distribution network;

[0005] Constructing an upper envelope and a lower envelope of the initial curve of the load data; obtaining a load characteristic curve according to positional characteristics of the upper envelope and the lower envelope;

[0006] Obtaining a division base point according to the data change characteristics of the load characteristic curve; dividing the load characteristic curve according to the division base point to obtain different load interval segments; obtaining a difference characteristic value according to the data difference characteristics between the upper envelope and the lower envelope at the same time; obtaining a first load fluctuation characteristic value according to the data distribution characteristics of the difference characteristic value in the time period where the load interval segment is located; obtaining a second load fluctuation characteristic value according to the data fluctuation characteristics of the load interval segment;

[0007] A collection frequency index of a load interval is obtained according to the first load fluctuation characteristic value and the second load fluctuation characteristic value; data is collected on an initial curve of load data according to the collection frequency index to obtain a load data sampling sequence of the distribution network.

[0008] Furthermore, the step of acquiring a load characteristic curve according to the position characteristics of the upper envelope and the lower envelope comprises:

[0009] The numerical average values ​​of the upper envelope and the lower envelope at the same time are calculated to obtain the load characteristic value; and the load characteristic curve is constructed according to the load characteristic value corresponding to each moment in the initial curve of the load data.

[0010] Furthermore, the step of obtaining a division base point according to the data change characteristics of the load characteristic curve includes:

[0011] The data points whose first-order derivative values ​​in the load characteristic curve are constant 0 are calculated to obtain screening points; the ratio of the first-order derivative values ​​of two adjacent data points of the screening point is calculated to obtain the change characteristic value of the screening point; and the screening point whose change characteristic value is negative is used as the division base point.

[0012] Furthermore, the step of dividing the load characteristic curve according to the division base point to obtain different load interval segments includes:

[0013] The load characteristic curve is divided at the position of the division base point to obtain different load interval segments.

[0014] Further, the step of obtaining a difference feature value according to the data difference feature between the upper envelope and the lower envelope at the same time comprises:

[0015] The numerical difference between the upper envelope and the lower envelope at any time is calculated to obtain the difference characteristic value at the any time.

[0016] Furthermore, the step of obtaining the first load fluctuation characteristic value according to the data distribution characteristics of the difference characteristic value in the time period where the load interval segment is located includes:

[0017] Calculate the average value of the difference characteristic value in the time period where the load interval segment is located and normalize it to obtain the difference factor of the load interval segment; calculate the variance of the difference characteristic value in the time period where the load interval segment is located and normalize it to obtain the change factor of the load interval segment; calculate the product of the difference factor and a preset first coefficient to obtain the difference weight; calculate the product of the change factor and a preset second coefficient to obtain the change weight; calculate the sum of the difference weight and the change weight to obtain the first load fluctuation characteristic value of the load interval segment.

[0018] Furthermore, the step of obtaining a second load fluctuation characteristic value according to the data fluctuation characteristic of the load interval segment includes:

[0019] The average value of the absolute value of the slope between the data point in the load interval and the adjacent previous data point is calculated and normalized to obtain a second load fluctuation characteristic value.

[0020] Further, the step of obtaining a collection frequency index of a load interval according to the first load fluctuation characteristic value and the second load fluctuation characteristic value comprises:

[0021] Calculate the product of the first load fluctuation characteristic value and the preset first weight to obtain the first fluctuation weight; calculate the product of the second load fluctuation characteristic value and the preset second weight to obtain the second fluctuation weight; calculate the sum of the first fluctuation weight and the second fluctuation weight to obtain the collection frequency index of the load interval segment.

[0022] Furthermore, the step of collecting data on the initial curve of the load data according to the collection frequency index to obtain a load data sampling sequence of the distribution network includes:

[0023] The larger the acquisition frequency index is, the higher the data acquisition frequency of the initial curve of load data corresponding to the load interval segment is; the data points collected in the initial curve of load data corresponding to all load interval segments are sorted in chronological order to obtain the load data sampling sequence.

[0024] The present invention also proposes a distribution network information automatic collection system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the steps of a distribution network information automatic collection method.

[0025] The present invention has the following beneficial effects:

[0026] In the present invention, the load characteristic curve obtained according to the upper envelope and the lower envelope can more clearly characterize the load change characteristics of the initial curve of the load data, remove the slight fluctuations of the load data, and make the segmentation result more accurate. Obtaining the division base point can accurately divide the load characteristic curve, improve the accuracy of the segmentation, and make the load change characteristics after segmentation similar; obtaining the load interval segment can adaptively obtain the acquisition frequency according to the data characteristics of each interval segment, and improve the accuracy of the acquisition frequency. Obtaining the difference characteristic value can characterize the degree of change of the load characteristic; obtaining the first load fluctuation characteristic value can accurately characterize the degree of load change fluctuation according to the difference characteristic value obtained by the envelope, and obtaining the second load fluctuation characteristic value can characterize the degree of load change fluctuation according to the data fluctuation characteristics of the load interval segment; according to the first load fluctuation characteristic value and the second load fluctuation characteristic value, the acquisition frequency index of the load interval segment can be accurately determined; according to the acquisition frequency index, the initial curve of the load data is collected to obtain the load data sampling sequence, which can reduce the data acquisition storage amount without reducing the accuracy of the load data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 A flow chart of a method for automatic collection of distribution network information provided by an embodiment of the present invention;

[0029] Figure 2 A schematic diagram of an envelope provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the distribution network information automatic collection system and method proposed by the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0031] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0032] The specific scheme of the automatic distribution network information collection system and method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0033] See also Figure 1 , which shows a flow chart of a method for automatic collection of distribution network information provided by an embodiment of the present invention, the method comprising the following steps:

[0034] Step S1, obtaining an initial curve of load data of the distribution network.

[0035] In an embodiment of the present invention, the implementation scenario is to adaptively collect load data of equipment in the distribution network, thereby reducing the amount of data collection and storage without reducing the accuracy of load data analysis. First, the initial curve of load data of the distribution network is obtained. There are equipment such as substations and distribution boxes in the distribution network. For any equipment, characteristic objects that can reflect the load, such as voltage, current, and power, are collected. In an embodiment of the present invention, the initial curve of load data is constructed with the power data at a distribution box node in the distribution network; the horizontal axis of the curve is the different moments of data collection, and the vertical axis is the power value. The power data at adjacent moments are connected to obtain the initial curve of load data. It should be noted that the acquisition frequency of the initial curve of load data is based on the rated acquisition frequency of the acquisition sensor, and the load data at each moment can be acquired in detail.

[0036] Step S2, constructing an upper envelope and a lower envelope of the initial curve of the load data; and obtaining a load characteristic curve according to the position characteristics of the upper envelope and the lower envelope.

[0037] Due to the large number of device nodes in the distribution network, the load data collection frequency of each device node is high, resulting in too much data storage during the analysis and monitoring process, and the analysis process is more complicated; if the overall data collection frequency is reduced by downsampling, it is easy to cause some load abnormalities to not be collected and recorded, affecting the accuracy of load monitoring. Therefore, in order to reduce the amount of data collection and storage without reducing the accuracy of load data analysis, it is necessary to perform adaptive collection and processing on load data. During the normal operation of the distribution network, the load data is relatively stable; when the load data changes or fluctuates significantly, it is necessary to focus on analyzing the reasons for the change or fluctuation of the load data, and use a higher collection frequency during the period when such situations occur, so as to analyze and regulate the operation status of the device node based on more intensive load data; when the load data is relatively stable, it means that the device node is operating normally, and a lower collection frequency can be used to record the load data to reduce the amount of data collection and storage. Therefore, according to the characteristics of the initial curve of the load data, a higher collection frequency is used in the period when the load characteristics change more complexly, and a lower collection frequency is used in the period when the load characteristics are relatively stable.

[0038] In order to collect load data using an adaptive collection frequency, it is necessary to segment the initial curve of the load data and divide the intervals with similar load characteristic change trends into different intervals, so as to use different collection frequencies for different intervals. Because the load values ​​in the initial curve of the load data will also have slight changes under normal circumstances, if the initial curve of the load data is segmented directly, the segmentation will be inaccurate due to slight changes in the load data. Therefore, the initial curve of the load data needs to be further processed to improve the accuracy of the segmentation. First, construct the upper envelope and lower envelope of the initial curve of the load data, such as Figure 2The solid line in the envelope diagram represents the initial curve of the load data, the long dashed line above the solid line is the upper envelope, and the short dashed line below is the lower envelope; it should be noted that the acquisition of the upper envelope and the lower envelope belongs to the prior art, and the specific steps are not repeated here. The upper envelope and the lower envelope are constructed according to the maximum and minimum points of the initial curve of the load data, respectively, and the upper envelope and the lower envelope can reflect the overall change trend of the load data. In order to quickly and accurately obtain the fluctuation change characteristics of the load data, the load characteristic curve can be obtained according to the position characteristics of the upper envelope and the lower envelope.

[0039] Preferably, in one embodiment of the present invention, the step of obtaining the load characteristic curve includes: calculating the numerical average of the upper envelope and the lower envelope at the same time to obtain the load characteristic value; the load characteristic value reflects the average level of the numerical values ​​of the upper envelope and the lower envelope at the same time. The load characteristic curve is constructed according to the load characteristic value corresponding to each moment in the initial curve of the load data. The load characteristic curve is smoother than the initial curve of the load data, but the overall load change trend will not change, so it is faster and more accurate to segment the load characteristic change of the load characteristic curve.

[0040] Step S3, obtaining a division base point according to the data change characteristics of the load characteristic curve; dividing the load characteristic curve according to the division base point to obtain different load interval segments; obtaining a difference characteristic value according to the data difference characteristics between the upper envelope and the lower envelope at the same time; obtaining a first load fluctuation characteristic value according to the data distribution characteristics of the difference characteristic value of the time period in which the load interval segment is located; obtaining a second load fluctuation characteristic value according to the data fluctuation characteristics of the load interval segment.

[0041] The load characteristic curve has the same overall change characteristics as the initial curve of the load data, but the load characteristic curve removes the slight fluctuations, so that segmenting the load characteristic curve can greatly improve the accuracy and efficiency of the segmentation. Therefore, the division base point is obtained according to the data change characteristics of the load characteristic curve. Preferably, in the embodiment of the present invention, the step of obtaining the division base point includes: calculating the data point whose first-order derivative value is a constant of 0 in the load characteristic curve to obtain the screening point; calculating the ratio of the first-order derivative values ​​of the two adjacent data points of the screening point to obtain the change characteristic value of the screening point; taking the screening point whose change characteristic value is a negative number as the division base point. When the screening point satisfies the first-order derivative value of the constant 0 and the positive and negative first-order derivative values ​​of the adjacent front and rear data points are different, it means that the screening point is the inflection point of the load characteristic curve, and the change trend of the load characteristic curve at the inflection point has changed, so the screening point is used as the division base point. Then, the load characteristic curve is divided according to the division base point to obtain different load interval segments, which specifically includes: dividing the load characteristic curve at the position of the division base point to obtain different load interval segments; in the embodiment of the present invention, each division base point is divided to the last data point of the corresponding load interval segment.

[0042] Furthermore, after determining different load intervals, the acquisition frequency corresponding to each load interval can be analyzed. When the interval between the upper envelope and the lower envelope corresponding to the load interval is larger, it means that the load fluctuation of the initial curve of the load data in the load interval is more obvious; when the interval between the upper envelope and the lower envelope changes more, it means that the load characteristic change of the initial curve of the load data is more complex. Therefore, the difference characteristic value is obtained according to the data difference characteristics between the upper envelope and the lower envelope at the same time. Preferably, in an embodiment of the present invention, the step of obtaining the difference characteristic value includes: calculating the numerical difference between the upper envelope and the lower envelope at any time, and obtaining the difference characteristic value at any time; when the difference characteristic value is larger, it means that the interval between the upper envelope and the lower envelope at any time is larger. Then, the first load fluctuation characteristic value is obtained according to the data distribution characteristics of the difference characteristic value of the time period in which the load interval is located.

[0043] Preferably, in the embodiment of the present invention, the step of obtaining the first load fluctuation characteristic value includes: calculating the average value of the difference characteristic value of the time period where the load interval segment is located and normalizing it to obtain the difference factor of the load interval segment; when the difference factor is larger, it means that the overall interval between the upper envelope and the lower envelope of the time period corresponding to the load interval segment is larger, the load change of the corresponding load data initial curve is more obvious, and the more emphasis is needed on analyzing the time period during the monitoring process, the greater the acquisition frequency needs to be, and the data density representing the obvious change of the load characteristic is improved. Calculate the variance of the difference characteristic value of the time period where the load interval segment is located and normalize it to obtain the change factor of the load interval segment; when the change factor is larger, it means that the load data change of the time period is more complex, and the more emphasis is needed on analyzing the time period during the monitoring process, the greater the acquisition frequency needs to be, and the data density representing the complex change of the load characteristic is improved. Calculate the product of the difference factor and the preset first coefficient to obtain the difference weight; calculate the product of the change factor and the preset second coefficient to obtain the change weight; in the embodiment of the present invention, the preset first coefficient is 0.4, and the preset second coefficient is 0.6, which can be determined by the implementer according to the implementation scenario. The sum of the difference weight and the change weight is calculated to obtain the first load fluctuation characteristic value of the load interval segment; the larger the value of the first load fluctuation characteristic value is, the more obvious and complex the load characteristic fluctuation corresponding to the period is.

[0044] Furthermore, when the data fluctuation in the load interval segment is stronger, it means that the degree of load characteristic fluctuation is greater, so the second load fluctuation characteristic value is obtained according to the data fluctuation characteristics of the load interval segment; preferably, in an embodiment of the present invention, the step of obtaining the second load fluctuation characteristic value includes: calculating the average value of the absolute value of the slope of the data point in the load interval segment and the adjacent previous data point and normalizing it to obtain the second load fluctuation characteristic value; when the absolute value of the slope is larger, it means that the amplitude of data change is larger, and when the average value of the absolute value of the slope is larger, the second load fluctuation characteristic value is larger, the greater the degree of load characteristic fluctuation is, the more emphasis needs to be placed on analyzing this period during the monitoring process, and the greater the acquisition frequency needs to be.

[0045] Step S4, obtaining a collection frequency index of the load interval according to the first load fluctuation characteristic value and the second load fluctuation characteristic value; collecting data on the load data initial curve according to the collection frequency index to obtain a load data sampling sequence of the distribution network.

[0046] Then, the collection frequency index of the load interval segment is obtained according to the first load fluctuation characteristic value and the second load fluctuation characteristic value. Preferably, in the embodiment of the present invention, the step of obtaining the collection frequency index includes: calculating the product of the first load fluctuation characteristic value and the preset first weight to obtain the first fluctuation weight; calculating the product of the second load fluctuation characteristic value and the preset second weight to obtain the second fluctuation weight; in the embodiment of the present invention, the preset first weight and the preset second weight are 0.5 respectively, and the implementer can determine it according to the implementation scenario. Calculate the sum of the first fluctuation weight and the second fluctuation weight to obtain the collection frequency index of the load interval segment; when the collection frequency index is larger, it means that the load characteristic changes corresponding to the load interval segment are more obvious and complex. In order to improve the monitoring accuracy, it is necessary to increase the collection frequency of load data in this period. The formula for obtaining the collection frequency index includes:

[0047]

[0048] Where R represents the acquisition frequency index of the load interval segment, Indicates the preset first weight, Indicates the preset second weight, Indicates the preset first coefficient, Indicates the preset second coefficient, represents the normalization function, B represents the number of data points in the load interval, represents the difference eigenvalue corresponding to the moment of the b-th data point, represents the difference factor, represents the difference weight, S represents the change factor, represents the change weight, represents the first load fluctuation characteristic value; It represents the absolute value of the slope between the bth data point and the adjacent previous data point. represents the second load fluctuation characteristic value, represents the second volatility weight, Represents the first volatility weight.

[0049] Further, the initial curve of the load data is collected according to the collection frequency index to obtain the load data sampling sequence of the distribution network. Preferably, in the embodiment of the present invention, the step of obtaining the load data sampling sequence includes: the larger the collection frequency index, the higher the data collection frequency of the initial curve of the load data corresponding to the load interval segment. In the embodiment of the present invention, for the initial curve of the load data corresponding to the load interval segment with a collection frequency index exceeding 0.7, the collection frequency is set to once per second; for the initial curve of the load data corresponding to the load interval segment with a collection frequency index not exceeding 0.7 and not less than 0.4, the collection frequency is set to once every 3 seconds; for the initial curve of the load data corresponding to the load interval segment with a collection frequency index less than 0.4, the collection frequency is set to once every 15 seconds; the implementer can determine the collection frequency of the corresponding time period of different load interval segments according to the implementation scenario. The data points collected in the initial curve of the load data corresponding to all load interval segments are sorted in chronological order to obtain the load data sampling sequence, and then monitoring and analysis are performed according to the load data sampling sequence. The embodiment of the present invention analyzes the fluctuation change characteristics of the initial curve of the load data, and performs adaptive collection of load data, while reducing the data collection storage amount without reducing the accuracy of load data analysis.

[0050] In summary, the embodiment of the present invention provides a method for automatic collection of distribution network information; a load characteristic curve is obtained according to the position characteristics of the upper envelope and the lower envelope of the initial curve of the load data; different load intervals are obtained according to the data change characteristics of the load characteristic curve; a difference characteristic value is obtained according to the data difference characteristics between the upper envelope and the lower envelope at the same time; and a collection frequency index of the load interval is obtained according to the data distribution characteristics of the difference characteristic value of the time period in which the load interval is located and the data fluctuation characteristics of the load interval. The present invention performs adaptive data collection on the initial curve of the load data according to the collection frequency index to obtain a load data sampling sequence of the distribution network; while not reducing the accuracy of load data analysis, the data collection storage volume is reduced.

[0051] The present invention also proposes a distribution network information automatic collection system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement any one of the steps of a distribution network information automatic collection method.

[0052] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for automatic collection of distribution network information, characterized in that: The method comprises the following steps: Obtaining the initial curve of load data of the distribution network; Constructing an upper envelope and a lower envelope of the initial curve of the load data; obtaining a load characteristic curve according to positional characteristics of the upper envelope and the lower envelope; Obtaining a division base point according to the data change characteristics of the load characteristic curve; dividing the load characteristic curve according to the division base point to obtain different load interval segments; obtaining a difference characteristic value according to the data difference characteristics between the upper envelope and the lower envelope at the same time; obtaining a first load fluctuation characteristic value according to the data distribution characteristics of the difference characteristic value in the time period where the load interval segment is located; obtaining a second load fluctuation characteristic value according to the data fluctuation characteristics of the load interval segment; Obtaining a collection frequency index of a load interval according to the first load fluctuation characteristic value and the second load fluctuation characteristic value; performing data collection on an initial curve of load data according to the collection frequency index to obtain a load data sampling sequence of a distribution network; The step of obtaining the first load fluctuation characteristic value according to the data distribution characteristics of the difference characteristic value in the time period where the load interval segment is located comprises: Calculate the average value of the difference characteristic value in the time period where the load interval segment is located and normalize it to obtain the difference factor of the load interval segment; calculate the variance of the difference characteristic value in the time period where the load interval segment is located and normalize it to obtain the change factor of the load interval segment; calculate the product of the difference factor and a preset first coefficient to obtain the difference weight; calculate the product of the change factor and a preset second coefficient to obtain the change weight; calculate the sum of the difference weight and the change weight to obtain the first load fluctuation characteristic value of the load interval segment; The step of obtaining a second load fluctuation characteristic value according to the data fluctuation characteristic of the load interval segment comprises: The average value of the absolute value of the slope between the data point in the load interval and the adjacent previous data point is calculated and normalized to obtain a second load fluctuation characteristic value.

2. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of acquiring a load characteristic curve according to the position characteristics of the upper envelope and the lower envelope comprises: The numerical average values ​​of the upper envelope and the lower envelope at the same time are calculated to obtain the load characteristic value; and the load characteristic curve is constructed according to the load characteristic value corresponding to each moment in the initial curve of the load data.

3. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of obtaining a division base point according to the data change characteristics of the load characteristic curve comprises: The data points whose first-order derivative values ​​in the load characteristic curve are constant 0 are calculated to obtain screening points; the ratio of the first-order derivative values ​​of two adjacent data points of the screening point is calculated to obtain the change characteristic value of the screening point; and the screening point whose change characteristic value is negative is used as the division base point.

4. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of dividing the load characteristic curve according to the division base point to obtain different load interval segments comprises: The load characteristic curve is divided at the position of the division base point to obtain different load interval segments.

5. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of obtaining a difference characteristic value according to the data difference characteristics between the upper envelope and the lower envelope at the same time comprises: The numerical difference between the upper envelope and the lower envelope at any time is calculated to obtain the difference characteristic value at the any time.

6. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of obtaining the acquisition frequency index of the load interval according to the first load fluctuation characteristic value and the second load fluctuation characteristic value comprises: Calculate the product of the first load fluctuation characteristic value and the preset first weight to obtain the first fluctuation weight; calculate the product of the second load fluctuation characteristic value and the preset second weight to obtain the second fluctuation weight; calculate the sum of the first fluctuation weight and the second fluctuation weight to obtain the collection frequency index of the load interval segment.

7. A method for automatic collection of distribution network information according to claim 1, characterized in that: The step of collecting data on the initial curve of the load data according to the collection frequency index to obtain a load data sampling sequence of the distribution network comprises: The larger the acquisition frequency index is, the higher the data acquisition frequency of the initial curve of load data corresponding to the load interval segment is; the data points collected in the initial curve of load data corresponding to all load interval segments are sorted in chronological order to obtain the load data sampling sequence.

8. A distribution network information automatic collection system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

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