Data transmission method and system for power grid dispatching data network

Abstract

The invention relates to the field of digital information transmission, in particular to a data transmission method and system for a power grid dispatching data network, and the method comprises the steps: obtaining the current and voltage in the power grid dispatching data, and determining the local range of each data point; performing curve fitting on the current data and the voltage data in the local range by using a least square method, and obtaining a noise expression degree of each data point in the power grid dispatching data according to a fitting result; calculating the area enclosed by adjacent data points in the local range, and calculating the credibility of the data points by using an exponential function in combination with the area standard deviation and the noise expression degree; and based on the credibility correction Fisher optimal solution algorithm, clustering the power grid dispatching data, and transmitting the power grid dispatching data according to a clustering result. According to the method, the credibility of each data point is introduced, so that the influence of noise on a clustering result is reduced, and the accuracy and reliability of data transmission are improved.

Description

Technical Field

[0001] The present invention relates to the field of digital information transmission. More specifically, the present invention relates to a data transmission method and system for a power grid dispatching data network. Background Art

[0002] Power grid dispatching data mainly relies on dedicated communication lines or private networks for transmission, such as telephone lines, power line carrier communication, etc. These traditional transmission methods have problems such as slow transmission speed, limited transmission capacity, high cost, and low security, and it is difficult to meet the requirements of modern power systems for efficient and secure transmission. With the development of information technology and the intelligent requirements of power systems, modern power grid dispatching data network transmission technologies have emerged, such as wireless communication technology, etc. They have advantages such as fast transmission speed, large capacity, low cost, and high security. These transmission technologies need to divide power grid dispatching data into many data packets to improve the data transmission efficiency.

[0003] The existing Chinese patent application document with the publication number CN117596273A discloses a data transmission method and system between power grid dispatching systems. Its method is that the sending end respectively sends the power grid common information model and the power grid measurement information point table, and performs inter-group data redundancy grouping processing on the data point numbers in units of substations to form the grouped power grid measurement information point table and send it to the receiving end, realizing the redundancy mutual backup of the data point numbers of each substation between different groups, avoiding the easy omission of data during data communication, and improving the reliability of data transmission between the receiving end and the sending end. The sending end groups the power grid measurement data to be transmitted in units of substations and forms multiple data blocks from multiple groups.

[0004] This application document parallelly parses multiple data blocks through the receiving end, performs data matching of the measurement point information in the information index table, and updates the measurement data of the measurement points, thereby improving the efficiency of data transmission and matching. Currently, the Fisher optimal solution method is a method for clustering ordered samples. It does not allow breaking the order of samples during the classification process, that is, power grid data can be divided into multiple segments with relatively high similarity, and each segment is transmitted as an independent data packet, reducing the redundant information between data packets and improving the compactness and efficiency of data transmission. However, the power grid working environment is complex, and the data is affected by more noise. These noises will affect the clustering process of the Fisher optimal solution method. Because this method finds the optimal segmentation point by minimizing the loss function, the noise may cause the minimum loss function to increase, thereby affecting the division and transmission efficiency of data packets. Summary of the Invention

[0005] To solve the problem that the power grid working environment is complex, the data is affected by more noise, which leads to the noise affecting the clustering process of Fisher's optimal solution method, thus affecting the division and transmission efficiency of data packets, the present invention provides solutions in the following aspects.

[0006] In the first aspect, a data transmission method for a power grid dispatching data network includes: obtaining power grid dispatching data, where the power grid dispatching data includes current and voltage. Taking each data point in the power grid dispatching data as the center point, a preset number of data points are set on both the left and right sides to determine the local range; using the least squares method to perform curve fitting on the current data and voltage data within the local range respectively, and obtaining the noise performance degree of each data point in the power grid dispatching data according to the difference between the fitting result and the actual value; calculating the area enclosed between adjacent data points within the local range, and using an exponential function to calculate the product of the standard deviation of the area set between adjacent two data points within the local range and the noise performance degree of the corresponding data point to obtain the credibility of each data point; correcting the Fisher optimal solution algorithm based on the credibility, clustering the power grid dispatching data according to the corrected Fisher optimal solution algorithm, and transmitting the power grid dispatching data according to the clustering result.

[0007] The effect is that: by performing least squares curve fitting on the current and voltage data within the local range, the noise performance degree of each data point can be quantified. This method can identify the data points that deviate greatly from the fitting curve, so as to evaluate the degree of their being affected by noise; by calculating the area enclosed between adjacent data points within the local range and combining the noise performance degree, using an exponential function to calculate the credibility of each data point, which helps to distinguish high-quality and low-quality data points in subsequent processing. Based on the credibility of the data points, the Fisher optimal solution algorithm is corrected. This method reduces the influence of noise data points on the clustering result and improves the accuracy and efficiency of clustering.

[0008] Preferably, the performing curve fitting on the current data and voltage data within the local range respectively includes: Taking the time series serial number of the data point within the local range as the abscissa and the current or voltage value of the data point as the ordinate, and fitting the current curve and voltage curve respectively.

[0009] Preferably, obtaining the noise performance degree includes: Calculating the average of the absolute differences between the fitting values and the actual values of the current and voltage within the local range respectively, performing normalization processing, and taking the sum average as the noise performance of each data point within the local range.

[0010] The effects are as follows: By identifying data points with a relatively high degree of noise manifestation, these data points can be further analyzed or cleaned, thereby improving the quality of the overall data set. During data transmission, the impact of noisy data points is reduced, and the efficiency and reliability of data transmission are improved. This helps reduce the number of data packets and lower the transmission error rate.

[0011] Preferably, obtaining the degree of noise manifestation further includes: Calculating the difference between the actual value and the moving average of data points within a local range, dividing the difference by the moving average, and performing a square operation to obtain the squared deviation of each data point. Summing up the squared deviations of all data points and dividing by the number of data points within the local range to obtain the degree of noise manifestation of each data point.

[0012] The effects are as follows: By dividing the difference by the moving average, data in different ranges can be standardized for comparison. Through the square operation, the impact of larger deviations is amplified, making these deviations more prominent in subsequent analyses, which helps identify outliers or noisy data points.

[0013] Preferably, calculating the area enclosed between adjacent data points within the local range includes: Taking any data point within the local range as the marked midpoint, calculating the vertical distance between the current fitting curve and the voltage fitting curve of the marked points, and obtaining the area enclosed by the current fitting curve and the voltage fitting curve between all adjacent data points within the local range.

[0014] The effects are as follows: Calculating the vertical distance between the current and voltage fitting curves can evaluate the consistency of data points within the local range. If the trends of current and voltage changes are consistent, the distance between these two curves should be small, indicating a high degree of consistency between data points. If at certain data points, the distance between the current and voltage fitting curves is abnormally large, this may indicate that these points are outliers or affected by noise.

[0015] Preferably, calculating the area enclosed between adjacent data points within the local range further includes: Calculating the sum of the differences between the current and voltage fitting values between adjacent data points within the local range to obtain the total sum of the current and voltage differences between two adjacent data points, and using the trapezoidal rule formula to obtain the area between adjacent data points.

[0016] The effects are as follows: Through the trapezoidal rule, it can be used to approximately calculate the area under the current and voltage fitting curves between two adjacent data points. It is easier to calculate compared to integration, especially for complex functions, simplifies the calculation process, makes the calculation faster and more practical, especially when dealing with a large number of data points, which helps improve the efficiency of the entire data analysis process.

[0017] Preferably, the correction process satisfies the following relational expression: ; In the formula, represents the method of dividing ordered samples into categories in the Fisher optimal solution method process, represents the number of data points in the th clustering cluster, represents the mean coordinate of the th clustering cluster, represents the data of the th data point in the th clustering cluster, represents the credibility of the th data point in the

[0018] In a second aspect, a data transmission system for a power grid dispatching data network includes: a processor and a memory, where the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data transmission method for the power grid dispatching data network described above is implemented.

[0019] The present invention has the following effects: 1. By introducing the credibility of each data point, the present invention improves the loss function of the Fisher optimal solution method when processing power grid dispatching data, reduces the influence of noise on the clustering result, and makes the clustering result more accurate. The accurate clustering result helps to better understand the operation state of the power grid, optimize the dispatching strategy of the power grid, and improve the operation efficiency of the power grid.

[0020] 2. By identifying and processing noise data points, the present invention improves the quality of the overall power grid dispatching data. During the data transmission process, low-quality data points may lead to incorrect or inaccurate decisions. By reducing the influence of noise data points, the accuracy and reliability of the data can be improved, thereby improving the efficiency and security of power grid dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] By referring to the drawings and reading the following detailed description, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become easily understandable. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, where: Figure 1 is the flowchart of the method from step S1 to step S4 in the data transmission method for the power grid dispatching data network according to the embodiment of the present invention.

[0022] Figure 2It is a structural block diagram of the data transmission system for the power grid dispatching data network in the embodiments of the present invention. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of the present invention.

[0024] Next, the detailed implementation manners of the present invention will be described in conjunction with the accompanying drawings.

[0025] Refer to Figure 1 , the data transmission method for the power grid dispatching data network includes steps S1 - S4, specifically as follows: It should be noted that, in combination with a specific scenario, since the current sensor and voltage sensor are affected by the surrounding environment during the process of collecting current and voltage data, resulting in noise in the power grid dispatching data sequence. Such noise is manifested as data points breaking their regular changes. Therefore, the noise manifestation degree of the power grid dispatching data points can be calculated using their regularity. The better the regularity, the lower the noise manifestation degree of the data points.

[0026] S1: Obtain power grid dispatching data. Among them, the power grid dispatching data includes current and voltage. With each data point in the power grid dispatching data as the center point, a preset number of data points are set on both the left and right sides to determine the local range.

[0027] Exemplarily, the power grid dispatching data includes, but is not limited to, current data and voltage data of each node. Then, the current sensor and voltage sensor are respectively used to collect the current data and voltage data of each node in the power grid (such as substations, power plants, etc.). The collection frequency is 50Hz. The current data and voltage data of any power grid node obtained by collection are analyzed for the power grid dispatching data sequence S.

[0028] A power grid dispatching data point contains a current data point and a voltage data point. Therefore, the regularity of the power grid dispatching data point includes the regularity of the current data and the regularity of the voltage data. The higher the regularity of the current and voltage, the higher the regularity of the data point. The regularity of one data point can be represented by the average fitting error when performing curve fitting within the local range of the data point. The larger the average fitting error, the worse the regularity, because the more regular the data point set, the more conducive to the curve fitting, that is, the smaller the fitting error.

[0029] Exemplarily, let be the data points, , Represent the power grid dispatching data points The local range of the corresponding current data points and voltage data points is 2m+1 data point lengths centered on the current (edge ​​data points are discarded accordingly).

[0030] S2: Use the least squares method to perform curve fitting on the current data and voltage data in the local range respectively, and use the difference between the fitting result and the actual value to obtain the noise performance degree of each data point in the power grid dispatching data.

[0031] The time sequence number of the data point in the local range is used as the horizontal axis, and the current or voltage value of the data point is used as the vertical axis to fit the current curve and voltage curve respectively.

[0032] Get noise performance levels, including: The average values ​​of the absolute differences between the fitted values ​​and the actual values ​​of the current and voltage in the local range are calculated for normalization, and the summed average is taken as the noise performance of each data point in the local range.

[0033] Specifically, the noise performance level satisfies the following relationship: ; In the formula, Indicates The noise level of each data point is Indicates data points correspond to the number of data points in the local range, Indicates The data point corresponds to the local range The current fitting value of the data points is Indicates The data point corresponds to the local range The actual current value of the data point, Indicates The data point corresponds to the local range The voltage fitting value of the data points is Indicates The data point corresponds to the local range The actual voltage value of the data point, Represents the normalization function.

[0034] That is to say, represents the fitting error of this point, then Represents a grid dispatch data point The average fitting error of the current data fitting curve within a local range represents the regularity of the current data and is negatively correlated with the regularity; Similarly represents the power grid dispatching data points The average fitting error of the voltage data fitting curve within a local range represents the regularity of the voltage data; and since the regularity is negatively correlated with the degree of noise manifestation, the average fitting error is positively correlated with the degree of noise manifestation; Use functions to perform normalization respectively to eliminate the dimension between the current data and the voltage data, which is also the normalization operation for the degree of noise manifestation.

[0035] Furthermore, it is further explained that since there may be some normal data changes (such as load changes) in the power grid dispatching data, which cause changes in the current or voltage data, such changes make the change characteristics of the samples within a local range similar to noise. Therefore, it is necessary to adjust the degree of noise manifestation of the samples with load changes to make the credibility calculation more accurate. And in the power grid, the voltage and current are in a positive correlation relationship, that is, if it is a normal data change, the changes of its voltage and current within a local range must be positively correlated, while the data changes caused by noise are random; therefore, the correlation between the voltage and current of the power grid dispatching data points within a local range can be used to correct the degree of noise manifestation, and its logical relationship is: the stronger the correlation, the lower the degree of noise manifestation, and the higher the credibility; It should be noted that the correlation between the current data and the voltage data within a local range of the power grid dispatching data points can be directly represented by the consistency of the area enclosed by two adjacent points in the fitting curves of the above two. Because if the current and voltage data within a local range are more positively correlated, the change trends of their fitting curves are the same, then the areas enclosed by two adjacent points of the fitting curves are more consistent.

[0036] In addition, in another embodiment, it further includes: calculating the difference between the actual value and the moving average of the data points within a local range, dividing it by the moving average, and performing a square process to obtain the squared deviation of each data point, summing up the squared deviations of all data points and dividing by the number of data points within the local range to obtain the degree of noise manifestation of each data point.

[0037] Specifically, the degree of noise manifestation satisfies the following relational expression: ; In the formula, represents the degree of noise manifestation of the th data point, represents the number of data points within the local range corresponding to the th data point, represents the The actual value of a data point, indicating the moving average value of the

[0038] Exemplarily, an odd number is selected as the window size. For the th data point, calculate the sum of all data points from to . Divide the sum of the data points within the window by the window size. By using a weighted moving average, different weights are assigned to different data points within a local range. Usually, the weight of the most recent data point is higher. Calculate the weighted average value to obtain the moving average value. The moving average value reflects the local average behavior of the data points, which helps to identify and smooth short-term fluctuations. By dividing the deviation by the moving average value and squaring it, the noise performance of different data points can be standardized.

[0039] S3: Calculate the area enclosed between adjacent data points within a local range. Use an exponential function to calculate the product of the standard deviation of the set of areas between adjacent two data points within a local range and the degree of noise performance of the corresponding data point to obtain the credibility of each data point.

[0040] Taking any data point within a local range as the marked midpoint, calculate the vertical distance between the current fitting curve and the voltage fitting curve to obtain the area enclosed by the current fitting curve and the voltage fitting curve between all adjacent data points within a local range.

[0041] Specifically, the area satisfies the following relational expression: ; In the formula, represents the area enclosed by the current fitting curve and the voltage fitting curve between the th and the th adjacent points within the local range of the grid dispatching data point . represents the integral function, represents the current fitting value of the th data point corresponding to the th data point within the local range, represents the voltage fitting value of the th data point corresponding to the th data point within the local range.

[0042] Furthermore, the set of areas between all adjacent points within the local range of the grid dispatching data point is , where, in this article, represents the number of samples within the local range of the grid dispatching data point, that is, the number of current data points or voltage data points participating in the fitting.

[0043] It should be noted that in the power grid, current and voltage are usually positively correlated, that is, their change trends should be consistent. If the change trends of current and voltage are inconsistent, it may indicate that there is noise or abnormality in the data; the area reflects the difference between the current and voltage fitting curves within a local range. If this area is large, it means that the change trends of current and voltage are inconsistent, and there may be noise or abnormality. On the contrary, if this area is small, it means that the change trends of current and voltage are relatively consistent and the data is relatively reliable.

[0044] The above method for calculating the area is applicable when the fitting curve is relatively complex or high-precision area calculation is required, but the calculation process may be relatively complex and time-consuming. It can provide accurate area calculation results and is applicable to continuously changing curves.

[0045] In addition, another embodiment also includes: Calculate the sum of the differences between the current and voltage fitting values of adjacent data points within a local range to obtain the total difference between current and voltage between two adjacent data points, and use the trapezoidal rule formula to obtain the area between adjacent data points.

[0046] Specifically, the area satisfies the following relationship: ; In the formula, represents the area enclosed by the current fitting curve and the voltage fitting curve between the th and the th adjacent points within the local range of power grid dispatching data points, represents the vertical distance between adjacent data points, represents the current fitting value of the th data point corresponding to the th data point within the local range, represents the voltage fitting value of the th data point corresponding to the th data point within the local range, represents the current fitting value of the th data point corresponding to the th data point within the local range, represents the voltage fitting value of the th data point corresponding to the th data point within the local range.

[0047] That is to say, the trapezoidal rule is a numerical integration method that calculates by approximating the area under the curve as a trapezoid, improving the calculation efficiency. The area reflects the energy loss or power difference caused by the inconsistency between current and voltage between two adjacent measurement points. For example, if the phases of current and voltage are not synchronized, it may lead to a decrease in power factor, thus affecting the efficiency of the power grid. It helps to identify abnormal areas in the power grid, such as equipment failures, load imbalances, or data acquisition errors.

[0048] It should also be noted that this method is applicable when the data points are relatively evenly distributed and the fitting curve changes relatively smoothly. By approximating the area under the curve as a trapezoid, it is suitable for scenarios where a quick estimation of the area is required.

[0049] In practical applications, it can be based on specific data characteristics, computing resources, and accuracy requirements. For power grid dispatching data, if the data acquisition frequency is high and the changes are smooth, the trapezoidal rule may be a more practical choice. On the contrary, if a precise analysis of the power grid operation status is required, an integration method may be needed to obtain more accurate results; at the same time, during the calculation process, the value ranges of current and voltage data are limited to avoid the occurrence of extreme situations.

[0050] Specifically, the credibility satisfies the following relational expression: ; In the formula, represents the credibility of the power grid dispatching data point , represents the noise performance degree of the power grid dispatching data point , represents the set of areas between all adjacent points within the local range of the power grid dispatching data point , represents the standard deviation function, represents the exponential function with as the base.

[0051] That is to say, represents the consistency of the area enclosed between two adjacent points of the current fitting curve and the voltage fitting curve within the local range of the power grid dispatching data point . The consistency of the area is positively correlated with the noise performance degree and negatively correlated with the credibility.

[0052] S4: Modify the Fisher optimal solution algorithm based on the credibility, cluster the power grid dispatching data according to the modified Fisher optimal solution algorithm, and transmit the power grid dispatching data according to the clustering results.

[0053] It should be noted that the Fisher optimal solution algorithm is a well-known technology in the field and will not be described in detail.

[0054] Specifically, the correction process satisfies the following relational expression: ; In the formula, represents the method of dividing ordered samples into categories in the Fisher optimal solution method process, represents the number of data points in the th clustering cluster, represents the mean coordinate of the th clustering cluster, represents the data of the th data point in the th clustering cluster, represents the credibility of the th data point in the

[0055] It should also be noted that the number of clusters can be directly determined by using existing technologies such as the elbow method. Each clustering cluster in the clustering result is a segment; for each segment, it can be encapsulated into a standardized data packet, and the encapsulated data packet can be encrypted to ensure confidentiality and integrity during transmission. The encrypted data packet can be transmitted between nodes through the power dispatching data network.

[0056] The present invention also provides a data transmission system for the power grid dispatching data network. As Figure 2 shown, the system includes a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data transmission method for the power grid dispatching data network according to the first aspect of the present invention is implemented.

[0057] The system also includes other components well known to those skilled in the art such as a communication bus and a communication interface, and their settings and functions are known in the art, so they will not be elaborated here.

[0058] In the present invention, the foregoing memory may be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory (RRAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), an enhanced dynamic random access memory (EDRAM), a high-bandwidth memory (HBM), a hybrid memory cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application program, a module, or both. Any such computer storage medium may be part of the device or accessible or connectable to the device. Any application or module described in the present invention may be implemented by computer-readable / executable instructions stored or otherwise held by such a computer-readable medium.

[0059] In the description of this specification, the meanings of "a plurality of" and "several" are at least two, such as two, three, or more, etc., unless otherwise specifically defined.

[0060] Although this specification has shown and described multiple embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will think of many changes, alterations, and alternative ways without departing from the spirit and scope of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in practicing the present invention.

Claims

1. A data transmission method for a power grid dispatching data network, characterized in that: include: Obtaining power grid dispatching data, wherein the power grid dispatching data includes: current and voltage, taking each data point in the power grid dispatching data as a center point, setting a preset number of data points on both sides to determine a local range; The least square method is used to perform curve fitting on the current data and voltage data in the local range respectively, and the difference between the fitting result and the actual value is used to obtain the noise performance degree of each data point in the power grid dispatching data; Calculate the area enclosed by adjacent data points in the local range, and use the exponential function to calculate the product of the standard deviation of the area set between two adjacent data points in the local range and the noise performance level of the corresponding data point to obtain the credibility of each data point; The Fisher optimal solution algorithm is modified based on the credibility, the power grid dispatching data is clustered according to the modified Fisher optimal solution algorithm, and the power grid dispatching data is transmitted according to the clustering result.

2. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: The curve fitting of the current data and the voltage data in the local range respectively comprises: The time sequence number of the data point in the local range is used as the horizontal axis, and the current or voltage value of the data point is used as the vertical axis to fit the current curve and voltage curve respectively.

3. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: Obtaining the noise performance level includes: The average values ​​of the absolute differences between the fitted values ​​and the actual values ​​of the current and voltage in the local range are calculated for normalization, and the summed average is taken as the noise performance of each data point in the local range.

4. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: Acquiring the noise performance level also includes: The difference between the actual value of the data point in the local range and the moving average is calculated and divided by the moving average, and then squared to obtain the square of the deviation of each data point. The square of the deviation of all data points is summed and divided by the number of data points in the local range to obtain the noise performance of each data point.

5. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: The calculating the area enclosed by adjacent data points within the local range includes: According to any data point in the local range as the marked midpoint, the vertical distance between the current fitting curve and the voltage fitting curve of the marked point is calculated to obtain the area enclosed by the current fitting curve and the voltage fitting curve between all adjacent data points in the local range.

6. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: The calculation of the area enclosed by adjacent data points within the local range also includes: The differences between the current and voltage fitting values ​​between adjacent data points in the local range are calculated and added to obtain the sum of the current and voltage differences between two adjacent data points, and the trapezoidal rule formula is used to obtain the area between adjacent data points.

7. The data transmission method for a power grid dispatching data network according to claim 1, characterized in that: The correction process satisfies the following relationship: ； In the formula, Indicates that in the process of Fisher optimal solution, The ordered samples are divided into Classification Indicates The number of data points in a cluster. Indicates The mean coordinates of the clusters, Indicates The first data points, express The first The credibility of a data point.

8. A data transmission system for a power grid dispatching data network, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data transmission method for a power grid dispatching data network according to any one of claims 1 to 7 is implemented.

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