Power data wireless communication method and system based on deterministic network

Abstract

The invention relates to the technical field of electric power data acquisition, and particularly discloses an electric power data wireless communication method and system based on a deterministic network, and the method comprises the steps: obtaining the electric power data of each piece of electric power equipment, analyzing the electric power data, and classifying the electric power equipment according to the periodicity of the electric power data; determining the data benefit of each power device in each type of power devices; the data benefit represents the importance degree of the data of the power equipment; determining a communication resource allocation amount according to the data benefit and the equipment parameter of each power equipment, and constructing a deterministic network; the method analyzes the power data of each power device, evaluates the data benefit of the power device, distributes limited resources in combination with the importance of the power device, enables the data of the important power device to have real-time performance, carries out simulation prediction on the unimportant power device according to the data of the similar device, and improves the prediction efficiency of the power device. A simulation type deterministic network with extremely high accuracy is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power data acquisition, and in particular to a method and system for wireless communication of power data based on a deterministic network. Background Art

[0002] In power systems, data transmission often requires high reliability, low latency, and stability, which requires the use of deterministic networks. Deterministic networks refer to networks with clear performance guarantees and predictable behavior. Such networks can provide strict control over latency, bandwidth, delay jitter, etc., thereby ensuring the reliability and consistency of data transmission.

[0003] If there are sufficient resources, that is, if the performance of all devices is good enough, then a deterministic network is very easy to build. No matter how much data or how complex it is, it can be uploaded to the data center very quickly. However, if there are insufficient resources, a deterministic network will be difficult to build. How to build a deterministic network as much as possible when resources are insufficient is the technical problem that the technical solution of the present invention aims to solve. Summary of the Invention

[0004] The object of the present invention is to provide a method and system for wireless communication of electric power data based on a deterministic network, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method and system for wireless communication of electric power data based on a deterministic network, the method comprising:

[0007] Obtain power data from each power device, analyze the power data, and classify the power devices based on the periodicity of the power data;

[0008] For each type of power equipment, collect power data within a preset time range to create a two-dimensional matrix; the rows of the two-dimensional matrix correspond one-to-one to the power equipment, and the columns of the two-dimensional matrix correspond one-to-one to the time tags of the power data, and the power data of all power equipment are collected at the same frequency;

[0009] Randomly selecting a row and column position in a two-dimensional matrix, calculating the prediction accuracy of the row and column position, and determining the data benefit of each power device in the class of power devices based on the calculated prediction accuracy of the row and column position; the data benefit represents the importance of the data of the power device;

[0010] Determine the communication resource allocation based on the data benefits and device parameters of each power device to build a deterministic network;

[0011] Among them, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented.

[0012] Furthermore, the steps of acquiring power data of each power device, analyzing the power data, and classifying the power devices according to the periodicity of the power data include:

[0013] Obtain power data of each power device;

[0014] Taking the current moment as the end moment, reading the power data before the preset period, and performing Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called the fundamental function;

[0015] Extract the amplitude, frequency and phase of the harmonic function as the features of the power data;

[0016] The electrical equipment is classified according to the characteristics.

[0017] Furthermore, the step of classifying the electrical equipment according to the characteristics includes:

[0018] Determine weights based on the inverse of frequency;

[0019] For any two power devices, the parameters are paired according to the order of the harmonic function. After the pairing is completed, the amplitude difference and phase difference are calculated.

[0020] summing the amplitude difference and the phase difference based on the weight to obtain a total amplitude difference and a total phase difference;

[0021] When the total amplitude difference is smaller than a preset amplitude threshold and the total phase difference is smaller than a preset phase threshold, the corresponding two power devices are classified into one category.

[0022] Furthermore, the steps of randomly selecting row and column positions in the two-dimensional matrix, calculating the prediction accuracy of the row and column positions, and determining the data benefit of each power device in the type of power devices according to the calculated prediction accuracy of the row and column positions include:

[0023] Randomly select at least one row and column position in the two-dimensional matrix;

[0024] Determine predicted data at the row and column position based on data surrounding the row and column position;

[0025] Compare the predicted data with the original data and calculate the difference ratio;

[0026] Execute the loop until the number of selected row and column positions reaches a preset threshold;

[0027] The difference ratios of all row and column positions of each power device are counted, and the data benefit is determined according to the difference ratios.

[0028] Furthermore, the process of determining the predicted data at the row and column position based on the data around the row and column position is:

[0029] Locate the column at the row and column position, and get the adjacent elements in the column as the column adjacent elements;

[0030] Calculate the ratio of the adjacent elements in the column to the elements in the adjacent row;

[0031] Locate the row at the row and column position, and get the adjacent elements in the row as the row adjacent elements;

[0032] Calculating prediction data based on the ratio and the row adjacent elements;

[0033] The process of counting the difference ratios of all row and column positions of each power device and determining the data benefit based on the difference ratios includes:

[0034] V=αE(B i )+βσ(B i ); where V represents data benefit, α and β are preset weight coefficients, and B i is the difference ratio of the i-th power equipment, E(B i ) means B i The mean value, σ(B i ) means B i The standard deviation of .

[0035] Furthermore, the step of determining the communication resource allocation amount based on the data benefits and device parameters of each power device and building a deterministic network includes:

[0036] Obtain the equipment parameters of each power device and query the benchmark allocation amount in the preset resource allocation table based on the equipment parameters;

[0037] Reading the data benefits of each power device and determining the floating allocation amount according to the data benefits;

[0038] Allocating communication resources based on a baseline allocation and a floating allocation for each power device to obtain a communication resource allocation for each power device;

[0039] When the communication resource allocation amount of each power device is determined, a deterministic network is obtained.

[0040] The technical solution of the present invention also provides a power data wireless communication system based on a deterministic network, the system comprising:

[0041] The power equipment classification module is used to obtain power data of each power equipment, analyze the power data, and classify the power equipment according to the periodicity of the power data;

[0042] The power data statistics module is used to collect power data of each type of power equipment within a preset time range and create a two-dimensional matrix; the rows of the two-dimensional matrix correspond one-to-one with the power equipment, and the columns of the two-dimensional matrix correspond one-to-one with the time tags of the power data, and the power data of all power equipment are collected at the same frequency;

[0043] A data benefit analysis module is configured to randomly select a row or column position in a two-dimensional matrix, calculate the prediction accuracy of the row or column position, and determine the data benefit of each power device in the class of power devices based on the calculated prediction accuracy of the row or column position; the data benefit represents the importance of the data of the power device;

[0044] The resource allocation module is used to determine the communication resource allocation amount based on the data benefits and equipment parameters of each power device and build a deterministic network;

[0045] Among them, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented.

[0046] Furthermore, the power equipment classification module includes:

[0047] A data reading unit, used to obtain power data of each power device;

[0048] A frequency domain conversion unit is configured to read the power data before a preset period of time with the current time as the end time, and perform Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called a fundamental function;

[0049] A feature extraction unit, used to extract the amplitude, frequency and phase of the harmonic function as features of the power data;

[0050] The feature application unit is used to classify the electric equipment according to the features.

[0051] Furthermore, the data benefit analysis module includes:

[0052] A random selection unit, used for randomly selecting at least one row and column position in the two-dimensional matrix;

[0053] a data prediction unit, configured to determine predicted data at a row or column position based on data surrounding the row or column position;

[0054] Data comparison unit, used to compare predicted data with original data and calculate the difference ratio;

[0055] A loop execution unit, configured to execute the loop until the number of selected row and column positions reaches a preset number threshold;

[0056] The data statistics unit is used to count the difference ratios of all row and column positions of each power device and determine the data benefit according to the difference ratios.

[0057] Furthermore, the resource allocation module includes:

[0058] A benchmark query unit, configured to obtain device parameters of each power device and query a benchmark allocation amount in a preset resource allocation table based on the device parameters;

[0059] a floating determination unit, configured to read the data benefit of each power device and determine the floating allocation amount according to the data benefit;

[0060] an allocation execution unit, configured to allocate communication resources based on a baseline allocation amount and a floating allocation amount of each power device, to obtain a communication resource allocation amount for each power device;

[0061] The network output unit is used to obtain a deterministic network after the communication resource allocation amount of each power device is determined.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] The present invention analyzes the power data of each power device, evaluates the data benefits of the power equipment, and allocates limited resources based on the importance of the power equipment itself, so that the data of important power equipment is real-time. For unimportant power equipment, simulation prediction is performed based on the data of similar equipment, realizing a highly accurate simulation deterministic network. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0065] Figure 1 The figure shows the overall flow chart of the power data wireless communication method based on the deterministic network.

[0066] Figure 2 The figure shows a structural diagram of a power data wireless communication system based on a deterministic network. DETAILED DESCRIPTION

[0067] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0068] Figure 1The following is a flowchart of a method and system for wireless communication of electric power data based on a deterministic network. In an embodiment of the present invention, a method for wireless communication of electric power data based on a deterministic network includes:

[0069] Step S100: acquiring power data of each power device, analyzing the power data, and classifying the power devices according to the periodicity of the power data;

[0070] Power equipment includes transformers, cables, switches, etc. Under the existing technical background, data acquisition instruments or data acquisition sensors are installed in these power equipment. With the help of data acquisition instruments or data acquisition sensors, the parameters of the power equipment during operation can be remotely obtained, which is called power data; by analyzing the power data, power equipment with similar changes can be classified into one category. The same type of power equipment has the same data fluctuations, so even if the data of some power equipment is missing, it can be supplemented by the data changes of other power equipment; to achieve this function, this application classifies power equipment according to the periodicity of power data.

[0071] It is worth mentioning that electrical equipment classified into the same category generally has a series relationship.

[0072] Step S200: For each type of power equipment, collect power data within a preset time range to create a two-dimensional matrix; the rows of the two-dimensional matrix correspond one-to-one to the power equipment, and the columns of the two-dimensional matrix correspond one-to-one to the time tags of the power data. The power data of all power equipment are collected at the same frequency;

[0073] After the classification of power equipment is completed, for each type of power equipment, its power data within a preset time range is counted. The time range is generally one week. At the current moment, the power data of the previous week is obtained. Of course, the time range can be expanded or shortened. In addition, power data is discrete data, and there is a power data at each moment. The power equipment is taken as a row and the moment as a column. The power data of all power equipment at each moment is counted to obtain a two-dimensional matrix.

[0074] It should be noted that the data collection frequency of each power device is the same, which makes the acquisition time of power data of each power device similar. As long as the time difference is less than the preset threshold, it is considered to be power data at the same time.

[0075] Step S300: Randomly select a row and column position in a two-dimensional matrix, calculate the prediction accuracy of the row and column position, and determine the data benefit of each power device in the class of power devices based on the calculated prediction accuracy of the row and column position; the data benefit represents the importance of the data of the power device;

[0076] A two-dimensional matrix represents the power data of multiple power devices within a time range. By analyzing the data at each position in the two-dimensional matrix, it can be determined that if the data at that position is missing, the accuracy of the prediction based on the surrounding data (called prediction accuracy) can be determined. The higher the accuracy, the lower the value of the corresponding data. For a power device, if most of its data are low-value data, then the benefit of investing resources to obtain data will be very low, because most of the data can be predicted through other data.

[0077] Step S400: Determine the communication resource allocation amount based on the data benefits and device parameters of each power device, and build a deterministic network;

[0078] After the data benefit calculation of each power device is completed, the device parameters of each power device are obtained. Combining the device parameters and data benefits, the communication resource allocation amount of each power device can be jointly determined. The more communication resource allocation amount, the faster the power data of the power device is acquired. After the communication resource allocation amount of each power device is determined, a deterministic network is obtained.

[0079] In the technical solution of the present invention, communication resources are mainly allocated to some relatively important power equipment (power equipment with greater data collection significance). Under the condition of limited communication resources, the real-time data of relatively important power equipment can be guaranteed first. For less important power equipment, when real data cannot be obtained in time, it can be predicted and supplemented with the help of existing data; specifically, at the port where the power equipment data needs to be obtained, that is, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented; the prediction and supplement method can adopt the prediction method in step S300.

[0080] Regarding step S100, the steps of acquiring power data of each power device, analyzing the power data, and classifying the power devices according to the periodicity of the power data include:

[0081] Obtain power data of each power device;

[0082] Taking the current moment as the end moment, reading the power data before the preset period, and performing Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called the fundamental function;

[0083] Extract the amplitude, frequency and phase of the harmonic function as the features of the power data;

[0084] The electrical equipment is classified according to the characteristics.

[0085] When classifying power equipment, this application only considers periodicity, obtains power data of each power equipment, takes the current moment as the end moment, reads the power data before the preset period (power data within a certain period of time), performs Fourier transform on the read power data, and obtains a harmonic function in triangular form; extracts the amplitude, frequency and phase of the harmonic function as the characteristics of the power data, and uses the characteristics as a reference to classify the power equipment.

[0086] Furthermore, the step of classifying the electrical equipment according to the characteristics includes:

[0087] Determine weights based on the inverse of frequency;

[0088] For any two power devices, the parameters are paired according to the order of the harmonic function. After the pairing is completed, the amplitude difference and phase difference are calculated.

[0089] summing the amplitude difference and the phase difference based on the weight to obtain a total amplitude difference and a total phase difference;

[0090] When the total amplitude difference is smaller than a preset amplitude threshold and the total phase difference is smaller than a preset phase threshold, the corresponding two power devices are classified into one category.

[0091] The higher the frequency, the lower the weight of the corresponding harmonic function. This is the property of Fourier transform. The weight is determined according to the inverse ratio of the frequency. For any two electrical devices, the harmonic functions are paired, and then the amplitude difference and phase difference are calculated. The amplitude difference and phase difference are summed according to the weight corresponding to the frequency to obtain the total amplitude difference and total phase difference. When the total amplitude difference and total phase difference are relatively small, the corresponding two electrical devices are classified into one category.

[0092] Regarding step S300, the steps of randomly selecting a row and column position in the two-dimensional matrix, calculating the prediction accuracy of the row and column position, and determining the data benefit of each power device in the class of power devices based on the calculated prediction accuracy of the row and column position include:

[0093] Randomly select at least one row and column position in the two-dimensional matrix;

[0094] Determine predicted data at the row and column position based on data surrounding the row and column position;

[0095] Compare the predicted data with the original data and calculate the difference ratio;

[0096] Execute the loop until the number of selected row and column positions reaches a preset threshold;

[0097] The difference ratios of all row and column positions of each power device are counted, and the data benefit is determined according to the difference ratios.

[0098] The prediction process is a cyclic process that needs to be executed many times. Each time, data prediction is performed on a position. After the predicted data is obtained, it is compared with the previous original data to calculate the difference ratio. The difference ratio is the absolute value of the difference between the predicted data and the original data divided by the original data.

[0099] Each prediction will obtain the difference ratio at a row and column position. The prediction process is repeated to obtain the difference ratios of multiple row and column positions. Finally, based on the power equipment, all the difference ratios at a row position corresponding to the power equipment are counted to determine the data benefit.

[0100] Specifically, the process of determining the predicted data at the row and column position based on the data around the row and column position is:

[0101] Locate the column at the row and column position, and get the adjacent elements in the column as the column adjacent elements;

[0102] Calculate the ratio of the adjacent elements in the column to the elements in the adjacent row;

[0103] Locate the row at the row and column position, and get the adjacent elements in the row as the row adjacent elements;

[0104] Prediction data is calculated based on the ratio and the row neighboring elements.

[0105] The working principle of the above content is very simple. For the sake of convenience, this application uses the upper and lower relationships for intuitive description. For a position to be predicted, obtain the data above (or below) it, and calculate the ratio of the data above (or below) it in the row where it is located to the previous data; then, read the ratio and multiply it by the previous data of the position to be predicted in the row where it is located to obtain the predicted data.

[0106] The process of counting the difference ratios of all row and column positions of each power device and determining the data benefit based on the difference ratios includes:

[0107] V=αE(B i )+βσ(B i ); where V represents data benefit, α and β are preset weight coefficients, and B i is the difference ratio of the i-th power equipment, E(B i ) means B i The mean value, σ(B i ) means B i The standard deviation of .

[0108] The above content only provides a solution. Data efficiency is related to the mean and standard deviation of the difference ratio. The larger the mean, the greater the difference, and the more real-time acquisition is needed. Therefore, the greater the data efficiency and the larger the standard deviation, the more drastic the fluctuation of the difference, and the more real-time acquisition is needed. Therefore, the data efficiency is greater.

[0109] Regarding step S400, the steps of determining the communication resource allocation amount based on the data benefits and device parameters of each power device and building a deterministic network include:

[0110] Obtain the equipment parameters of each power device and query the benchmark allocation amount in the preset resource allocation table based on the equipment parameters;

[0111] Reading the data benefits of each power device and determining the floating allocation amount according to the data benefits;

[0112] Allocating communication resources based on a baseline allocation and a floating allocation for each power device to obtain a communication resource allocation for each power device;

[0113] When the communication resource allocation amount of each power device is determined, a deterministic network is obtained.

[0114] In an example of the technical solution of the present invention, the resource allocation process is described in detail. First, the equipment parameters of each power equipment are obtained, and the importance of the power equipment is determined according to the equipment parameters as the benchmark allocation amount. The relationship between the equipment parameters and the benchmark allocation amount is pre-set by the staff; then, the calculated data benefit of each power equipment is read, and the floating allocation amount is determined according to the data benefit. The greater the data benefit, the greater the floating allocation amount; after the above processing, each power equipment will have a benchmark allocation amount and a floating allocation amount; finally, for the existing communication resources, the communication resources are allocated to each power equipment, first meeting the benchmark allocation amount, and then allocating them in descending order of the floating allocation amount, thereby ensuring the timeliness of important power equipment. For unimportant power equipment, they can be predicted based on existing data to ensure timeliness.

[0115] Figure 2 The structure diagram of a power data wireless communication system based on a deterministic network is shown. In a preferred embodiment of the technical solution of the present invention, a power data wireless communication system based on a deterministic network is also provided. The system 10 includes:

[0116] The power equipment classification module 11 is used to obtain power data of each power equipment, analyze the power data, and classify the power equipment according to the periodicity of the power data;

[0117] The power data statistics module 12 is used to collect power data of each type of power equipment within a preset time range and create a two-dimensional matrix; the rows of the two-dimensional matrix correspond one-to-one with the power equipment, and the columns of the two-dimensional matrix correspond one-to-one with the time tags of the power data, and the power data of all power equipment are collected at the same frequency;

[0118] The data benefit analysis module 13 is configured to randomly select a row or column position in the two-dimensional matrix, calculate the prediction accuracy of the row or column position, and determine the data benefit of each power device in the class of power devices based on the calculated prediction accuracy of the row or column position; the data benefit represents the importance of the data of the power device;

[0119] The resource allocation module 14 is used to determine the communication resource allocation amount according to the data benefits and device parameters of each power device and build a deterministic network;

[0120] Among them, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented.

[0121] Furthermore, the power equipment classification module 11 includes:

[0122] A data reading unit, used to obtain power data of each power device;

[0123] A frequency domain conversion unit is configured to read the power data before a preset period of time with the current time as the end time, and perform Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called a fundamental function;

[0124] A feature extraction unit, used to extract the amplitude, frequency and phase of the harmonic function as features of the power data;

[0125] The feature application unit is used to classify the electric equipment according to the features.

[0126] Specifically, the data benefit analysis module 13 includes:

[0127] A random selection unit, used for randomly selecting at least one row and column position in the two-dimensional matrix;

[0128] a data prediction unit, configured to determine predicted data at a row or column position based on data surrounding the row or column position;

[0129] Data comparison unit, used to compare predicted data with original data and calculate the difference ratio;

[0130] A loop execution unit, configured to execute the loop until the number of selected row and column positions reaches a preset number threshold;

[0131] The data statistics unit is used to count the difference ratios of all row and column positions of each power device and determine the data benefit according to the difference ratios.

[0132] Furthermore, the resource allocation module 14 includes:

[0133] A benchmark query unit, configured to obtain device parameters of each power device and query a benchmark allocation amount in a preset resource allocation table based on the device parameters;

[0134] a floating determination unit, configured to read the data benefit of each power device and determine the floating allocation amount according to the data benefit;

[0135] an allocation execution unit, configured to allocate communication resources based on a baseline allocation amount and a floating allocation amount of each power device, to obtain a communication resource allocation amount for each power device;

[0136] The network output unit is used to obtain a deterministic network after the communication resource allocation amount of each power device is determined.

[0137] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for wireless communication of electric power data based on a deterministic network, characterized in that: The method comprises: Obtain power data of each power device, analyze the power data, and classify the power devices according to the periodicity of the power data; For each type of power equipment, the power data within a preset time range is counted to create a two-dimensional matrix; the rows of the two-dimensional matrix correspond to the power equipment one by one, the columns of the two-dimensional matrix correspond to the time tags of the power data one by one, and the power data of all power equipment are collected at the same frequency; Randomly selecting row and column positions in a two-dimensional matrix, calculating the prediction accuracy of the row and column positions, and determining the data benefit of each power device in the type of power devices according to the calculated prediction accuracy of the row and column positions; the data benefit indicates the importance of the data of the power device; Determine the communication resource allocation amount based on the data benefits and equipment parameters of each power device and build a deterministic network; Among them, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented.

2. The method for wireless power data communication based on a deterministic network according to claim 1, characterized in that: The steps of acquiring power data of each power device, analyzing the power data, and classifying the power devices according to the periodicity of the power data include: Obtain power data of each power device; Taking the current moment as the end moment, reading the power data before the preset period, and performing Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called a fundamental function; Extract the amplitude, frequency and phase of the harmonic function as the characteristics of the power data; The electrical equipment is classified according to the characteristics.

3. The method for wireless power data communication based on a deterministic network according to claim 2, characterized in that: The step of classifying the electrical equipment according to the characteristics comprises: The weights are determined based on the inverse ratio of the frequencies; For any two power devices, the parameters are paired according to the order of the harmonic function. After the pairing is completed, the amplitude difference and phase difference are calculated; Summing the amplitude difference and the phase difference based on the weight to obtain a total amplitude difference and a total phase difference; When the total amplitude difference is smaller than a preset amplitude threshold and the total phase difference is smaller than a preset phase threshold, the corresponding two power devices are classified into one category.

4. The method for wireless power data communication based on a deterministic network according to claim 1, characterized in that: The steps of randomly selecting row and column positions in the two-dimensional matrix, calculating the prediction accuracy of the row and column positions, and determining the data benefit of each power device in the type of power devices according to the calculated prediction accuracy of the row and column positions include: Randomly select at least one row and column position in the two-dimensional matrix; Determine predicted data at the row and column position based on data surrounding the row and column position; Compare the predicted data with the original data and calculate the difference ratio; The process is executed repeatedly until the number of selected row and column positions reaches a preset number threshold; The difference ratios of all row and column positions of each power device are counted, and the data benefit is determined according to the difference ratios.

5. The method for wireless power data communication based on a deterministic network according to claim 4, characterized in that: The process of determining the predicted data at the row and column position based on the data around the row and column position is: Locate the column of the row and column position, and obtain the adjacent elements in the column as the column adjacent elements; Calculate the ratio of the adjacent elements of the column in its row to the elements in its adjacent row; Locate the row at the row and column position, and obtain the adjacent elements in the row as the row adjacent elements; Calculate prediction data based on the ratio and the row adjacent elements; The content of counting the difference ratios of all row and column positions of each power device and determining the data benefit according to the difference ratios includes: V=αE(B i )+βσ(B i ), where V represents data benefit, α and β are preset weight coefficients, and B i is the ith difference ratio of the power equipment, E(B i ) means B i The mean value, σ(B i ) means B i The standard deviation of .

6. The method for wireless power data communication based on a deterministic network according to claim 1, characterized in that: The steps of determining the communication resource allocation amount according to the data benefit and device parameters of each power device and building a deterministic network include: Obtain equipment parameters of each power equipment, and query the benchmark allocation amount in a preset resource allocation table according to the equipment parameters; Reading the data benefits of each electric device, and determining the floating allocation amount according to the data benefits; Allocate communication resources based on the reference allocation and floating allocation of each power device to obtain the communication resource allocation of each power device; When the communication resource allocation amount of each power device is determined, a deterministic network is obtained.

7. A power data wireless communication system based on a deterministic network, characterized in that: The system comprises: The power equipment classification module is used to obtain power data of each power equipment, analyze the power data, and classify the power equipment according to the periodicity of the power data; The power data statistics module is used to count the power data of each type of power equipment within a preset time range and create a two-dimensional matrix; the rows of the two-dimensional matrix correspond to the power equipment one by one, the columns of the two-dimensional matrix correspond to the time tags of the power data one by one, and the power data of all power equipment are collected at the same frequency; A data benefit analysis module is used to randomly select row and column positions in a two-dimensional matrix, calculate the prediction accuracy of the row and column positions, and determine the data benefit of each power device in the class of power devices according to the calculated prediction accuracy of the row and column positions; the data benefit indicates the importance of the data of the power device; Resource allocation module, used to determine the communication resource allocation amount according to the data benefits and equipment parameters of each power equipment, and build a deterministic network; Among them, at the data receiving end, when the power data of a certain power equipment is missing, it is predicted and supplemented.

8. The power data wireless communication system based on a deterministic network according to claim 7, characterized in that: The electric equipment classification module comprises: A data reading unit, used to obtain power data of each power device; A frequency domain conversion unit is used to read the power data before the preset time period with the current time as the end time, and perform Fourier transform to obtain a harmonic function; the harmonic function is in the form of a trigonometric function, the number of harmonic functions is a preset value, and the first term is called a fundamental wave function; A feature extraction unit, used for extracting the amplitude, frequency and phase of the harmonic function as the features of the power data; The feature application unit is used to classify the electric equipment according to the features.

9. The power data wireless communication system based on a deterministic network according to claim 7, characterized in that: The data benefit analysis module includes: A random selection unit, used for randomly selecting at least one row and column position in the two-dimensional matrix; A data prediction unit, used to determine predicted data at the row and column position based on data around the row and column position; A data comparison unit is used to compare the predicted data with the original data and calculate the difference ratio; A loop execution unit, used for loop execution until the number of selected row and column positions reaches a preset number threshold; The data statistics unit is used to count the difference ratios of all row and column positions of each power device, and determine the data benefit according to the difference ratios.

10. The power data wireless communication system based on a deterministic network according to claim 7, characterized in that: The resource allocation module comprises: A benchmark query unit, used to obtain equipment parameters of each power equipment, and query the benchmark allocation amount in a preset resource allocation table according to the equipment parameters; A floating determination unit, used for reading the data benefit of each electric power equipment and determining the floating allocation amount according to the data benefit; An allocation execution unit, configured to allocate communication resources based on a reference allocation amount and a floating allocation amount of each power device, to obtain a communication resource allocation amount of each power device; The network output unit is used to obtain a deterministic network after the communication resource allocation amount of each power device is determined.

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