Short message communication method and system for FTU equipment of power distribution network

Abstract

The invention discloses a short message communication method and system for FTU (feeder terminal unit) equipment of a power distribution network. The method comprises the following steps: acquiring a power state data stream, an equipment fault data stream and an equipment health state data stream in the FTU equipment of the power distribution network; each data stream is preprocessed; calculating the priority of each data stream by using a dynamic priority sorting algorithm based on each preprocessed data stream, and classifying the data streams into a high-priority data stream and a low-priority data stream; monitoring the real-time quality data of the communication link based on the Beidou No.3 satellite system, and predicting the health state of the satellite link by using an extended Kalman filtering algorithm to obtain a link health state prediction result; the real-time quality data comprises link delay, bandwidth and packet loss rate; and calculating a quality score of each link by using a nonlinear programming algorithm based on a link health state prediction result, and selecting the link according to the score to carry out data stream transmission. The reliability and the transmission efficiency of the system can be improved.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of message communication, and particularly relates to a short message communication method and system for a distribution network FTU device. Background Art

[0002] In the prior art, power distribution network systems usually rely on public network communication or other traditional wireless communication methods for data transmission. However, in remote areas or environments without public network signals, these communication methods often face problems such as unstable signals and incomplete network coverage, resulting in the real-time performance and accuracy of data transmission being affected. In addition, existing distribution network devices often rely on fixed communication protocols during data transmission, which makes it difficult to achieve good compatibility between different communication systems and brings certain technical problems to data exchange between devices. Especially in some special scenarios (such as mountainous areas or areas with relatively scattered power equipment), the instability of the communication link makes it difficult for the distribution network system to operate efficiently and stably.

[0003] In terms of data transmission, traditional short message communication technologies have limitations on the length of transmitted messages. Although the short message communication function provided by the Beidou system has certain advantages in some applications, when the transmitted power data exceeds the single-frame message limit of the system, the prior art usually relies on manual intervention or complex manual splitting methods. This method not only increases the operation complexity but also reduces the efficiency and accuracy of data transmission. In addition, existing distribution network communication systems also have certain deficiencies in device positioning and time synchronization, lacking a unified high-precision positioning and timing mechanism, which causes certain difficulties for the distribution network system in asset management, fault location, and scheduling. Summary of the Invention

[0004] In view of the technical problems existing in the prior art, the present invention provides a short message communication method and system for a distribution network FTU device that improve the reliability and transmission efficiency of the system.

[0005] To solve the above technical problems, the technical solution proposed by the present invention is as follows:

[0006] A short message communication method for a distribution network FTU device, comprising the steps of:

[0007] Obtain the power status data stream, device fault data stream, and device health status data stream in the distribution network FTU device;

[0008] Preprocess the power status data stream, device fault data stream, and device health status data stream, remove noise, and convert the data stream into a unified format;

[0009] Based on the pre - processed power status data stream, equipment failure data stream, and equipment health status data stream, use the dynamic priority sorting algorithm to calculate the priority of each data stream, and classify the data streams into high - priority data streams and low - priority data streams;

[0010] Monitor the real - time quality data of the communication link based on the Beidou - 3 satellite system, and use the extended Kalman filter algorithm to predict the health status of the satellite link to obtain the predicted result of the link health status; the real - time quality data includes link delay, bandwidth, and packet loss rate;

[0011] Based on the predicted result of the link health status, use the non - linear programming algorithm to calculate the quality score of each link, and select the link for data stream transmission according to the score.

[0012] Preferably, during data stream transmission, for packets exceeding the maximum transmission length, use the adaptive splitting algorithm to split the packet into multiple small packets, and sort and transmit the split packets according to the priority of the data stream; encrypt the split packets and use symmetric encryption technology to protect the data transmission process to ensure communication security.

[0013] Preferably, the specific process of using the adaptive splitting algorithm to split a packet into multiple small packets is as follows:

[0014] During the packet transmission process, detect whether the length L of the packet to be transmitted exceeds the set maximum transmission length L max ; if the length L of the packet ≤ L max , then the packet is directly transmitted without splitting; if the length L of the packet > L max , then enter the packet splitting process;

[0015] If the bandwidth of the link is greater than the corresponding preset threshold and the network delay is lower than the corresponding preset threshold, select the fixed - length splitting method and evenly split the packet into multiple sub - packets with a length not exceeding the maximum transmission length L max ;

[0016] If the bandwidth of the link is less than or equal to the corresponding preset threshold and the network delay is greater than or equal to the corresponding preset threshold, then calculate the maximum transmission length L avail of the split sub - packets according to the current available bandwidth B sub , and determine the size of each packet after splitting according to the following formula, expressed as:

[0017]

[0018] where T max is the maximum tolerance limit of the transmission delay, and N is the total number of packets to be transmitted in the current system.

[0019] Preferably, symmetric encryption technology is used to protect the data transmission process, which specifically includes: for each split data packet, select a symmetric encryption algorithm according to the encryption strength requirements and computing resources of the current system for encryption;

[0020] During the encryption process, an encryption key is generated. When encrypting each split data packet, use the selected symmetric encryption algorithm to encrypt the content of the data packet;

[0021] During the encryption process, the data packet is processed in blocks and encrypted block by block. Finally, the encrypted data packet is obtained. A key identifier and an encryption algorithm version number are attached to each encrypted data packet;

[0022] Send the encrypted data packet to the receiving end. During the transmission process, the data packet remains encrypted. After the receiving end receives the encrypted data packet, select the corresponding key according to the key identifier and the encryption algorithm version number, and verify its legality. The receiving end uses the corresponding symmetric key to decrypt the received data packet;

[0023] During the decryption process, the receiving end verifies the integrity of the data packet. Verify whether the data packet has been tampered with during the transmission process through the attached checksum. If the checksum is inconsistent, discard the data packet and request retransmission; if the checksum is consistent, use the symmetric key to decrypt the encrypted data and restore the original data content.

[0024] Preferably, it further includes: using a Markov chain model to predict the occurrence probability of a link failure. When the link quality drops to a preset threshold, switch to a backup link; after the link is switched, use a queuing model to schedule multiple data streams transmitted through the backup link, and adjust the transmission order and bandwidth allocation of the data streams.

[0025] Preferably, the dynamic priority sorting algorithm is expressed as:

[0026]

[0027] where P i represents the priority of the i-th data stream, S p represents the physical quantity of the power state, S f represents the physical quantity of the device failure data stream, S h represents the physical quantity of the device health state, ΔP represents the change in grid power, ΔV represents the change in voltage, P nom is the nominal power, representing the rated power value of the device under normal operating conditions, V nom is the nominal voltage, representing the rated voltage value of the device under normal operating conditions, T recover represents the time required for the power grid to recover from a disturbance, T maxrepresents the maximum recovery time of the power grid, α1 represents the sensitivity factor of the power grid recovery ability, T f represents the time after the fault occurs, ΔA f represents the change in the fault impact range, D f represents the severity of the fault; T max 、A max 、D max represent the maximum values of the fault time, impact range, and severity respectively; T h represents the temperature of the device, L h represents the load of the device, U h represents the service life of the device; T max 、L max 、U max represent the maximum allowable values of the device temperature, load, and service life;

[0028] Classifying data streams into high-priority data streams and low-priority data streams includes comparing the priority of the data stream calculated at each moment with a preset priority threshold; when the priority of the data stream at a certain moment exceeds the preset threshold, all information streams at that moment are judged as high-priority data streams; otherwise, they are judged as low-priority data streams.

[0029] Preferably, the specific process of predicting the health state of the satellite link using the extended Kalman filter algorithm is as follows:

[0030] Define the health state of the satellite link as a state vector; the state vector includes state variables of the link delay, bandwidth, and packet loss rate;

[0031] According to the dynamic change of the link health state, establish a state equation to describe the transition of the link state from the previous moment to the current moment, expressed as:

[0032] x k =Ax k-1 +Bu k +w k

[0033] where, x k is the link health state vector at time k, A is the state transition matrix, B is the control input matrix, u k is the control input, w k is the process noise;

[0034] Combine the real-time link quality data with the state vector for prediction, establish an observation equation to describe the relationship between the state variables and the observation data, expressed as:

[0035] z k =Hx k +v k

[0036] Among them, z k is the link quality data observation vector at time k, H is the observation matrix, and v k is the observation noise;

[0037] Based on the state equation and the observation equation, the extended Kalman filter algorithm is used to estimate the link health state. The extended Kalman filter algorithm adjusts the estimated value of the link health state through the prediction step and the update step;

[0038] In the prediction step, the link health state at the current time is predicted through the estimated value at the previous time. According to the link health state estimation at the previous time and the covariance matrix P k-1 , the link health state at the current time is predicted using the state equation, expressed as:

[0039]

[0040] The predicted state covariance matrix is expressed as:

[0041]

[0042] Among them, is the predicted value of the link health state at time k, is the predicted state covariance matrix, and Q is the process noise covariance matrix;

[0043] In the update step, according to the actual observation data z k and the predicted state value the link health state is updated using the Kalman gain matrix, expressed as:

[0044]

[0045] The updated state covariance matrix is:

[0046]

[0047] Among them, K k is the Kalman gain matrix, R is the observation noise covariance matrix, P k is the updated state covariance matrix, and I is the identity matrix;

[0048] By continuously iterating the prediction step and the update step, the estimated value of the link health state at each time is obtained representing the estimated values of link delay, bandwidth, and packet loss rate.

[0049] Preferably, the specific process of calculating the quality score of each link using the nonlinear programming algorithm is:

[0050] Based on the prediction results of the health status of the link, including the delay x of the link d , the bandwidth x b and the packet loss rate x l , define the link quality score Q i , expressed as:

[0051]

[0052] where C Shannon (x b ) represents the bandwidth evaluation function based on the Shannon channel capacity formula, x b is the estimated value of the link bandwidth, SNR is the signal-to-noise ratio, represents the impact of the link delay x d on the link quality, α2 is the sensitivity parameter of the delay, x d is the estimated value of the link delay, represents the impact of the packet loss rate x l on the link quality, α3 is the impact coefficient of the packet loss rate, x l is the estimated value of the packet loss rate of the link.

[0053] Preferably, use the nonlinear programming algorithm to optimize the selection of the link. The optimization goal is to maximize the sum of the link quality scores. Set the optimization objective function, expressed as:

[0054]

[0055] where x i is the decision variable, indicating whether to select the i-th link for data transmission;

[0056] If x i = 1, then select this link; if x i = 0, then do not select this link;

[0057] Set the dynamic constraint conditions, expressed as:

[0058]

[0059] where x b is the bandwidth of link i, B max is the maximum available bandwidth, x d is the delay of link i, T max is the maximum allowable delay, x l is the packet loss rate of link i, L max is the maximum acceptable packet loss rate;

[0060] Select the link with a quality score greater than the corresponding preset threshold for high-priority data stream transmission.

[0061] The present invention further discloses a short message communication system for a distribution network FTU device, which includes a memory and a processor connected to each other. A computer program is stored on the memory, and when the computer program is run by the processor, it executes the steps of the method described above.

[0062] Compared with the prior art, the advantages of the present invention are as follows:

[0063] In the short message communication method for the distribution network FTU device of the present invention, by introducing a link health status prediction mechanism and a dynamic priority scheduling algorithm, the link status can be monitored in real time, the link selection and the data flow transmission order can be automatically adjusted to ensure the timely transmission of high-priority data flows, thereby significantly improving the reliability and transmission efficiency of the system. In addition, by dynamically predicting the link quality and failure probability based on the non-linear programming algorithm and the Markov chain model, the link failure risk can be identified in advance and automatically switched to the backup link, effectively avoiding the delayed processing after the link failure occurs in the traditional technology. The adaptive splitting algorithm ensures that when the link bandwidth is insufficient, the data packets can be reasonably split and scheduled according to the current network conditions, optimizing the utilization rate of bandwidth resources; at the same time, the symmetric encryption technology is used to ensure the security of the data during the transmission process, preventing the data from being tampered with or leaked. The present invention as a whole improves the performance of the distribution network FTU device in link switching, data flow scheduling and bandwidth allocation. Description of the Drawings

[0064] Figure 1 It is a flow chart of the short message communication method for the distribution network FTU device of the present invention in an embodiment. Detailed Embodiments

[0065] The present invention will be further described below in conjunction with the specification drawings and specific embodiments.

[0066] As Figure 1 shown, the short message communication method for the distribution network FTU device provided by the embodiment of the present invention specifically includes the following steps:

[0067] S1. Real-time collect power status data flow, device failure data flow and device health status data flow from the distribution network FTU device (Feeder Terminal Unit);

[0068] S2. Preprocess the collected power status data flow, device failure data flow and device health status data flow, use denoising technology to remove noise, and convert the data flow into a unified format;

[0069] S3. Based on the preprocessed power status data flow, device failure data flow and device health status data flow, use the dynamic priority sorting algorithm to calculate the priority of each data flow, and classify the data flow into high-priority data flow and low-priority data flow;

[0070] S4. Monitor the real-time quality data of the communication link based on the Beidou-3 satellite system, and use the extended Kalman filter algorithm to predict the health status of the satellite link. The real-time quality data includes link delay, bandwidth, and packet loss rate.

[0071] S5. Based on the prediction result of the link health status, use the nonlinear programming algorithm to calculate the quality score of each link, and select the link for data stream transmission according to the score.

[0072] S8. For packets exceeding the maximum transmission length, use the adaptive splitting algorithm to split the packets into multiple small packets, and sort and transmit the split packets according to the priority of the data stream.

[0073] S11. Encrypt the split packets, use symmetric encryption technology to protect the data transmission process, and ensure the security of communication.

[0074] S14. Use the Markov chain model to predict the occurrence probability of link failures. When the link quality drops to the preset threshold, switch to the backup link.

[0075] S17. After the link switch, use the queuing model to schedule multiple data streams transmitted through the backup link, and adjust the transmission order and bandwidth allocation of the data streams.

[0076] In step S3, the dynamic priority sorting algorithm is expressed as:

[0077]

[0078]

[0079] where P i represents the priority of the i-th data stream, S p represents the physical quantity of the power state, S f represents the physical quantity of the device failure data stream, S h represents the physical quantity of the device health status, ΔP represents the change in grid power, ΔV represents the change in voltage, P nom is the nominal power, representing the rated power value of the device under normal operating conditions, V nom is the nominal voltage, representing the rated voltage value of the device under normal operating conditions, T recover represents the time required for the power grid to recover from the disturbance, T max represents the maximum recovery time of the power grid, α1 represents the sensitivity factor of the power grid recovery ability, T f represents the time after the fault occurs, ΔA f represents the change in the fault impact range, D f represents the severity of the fault; Tmax 、A max 、D max represent the maximum values of the failure time, the affected range, and the severity respectively; T h represents the temperature of the device, L h represents the load of the device, U h represents the service life of the device; T max 、L max 、U max represent the maximum allowable values of the device temperature, load, and service life;

[0080] Classifying data streams into high-priority data streams and low-priority data streams includes comparing the priority of the data stream calculated at each moment with a preset priority threshold. When the priority of the data stream at a certain moment exceeds the preset threshold, all the information streams at that moment are judged as high-priority data streams; otherwise, they are judged as low-priority data streams.

[0081] In step S4, the extended Kalman filter algorithm is used to predict the health state of the satellite link, including defining the health state of the satellite link as a state vector, and the state vector includes state variables of the link delay, bandwidth, and packet loss rate;

[0082] According to the dynamic change of the link health state, a state equation is established to describe the transition of the link state from the previous moment to the current moment, expressed as:

[0083] x k = Ax k-1 + Bu k + w k

[0084] where, x k is the link health state vector at time k, A is the state transition matrix, B is the control input matrix, u k is the control input, w k is the process noise;

[0085] Combining the real-time link quality data and the state vector for prediction, an observation equation is established to describe the relationship between the state variables and the observation data, expressed as:

[0086] z k = Hx k + v k

[0087] where, z k is the link quality data observation vector at time k, H is the observation matrix, v k is the observation noise.

[0088] Based on the state equation and the observation equation, the extended Kalman filter algorithm is used to estimate the link health state. The extended Kalman filter algorithm adjusts the estimated value of the link health state through the prediction step and the update step;

[0089] In the prediction step, the link health state at the current moment is predicted through the estimated value at the previous moment, and the link health state is estimated based on the previous moment and the covariance matrix P k-1 , and the state equation is used to predict the link health state at the current moment, expressed as:

[0090]

[0091] The predicted state covariance matrix is expressed as:

[0092]

[0093] where is the predicted value of the link health state at time k, is the predicted state covariance matrix, and Q is the process noise covariance matrix;

[0094] In the update step, according to the actual observation data z k and the predicted state value the link health state is updated using the Kalman gain matrix, expressed as:

[0095]

[0096] The updated state covariance matrix is:

[0097]

[0098] where K k is the Kalman gain matrix, R is the observation noise covariance matrix, P k is the updated state covariance matrix, and I is the identity matrix;

[0099] By continuously iterating the prediction step and the update step, the estimated value of the link health state at each moment is obtained representing the estimated values of link delay, bandwidth, and packet loss rate.

[0100] In step S5, the nonlinear programming algorithm is used to calculate the quality score of each link, including according to the prediction result of the link health state, including the link delay x d , bandwidth x b and packet loss rate x l , and the link quality score Q i is defined and expressed as:

[0101]

[0102] Among them, C Shannon (x b ) represents the bandwidth evaluation function based on the Shannon channel capacity formula, where x b is the bandwidth estimation value of the link, SNR is the signal-to-noise ratio, represents the impact of the link delay x d on the link quality, α2 is the sensitivity parameter of the delay, and x d is the delay estimation value of the link. represents the impact of the packet loss rate x l on the link quality, α3 is the impact coefficient of the packet loss rate, and x l is the packet loss rate estimation value of the link.

[0103] Furthermore, the non-linear programming algorithm is used to optimize the selection of the link. The optimization objective is to maximize the sum of the link quality scores. The optimization objective function is set as follows:

[0104]

[0105] Among them, x i is the decision variable, indicating whether to select the i-th link for data transmission;

[0106] If x i = 1, then select this link; if x i = 0, then do not select this link;

[0107] The dynamic constraint conditions are set as follows:

[0108]

[0109]

[0110] Among them, x b is the bandwidth of link i, B max is the maximum available bandwidth, x d is the delay of link i, T max is the maximum allowable delay, x l is the packet loss rate of link i, L max is the maximum acceptable packet loss rate;

[0111] Select the link with a quality score greater than the preset threshold for high-priority data stream transmission.

[0112] In step S6, the adaptive splitting algorithm is used, including detecting whether the length of the data packet to be transmitted exceeds the set maximum transmission length L max , if the length L of the data packet ≤ L max, then the data packet can be directly transmitted without splitting. If the length L of the data packet > L max , then it enters the data packet splitting process;

[0113] If the bandwidth of the link is greater than the preset threshold and the network latency is lower than the preset threshold, select the fixed-length splitting method and evenly split the data packet into multiple sub-packets with a length not exceeding the maximum transmission length L max ;

[0114] If the bandwidth of the link is less than or equal to the preset threshold and the network latency is greater than or equal to the preset threshold, then calculate the maximum transmission length L of the split sub-packets according to the current available bandwidth B avail and determine the size of each packet after splitting according to the following formula, expressed as: sub where T

[0115]

[0116] is the maximum tolerance time limit of the transmission delay, and N is the total number of data packets to be transmitted in the current system. max ;

[0117] In step S7, using symmetric encryption technology to protect the data transmission process includes, for each split data packet, selecting a symmetric encryption algorithm for encryption according to the encryption strength requirements and computing resources of the current system;

[0118] During the encryption process, generate an encryption key. When encrypting each split data packet, use the selected symmetric encryption algorithm to encrypt the data packet content;

[0119] During the encryption process, perform block processing on the data packet and encrypt each block one by one. Finally, obtain the encrypted data packet, and attach a key identifier and an encryption algorithm version number to each encrypted data packet;

[0120] Send the encrypted data packet to the receiving end. During the transmission process, the data packet remains encrypted. After the receiving end receives the encrypted data packet, select the corresponding key according to the key identifier and the encryption algorithm version number and verify its legality. The receiving end uses the corresponding symmetric key to decrypt the received data packet;

[0121] During the decryption process, the receiving end verifies the integrity of the data packet. Verify whether the data packet has been tampered with during the transmission process through the attached checksum. If the checksum is inconsistent, discard the data packet and request retransmission. If the checksum is consistent, use the symmetric key to decrypt the encrypted data and restore the original data content.

[0122] The short message communication method for the distribution network FTU equipment of the present invention, by introducing a link health status prediction mechanism and a dynamic priority scheduling algorithm, can monitor the link status in real time, automatically adjust the link selection and data stream transmission order, and ensure the timely transmission of high-priority data streams, thereby significantly improving the reliability and transmission efficiency of the system. In addition, by dynamically predicting the link quality and failure probability based on a nonlinear programming algorithm and a Markov chain model, it is possible to identify the risk of link failure in advance and automatically switch to a backup link, effectively avoiding the delayed processing after the link failure occurs in traditional technologies. The adaptive splitting algorithm ensures that when the link bandwidth is insufficient, the data packets can be reasonably split and scheduled according to the current network conditions, thereby optimizing the utilization rate of bandwidth resources; at the same time, the use of symmetric encryption technology ensures the security of the data during transmission and prevents data from being tampered with or leaked. The present invention overall improves the performance of the distribution network FTU equipment in link switching, data stream scheduling, and bandwidth allocation.

[0123] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0124] like Figure 1 As shown, the short message communication method for distribution network FTU equipment provided by the embodiment of the present invention specifically includes the steps of:

[0125] Step 1: Collect power status data stream, equipment fault data stream and equipment health status data stream from the distribution network FTU equipment in real time; the power status data stream includes power change and voltage change, etc.; the equipment fault data stream includes the time T after the fault occurs. f , the change in the fault impact range ΔA f , the severity of the fault D f , the sensitivity factor of the power grid recovery capability α1, etc.; the equipment health status data stream includes the temperature T of the equipment h , Equipment load L h and equipment service life U h ;

[0126] Step 2: Preprocess the collected power status data stream, equipment fault data stream, and equipment health status data stream, remove noise using denoising technology, and convert the data stream into a unified format;

[0127] Step 3: Based on the pre-processed power status data stream, equipment fault data stream, and equipment health status data stream, a dynamic priority sorting algorithm is used to calculate the priority of each data stream and classify the data streams into high-priority data streams and low-priority data streams.

[0128] Specifically, the dynamic priority sorting algorithm is expressed as:

[0129]

[0130] Among them, P i represents the priority of the i-th data stream, and S p represents the physical quantity of the power state, and S f represents the physical quantity of the device fault data stream, and S h represents the physical quantity of the device health state. ΔP represents the change in grid power, and ΔV represents the change in voltage. P nom is the nominal power, which represents the rated power value of the device under normal operating conditions, and V nom is the nominal voltage, which represents the rated voltage value of the device under normal operating conditions, and T recover represents the time required for the power grid to recover from a disturbance, and T max represents the maximum recovery time of the power grid, and α1 represents the sensitivity factor of the power grid recovery ability, and T f represents the time after a fault occurs, and ΔA f represents the change in the fault impact range, and D f represents the severity of the fault; T max and A max and D max respectively represent the maximum values of the fault time, impact range, and severity; T h represents the temperature of the device, and L h represents the load of the device, and U h represents the service life of the device; T max and L max and U max respectively represent the maximum allowable values of the device temperature, load, and service life;

[0131] Classifying the data stream into high-priority data stream and low-priority data stream specifically includes: comparing the priority of the data stream calculated at each moment with a preset priority threshold; when the priority of the data stream at a certain moment exceeds the preset threshold, all the information streams at that moment are judged as high-priority data streams; otherwise, they are judged as low-priority data streams.

[0132] It should be noted that in the physical quantity S f of the device fault information stream, some difficult-to-define parameters need a clear calculation method. For example, the time T f after a fault occurs, the change ΔA f in the fault impact range, the severity D f of the fault, the sensitivity factor α1 of the power grid recovery ability, etc., are all obtained through a specific power grid monitoring and evaluation system.

[0133] The time T fIt is the time span from the occurrence of a fault to the current moment. This time is usually calculated from the time difference between the occurrence moment of the fault event recorded by the distribution network monitoring system and the time when the system detects this event. The fault event is triggered by circuit breakers, relays, substation control systems, etc. The monitoring system will record the exact moment of the fault occurrence, and the time of the system response is recorded and used for calculating T f as the basis.

[0134] The change in the fault impact scope ΔA f is used to represent the expansion of the grid equipment or area affected after the fault occurs. This parameter is estimated through the automatic reconfiguration system of the distribution network. After a fault occurs, the grid will quickly cut off the fault area through automation equipment (such as automatic switches, relays, automatic power-off devices, etc.). The system evaluates the affected equipment and areas based on power flow analysis and real-time monitoring data, and determines the fault impact scope through the grid topology map. The size of the fault area and the degree of change in the power flow can be obtained through the distribution network management system.

[0135] The severity of the fault D f is a quantitative description of the degree of fault impact. This value is usually calculated by combining multiple factors. First, it is classified according to the fault type (such as short circuit, grounding, equipment failure, etc.), and the degree of load loss caused by the fault is evaluated. The load loss can be calculated by monitoring the output power of grid equipment, and the system obtains the working state and load data of the equipment in real time. Secondly, the degree of equipment damage also affects the severity assessment. According to the equipment type and historical fault data, the degree of damage caused by the fault can be calculated, which includes the influence of factors such as equipment temperature, load, and fault type. Finally, the system stability analysis tool can simulate the impact of the fault on the stability of the entire grid according to the grid topology structure and the location where the fault occurs.

[0136] The sensitivity factor α1 of the grid restoration ability is used to adjust the influence of the grid restoration time on the priority ranking. This factor represents the relationship between the restoration speed and the grid load fluctuation during the grid restoration process. Specifically, after the grid encounters external disturbances, its restoration time is closely related to the grid load fluctuation and the complexity of the network structure. The sensitivity factor α1 of the restoration ability is obtained based on historical data and the grid performance evaluation model. Usually, by analyzing the past grid restoration time data, calculating the restoration efficiency of the grid under different loads and fault types, and then determining the value of this factor.

[0137] The physical quantity S of the power state information flow pAmong them, the power change ΔP and the voltage change ΔV are calculated based on the data of the power grid real-time monitoring system. The power change is obtained by monitoring the power flow of each node in the power grid, and the voltage change is obtained by real-time monitoring the data of the voltage sensor. The recovery ability of the power grid is represented by the time required for the power grid to recover from the fault state to the stable state, and this time value T recover is calculated through the response time of the power grid automatic recovery system. The system will record the timestamps during the recovery process and calculate the time required from the occurrence of the fault to the system stability.

[0138] The physical quantity S of the device health status information flow h Among them, the temperature T of the device h is the real-time data obtained through the temperature sensor. Usually, the device is equipped with an internal temperature sensor to monitor the working temperature of the device in real time. The device load L h is calculated according to the load condition and power flow of the power device and can be obtained in real time through the load monitoring device of the power grid monitoring system. The device service life U h is calculated based on the installation time and usage cycle of the device. Usually, the device management system records the commissioning time of the device and evaluates the health status of the device according to the change of the device service life.

[0139] Step 4: Monitor the real-time quality data of the communication link based on the Beidou-3 satellite system, and use the extended Kalman filter algorithm to predict the health status of the satellite link; the real-time quality data includes link delay, bandwidth, and packet loss rate;

[0140] Specifically, first, define the state vector of the link health status. This state vector contains three items: link delay, bandwidth, and packet loss rate, which respectively represent the response delay, transmission capacity, and data loss situation of the link. Define the state vector of the link health status as:

[0141]

[0142] Among them, x delay,k represents the link delay at time k, measuring the communication delay from the source device to the target device; x bandwidth,k represents the link bandwidth at time k, measuring the transmission capacity of the communication link; x loss,k represents the link packet loss rate at time k, measuring the proportion of data lost during transmission.

[0143] The health status of the link changes over time, and the state vector describes its dynamic changes through the state equation. Assuming that the link state at time k is affected by the state at the previous time k-1 and external factors (such as power grid load changes), the state equation is:

[0144] x k = Ax k-1+Bu k +w k

[0145] where x k is the link health state vector at time k, including the link delay, bandwidth, and packet loss rate; A is the state transition matrix, which describes the change law of the link state from the previous time k - 1 to the current time k. It is usually determined based on historical data or system modeling and represents the evolution characteristics of the link performance over time; B is the control input matrix, indicating the influence of external factors on the link state; external factors can include factors such as network load and environmental changes; u k is the control input, representing the influence on the link by the external environment (such as changes in power grid load, network traffic, etc.); w k is the process noise, which describes the uncertainty or error in the model. It is usually assumed to be Gaussian noise with zero mean.

[0146] To be able to update the health state based on the actual observed data of the link (such as link delay, bandwidth, packet loss rate), an observation equation is defined to relate the state variables of the link to the actual observed values. The observation equation is:

[0147] z k = Hx k + v k

[0148] where z k is the link quality observation vector at time k, including the actually observed link delay, bandwidth, and packet loss rate; H is the observation matrix, which describes the relationship between the link health state vector and the observed data. The observation matrix is used to convert the state vector into the actual observed data. This matrix may be an identity matrix or other forms, depending on the relationship between the link state and the observed data, v k is the observation noise, representing the measurement error of the link quality data. It is usually assumed to be Gaussian noise with zero mean.

[0149] Based on the above state equation and observation equation, the extended Kalman filter algorithm is used to estimate the link health state. The extended Kalman filter algorithm adjusts the estimated value of the link health state step by step through two steps: prediction and update:

[0150] Prediction step: In this stage, the link health state at the current time is predicted through the estimated value at the previous time. According to the link health state estimate at the previous time and the covariance matrix P k-1 , the state equation is used to predict the link health state at the current time:

[0151]

[0152] The predicted state covariance matrix is:

[0153]

[0154] in, is the link health status prediction value at time k. This value is based on the state estimation at the previous moment. Calculated by the state transfer matrix A, is the predicted state covariance matrix, which represents the estimate of the prediction error. It reflects the uncertainty of the link state predicted by the state equation. Q is the process noise covariance matrix, which represents the uncertainty or error in the model.

[0155] Update step: According to the actual observation data z k and the predicted state value The link health status is updated using the Kalman gain matrix. The updated estimate and covariance matrix are:

[0156]

[0157] The updated state covariance matrix is:

[0158]

[0159] Among them, K k is the Kalman gain matrix, which represents the influence of the current observation data on the state update. The Kalman gain determines the weight between the observation data and the predicted state to minimize the estimation error. R is the observation noise covariance matrix, which represents the uncertainty of the measurement data. It is usually assumed that the observation noise is zero-mean Gaussian noise. k is the updated state covariance matrix, representing the uncertainty of the current state estimate. The state estimate is updated using the Kalman gain and observations to reduce uncertainty. I is the identity matrix, which is used to correct the covariance matrix update. The identity matrix I ensures the positive definiteness of the state covariance matrix and prevents numerical instability during the estimation process.

[0160] By continuously iterating the above prediction and update steps, the estimated value of the link health status at each moment is obtained That is, the estimated values of the link's delay, bandwidth, and packet loss rate. The estimated values at each moment will serve as input for link quality scoring and optimization selection in subsequent steps.

[0161] Step 5: Based on the link health status prediction results, a nonlinear programming algorithm is used to calculate the quality score of each link, and a link is selected for data flow transmission based on the score;

[0162] Specifically, based on the health status prediction results of the link, including the link delay x d , bandwidth x b and packet loss rate xl , define the link quality score Q i , expressed as:

[0163]

[0164] where C Shannon (x b ) represents the bandwidth evaluation function based on the Shannon channel capacity formula; x b is the estimated value of the link bandwidth; SNR is the signal-to-noise ratio; represents the impact of the link delay x d on the link quality, α2 is the sensitivity parameter of the delay, x d is the estimated value of the link delay, represents the impact of the packet loss rate x l on the link quality, α3 is the impact coefficient of the packet loss rate, x l is the estimated value of the packet loss rate of the link.

[0165] It should be noted that the calculation formula of the signal-to-noise ratio SNR is:

[0166]

[0167] where P signal =P t is the signal power, P t is the transmission power of the transmitter, P noise =kTB is the noise power, where k is the Boltzmann constant, T is the temperature, B is the system bandwidth, and F is the receiver noise factor, indicating the amplification degree of the receiver to the noise.

[0168] Use the nonlinear programming algorithm to perform the optimal selection of the link. The optimization goal is to maximize the sum of the link quality scores. Set the optimization objective function, expressed as:

[0169]

[0170] where x i is the decision variable, indicating whether to select the i-th link for data transmission;

[0171] If x i =1, then select this link; if x i =0, then do not select this link;

[0172] Set the dynamic constraint condition, expressed as:

[0173]

[0174]

[0175] where xb is the bandwidth of link i, B max is the maximum available bandwidth, x d is the delay of link i, T max is the maximum allowable delay, x l is the packet loss rate of link i, L max is the maximum acceptable packet loss rate;

[0176] Select links with a quality score greater than a preset threshold for high-priority data stream transmission.

[0177] Step 6: For packets exceeding the maximum transmission length, use an adaptive splitting algorithm to split the packets into multiple small packets, and sort and transmit the split packets according to the priority of the data stream;

[0178] Specifically, during the packet transmission process, detect whether the length of the packet to be transmitted exceeds the set maximum transmission length L max , if the length L of the packet ≤ L max , then the packet can be directly transmitted without splitting. If the length L of the packet > L max , then enter the packet splitting process;

[0179] If the bandwidth of the link is greater than the preset threshold and the network delay is lower than the preset threshold, select the fixed-length splitting method and evenly split the packet into multiple sub-packets with a length not exceeding the maximum transmission length L max of sub-packets;

[0180] If the bandwidth of the link is less than or equal to the preset threshold and the network delay is greater than or equal to the preset threshold, then calculate the maximum transmission length L avail of the split sub-packets according to the current available bandwidth B sub , and determine the size of each split packet according to the following formula, expressed as:

[0181]

[0182] where T max is the maximum tolerance time limit of the transmission delay, and N is the total number of packets to be transmitted in the current system.

[0183] Add reconstruction information to each split sub-packet. The reconstruction information includes the packet sequence number, total number of packets, current packet number, and checksum information;

[0184] According to the priority of the data stream, the split sub - data packets will be transmitted in the order of priority. High - priority data streams will be transmitted first. If there are multiple high - priority data streams, the split data packets will be queued according to the priority level and time sequence. Low - priority data streams will be scheduled according to the availability of bandwidth to ensure their transmission when network resources permit.

[0185] The receiving end restores the order of the data packets according to the Header information of the sub - data packets and verifies the integrity of the data packets using the checksum. If a data packet is lost or in error, the system will request the lost data packet again to ensure reliable data transmission.

[0186] Through this adaptive splitting algorithm, the system can dynamically adjust the splitting method of data packets according to the real - time load of the network and the priority of the data stream, ensuring that high - priority data streams can be transmitted first, while maximizing the data transmission efficiency, reducing link congestion, and ensuring the integrity and reliability of the data.

[0187] Step 7: Encrypt the split data packets, use symmetric encryption technology to protect the data transmission process, and ensure the security of communication;

[0188] Specifically, first, for each split data packet, select a suitable symmetric encryption algorithm for encryption. The encryption algorithms include AES (Advanced Encryption Standard) or DES (Data Encryption Standard). The choice of encryption algorithm is based on the current system's encryption strength requirements and computing resources. If the security requirements of the data stream are high, the AES algorithm is preferred; if the system has high requirements for encryption computing resources, the DES algorithm is selected.

[0189] During the encryption process, to ensure the confidentiality and security of the data, an encryption key is generated. There are two ways to generate the encryption key, and the specific selection method depends on the system's key management scheme. The first is the fixed - key scheme, where a fixed key is shared in advance between the distribution network FTU device and the receiving - end device for encrypting all data packets. The second is the dynamic - key generation scheme, where a new encryption key is generated based on a pre - shared seed value before each data transmission and is only valid for the current data - packet transmission. By this means, the security of the key is improved and the risk of key leakage is reduced.

[0190] When encrypting each split data packet, use the selected symmetric encryption algorithm to encrypt the data - packet content to ensure that the data cannot be read or tampered with by a third party during transmission. During the encryption process, the data packet is processed in blocks and encrypted block by block, and finally the encrypted data packet is obtained. Each encrypted data packet will be appended with encryption information, including the key identifier and the encryption - algorithm version number, to ensure that the receiving end can correctly decrypt the data packet.

[0191] The encrypted data packet is sent to the receiving end. During the transmission process, the data packet remains encrypted to ensure the confidentiality of the data. After receiving the encrypted data packet, the receiving end first selects the corresponding key according to the key identifier and the encryption algorithm version number, and verifies its legality. The receiving end uses the corresponding symmetric key to decrypt the received data packet.

[0192] During the decryption process, first, the receiving end verifies the integrity of the data packet by verifying the attached checksum to check if the data packet has been tampered with during transmission. If the checksum does not match, the data packet is discarded and a retransmission is requested. If the checksum matches, the encrypted data is decrypted using the symmetric key to restore the original data content.

[0193] To ensure the integrity of the data during transmission, after decryption, the receiving end recalculates the checksum and verifies it again. If it is found that the data packet has been lost or damaged during transmission, the system requests the sending end to retransmit the missing part through the retransmission mechanism. This process ensures the reliable transmission and integrity of the data.

[0194] By using symmetric encryption technology, this solution can ensure the confidentiality, integrity, and anti-tampering of data during transmission, avoid malicious tampering or theft of data, and guarantee the communication security of the FTU devices in the distribution network.

[0195] Step 8: Use the Markov chain model to predict the occurrence probability of link failures. When the link quality drops to the preset threshold, switch to the backup link;

[0196] Specifically, the health state S of the link is divided into multiple discrete states, usually including the following states:

[0197] Normal state: The delay, bandwidth, and packet loss rate of the link are all within the normal range;

[0198] Slight fault state: The link has a slight increase in delay, a decrease in bandwidth, or an increase in packet loss rate, but it has little impact on data transmission;

[0199] Severe fault state: The link has an excessive delay, a too low bandwidth, or a packet loss rate reaching an unacceptable level, resulting in unstable data transmission or even interruption.

[0200] Define each state S i as a discrete state of the link, where S0 is the normal state, S1 is the slight fault state, and S2 is the severe fault state.

[0201] Use the Markov chain to describe the health state transition of the link. The health state transition of the link is described by the following transition probability matrix P:

[0202]

[0203] Among them, P ij represents the probability of transferring from state S i to state S j .

[0204] The specific transition probability is determined by the following factors:

[0205] Link delay x d : When the delay increases, the transition probability of the link state increases, especially the transition probability from the normal state to the faulty state.

[0206] Bandwidth x b : When the bandwidth decreases, the link quality deteriorates, especially the transition probability from the normal state or the slightly faulty state to the severely faulty state increases.

[0207] Packet loss rate x l : When the packet loss rate increases, the probability of the link failing increases sharply.

[0208] The calculation of the transition probability is based on the real-time parameters of the link and is deduced in combination with historical data. For each state transition P ij , it can be calculated through the following steps:

[0209] An increase in the link delay x d affects the state transition probability. The delay sensitivity function f d (x d ) is used to quantify the impact of the delay on the state transition. Assume the delay factor f d (x d ) is:

[0210]

[0211] Among them, α d is the threshold parameter of the delay, representing the maximum delay of the normal link.

[0212] When the link bandwidth x b decreases, the tolerance of the system will decrease, affecting the probability of the link failure. The bandwidth factor f b (x b ) can be expressed as:

[0213]

[0214] Among them, α b is the maximum bandwidth value configured by the system, representing the proportion of the impact of the bandwidth decrease on the link failure.

[0215] When the packet loss rate x l increases, the stability of the link drops sharply. The packet loss rate factor f l (xl ) is defined as:

[0216]

[0217] Among them, α l and β l They are the sensitivity and threshold of packet loss rate to link failure.

[0218] These factors f d (x d ),f b (x b ) and f l (x l ) is combined into the probability of each state transition, and the specific calculation formula is as follows:

[0219] The probability P of transitioning from the normal state S0 to the minor fault state S1 01 It can be expressed as:

[0220] P 01 =f d (x d )·f b (x b )·f l (x l )

[0221] The probability P of transitioning from the normal state S0 to the severe fault state S2 02 It can be expressed as:

[0222] P 02 =(1-f d (x d ))·(1-f b (x b ))·(1-f l (x l ))

[0223] Similarly, the transition probability from the minor fault state S1 to other states can also be calculated in a similar way.

[0224] The failure probability of the link P fail It refers to the probability of a link transitioning from a normal state S0 to a severe fault state S2. The probability of a link failure can be calculated using the steady-state probability of the Markov chain. Assuming that the state transition matrix P of the Markov chain model is a constant matrix, the steady-state probability π satisfies:

[0225] πP=π

[0226] Among them, π is the steady-state probability vector, which represents the long-term stable probability of each state. By solving the steady-state probability, the probability of link failure P can be calculated. fail, that is, the probability that the link is in a severe failure state.

[0227] When the failure probability P of the link health status fail exceeds the preset failure threshold P threshold , the link is automatically switched. Switch to the backup volume score and the real-time link health status for decision-making.

[0228] Step 9: After the link is switched, use the M / M / c queuing model to schedule multiple data streams transmitted through the backup link, and adjust the transmission order and bandwidth allocation of the data streams.

[0229] Specifically, after the link is switched to the backup link, use the M / M / c queuing model to schedule and optimize multiple data streams passing through the backup link. This queuing model is applicable to the scenario of multiple service desks (service channels), where each service channel represents an independent data stream transmission channel on the backup link. Through this model, dynamically adjust the transmission order, bandwidth allocation and priority of multiple data streams to ensure the efficient use of network resources. The specific implementation process is as follows:

[0230] The M / M / c queuing model is used to describe the data stream scheduling situation of multiple service channels, where M represents that the arrival process conforms to the Poisson distribution, the service process conforms to the exponential distribution, and c is the number of service channels.

[0231] The number of service channels c of the backup link is determined by the parallel transmission capacity of the link, indicating the maximum number of data streams that the backup link can process simultaneously.

[0232] The arrival rate λ i represents the rate at which the i-th data stream arrives at the backup link. The arrival rate λ i is determined by the generation rate of the data stream or the load of the receiving end.

[0233] The service rate μ i represents the service rate of the backup link for each data stream, usually determined by the bandwidth of the backup link and the number of service channels c. The service rate formula is:

[0234]

[0235] [[ID=ID=37]]Among them, B backup is the total bandwidth of the backup link, and c is the number of service channels, indicating the concurrent capacity of the link. The transmission rate of each service channel is proportional to the link bandwidth allocation.

[0236] According to the status of the backup link after the link is switched, schedule according to the priority of each data stream. The priority of the data stream is calculated by the dynamic priority sorting algorithm. According to the priority P of the data stream i sort the data streams and transmit them according to the following rules:

[0237] High-priority data streams are transmitted first, giving priority to higher-priority streams to ensure low-latency transmission of critical data streams; low-priority data streams are transmitted when there is sufficient remaining bandwidth.

[0238] By prioritizing data flows, it is possible to ensure that high-priority data flows are transmitted first when backup link resources are limited, reducing the impact of low-priority flows on network transmission.

[0239] In the backup link, bandwidth resource B backup The bandwidth is limited, so it is necessary to dynamically adjust bandwidth allocation based on the current network load and data flow priority. The following bandwidth allocation strategies are used to ensure the transmission efficiency of data flows:

[0240] Bandwidth is allocated based on the priority of data flows. High-priority data flows are given more bandwidth to ensure timely transmission.

[0241] When the link load is high, the bandwidth allocation is adjusted by adjusting the number of service channels c and the service rate μ to ensure that all data flows obtain reasonable bandwidth resources.

[0242] When the available bandwidth of the link is B backup When it is not enough to process all data streams at the same time, the size of each data stream L i and priority P i , reasonably allocate bandwidth. For low-priority data flows, the bandwidth allocation ratio will be reduced to ensure the timely transmission of high-priority flows.

[0243] The arrival process of each data flow follows a Poisson distribution, and the service process follows an exponential distribution. The M / M / c queuing model dynamically calculates the queuing time and service time for each data flow. This model allows us to predict the waiting time and transmission time of each data flow, thereby optimizing the queuing order and bandwidth allocation of data flows.

[0244] According to the queuing model, the transmission time of the data flow is T i The calculation formula is:

[0245]

[0246] Among them, L i is the size of the i-th data stream (unit: bit), μ i The service rate for this data stream. Multiple data streams share the bandwidth of the backup link. Bandwidth allocation and queue scheduling are performed based on the current network load and the size of each data stream, ensuring that all data streams are transmitted according to priority and bandwidth resource allocation order.

[0247] When the standby link experiences a situation of excessive load, the load can be balanced by increasing the number of service channels c of the standby link or adjusting the bandwidth allocation scheme, so as to improve the transmission capacity of the link. Monitor the load and health status of the standby link to ensure that the link can perform reasonable resource allocation according to the network load.

[0248] If the bandwidth B of the standby link backup is insufficient, other standby links will be enabled or the bandwidth allocation will be increased.

[0249] When the link is in good health status and the bandwidth is sufficient, multiple parallel service channels are preferentially selected to ensure the fast transmission of data streams.

[0250] After all data streams are transmitted, all data streams in the current link will be cleared and the next round of data stream scheduling will be entered. After each data stream is transmitted, information such as transmission delay and bandwidth utilization rate is recorded for subsequent link optimization and performance evaluation.

[0251] The short message communication method of the distribution network FTU device provided by the present invention can identify the link failure risk in advance and automatically switch to the standby link, effectively avoiding the delayed processing after the link failure in the traditional technology.

[0252] The embodiments of the present invention also provide a computer program product, including a computer program, and the computer program executes the steps of the above-mentioned method when being run by a processor. The embodiments of the present invention further disclose a computer-readable storage medium, on which a computer program is stored, and the computer program executes the steps of the above-mentioned method when being run by a processor. The embodiments of the present invention also disclose a computer device, including a memory and a processor connected to each other, and a computer program is stored on the memory, and the computer program executes the steps of the above-mentioned method when being run by a processor. The products, media and systems of the present invention correspond to the above-mentioned method and have the same advantages as those of the above-mentioned method.

[0253] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0254] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0255] More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memories), fiber optic devices, and portable compact disc read-only memories (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or otherwise processing it as necessary, and then storing it in a computer memory.

[0256] It should be understood that each part of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following techniques well known in the art or a combination thereof can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0257] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, several improvements and refinements made without departing from the principle of the present invention should be regarded as within the protection scope of the present invention.

Claims

1. A short message communication method for a distribution network FTU device, characterized in that, Including the steps: Obtain the power status data stream, device failure data stream, and device health status data stream in the distribution network FTU device; Preprocess the power status data stream, device failure data stream, and device health status data stream, remove noise and convert the data stream into a unified format; Based on the preprocessed power status data stream, device failure data stream, and device health status data stream, use the dynamic priority sorting algorithm to calculate the priority of each data stream, and classify the data stream into high-priority data stream and low-priority data stream; Monitor the real-time quality data of the communication link based on the Beidou-3 satellite system, use the extended Kalman filter algorithm to predict the health status of the satellite link, and obtain the link health status prediction result; The real-time quality data includes link delay, bandwidth, and packet loss rate; Based on the link health status prediction result, use the nonlinear programming algorithm to calculate the quality score of each link, and select the link for data stream transmission according to the score.

2. The short message communication method for the distribution network FTU device according to claim 1, wherein, During the data stream transmission, for the packet exceeding the maximum transmission length, use the adaptive splitting algorithm to split the packet into multiple small packets, and sort and transmit the split packets according to the priority of the data stream; encrypt the split packets, and use the symmetric encryption technology to protect the data transmission process to ensure the security of communication.

3. The short message communication method for distribution network FTU equipment according to claim 2, characterized in that: The specific process of using the adaptive splitting algorithm to split the packet into multiple small packets is: During the data packet transmission process, detect whether the length L of the data packet to be transmitted exceeds the set maximum transmission length L max , if the length L of the data packet satisfies L ≤ L max , then the data packet is directly transmitted without splitting; if the length L of the data packet satisfies L > L max , then enter the data packet splitting process; If the bandwidth of the link is greater than the corresponding preset threshold and the network latency is lower than the corresponding preset threshold, select the fixed-length splitting method to evenly split the data packet into multiple sub-packets with a length not exceeding the maximum transmission length L max ; If the bandwidth of the link is less than or equal to the corresponding preset threshold and the network delay is greater than or equal to the corresponding preset threshold, then according to the current available bandwidth B avail calculate the maximum transmission length L of the sub-packets after splitting sub , and determine the size of each packet after splitting according to the following formula, expressed as: Among them, T max is the maximum tolerable time limit of transmission delay, and N is the total number of data packets to be transmitted in the current system.

4. The short message communication method for FTU equipment in the distribution network according to claim 3, characterized in that: Using the symmetric encryption technology to protect the data transmission process specifically includes: for each split packet, select the symmetric encryption algorithm for encryption according to the current system's encryption strength requirement and computing resources; During the encryption process, generate the encryption key, and when encrypting each split packet, use the selected symmetric encryption algorithm to encrypt the packet content; During the encryption process, perform block processing on the packet, encrypt each block one by one, and finally obtain the encrypted packet. The key identifier and encryption algorithm version number are attached to each encrypted packet; Send the encrypted packet to the receiving end. During the transmission process, the packet remains encrypted. After the receiving end receives the encrypted packet, select the corresponding key according to the key identifier and encryption algorithm version number, and verify its legality. The receiving end uses the corresponding symmetric key to decrypt the received packet; During the decryption process, the receiving end verifies the integrity of the packet, and verifies whether the packet is tampered with during the transmission process through the attached checksum. If the checksum is inconsistent, discard the packet and request retransmission; if the checksum is consistent, use the symmetric key to decrypt the encrypted data and restore the original data content.

5. The short message communication method for FTU equipment in a distribution network according to any one of claims 1 to 4, characterized in that: It also includes: Use the Markov chain model to predict the occurrence probability of link failure. When the link quality drops to the preset threshold, switch to the standby link; after the link switch, use the queuing model to schedule multiple data streams transmitted through the standby link, and adjust the transmission order and bandwidth allocation of the data stream.

6. The short message communication method for FTU equipment in a distribution network according to any one of claims 1 to 4, characterized in that: The dynamic priority sorting algorithm is expressed as: Among them, P i Indicates the priority of the i-th data flow, S p Represents the physical quantity of power state, S f The physical quantity representing the device failure data flow, S h The physical quantity that indicates the health status of the equipment, ΔP indicates the change in grid power, ΔV indicates the change in voltage, P nom Is the nominal power, which indicates the rated power value of the device under normal working conditions, V nom It is the nominal voltage, which indicates the rated voltage value of the equipment under normal working conditions. recover It represents the time required for the power grid to recover from disturbance, T max represents the maximum recovery time of the power grid, α1 represents the sensitivity factor of the power grid recovery capability, T f Indicates the time after the fault occurs, ΔA f Indicates the change in the scope of fault impact, D f Indicates the severity of the fault; T max , A max , D max Represents the maximum value of fault time, impact range and severity respectively; T h Indicates the temperature of the device, L h Indicates the load of the equipment, U h Indicates the service life of the equipment; T max , L max , U max Indicates the maximum allowable values of equipment temperature, load and service life; Classifying data streams into high-priority data streams and low-priority data streams includes comparing the priority of the data stream calculated at each moment with a preset priority threshold; when the priority of the data stream at a certain moment exceeds the preset threshold, all information streams at that moment are judged as high-priority data streams; otherwise, they are judged as low-priority data streams.

7. The method for short message communication of a distribution network FTU device according to any one of claims 1 to 4, characterized in that: The specific process of predicting the health status of a satellite link using the extended Kalman filter algorithm is as follows: Define the health status of the satellite link as a state vector; the state vector includes state variables of the link's delay, bandwidth, and packet loss rate; According to the dynamic changes in the link health status, establish a state equation to describe the transition of the link status from the previous moment to the current moment, expressed as: x k = Ax k-1 + Bu k + w k where x k is the link health state vector at time k, A is the state transition matrix, B is the control input matrix, u k is the control input, and w k is the process noise; Combine the real-time link quality data with the state vector for prediction, and establish an observation equation to describe the relationship between the state variables and the observation data, expressed as: z k = Hx k + v k where z k is the link quality data observation vector at time k, H is the observation matrix, and v k is the observation noise; Based on the state equation and the observation equation, use the extended Kalman filter algorithm to estimate the link health status. The extended Kalman filter algorithm adjusts the estimated value of the link health status through the prediction step and the update step; In the prediction step, the link health state at the current moment is predicted based on the estimated value at the previous moment, according to the link health state estimation at the previous moment and the covariance matrix P k-1 , and the state equation is used to predict the link health state at the current moment, expressed as: The predicted state covariance matrix, expressed as: where, is the predicted value of the link health state at time k, is the predicted state covariance matrix, and Q is the process noise covariance matrix; In the update step, according to the actual observation data z k and the predicted state value The link health status is updated using the Kalman gain matrix, which is expressed as: The updated state covariance matrix is: Among them, K k is the Kalman gain matrix, R is the observation noise covariance matrix, and P k is the updated state covariance matrix, and I is the identity matrix; By continuously iterating the prediction step and the update step, an estimated value of the link health status at each moment is obtained It represents the estimated values of link delay, bandwidth, and packet loss rate.

8. The short message communication method for the distribution network FTU device according to any one of claims 1-4, characterized in that, The specific process of calculating the quality score of each link using the nonlinear programming algorithm is as follows: Predict the results based on the health status of the link, including the link delay x d , bandwidth x b and packet loss rate x l , define the link quality score Q i , expressed as: Among them, C Shannon (x b ) represents the bandwidth evaluation function based on the Shannon channel capacity formula, x b is the estimated bandwidth of the link, SNR is the signal-to-noise ratio, Indicates the link delay x d Impact on link quality, α2 is the delay sensitivity parameter, x d is the estimated delay of the link, Indicates the packet loss rate x l Impact on link quality, α3 is the impact coefficient of packet loss rate, x l is the estimated packet loss rate of the link.

9. The short message communication method for the distribution network FTU device according to claim 8, wherein, Use the nonlinear programming algorithm to perform optimal selection of the link. The optimization goal is to maximize the sum of the link quality scores. Set the optimization objective function, expressed as: Among them, x i is a decision variable, indicating whether to select the i-th link for data transmission; If x i = 1, then select this link; if x i = 0, then do not select this link; Set the dynamic constraint conditions, expressed as: Among them, x b is the bandwidth of link i, B max is the maximum available bandwidth, x d is the delay of link i, T max is the maximum allowable delay, x l is the packet loss rate of link i, L max is the maximum acceptable packet loss rate; Select the links with quality scores greater than the corresponding preset thresholds for high-priority data stream transmission.

10. A short message communication system for a distribution network FTU device, comprising a memory and a processor connected to each other, wherein a computer program is stored on the memory, characterized in that, The computer program, when run by a processor, executes the steps of the method according to any one of claims 1-9.

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