A power distribution network distributed differential protection method and system suitable for 1.4GIGS communication network

Abstract

The application relates to the technical field of differential protection, in particular to a power distribution network distributed differential protection method and system suitable for a 1.4GIGS communication network, which comprises the following steps: based on the current and voltage parameters of each node of the power distribution network, real-time data is extracted and analyzed, the difference between the nodes is calculated, the nodes meeting the conditions are screened out by analyzing the difference values, signal receiving monitoring is carried out, and a list of key monitoring nodes is generated. In the application, the node signal transmission path is optimized through a power distribution algorithm, the time-frequency resource distribution of the signal is dynamically adjusted, the efficiency and stability of signal transmission are realized, the bit error rate in the signal transmission process is effectively reduced, the response speed and accuracy of the power distribution network differential protection system are improved, the interference information in the signal is processed through a particle swarm optimization algorithm, the frequency spectrum structure of the signal is optimized by rearranging and rotating the interference signal, the transmission parameters of the signal are adjusted, and the stability and anti-interference ability of signal receiving are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of differential protection technology, and in particular to a distributed differential protection method and system for distribution networks adapted to 1.4G IGS communication networks. Background Technology

[0002] Differential protection technology is mainly used to detect and locate faults in the power grid, especially short circuits and other abnormal conditions. By comparing the current in different parts of the power grid, when the detected current difference exceeds a predetermined threshold, the system will trigger the protection device to isolate the fault area, thereby preventing further damage to the power grid and the occurrence of large-scale power outages.

[0003] The purpose of the distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks is to achieve efficient and accurate differential protection in distributed power systems by utilizing the high-speed data transmission capability of 1.4G IGS communication networks. This aims to improve the stability and security of power systems, especially in the face of complex power grid structures and variable load conditions, enabling rapid identification and isolation of faults to ensure the continuity and reliability of power supply.

[0004] Traditional methods rely on fixed signal transmission paths and preset parameter configurations when dealing with complex power grid structures and variable load conditions. Static processing methods cannot adapt to dynamically changing power grid environments, resulting in delayed responses during fault identification and isolation. Traditional methods also lack effective optimization methods for handling signal interference, which can easily lead to false alarms or missed alarms, affecting the overall stability of the system. This can cause fault areas to be unable to be isolated in a timely manner, expanding the scope of the fault's impact and potentially even causing larger-scale power outages, seriously threatening the safety and continuous operation of the power system. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a distributed differential protection method and system for distribution networks adapted to 1.4G IGS communication networks.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks, comprising the following steps:

[0007] Step 1: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, filter out nodes that meet the conditions by analyzing the difference values, monitor signal reception, and generate a list of key monitoring nodes.

[0008] Step 2: Based on the list of key monitoring nodes, configure the communication resources of each monitoring node, analyze the interference signals between nodes, filter and eliminate interference signals by calculating the strength and spectrum distribution of the interference signals, and generate a channel gain configuration scheme by considering the channel gain of the nodes.

[0009] Step 3: Based on the channel gain configuration scheme, a power allocation algorithm is used to optimize the transmission path of the node signal, adjust the time-frequency resource allocation of the signal, and generate the transmission path optimization result by real-time monitoring of the signal strength and interference in the transmission path.

[0010] Step 4: Based on the transmission path optimization results, evaluate the quality of the signal received by the node, calculate the bit error rate in signal transmission, adjust the transmission by re-encoding signals that exceed the set threshold, and generate a signal reception quality evaluation result.

[0011] Step 5: Based on the signal reception quality assessment results, the particle swarm optimization algorithm is used to process the interference information in the signal. By rearranging and rotating the interference signals, the signal transmission parameters are adjusted to improve the stability of signal reception and generate symbol-level interference optimization results.

[0012] Step Six: Based on the symbol-level interference optimization results, make final adjustments to the communication channels of all nodes, comprehensively analyze the channel gain and interference elimination between nodes, select the optimal communication configuration, and generate a comprehensive communication channel configuration scheme.

[0013] As a further aspect of the present invention, the specific steps for generating the list of key monitoring nodes are as follows:

[0014] Based on the current and voltage parameters of each node in the distribution network, real-time data is extracted, and preliminary calculations of the current and voltage values ​​of each node are performed. By comparing the rate of change at adjacent time points, the trend of change is analyzed and recorded, and basic values ​​of node differences are generated.

[0015] Based on the node difference baseline value, analyze the historical fluctuation data of each node, perform time series analysis, calculate the fluctuation range and compare it with the current data to obtain the trend of change and generate the node difference fluctuation value;

[0016] Based on the fluctuation values ​​of node differences, nodes with fluctuation values ​​within a set range are selected for signal reception monitoring. By comparing real-time data updates with fluctuation values, nodes that meet the criteria are marked, and a list of key monitoring nodes is generated.

[0017] As a further aspect of the present invention, the specific steps for generating the channel gain configuration scheme are as follows:

[0018] Based on the list of key monitoring nodes, the communication resources of each node are configured, the interference signals between nodes are analyzed, and the interference signals are classified and recorded by comparing the signal strength and spectrum distribution, generating interference signal analysis results.

[0019] Based on the interference signal analysis results, interference signals with signal strength exceeding the threshold are screened, and the interference signals are eliminated and suppressed. An interference signal suppression scheme is generated by adjusting the signal frequency band.

[0020] Based on the aforementioned interference signal suppression scheme, the channel gain of each node is comprehensively analyzed, communication resources are adjusted through channel allocation, the channel configuration between nodes is optimized, the stability of signal transmission is ensured, and a channel gain configuration scheme is generated.

[0021] As a further aspect of the present invention, the specific steps for generating the transmission path optimization result are as follows:

[0022] Based on the channel gain configuration scheme, the transmission path of each node is analyzed, the signal transmission path of each node is extracted, the path is initially adjusted, and the distribution of signal strength on the path is calculated to establish a preliminary path model and generate a preliminary transmission path configuration.

[0023] Based on the initial transmission path configuration, a power allocation algorithm is adopted to adjust the allocation of time and frequency resources, analyze the resource requirements of each node, dynamically allocate the signal transmission path by allocating different time and frequency resource segments, monitor the utilization rate of the signal on time and frequency resources, and generate a time and frequency resource allocation scheme.

[0024] Based on the aforementioned time-frequency resource allocation scheme, the signal transmission path is optimized, the resource configuration on the path is adjusted, and the stability of the signal transmission is monitored in real time by comparing signal strength and interference, thereby completing the path optimization and generating the transmission path optimization result.

[0025] As a further aspect of the present invention, the power allocation algorithm is based on the formula:

[0026]

[0027] Where: P i h represents the power allocated to the i-th node. i Let α represent the channel gain of the i-th node. i β represents the dynamic load factor of the i-th node. i P represents the interference suppression coefficient of the i-th node, γ represents the weight correction factor, and P represents the interference suppression coefficient of the i-th node. total This represents the total power available for allocation, and N represents the total number of nodes.

[0028] As a further aspect of the present invention, the specific steps for generating the signal reception quality assessment result are as follows:

[0029] Based on the transmission path optimization results, the quality of the signals received by each node is evaluated, relevant parameters of the received signals are extracted, the bit error rate of each node is calculated, and signals with excessive bit error rates are filtered out by comparing the bit error rate with a set threshold, generating bit error rate analysis results.

[0030] Based on the bit error rate analysis results, signals with excessive bit error rates are re-encoded. By analyzing the signal's encoding structure and resetting the encoding parameters, the signals are re-encoded to ensure the accuracy of signal transmission and generate a re-encoded signal set.

[0031] Based on the recoded signal set, the transmission path of the recoded signal is adjusted, the transmission efficiency of the signal on the path is analyzed, and the stability of the signal transmission is ensured by fine-tuning the path, thereby generating a signal reception quality assessment result.

[0032] As a further aspect of the present invention, the specific steps for generating the symbol-level interference optimization result are as follows:

[0033] Based on the signal reception quality assessment results, interference information in the received signal is extracted, the signal amplitude and phase are decomposed, the frequency components of the signal are analyzed, the interference intensity of each component is compared, the interference components are classified and labeled, and an interference signal component table is generated.

[0034] Based on the interference signal component table, the particle swarm optimization algorithm is used to rearrange the labeled interference signals. By adjusting the frequency and intensity distribution of the interference components, the spectral structure of the signal is optimized. Combined with phase rotation operation, the relative positions between signals are adjusted to generate the interference signal adjustment result.

[0035] Based on the interference signal adjustment results, the signal transmission parameters are optimized. By reconfiguring the signal power, bandwidth and phase, the transmission path of each node is adjusted to generate symbol-level interference optimization results.

[0036] As a further aspect of the present invention, the particle swarm optimization algorithm is based on the formula:

[0037]

[0038] Where: v i (t+1) represents the velocity of the i-th particle at time t+1, v i (t) represents the velocity of the i-th particle at time t, W is the inertial weight, c1 is the individual acceleration factor, and r1 represents a random number in the interval [0, 1]. Let c2 be the historical best position of the i-th particle, c2 be the social acceleration factor, r2 be a random number in the interval [0, 1], and g be the social acceleration factor. best The global optimal position is given by α, where α is the adjustment coefficient and f is the position. i (t) is a function relating the strength and frequency of the interference signal. These are component characteristic parameters.

[0039] As a further aspect of the present invention, the specific steps for generating the integrated communication channel configuration scheme are as follows:

[0040] Based on the symbol-level interference optimization results, the communication channels of all nodes are analyzed, channel gain data between nodes is extracted, interference elimination information is combined, the channel performance of each node is compared and filtered, and channel gain and interference data are generated.

[0041] Based on the channel gain and interference data, the communication channel is adjusted, and by analyzing the bandwidth and transmission efficiency between channels, the communication resources of each node are reallocated, the channel configuration is optimized to reduce interference, and the channel configuration adjustment result is generated.

[0042] Based on the channel configuration adjustment results, the allocation of communication resources is adjusted by taking into account the communication channel status of all nodes, and a comprehensive communication channel configuration scheme is generated according to the channel gain and interference elimination effect.

[0043] A distributed differential protection system for distribution networks adapted to a 1.4G IGS communication network, wherein the distributed differential protection system for distribution networks adapted to a 1.4G IGS communication network is used to execute the aforementioned distributed differential protection method for distribution networks adapted to a 1.4G IGS communication network, the system comprising:

[0044] Node monitoring module: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, determine nodes that meet the conditions, and establish a list of key monitoring nodes by analyzing the changing trends and recording the changing data.

[0045] Channel configuration module: Based on the list of key monitoring nodes, configure the communication resources of each node, analyze the interference signals between nodes, filter and eliminate interference signals by comparing signal strength and spectrum distribution, and generate a channel gain configuration scheme according to the channel gain of the node.

[0046] Path optimization module: Based on the channel gain configuration scheme, extract the signal transmission path of each node, adjust the path by calculating the distribution of signal strength on the path, dynamically allocate time and frequency resource segments, monitor the utilization rate of signal transmission, and generate transmission path optimization results;

[0047] Signal quality assessment module: Based on the transmission path optimization results, analyze the relevant parameters of the received signal of the node, calculate and compare the bit error rate of each node, filter out signals with excessive bit error rate, re-encode them, adjust the transmission path, and establish a signal reception quality report;

[0048] Interference optimization module: Based on the signal reception quality report, extract information of the interference signal, decompose the signal amplitude and phase, analyze the signal frequency components and interference intensity, classify and label the interference components, rearrange the interference signal and optimize the signal spectrum structure, and generate interference signal optimization results;

[0049] Channel adjustment module: Based on the interference signal optimization results, analyze the channel gain data between nodes, combine with interference elimination information, readjust the communication channel, optimize the channel configuration and reduce interference, and generate a channel configuration adjustment scheme;

[0050] Integrated Configuration Module: Based on the aforementioned channel configuration adjustment scheme, the communication channels of all nodes are finally adjusted. By reallocating communication resources and considering the channel gain and interference elimination effects between nodes, an integrated communication channel configuration scheme is established.

[0051] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0052] 1. In this invention, a power allocation algorithm is used to precisely optimize the signal transmission path of each node in the distribution network. A dynamic time-frequency resource allocation strategy is adopted, which adjusts the power distribution and time-frequency resource allocation in the transmission path in real time according to the channel gain and interference of each node. This improves the efficiency of signal transmission, effectively reduces the bit error rate caused by signal path attenuation or interference, and ensures the stable transmission of high-quality signals through real-time monitoring and optimization of the transmission path. This significantly improves the response speed and accuracy of the distribution network differential protection system and enhances the system's sensitivity and timeliness to faults.

[0053] 2. In this invention, the particle swarm optimization algorithm is used to rearrange and rotate the phase of the interference signal, further optimizing the signal's spectral structure. This includes precise decomposition of the signal's amplitude and phase, combined with adjustments to the interference signal's strength and frequency, significantly enhancing the signal's anti-interference capability during transmission. Simultaneously, by adjusting the signal's transmission parameters, including power, bandwidth, and phase, it adapts to the variable interference in complex power grid environments, ensuring stable signal reception, improving anti-interference capability and signal reception stability, and guaranteeing the reliable operation of the distribution network differential protection system in complex environments.

[0054] 3. In this invention, the communication efficiency between nodes in the distribution network system is improved by optimizing the configuration of communication channels. By analyzing the channel gain and interference between nodes, the channel configuration is precisely adjusted, reducing potential signal interference and ensuring that the communication resources of each node are reasonably allocated. By optimizing the bandwidth and transmission efficiency between channels, communication failures caused by channel congestion or interference are reduced. Furthermore, by integrating the communication channel data of all nodes, the optimal communication channel configuration scheme is generated, providing a more reliable communication guarantee for the distribution network differential protection system and ensuring that the system can still operate stably under high load conditions. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0056] Figure 2 This is a system flowchart of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] Example 1

[0059] Please see Figure 1 This invention provides a technical solution: a distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks, comprising the following steps:

[0060] Step 1: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, filter out nodes that meet the conditions by analyzing the difference values, monitor signal reception, and generate a list of key monitoring nodes.

[0061] Step 2: Based on the list of key monitoring nodes, configure the communication resources of each monitoring node, analyze the interference signals between nodes, filter and eliminate interference signals by calculating the strength and spectrum distribution of the interference signals, and generate a channel gain configuration scheme by considering the channel gain of the nodes.

[0062] Step 3: Based on the channel gain configuration scheme, the power allocation algorithm is used to optimize the transmission path of the node signal, adjust the time and frequency resource allocation of the signal, and generate the transmission path optimization result by real-time monitoring of the signal strength and interference in the transmission path.

[0063] Step 4: Based on the transmission path optimization results, evaluate the quality of the signal received by the node, calculate the bit error rate in the signal transmission, adjust the transmission by recoding signals that exceed the set threshold, and generate the signal reception quality evaluation results.

[0064] Step 5: Based on the signal reception quality assessment results, the particle swarm optimization algorithm is used to process the interference information in the signal. By rearranging and rotating the interference signals, the signal transmission parameters are adjusted to improve the stability of signal reception and generate symbol-level interference optimization results.

[0065] Step Six: Based on the symbol-level interference optimization results, make final adjustments to the communication channels of all nodes, comprehensively analyze the channel gain and interference elimination between nodes, select the optimal communication configuration, and generate a comprehensive communication channel configuration scheme.

[0066] The specific steps for generating a list of key monitoring nodes are as follows:

[0067] Based on the current and voltage parameters of each node in the distribution network, real-time data is extracted, and preliminary calculations of the current and voltage values ​​of each node are performed. By comparing the rate of change at adjacent time points, the trend of change is analyzed and recorded, and basic values ​​of node differences are generated.

[0068] Based on the node difference baseline value, analyze the historical fluctuation data of each node, perform time series analysis, calculate the fluctuation range and compare it with the current data to obtain the trend of change and generate the node difference fluctuation value;

[0069] Based on the fluctuation values ​​of node differences, nodes with fluctuation values ​​within a set range are selected for signal reception monitoring. By comparing real-time data updates with fluctuation values, nodes that meet the conditions are marked, and a list of key monitoring nodes is generated.

[0070] Based on the current and voltage parameters of each node in the distribution network, a sliding window algorithm with a window size of 5 seconds is used to collect and segment the real-time current and voltage data of the nodes. The data in each window are averaged to obtain the average current and voltage values ​​of each time window. By comparing the rate of change of the average values ​​of adjacent time windows, difference analysis is performed, the trend of change is recorded, and the basic value of node difference is generated.

[0071] Based on the node difference baseline value, the historical fluctuation data of each node is processed using time series analysis. The specific steps include fitting the fluctuation data with a time series model, the model parameters of which include an autoregressive term of p=2, a difference term of d=1, and a moving average term of q=2, calculating the fluctuation range, comparing the fitted historical fluctuation data with the current real-time data, and generating node difference fluctuation values ​​by calculating the changing trend of each node.

[0072] Based on the node difference fluctuation value, a conditional filtering algorithm is adopted, and the fluctuation value filtering threshold is set to ±5%. Nodes with fluctuation values ​​within the range are filtered. Then, a dynamic monitoring algorithm is adopted to monitor the signal reception of nodes that meet the conditions. During the monitoring process, a real-time update function is called to update the node fluctuation value every 10 seconds and compare the real-time fluctuation value with the historical fluctuation value. Nodes that meet the filtering conditions are marked as monitoring nodes, and finally a list of key monitoring nodes is generated.

[0073] The specific steps for generating a channel gain configuration scheme are as follows:

[0074] Based on the list of key monitoring nodes, the communication resources of each node are configured, the interference signals between nodes are analyzed, and the interference signals are classified and recorded by comparing the signal strength and spectrum distribution, generating interference signal analysis results.

[0075] Based on the analysis results of interference signals, interference signals with signal strength exceeding the threshold are screened out, and the interference signals are eliminated and suppressed. Furthermore, an interference signal suppression scheme is generated by adjusting the signal frequency band.

[0076] Based on the interference signal suppression scheme, the channel gain of each node is comprehensively analyzed, communication resources are adjusted through channel allocation, the channel configuration between nodes is optimized, the stability of signal transmission is ensured, and a channel gain configuration scheme is generated.

[0077] Based on the list of key monitoring nodes, a static resource allocation algorithm is adopted. First, the bandwidth and time-frequency resources of each node are initially allocated. Then, the communication resources are adjusted and optimized by calculating parameters such as signal-to-noise ratio and channel attenuation coefficient using the channel evaluation function. The configuration parameters are recorded to generate a node communication resource configuration scheme.

[0078] Based on the node communication resource configuration scheme, an interference detection algorithm is adopted. By setting the signal strength threshold to -80dBm, the interference signal between nodes is detected using a spectrum analysis function. The specific execution steps include frequency domain transformation of the signal, extraction of spectrum feature values, spectrum comparison with the expected signal, classification and recording of the detected interference signals, and generation of interference signal analysis results.

[0079] Based on the interference signal analysis results, a signal suppression algorithm is used to screen out interference signals with a strength exceeding -70dBm. The frequency band is then adjusted by calling a frequency band adjustment function, which includes reallocating the signal frequency and compressing the bandwidth, calculating the suppression coefficient of the interference signal, suppressing the power of the interference signal, and generating an interference signal suppression scheme.

[0080] The specific steps for generating the transmission path optimization results are as follows:

[0081] Based on the channel gain configuration scheme, the transmission path of each node is analyzed, the signal transmission path of each node is extracted, the path is initially adjusted, and the distribution of signal strength on the path is calculated to establish a preliminary path model and generate a preliminary transmission path configuration.

[0082] Based on the initial transmission path configuration, a power allocation algorithm is adopted to adjust the allocation of time and frequency resources, analyze the resource requirements of each node, dynamically allocate the signal transmission path by allocating different time and frequency resource segments, monitor the utilization rate of the signal on time and frequency resources, and generate a time and frequency resource allocation scheme.

[0083] Based on the time-frequency resource allocation scheme, the signal transmission path is optimized, the resource configuration on the path is adjusted, and the stability of the signal transmission is monitored in real time by comparing the signal strength and interference, so as to complete the path optimization and adjustment and generate the transmission path optimization result.

[0084] Based on the channel gain configuration scheme, a path analysis algorithm is used to analyze the transmission path of each node. The specific steps include using the signal strength evaluation function to calculate the signal strength of the signal transmission path of each node, extracting key path parameters by the distribution of signal strength on the path, establishing a preliminary path model, and making preliminary adjustments to the path according to the model to generate a preliminary transmission path configuration.

[0085] Based on the initial transmission path configuration, a power allocation algorithm is used to adjust the time-frequency resources. First, the resource demand analysis function is called to calculate the time-frequency resource demand of each node, and analyze the node's bandwidth usage, power requirements and other resource requirements. Then, the dynamic allocation function is used to allocate different time-frequency resource segments to each signal transmission path, monitor the utilization rate of the signal on the time-frequency resources in real time, and generate a time-frequency resource allocation scheme.

[0086] Based on the time-frequency resource allocation scheme, a path optimization algorithm is used to make final adjustments to the signal transmission path. The specific steps include real-time monitoring of the signal strength and interference on the path through a signal strength comparison function, adjusting the resource configuration on the path according to the monitoring results, optimizing the parameter settings of the transmission path through multiple iterations, and finally generating the optimized transmission path result.

[0087] The power allocation algorithm is based on the formula:

[0088]

[0089] Where: P i h represents the power allocated to the i-th node. i Let α represent the channel gain of the i-th node. i β represents the dynamic load factor of the i-th node. iP represents the interference suppression coefficient of the i-th node, γ represents the weight correction factor, and P represents the interference suppression coefficient of the i-th node. total This represents the total power available for allocation, and N represents the total number of nodes;

[0090] Execution process: First, analyze the channel gain h of each node in the distribution network. i The channel conditions of each node in the 1.4GIGS communication network are evaluated. Then, a dynamic load factor α is set according to the importance of each node in the distribution network and the real-time load situation. i To ensure that high-load nodes receive more reasonable time-frequency resource allocation, the interference suppression coefficient β of each node is then calculated. i Considering potential interference sources and environmental factors in the 1.4GIGS communication network, and to ensure stable communication for nodes even under high interference conditions, a weight correction factor γ is introduced. Based on historical operating data or simulation test results, the overall power allocation is fine-tuned to better adapt to the characteristics of the 1.4GIGS network and the protection requirements of the distribution network, ensuring that the sum of the power allocations for each node meets the total power P. total The system is designed to dynamically allocate the optimal transmission path for signals and effectively monitor and manage the utilization of time and frequency resources, while also addressing the constraints imposed by the system.

[0091] The specific steps for generating signal reception quality assessment results are as follows:

[0092] Based on the transmission path optimization results, the quality of the signals received by each node is evaluated, relevant parameters of the received signals are extracted, the bit error rate of each node is calculated, and signals with excessive bit error rates are filtered out by comparing the bit error rate with a set threshold, generating bit error rate analysis results.

[0093] Based on the bit error rate analysis results, signals with excessive bit error rates are re-encoded. By analyzing the signal's encoding structure and resetting the encoding parameters, the signals are re-encoded to ensure the accuracy of signal transmission and generate a set of re-encoded signals.

[0094] Based on the recoded signal set, the transmission path of the recoded signal is adjusted, the transmission efficiency of the signal on the path is analyzed, and the stability of signal transmission is ensured by fine-tuning the path, thereby generating a signal reception quality assessment result.

[0095] Based on the transmission path optimization results, a bit error rate (BER) calculation algorithm is used to assess the quality of the signals received by each node. First, the signal parameter extraction function is called to extract the key parameters of the received signal, including signal strength, phase, frequency, etc. Then, the BER calculation function is used to calculate the BER of each node. By comparing the calculated BER with a preset threshold, signals with excessive BER are filtered out, and BER analysis results are generated.

[0096] Based on the bit error rate analysis results, a signal re-coding algorithm is used to re-encode signals with excessive bit error rates. First, the coding structure analysis function is called to parse the coding structure of the original signal to determine the coding type and coding parameters. Then, the coding parameters are reset, specifically including modifying the coding rate and coding method. The signal is then re-encoded through the coding execution function to generate a re-coded signal set.

[0097] Based on the recoded signal set, a path adjustment algorithm is used to adjust the transmission path of the recoded signal. First, the transmission efficiency analysis function is called to analyze the transmission efficiency of the signal on the path. The specific steps include calculating the path delay and bandwidth utilization, comparing and fine-tuning them, and calling the path fine-tuning function to optimize and adjust the signal transmission path, generating a signal reception quality evaluation result.

[0098] The specific steps for generating symbol-level interference optimization results are as follows:

[0099] Based on the signal reception quality assessment results, interference information in the received signal is extracted, the signal amplitude and phase are decomposed, the frequency components of the signal are analyzed, the interference intensity of each component is compared, the interference components are classified and labeled, and an interference signal component table is generated.

[0100] Based on the interference signal component table, the particle swarm optimization algorithm is used to rearrange the labeled interference signals. By adjusting the frequency and intensity distribution of the interference components, the spectral structure of the signal is optimized. Combined with phase rotation operation, the relative positions between signals are adjusted to generate the interference signal adjustment result.

[0101] Based on the interference signal adjustment results, the signal transmission parameters are optimized. By reconfiguring the signal power, bandwidth and phase, the transmission path of each node is adjusted to generate symbol-level interference optimization results.

[0102] Based on the signal reception quality assessment results, an interference decomposition algorithm is used to process the interference information in the received signal. First, the signal amplitude decomposition function and the signal phase decomposition function are called to decompose the signal amplitude and phase respectively, decomposing the signal into multiple frequency components. Then, the frequency component analysis function is used to analyze the interference intensity of each frequency component. The interference components are classified by comparing the interference intensity. At the same time, the interference labeling function is called to label different types of interference signals, generating an interference signal component table.

[0103] Based on the interference signal component table, the particle swarm optimization algorithm is used to rearrange the labeled interference signals. First, the frequency adjustment function is called to adjust the frequency of each interference component. During the adjustment process, the frequency distribution is optimized according to the interference intensity. Then, the phase rotation function is used to adjust the relative position of the signal. Combining the frequency and intensity distribution of the interference signal, the spectral structure of the signal is optimized, and finally the interference signal adjustment result is generated.

[0104] Based on the interference signal adjustment results, a transmission parameter optimization algorithm is used to optimize the transmission parameters of the signal. First, the power configuration function is called to reconfigure the transmission power of the signal. Then, the bandwidth adjustment function is used to redistribute the bandwidth of the signal. Combined with the phase configuration function, the phase of the signal is adjusted. Finally, the transmission path of each node is optimized and adjusted to generate symbol-level interference optimization results.

[0105] Particle swarm optimization algorithm, according to the formula:

[0106]

[0107] Where: v i (t+1) represents the velocity of the i-th particle at time t+1, v i (t) represents the velocity of the i-th particle at time t, w is the inertial weight, c1 is the individual acceleration factor, and r1 represents a random number in the interval [0, 1]. Let c2 be the historical best position of the i-th particle, c2 be the social acceleration factor, r2 be a random number in the interval [0, 1], and g be the social acceleration factor. best The global optimal position is given by α, where α is the adjustment coefficient and f is the position. i (t) is a function relating the strength and frequency of the interference signal. These are component characteristic parameters;

[0108] Execution process: First, calculate the current particle velocity v. i (t) and inertial weight w are used to adjust the dynamic characteristics of the particles, ensuring that in the distributed differential protection system, the particles can accurately reflect the current, voltage and other state parameters of the distribution network in the communication network and avoid excessive fluctuations. Individual acceleration factor c1 and social acceleration factor c2 are used to influence the particles to their historical optimal positions. and the global optimal position g best The algorithm considers the movement trend and incorporates random perturbations introduced by random numbers r1 and r2 to ensure that it possesses good global search capabilities in distributed systems and can quickly converge to the optimal protection strategy. Additional terms... The adjustment coefficient α is introduced to control the impact of additional disturbances. By adjusting the frequency and intensity distribution of signal interference components, the performance of the distribution network differential protection is optimized. This can be determined through experiments or historical data analysis to ensure applicability in 1.4GIGS communication networks. The function f... i (t) By describing the time-varying characteristics of interference signals, it can adapt to time-varying signals in communication networks, characteristic parameters This reflects the interference signal component with the best correlation to the target signal, ensuring the accuracy and response speed of the distributed differential protection method, and calculating the particle's velocity v in the next time step. i (t+1) determines the direction of particle adjustment for protection decisions in the network, ensuring a rapid and accurate response to changes in network state.

[0109] The specific steps for generating a comprehensive communication channel configuration scheme are as follows:

[0110] Based on the symbol-level interference optimization results, the communication channels of all nodes are analyzed, channel gain data between nodes is extracted, interference elimination information is combined, the channel performance of each node is compared and filtered, and channel gain and interference data are generated.

[0111] Based on channel gain and interference data, the communication channel is adjusted, and by analyzing the bandwidth and transmission efficiency between channels, the communication resources of each node are reallocated, the channel configuration is optimized to reduce interference, and the channel configuration adjustment results are generated.

[0112] Based on the channel configuration adjustment results, the communication channel status of all nodes is considered, the allocation of communication resources is adjusted, and a comprehensive communication channel configuration scheme is generated based on channel gain and interference elimination effect.

[0113] Based on the symbol-level interference optimization results, a channel analysis algorithm is used to perform a detailed analysis of the communication channels of all nodes. First, the channel gain extraction function is called to extract the channel gain data between nodes. Then, the interference elimination analysis function is used in conjunction with the interference elimination information to compare the channel performance of each node. By comparing the channel gain and interference elimination effect, the channel gain and interference data are generated.

[0114] Based on channel gain and interference data, a channel configuration adjustment algorithm is used to adjust the communication channel. First, the bandwidth analysis function is called to analyze the bandwidth usage of each channel. Then, the transmission efficiency calculation function is used to evaluate the transmission efficiency of each channel. By reallocating the communication resources of each node, the channel configuration is optimized and adjusted to reduce interference and generate the channel configuration adjustment result.

[0115] Based on the channel configuration adjustment results, a comprehensive channel configuration algorithm is adopted to integrate the communication channel status of all nodes. First, the resource allocation function is called to reallocate communication resources. Then, a comprehensive analysis is performed by combining channel gain and interference elimination effect to finally generate a comprehensive communication channel configuration scheme.

[0116] Please see Figure 2 A distributed differential protection system for distribution networks adapted to a 1.4G IGS communication network is provided. This system is used to execute the aforementioned distributed differential protection method for distribution networks adapted to a 1.4G IGS communication network. The system includes:

[0117] Node monitoring module: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, identify nodes that meet the conditions, and establish a list of key monitoring nodes by analyzing the changing trends and recording the changing data.

[0118] Channel configuration module: Based on the list of key monitoring nodes, configure the communication resources of each node, analyze the interference signals between nodes, filter and eliminate interference signals by comparing signal strength and spectrum distribution, and generate a channel gain configuration scheme according to the channel gain of the node.

[0119] Path optimization module: Based on the channel gain configuration scheme, extract the signal transmission path of each node, adjust the path by calculating the distribution of signal strength on the path, dynamically allocate time and frequency resource segments, monitor the utilization rate of signal transmission, and generate transmission path optimization results;

[0120] Signal quality assessment module: Based on the transmission path optimization results, it analyzes the relevant parameters of the received signal at each node, calculates and compares the bit error rate of each node, filters out signals with excessive bit error rates, re-encodes them, adjusts the transmission path, and establishes a signal reception quality report;

[0121] Interference optimization module: Based on the signal reception quality report, it extracts information about the interference signal, decomposes the signal amplitude and phase, analyzes the signal frequency components and interference intensity, classifies and labels the interference components, rearranges the interference signal and optimizes the signal's spectral structure, and generates interference signal optimization results;

[0122] Channel adjustment module: Based on the interference signal optimization results, analyze the channel gain data between nodes, combine with interference elimination information, readjust the communication channel, optimize the channel configuration and reduce interference, and generate a channel configuration adjustment scheme;

[0123] Integrated Configuration Module: Based on the channel configuration adjustment scheme, the module performs final adjustments to the communication channels of all nodes. By reallocating communication resources and considering the channel gain and interference elimination effects between nodes, it establishes an integrated communication channel configuration scheme.

[0124] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks, characterized in that, Includes the following steps: Step 1: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, filter out nodes that meet the conditions by analyzing the difference values, monitor signal reception, and generate a list of key monitoring nodes. Step 2: Based on the list of key monitoring nodes, configure the communication resources of each monitoring node, analyze the interference signals between nodes, filter and eliminate interference signals by calculating the strength and spectrum distribution of the interference signals, and generate a channel gain configuration scheme by considering the channel gain of the nodes. Step 3: Based on the channel gain configuration scheme, a power allocation algorithm is used to optimize the transmission path of the node signal, adjust the time-frequency resource allocation of the signal, and generate the transmission path optimization result by real-time monitoring of the signal strength and interference in the transmission path. Step 4: Based on the transmission path optimization results, evaluate the quality of the signal received by the node, calculate the bit error rate in signal transmission, adjust the transmission by re-encoding signals that exceed the set threshold, and generate a signal reception quality evaluation result. Step 5: Based on the signal reception quality assessment results, the particle swarm optimization algorithm is used to process the interference information in the signal. By rearranging and rotating the interference signals, the signal transmission parameters are adjusted to improve the stability of signal reception and generate symbol-level interference optimization results. Step Six: Based on the symbol-level interference optimization results, make final adjustments to the communication channels of all nodes, comprehensively analyze the channel gain and interference elimination between nodes, select the optimal communication configuration, and generate a comprehensive communication channel configuration scheme.

2. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the list of key monitoring nodes are as follows: Based on the current and voltage parameters of each node in the distribution network, real-time data is extracted, and preliminary calculations of the current and voltage values ​​of each node are performed. By comparing the rate of change at adjacent time points, the trend of change is analyzed and recorded, and basic values ​​of node differences are generated. Based on the node difference baseline value, analyze the historical fluctuation data of each node, perform time series analysis, calculate the fluctuation range and compare it with the current data to obtain the trend of change and generate the node difference fluctuation value; Based on the fluctuation values ​​of node differences, nodes with fluctuation values ​​within a set range are selected for signal reception monitoring. By comparing real-time data updates with fluctuation values, nodes that meet the criteria are marked, and a list of key monitoring nodes is generated.

3. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the channel gain configuration scheme are as follows: Based on the list of key monitoring nodes, the communication resources of each node are configured, the interference signals between nodes are analyzed, and the interference signals are classified and recorded by comparing the signal strength and spectrum distribution, generating interference signal analysis results. Based on the interference signal analysis results, interference signals with signal strength exceeding the threshold are screened, and the interference signals are eliminated and suppressed. An interference signal suppression scheme is generated by adjusting the signal frequency band. Based on the aforementioned interference signal suppression scheme, the channel gain of each node is comprehensively analyzed, communication resources are adjusted through channel allocation, the channel configuration between nodes is optimized, the stability of signal transmission is ensured, and a channel gain configuration scheme is generated.

4. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the transmission path optimization result are as follows: Based on the channel gain configuration scheme, the transmission path of each node is analyzed, the signal transmission path of each node is extracted, the path is initially adjusted, and the distribution of signal strength on the path is calculated to establish a preliminary path model and generate a preliminary transmission path configuration. Based on the initial transmission path configuration, a power allocation algorithm is adopted to adjust the allocation of time and frequency resources, analyze the resource requirements of each node, dynamically allocate the signal transmission path by allocating different time and frequency resource segments, monitor the utilization rate of the signal on time and frequency resources, and generate a time and frequency resource allocation scheme. Based on the aforementioned time-frequency resource allocation scheme, the signal transmission path is optimized, the resource configuration on the path is adjusted, and the stability of the signal transmission is monitored in real time by comparing signal strength and interference, thereby completing the path optimization and generating the transmission path optimization result.

5. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The power allocation algorithm is based on the formula: ； in: Indicates assignment to the first The power of each node, Indicates the first Channel gain of each node, Indicates the first The dynamic load factor of each node. Indicates the first The interference suppression coefficient of each node, Indicates the weighting adjustment factor. This represents the total power available for allocation. This represents the total number of nodes.

6. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the signal reception quality assessment result are as follows: Based on the transmission path optimization results, the quality of the signals received by each node is evaluated, relevant parameters of the received signals are extracted, the bit error rate of each node is calculated, and signals with excessive bit error rates are filtered out by comparing the bit error rate with a set threshold, generating bit error rate analysis results. Based on the bit error rate analysis results, signals with excessive bit error rates are re-encoded. By analyzing the signal's encoding structure and resetting the encoding parameters, the signals are re-encoded to ensure the accuracy of signal transmission and generate a re-encoded signal set. Based on the recoded signal set, the transmission path of the recoded signal is adjusted, the transmission efficiency of the signal on the path is analyzed, and the stability of the signal transmission is ensured by fine-tuning the path, thereby generating a signal reception quality assessment result.

7. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the symbol-level interference optimization results are as follows: Based on the signal reception quality assessment results, interference information in the received signal is extracted, the signal amplitude and phase are decomposed, the frequency components of the signal are analyzed, the interference intensity of each component is compared, the interference components are classified and labeled, and an interference signal component table is generated. Based on the interference signal component table, the particle swarm optimization algorithm is used to rearrange the labeled interference signals. By adjusting the frequency and intensity distribution of the interference components, the spectral structure of the signal is optimized. Combined with phase rotation operation, the relative positions between signals are adjusted to generate the interference signal adjustment result. Based on the interference signal adjustment results, the signal transmission parameters are optimized. By reconfiguring the signal power, bandwidth and phase, the transmission path of each node is adjusted to generate symbol-level interference optimization results.

8. The distributed differential protection method for distribution networks adapted to 1.4G IGS communication networks according to claim 1, characterized in that, The specific steps for generating the integrated communication channel configuration scheme are as follows: Based on the symbol-level interference optimization results, the communication channels of all nodes are analyzed, channel gain data between nodes is extracted, interference elimination information is combined, the channel performance of each node is compared and filtered, and channel gain and interference data are generated. Based on the channel gain and interference data, the communication channel is adjusted, and by analyzing the bandwidth and transmission efficiency between channels, the communication resources of each node are reallocated, the channel configuration is optimized to reduce interference, and the channel configuration adjustment result is generated. Based on the channel configuration adjustment results, the allocation of communication resources is adjusted by taking into account the communication channel conditions of all nodes, and a comprehensive communication channel configuration scheme is generated according to the channel gain and interference elimination effect.

9. A distributed differential protection system for distribution networks adapted to 1.4G IGS communication networks, characterized in that, The distributed differential protection method for distribution networks adapted to 1.4GIGS communication networks according to any one of claims 1-8, wherein the system comprises: Node monitoring module: Based on the current and voltage parameters of each node in the distribution network, extract and analyze real-time data, calculate the differences between nodes, determine nodes that meet the conditions, and establish a list of key monitoring nodes by analyzing the changing trends and recording the changing data. Channel configuration module: Based on the list of key monitoring nodes, configure the communication resources of each node, analyze the interference signals between nodes, filter and eliminate interference signals by comparing signal strength and spectrum distribution, and generate a channel gain configuration scheme according to the channel gain of the node. Path optimization module: Based on the channel gain configuration scheme, extract the signal transmission path of each node, adjust the path by calculating the distribution of signal strength on the path, dynamically allocate time and frequency resource segments, monitor the utilization rate of signal transmission, and generate transmission path optimization results; Signal quality assessment module: Based on the transmission path optimization results, analyze the relevant parameters of the received signal of the node, calculate and compare the bit error rate of each node, filter out signals with excessive bit error rate, re-encode them, adjust the transmission path, and establish a signal reception quality report; Interference optimization module: Based on the signal reception quality report, extract information of the interference signal, decompose the signal amplitude and phase, analyze the signal frequency components and interference intensity, classify and label the interference components, rearrange the interference signal and optimize the signal spectrum structure, and generate interference signal optimization results; Channel adjustment module: Based on the interference signal optimization results, analyze the channel gain data between nodes, combine with interference elimination information, readjust the communication channel, optimize the channel configuration and reduce interference, and generate a channel configuration adjustment scheme; Integrated Configuration Module: Based on the aforementioned channel configuration adjustment scheme, the communication channels of all nodes are finally adjusted. By reallocating communication resources and considering the channel gain and interference elimination effects between nodes, an integrated communication channel configuration scheme is established.

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