Power distribution station room wireless communication method based on cooperative coding algorithm

Abstract

The invention provides a power distribution station house wireless communication method based on a cooperative coding algorithm, which comprises the following steps: data processing of dynamic environment adaptation: according to the real-time requirement of power distribution station house equipment data, segmenting original data into data blocks carrying priority labels, and dynamically generating a redundant coding strategy based on a real-time network state; network-aware cooperative transmission: transmitting data blocks and redundant information through multi-node cooperation, wherein a transmission path and a redundancy distribution proportion are dynamically adjusted according to network signal quality, node load and fault state; and fault-tolerant recovery of closed-loop feedback: the receiving end jointly decodes the data block and the redundant information, triggers a local retransmission instruction according to a decoding result, and feeds back the local retransmission instruction to the network architecture to optimize a subsequent transmission path.

Description

Technical Field

[0001] The present invention relates to technical fields such as power technology and wireless communication, and particularly relates to a wireless communication method for distribution substations based on a cooperative coding algorithm. Background Art

[0002] Currently, most of the newer distribution substations use wired methods such as optical fiber communication and power HPLC to communicate with the distribution automation system of the power supply company. However, many old distribution substation facilities still lack modern communication facilities and rely on traditional manual inspection and manual monitoring means.

[0003] First, it is highly dependent on manual inspection. The equipment status and operation conditions of the distribution substation are mainly obtained through regular manual inspections. Maintenance personnel need to regularly go to the substation for equipment inspections, data recording, and fault troubleshooting. Due to the periodicity and human factors of manual inspections, there may be problems such as untimely inspections and inaccurate data recording. Second, real-time monitoring is lacking. Due to the lack of communication facilities, the distribution substation cannot achieve real-time monitoring of equipment status. This means that any equipment failure or abnormality can only be discovered during inspections, resulting in a large time delay. Once a problem occurs with the equipment, it may not be possible to handle it in a timely manner, affecting the stability and reliability of the power system. At the same time, there is also the problem of inconvenient data recording. Equipment operation data needs to be manually recorded and sorted, and it is difficult to ensure the accuracy and integrity of the data. Since data cannot be automatically collected and transmitted, data analysis and fault prediction work face great challenges and it is difficult to carry out effective preventive maintenance and decision support.

[0004] In addition, the maintenance cost of old distribution substations is high. Manual inspection and maintenance require a large amount of manpower and time investment, and the maintenance cost is relatively high. Especially for distribution substations in remote or harsh environments, the safety of maintenance personnel also poses a greater risk. The handling of accidents is lagged. Equipment failures cannot be detected and reported in a timely manner, and the response speed for handling faults is slow, which may lead to an expansion of the fault range, affecting the power supply reliability of the power supply company. Sudden faults may cause long-term power outages, bringing inconvenience and economic losses to users. Due to the lack of communication facilities and real-time data, it is difficult for distribution substations to conduct big data analysis and intelligent management. The lack of equipment status and operation data makes it difficult to achieve distribution automation and intelligent dispatching.

[0005] With the development of power system automation and intelligence, the wireless communication technology of distribution substations has played an important role in improving the management efficiency and stability of the power system. However, existing wireless communication methods still have some significant drawbacks, which are mainly reflected in the following aspects: 1. Poor reliability Currently, common wireless communication methods in distribution substations, such as Wi-Fi, ZigBee, and LoRa, have many problems in practical applications. Wi-Fi communication is greatly affected by environmental interference and signal occlusion, which may lead to data loss or communication interruption; although ZigBee has the advantages of low power consumption and flexible networking, its communication stability and reliability will also be affected when the number of nodes is large or the communication distance is long; although LoRa communication is suitable for long-distance transmission, its data transmission rate is low and cannot meet the demand for real-time transmission of large-scale data.

[0006] 2. Low data transmission efficiency Traditional communication protocols may encounter bottlenecks during high-data-volume transmission, with the data transmission rate limited and unable to meet the requirements of real-time monitoring and data analysis. Since the transmission of wireless signals is greatly affected by the environment, frequent data retransmission and error correction further reduce the overall transmission efficiency. This inefficient data transmission not only increases communication latency but may also affect the system's real-time response ability to device status changes.

[0007] 3. High maintenance cost The maintenance cost of traditional communication equipment is relatively high. Especially in remote or inaccessible distribution substations, the safety and work efficiency of maintenance personnel are also affected. These factors increase the operating cost of the power distribution system and may have an adverse impact on the long-term stability of the system.

[0008] 4. Complex network topology and management In practical applications, the wireless communication network of distribution substations often needs to support complex topologies, including the connection of multiple terminal nodes, relay nodes, and control centers. Existing wireless communication methods have deficiencies in the flexibility and management of network topologies. Especially in a dynamically changing environment, it is difficult to network and optimize the network, resulting in the inability to fully utilize the overall performance of the system. Summary of the Invention

[0009] In view of the defects and deficiencies of the above-mentioned existing technologies, the present invention proposes a wireless communication method for distribution substations based on a cooperative coding algorithm. The main technical problems to be solved and the implementation means include: 1. Communication reliability By introducing a cooperative coding algorithm and using multi-device cooperative coding technology, the reliability of wireless communication is enhanced. By splitting data and generating redundant information, multiple terminal nodes and relay nodes jointly participate in data transmission and coding, thus effectively resisting environmental interference and signal attenuation. This method can perform real-time error correction during data transmission, improve data integrity and reliability, and ensure the stability of communication in distribution substations.

[0010] 2. Data transmission efficiency Adopt a collaborative coding algorithm to optimize the data transmission path and resource allocation, reduce the frequency of data retransmission and error correction, thereby improving the overall data transmission efficiency. Through multi-device collaborative transmission and redundant coding, the communication delay is reduced, the data transmission rate is increased, enabling the power distribution system to meet the requirements of real-time monitoring and data analysis.

[0011] 3. Reduce power consumption and maintenance costs Through the introduction of the collaborative coding algorithm, the present invention can optimize the power consumption of wireless communication devices, making the devices more energy-efficient during long-term operation. Due to the adoption of efficient coding and transmission strategies, unnecessary data retransmission and device maintenance requirements are reduced, thereby lowering the system's maintenance costs. In addition, the optimized communication strategy can improve the overall performance of the system and reduce the dependence on maintenance personnel.

[0012] 4. Simplify network topology and management Provide a flexible network topology design scheme that can adapt to the complex communication environment in the substation building. Through the application of collaborative coding technology, the network structure and management difficulty are simplified, and the system's dynamic adaptability is improved. The system can automatically adjust the network configuration according to the actual environmental changes, enhancing the stability and management efficiency of the communication network.

[0013] The present invention specifically adopts the following technical means: A wireless communication method for a substation building based on a collaborative coding algorithm, including: Data processing for dynamic environment adaptation: According to the real-time requirements of substation building equipment data, the original data is segmented into data blocks carrying priority tags, and a redundant coding strategy is dynamically generated based on the real-time network status; Network-aware collaborative transmission: Data blocks and redundant information are transmitted through multi-node collaboration, where the transmission path and redundant allocation ratio are dynamically adjusted according to network signal quality, node load, and fault status; Fault-tolerant recovery with closed-loop feedback: The receiving end jointly decodes the data blocks and redundant information, triggers local retransmission instructions according to the decoding results, and feeds them back to the network architecture to optimize subsequent transmission paths.

[0014] The above core design of the present invention realizes a double improvement in the reliability and efficiency of data transmission in the substation building through the collaborative design of dynamic environment adaptation, network-aware transmission, and closed-loop feedback, and is particularly suitable for scenarios with high interference and frequent node failures.

[0015] Further, the data processing for dynamic environment adaptation includes: Segment data with high real-time requirements into fine-grained data blocks, where the segmentation granularity of the fine-grained data blocks is dynamically adjusted according to the current network packet loss rate, and the segmentation granularity decreases as the network packet loss rate increases; Embed device identification, timestamp, and priority tags in each data block, where the assignment of the priority tags is dynamically updated according to the functional criticality level of the data source device.

[0016] The combination of fine-grained segmentation and dynamic priority tags ensures that critical data can still be quickly restored when the network deteriorates, while reducing the resource occupancy of non-critical data.

[0017] Furthermore, the generation of the redundant coding strategy includes: Dynamic selection of coding functions: Select at least one coding function from Reed-Solomon, LDPC, or Fountain Codes according to the priority tag of the data block and the real-time network signal-to-noise ratio; Dynamic adjustment of the redundancy ratio: The redundancy ratio of critical data increases with the increase of the signal-to-noise ratio to resist the packet loss risk caused by channel interference; The redundancy ratio of non-critical data decreases with the increase of node load to reduce the impact of network congestion on transmission efficiency.

[0018] Dynamically select coding functions and redundancy ratios based on network status to balance reliability and bandwidth efficiency in complex channel environments and avoid redundant waste.

[0019] Furthermore, the collaborative transmission of network awareness includes: Dynamic frequency band switching: Control the terminal node to dynamically switch between the 2.4GHz and 5GHz frequency bands according to the real-time channel interference monitoring results, where the 5GHz frequency band is preferentially used in high-interference scenarios to improve anti-interference ability; Redundancy allocation optimization: Based on the real-time monitoring value of node load and signal strength threshold, dynamically allocate redundant information to nodes with load lower than the preset threshold and signal strength meeting the standard, and link with the priority tag of the data block to ensure that the redundant information of critical data is preferentially allocated to high-stability nodes.

[0020] The dual-frequency switching and load-sensitive redundancy allocation strategy significantly improves the anti-packet loss ability in high-interference scenarios and optimizes the node resource utilization rate.

[0021] Furthermore, the fault tolerance recovery of the closed-loop feedback includes: Multi-channel verification and fault location: Perform multi-channel cross-verification on the data block according to the timestamp and device identification during decoding to identify lost or incorrect data blocks and their associated transmission nodes; Dynamic network reconstruction: Generate local retransmission instructions according to the verification results and automatically perform the following operations: Mask the faulty node and switch the subsequent data transmission to the backup path; Reduce the non-critical data transmission priority of the backup path and prioritize ensuring the bandwidth resources for critical data; Feed back the load status of the faulty node to the redundant encoding module and dynamically adjust the subsequent redundant allocation strategy.

[0022] The multi-channel verification and dynamic network reconstruction mechanism can complete the shielding of faulty nodes and path switching in a short time to ensure the continuous transmission of critical data.

[0023] Furthermore, it also includes: Edge preprocessing and encryption linkage: Before data segmentation, the terminal node performs noise filtering, anomaly detection, and data compression on the original data, and synchronously executes the AES-256 encryption algorithm in the preprocessing stage to generate encrypted data blocks; Dynamic signature and key management: Dynamically generate differentiated digital signatures according to the priority tags of data blocks, and allocate independent encryption keys for different devices through a distributed key management mechanism.

[0024] Encryption and compression are synchronously executed in the preprocessing stage, reducing the amount of transmitted data. At the same time, the balance between security and processing efficiency is achieved through differentiated signatures.

[0025] Furthermore, it also includes: Device-network joint prediction model: Based on the historical operation data of distribution equipment including voltage, current, and temperature and the network state data including packet loss rate and node load, jointly train a machine learning model to predict the network congestion risk and channel interference level in the future time period; Prediction-driven dynamic adjustment: According to the prediction results, perform the following operations in advance: In high congestion risk periods, reduce the redundancy ratio of non-critical data and preferentially allocate it to low-load paths; In high interference prediction areas, allocate additional redundant information for critical data and enable backup relay nodes.

[0026] Based on the joint prediction of device operation parameters and network status, optimize the encoding and transmission strategies in advance to reduce the impact of sudden failures on the system.

[0027] And, a wireless communication system for a substation building based on a cooperative coding algorithm, including: A dynamic environment adaptation module for segmenting data blocks according to the real-time requirements of substation building equipment data and dynamically generating a redundant encoding strategy; A network-aware transmission module for transmitting data blocks and redundant information through multi-node cooperation and dynamically adjusting the transmission path and redundant allocation according to the network state; A closed-loop feedback control module for jointly decoding data blocks and redundant information and triggering local retransmission instructions according to the decoding results to optimize the network architecture.

[0028] The system design matches the core design of the method of the present invention, realizes end-to-end optimization through a modular architecture (adaptation → transmission → feedback), is compatible with the transformation of old equipment and the deployment of new systems, and reduces the upgrade cost.

[0029] Further, the dynamic environment adaptation module includes: A data segmentation unit configured to segment high-real-time data into fine-grained data blocks and embed device identifiers, timestamps, and priority tags; A redundant coding unit configured to select a coding function according to the priority tag of the data block and the network signal-to-noise ratio and dynamically adjust the redundancy ratio; The network-aware transmission module includes: A dual-band communication unit integrating 2.4GHz and 5GHz dual-band wireless modules, and dynamically switching the communication frequency band according to channel interference; A load balancing controller configured to preferentially allocate redundant information to nodes with low load and high signal strength; The closed-loop feedback control module includes: A joint decoder configured to identify lost data blocks through multi-channel cross-checking; A network topology optimizer configured to mask faulty nodes and switch to an alternate path according to a retransmission instruction.

[0030] The hot-swappable interface and multi-antenna relay node design solve the problem of accessing old station equipment and enhance signal stability in complex electromagnetic environments.

[0031] Further, it further includes: An edge computing unit configured to perform data preprocessing and local caching; A security encryption unit integrating the AES-256 encryption algorithm and a digital signature generator; A visualization monitoring platform that displays the network health status and device anomaly warning information in real time.

[0032] The visualization platform and cloud collaboration unit support remote operation and maintenance and real-time security monitoring, meeting the stringent requirements of the power system for reliability and maintainability.

[0033] In addition, an electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, the steps of the wireless communication method for a distribution substation based on a cooperative coding algorithm as described above are implemented.

[0034] A non-transitory computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the wireless communication method for a distribution substation based on a cooperative coding algorithm as described above are implemented.

[0035] Compared with the prior art, the present invention and its preferred embodiments have at least the following beneficial effects: 1. Reliability of operation data transmission in distribution substations: The prior art usually relies on a single data transmission path, which makes the communication process vulnerable to interference and data loss. In contrast, the proposed solution in this application divides data into multiple data blocks through a cooperative coding algorithm and generates redundant information, enabling multiple terminal nodes to cooperate in coding and transmitting data. Even if some data blocks are lost, the system can still recover the original data through the redundant information, thus significantly improving the reliability of data transmission.

[0036] 2. Optimization of operation data transmission efficiency in distribution substations: Traditional wireless communication methods may have high latency and inefficient data transmission. This proposal reduces the number of retransmissions and improves data transmission efficiency through an optimized data transmission process and cooperative decoding technology. Especially in a complex power data environment, the optimized data transmission path and coding strategy can significantly improve the speed and accuracy of data transmission.

[0037] 3. Reduction of power consumption and maintenance costs: The prior art may require frequent equipment maintenance and high power consumption. By introducing a cooperative coding algorithm and a flexible network architecture, the present invention reduces the system power consumption and maintenance requirements. Cooperative coding reduces the dependence on repeated transmissions and retransmissions, while simplifying the network structure and reducing the overall maintenance cost of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described in detail below with reference to the drawings and specific embodiments: Figure 1 It is the overall flowchart of the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0039] Hereinafter, specific embodiments of the present application will be described in detail with reference to the drawings. According to these detailed descriptions, those skilled in the art can clearly understand the present application and can implement the present application. Without departing from the principle of the present application, the features in different embodiments can be combined to obtain a new implementation manner, or some features in some embodiments can be replaced to obtain other preferred implementation manners.

[0040] As Figure 1 shown, the overall technical solution provided by the embodiment of the present invention is specifically introduced as follows: 1. Cooperative coding algorithm (1)Multi-level data segmentation and adaptive coding design Data Classification and Partitioning: Based on the data collected from the distribution substation building, such as the switch status of the distribution substation building, the monitoring data of secondary equipment, the operating parameters of distribution transformers, temperature parameters, and meter information, etc., preliminary classification is carried out, and the data is divided into two major categories with high and low real-time performance; the data with high real-time performance is segmented with fine granularity to ensure independent transmission and decoding at key nodes.

[0041] Data Block Marking: Embed device identification, data type, timestamp, and priority information in each data block to facilitate recombination and verification according to priority and device characteristics during decoding.

[0042] Data Segmentation: Segment the data to be transmitted, such as the switch status of the distribution substation building, secondary equipment data, and metering information, into several data blocks. Assume the original data D is segmented into n data blocks Di, where i = 1, 2, …, n.

[0043] 。

[0044] Adaptive Coding Strategy: 1) Refinement of Coding Function: Use multiple coding methods (such as Reed - Solomon, LDPC, Fountain / Raptor Codes) to generate redundant information. Dynamically select an appropriate coding function f based on data importance and network status to ensure that key information is protected by a high redundancy ratio, while secondary data can use a lower redundancy ratio.

[0045] 2) Adaptive Adjustment of Coding Parameters: The system dynamically adjusts coding parameters (check code length, fragment size, and redundancy ratio) by real - time monitoring of the wireless link status, signal - to - noise ratio, and node load, and uses a prediction model to estimate transmission reliability in advance, so as to perform optimization processing at the data coding stage.

[0046] 3) Coding Generation: Generate corresponding redundant information for each data block of key information in the distribution substation building and distribute this information to multiple terminal nodes. Assume the redundant information is Ri, then: where f is the coding function, and the generated redundant information Ri will be distributed to multiple terminal nodes Tj, where j = 1, 2, …, m.

[0047] (2) Distributed Cooperative Coding and Task Allocation 1) Negotiation and Task Scheduling among Nodes: Use a lightweight protocol to achieve information exchange among terminal nodes (node computing power, current network load, channel quality, and device interface status), and formulate a global task allocation strategy based on the negotiation results.

[0048] 2) Dynamic task allocation: Using an adaptive scheduling algorithm, the original data blocks and generated redundant information are allocated to each node Tj in real time to ensure load balancing and optimize the allocation according to the specific hardware interfaces of the nodes (such as interfaces supporting different protocols).

[0049] 3) Distributed fault tolerance mechanism: When some nodes are unable to transmit data due to interference or faults, the system automatically triggers the fault tolerance mechanism, and redundant data is provided by other nodes for compensation to ensure the integrity of data transmission.

[0050] 4) Cooperative transmission: Multiple terminal nodes jointly participate in data transmission to improve transmission reliability through cooperation. Let the set of terminal nodes be: . Then each node Tj is responsible for transmitting the data blocks and redundant information allocated to it.

[0051] Data recombination: The receiving end restores the complete operation data of the substation building equipment by combining and decoding the received data blocks and redundant information. Let the data received by the receiving end be , then there is: where g is the decoding function.

[0052] (3) Data recombination and adaptive decoding 1) Joint decoding strategy: The control center uses the decoding function g to jointly process multiple data blocks and redundant information from different terminal nodes, and adopts multi-path parallel verification, cross-comparison and fault tolerance algorithms to restore the complete data.

[0053] 2) Adaptive decoding process: According to the number of received data blocks, signal strength and timestamp information, automatically determine the positions of missing data blocks and use redundant information for local complementation. An iterative decoding algorithm is adopted to ensure that key information can still be quickly restored in the case of a high data packet loss rate.

[0054] 3) Secondary retransmission mechanism: For data blocks that cannot be restored by one-time decoding, the system adopts a short-time local retransmission mechanism, combines historical statistical data, anticipates the retransmission window and frequency in advance, and optimizes the decoding success rate.

[0055] Optimization of wireless communication network architecture (1) Design of terminal nodes and integration of device interfaces Multi-protocol interface: The terminal node is configured with a multi-protocol data acquisition card, supporting the IEC 61850 protocol, to ensure seamless connection with substation building equipment such as circuit breakers, distribution transformers, temperature sensors and smart meters.

[0056] Embedded Processor and Local Storage: Equipped with a low-power embedded processor for preliminary data preprocessing, such as data filtering, compression, and local caching, to ensure data can be stored even when the link is interrupted for subsequent transmission.

[0057] Wireless Module and Dual-Band Communication: Integrated with 2.4GHz and 5GHz dual-band wireless modules, combined with a multi-antenna design to optimize signal coverage and interference suppression, adapting to complex electromagnetic environments.

[0058] (2)Relay Nodes and Intelligent Mesh Network 1)Automatic Signal Amplification and Link Selection: The relay node is built-in with a signal amplifier and an intelligent link selection algorithm. According to the real-time signal strength and interference situation, it automatically selects the best forwarding path.

[0059] 2)Self-Organizing Mesh Network: Build an ad-hoc mesh network among nodes. Nodes can dynamically reconstruct the network topology to ensure that data can be transmitted through other paths when any node fails.

[0060] 3)Redundant Backup and Fault Switching: Implement redundant backup among relay nodes. When the primary relay node fails, the standby node automatically takes over data relaying to ensure the continuity of data transmission.

[0061] (3)Control Center and Unified Management Platform Multi-Protocol Gateway Integration: The control center is equipped with a dedicated gateway that is compatible with various data transmission protocols to achieve unified data aggregation and distribution. Big Data Analysis and Cloud Backup: Establish a two-way data backup mechanism between local and cloud. Through big data analysis and machine learning algorithms, monitor the network status, load balancing, and anomaly detection in real time.

[0062] Real-Time Monitoring and Scheduling System: Adopt a visual monitoring interface to monitor the status of each network node, link quality, and data transmission in real time, and support automatic scheduling strategies, such as dynamically adjusting the transmission rate, allocating relay node tasks, etc.

[0063] Detailed Description of the Data Transmission Process Multi-Source Data Synchronous Acquisition: Each terminal node collects data in real time from the breaker status, transformer parameters, temperature, meter data, etc. in the power distribution station building, and uses clock synchronization technology to ensure the time consistency of the data.

[0064] Preprocessing and Compression: After data is collected, it first undergoes preprocessing work such as noise filtering, anomaly detection, and data compression, and generates data identifiers and priority tags for subsequent encoding and transmission.

[0065] Coding Processing and Redundancy Generation: Each data block completes preliminary coding locally to generate redundancy information, and uses edge computing to perform quality detection on the coding results; the redundancy information is embedded with redundant check codes, data type identifiers, timestamps, and device information in the data packet to ensure that lost data blocks can be quickly located and retransmitted during decoding.

[0066] Distributed Cooperative Data Transmission: The terminal node uses a dual-band wireless module to transmit the original data block and redundancy information simultaneously, sharing the data load through multiple wireless channels to reduce interference and signal attenuation; a dedicated transmission protocol is formulated to clarify the data packet format, transmission order, check mechanism, and retransmission mechanism, and handshake protocols are used between nodes to ensure data integrity.

[0067] Data Reception, Joint Decoding, and Correction: Joint Data Reorganization: The control center performs multi-channel joint processing on the received data, sorts the data blocks using timestamps and device identifiers to ensure correct data reorganization; an iterative decoding algorithm is used to perform error detection and correction on the data, and local errors are quickly corrected through the local retransmission mechanism to ensure complete data recovery.

[0068] Technical Advantages and Innovation Points Improved Communication Reliability: The combination of multi-level data segmentation and redundancy coding with distributed cooperative transmission can still ensure complete data transmission in a high-interference environment. The adaptive decoding and local retransmission mechanism effectively reduce data loss and transmission delay.

[0069] Optimized Data Transmission Efficiency: The application of dual-band wireless modules and intelligent relay nodes enables the network to have strong anti-interference and load balancing capabilities. The self-organizing mesh network technology ensures that when any node fails, the network can quickly reconstruct the transmission path and reduce system downtime.

[0070] Reduced Power Consumption and Operation and Maintenance Costs: The use of low-power terminal designs and embedded edge processing realizes local data preprocessing and caching, reducing the working power consumption of devices. Automatic fault detection, retransmission, and self-organizing network designs greatly reduce the dependence on manual intervention and on-site maintenance.

[0071] Interface Customization and System Compatibility: Dedicated acquisition modules are designed according to the characteristics of various devices in the substation building, supporting IEC 61850 standard interfaces to achieve unified management of data from multi-vendor devices. Multiple check codes and security authentication identifiers are embedded in the data packet to ensure high reliability of data during acquisition, transmission, and decoding.

[0072] Dynamic Adaptive Scheduling: Based on real-time network status and data priorities, the system can automatically adjust coding, transmission, and decoding strategies to ensure overall transmission stability even in the event of sudden network interference or node failures.

[0073] Implementation Plan and Application Optimization (1)System Deployment and Network Planning Terminal Node Deployment: Based on the on-site layout, equipment distribution, and interference environment of the substation building, conduct detailed node coverage planning. Set redundant nodes in key monitoring areas and arrange additional relay nodes in high-interference areas to ensure that all data sources can be stably connected to the network.

[0074] Network Topology Design: Build a distributed self-organizing network with the control center as the core and terminals and relay nodes as edge nodes, and adopt a hybrid topology of star and mesh to meet the requirements of different regions. Detailedly plan the signal links, backup links, and fault switching strategies between nodes to ensure that data transmission is not interrupted in case of anomalies.

[0075] (2)Data Management and Integrated Applications Unified Data Monitoring Platform: Establish a centralized data platform to uniformly access the device data from all terminal nodes, transformers, temperatures, electricity meters, etc. in the substation building, and achieve multi-dimensional and global monitoring.

[0076] Implement historical data storage, trend analysis, and anomaly warning modules, deeply mine and compare the data in real time through big data technology, and assist operation and maintenance personnel in carrying out refined management.

[0077] Linkage Control and Automatic Response: The system automatically analyzes abnormal phenomena according to the multi-source data fusion results, and timely triggers linkage control strategies (such as automatically adjusting the load, starting standby equipment, or sending alarms) to improve the overall security of the system. Combine auxiliary information such as real-time video monitoring and thermal imaging data to achieve a comprehensive evaluation of the device operation status and environmental parameters.

[0078] (3)System Optimization and Continuous Improvement Use on-site operation data to continuously monitor network performance, node load, and transmission success rate, form a data feedback mechanism, and continuously adjust coding parameters, scheduling strategies, and node distribution through adaptive algorithms. Regularly carry out simulation tests and on-site drills to verify the response speed and stability of the system in various abnormal situations, and optimize and update according to the feedback.

[0079] Embed multi-layer security authentication and encryption algorithms (such as AES-256 encryption, digital signature, two-way authentication mechanism) in each link of data acquisition, transmission, and decoding to ensure data integrity and confidentiality. Implement distributed key management and permission control to ensure that only authorized users and devices can access or operate sensitive data.

[0080] (4)Distribution Transformer Data Monitoring Configure a dedicated sensor module on the distribution transformer to collect parameters such as voltage, current, load rate, power factor, and oil temperature in real time. Use a high-precision ADC module and a local data processing unit to ensure the accuracy of the collected data, and adopt a data filtering algorithm to reduce noise interference. For abnormal loads, excessive temperature rises, etc., analyze in advance through edge computing and trigger an early warning mechanism, and feedback it to the monitoring platform in real time. Compare with historical data, establish an anomaly detection model based on machine learning, and continuously optimize the early warning strategy.

[0081] (5)Monitoring the switch status of distribution transformers Configure highly responsive switch status sensors and action recorders to collect the status changes of circuit breakers, disconnectors, and other key switches in real time. Record the time, duration, and current impact value of each action, and realize the historical traceability of the status through the event log module. Use the collected status data to establish a status change model, judge abnormal operations or potential faults in real time, and assist in formulating preventive maintenance plans. Conduct joint analysis of equipment operation parameters and switch status, optimize the opening and closing strategies of circuit breakers and disconnectors, and reduce the failure risk caused by equipment aging or abnormal loads.

[0082] (6)Monitoring ambient temperature and local temperature rise Install temperature sensors and infrared thermal imagers near the transformer and high-temperature components to achieve regional temperature monitoring and local hot spot detection. Adopt a thermal image data and temperature sensor data fusion algorithm to generate a thermal map of equipment operation in real time, identify local overheating areas, and early warn of equipment anomaly risks.

[0083] (7)Integration of electricity meters and energy consumption data Use an intelligent electricity meter system to collect power data, support multi-channel current and voltage monitoring, and converge data with the centralized system through a data gateway. Perform local data analysis at the data collection end to preliminarily judge and mark sudden energy consumption anomalies. Correlate and analyze electricity meter data with transformer parameters, switch status, and environmental data to construct a full-dimensional energy consumption model. Mine historical data through a big data platform to assist power supply companies in load forecasting, energy consumption optimization, and energy-saving transformation suggestions.

[0084] Device interfaces and customized special protocols For various devices in the substation building, design dedicated modules for data collection, and realize signal conversion, protocol adaptation, and data preprocessing. Each collection node provides multiple input interfaces, supports hot plugging and multi-device concurrent collection, and meets the access requirements of complex devices in large substation buildings.

[0085] Through redundant design, when a single interface or module fails, the remaining interfaces can automatically take over the acquisition task to ensure uninterrupted data acquisition. An embedded device-level security authentication module is used to authenticate the identity of each data acquisition module and verify the data integrity. Remote firmware upgrade and security patch push are supported to ensure the security and stability during the long-term operation of the system.

[0086] Based on the same inventive concept, the present invention further provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions. Specifically, it is used to load and execute one or more instructions in the computer storage medium to implement the above method.

[0087] It should be further noted that, based on the same inventive concept, the present invention further provides a computer storage medium, on which a computer program is stored, and the computer program, when run by a processor, executes the above method. The storage medium may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used or combined with an instruction execution system, apparatus, or device.

[0088] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0089] The foregoing has shown and described the basic principles, main features and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited by the above embodiments, and the above embodiments and the descriptions in the specification only illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure will have various changes and improvements, and these changes and improvements all fall within the scope of the present disclosure claimed.

[0090] The present invention is not limited to the above best mode. Anyone can derive other various forms of a wireless communication method for a distribution substation based on a collaborative coding algorithm under the inspiration of the present invention. All equivalent changes and modifications made in accordance with the scope of the patent application of the present invention shall fall within the scope of the present invention.

Claims

1. A wireless communication method for a distribution substation based on a collaborative coding algorithm, characterized in that Including: Data processing with dynamic environment adaptation: According to the real-time requirements of substation equipment data, the original data is segmented into data blocks with priority tags, and a redundant coding strategy is dynamically generated based on the real-time network status; Network-aware collaborative transmission: The data blocks and redundant information are transmitted through multi-node collaboration, where the transmission path and redundant allocation ratio are dynamically adjusted according to the network signal quality, node load, and fault status; Fault-tolerant recovery with closed-loop feedback: The receiving end jointly decodes the data blocks and redundant information, triggers local retransmission instructions according to the decoding results, and feeds them back to the network architecture to optimize the subsequent transmission path.

2. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, characterized in that: The data processing with dynamic environment adaptation includes: Segmenting the data with high real-time requirements into fine-grained data blocks, where the segmentation granularity of the fine-grained data blocks is dynamically adjusted according to the current network packet loss rate, and the segmentation granularity decreases as the network packet loss rate increases; Embedding device identification, timestamp, and priority tags in each data block, where the assignment of the priority tags is dynamically updated according to the functional criticality level of the data source device.

3. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, characterized in that: The generation of the redundant coding strategy includes: Dynamic selection of coding functions: According to the priority tags of the data blocks and the real-time network signal-to-noise ratio, at least one coding function is selected from Reed-Solomon, LDPC, or Fountain Codes; Dynamic adjustment of the redundancy ratio: The redundancy ratio of critical data increases as the signal-to-noise ratio increases to resist the packet loss risk caused by channel interference; The redundancy ratio of non-critical data decreases as the node load increases to reduce the impact of network congestion on the transmission efficiency.

4. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, wherein: The network-aware collaborative transmission includes: Dynamic frequency band switching: According to the real-time channel interference monitoring results, control the terminal node to dynamically switch between the 2.4GHz and 5GHz frequency bands. In high-interference scenarios, the 5GHz frequency band is preferentially used to improve the anti-interference ability; Optimization of redundant allocation: Based on the real-time monitoring value of the node load and the signal strength threshold, the redundant information is dynamically allocated to the nodes with a load lower than the preset threshold and a signal strength reaching the standard, and is linked with the priority tags of the data blocks to ensure that the redundant information of critical data is preferentially allocated to high-stability nodes.

5. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, characterized in that: The fault-tolerant recovery with closed-loop feedback includes: Multi-channel verification and fault location: During decoding, multi-channel cross-verification is performed on the data blocks according to the timestamp and device identification to identify the lost or incorrect data blocks and their associated transmission nodes; Dynamic network reconstruction: According to the verification results, generate local retransmission instructions and automatically perform the following operations: Mask the faulty nodes and switch the subsequent data transmission to the backup path; Reduce the transmission priority of non-critical data on the backup path and preferentially guarantee the bandwidth resources of critical data; Feed back the load status of the faulty nodes to the redundant coding module to dynamically adjust the subsequent redundant allocation strategy.

6. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, characterized in that, It also includes: Edge preprocessing and encryption linkage: Before data segmentation, the terminal node performs noise filtering, anomaly detection, and data compression on the original data, and synchronously executes the AES-256 encryption algorithm in the preprocessing stage to generate encrypted data blocks; Dynamic Signature and Key Management: Dynamically generate differentiated digital signatures based on the priority tags of data blocks, and allocate independent encryption keys to different devices through a distributed key management mechanism.

7. The wireless communication method for a distribution substation based on a collaborative coding algorithm according to claim 1, wherein It also includes: Device-Network Joint Prediction Model: Jointly train a machine learning model based on historical distribution equipment operation data including voltage, current, and temperature and network status data including packet loss rate and node load to predict network congestion risks and channel interference levels in future time periods; Prediction-Driven Dynamic Adjustment: According to the prediction results, perform the following operations in advance: During high congestion risk periods, reduce the redundancy ratio of non-critical data and preferentially allocate it to low-load paths; In high interference prediction areas, allocate additional redundant information to critical data and enable backup relay nodes.

8. A wireless communication system for a distribution substation based on a collaborative coding algorithm, characterized in that, It includes: Dynamic Environment Adaptation Module, used to segment data blocks according to the real-time requirements of substation equipment data and dynamically generate redundancy coding strategies; Network-Aware Transmission Module, used to transmit data blocks and redundant information through multi-node cooperation, and dynamically adjust the transmission path and redundancy allocation according to the network status; Closed-Loop Feedback Control Module, used to jointly decode data blocks and redundant information, and trigger local retransmission instructions according to the decoding results to optimize the network architecture.

9. The substation wireless communication system based on a cooperative coding algorithm according to claim 8, characterized in that: The dynamic environment adaptation module includes: Data Segmentation Unit, configured to segment high-real-time data into fine-grained data blocks and embed device identifiers, timestamps, and priority tags; Redundancy Coding Unit, configured to select a coding function according to the priority tag of the data block and the network signal-to-noise ratio, and dynamically adjust the redundancy ratio; The network-aware transmission module includes: Dual-Band Communication Unit, integrating 2.4GHz and 5GHz dual-band wireless modules, and dynamically switching communication bands according to channel interference; Load Balancing Controller, configured to preferentially allocate redundant information to low-load, high-signal-strength nodes; The closed-loop feedback control module includes: Joint Decoder, configured to identify lost data blocks through multi-channel cross-checking; Network Topology Optimizer, configured to mask faulty nodes and switch to backup paths according to retransmission instructions.

10. The wireless communication system for a distribution substation based on a collaborative coding algorithm according to claim 8, wherein It also includes: Edge Computing Unit, configured to perform data preprocessing and local caching; Security Encryption Unit, integrating the AES-256 encryption algorithm and a digital signature generator; Visualization Monitoring Platform, which displays the network health status and device anomaly warning information in real time.

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