Low power multi-mode ad hoc network communication method and system based on high voltage direct current power

Abstract

The application relates to the technical field of power communication, in particular to a low-power-consumption multi-mode ad hoc network communication method and system based on high-voltage direct-current power. The method comprises the following steps: obtaining a multi-mode link quality and energy consumption model by performing multi-mode link quality and energy consumption modeling according to obtained direct-current power field device topology and operating condition parameters; obtaining multi-mode link state data by collecting real-time residual energy data and multi-mode link quality data of a local end; obtaining a regional local network view by exchanging and integrating the collected multi-mode link state data; obtaining multi-mode ad hoc network routing data by analyzing and calculating the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm; and obtaining a target communication mode and a relay path by screening according to the multi-mode ad hoc network routing data and the operating condition parameters. The application can realize continuous, stable, reliable and energy consumption optimized ad hoc network communication capability in a complex high-voltage direct-current power field.

Description

Technical Field

[0001] This application relates to the field of power communication technology, and in particular to a low-power multimode self-organizing network communication method and system based on high-voltage direct current power. Background Technology

[0002] While high-voltage direct current (HVDC) transmission projects have been implemented on a large scale in areas such as large-capacity long-distance power transmission, inter-provincial transmission of renewable energy, and regional grid interconnection, and the on-site deployment of converter valves, DC field equipment, grounding electrodes, and various monitoring terminals generally relies on fiber optic communication, industrial Ethernet, or a single wireless private network to transmit on-site data back to the control center, existing projects mostly use pre-planned wired communication architectures or centralized wireless base station coverage modes, with fixed communication topologies. On-site terminals also mostly adopt active power supply modes, and overall, there is a lack of sufficient attention to the energy consumption of terminal operation and the adaptive capability of communication links. With the rapid development of digital substations, smart distribution networks, and flexible DC grids, the scale of sensor deployment in DC application scenarios continues to expand. Mobile inspection robots, smart switches, and various online monitoring devices have placed more stringent demands on real-time communication, transmission reliability, and low power consumption. Communication technologies are also gradually evolving towards multi-mode fusion, self-organizing network networking, and edge collaboration. Combining power line carrier, low-power wide-area wireless communication, and traditional fiber optic communication is an important path to improve the network coverage and anti-interference performance in complex power environments. The industry also urgently needs to rely on local network autonomy to reduce its dependence on centralized master stations.

[0003] However, most current communication solutions adapted to high-voltage direct current (HVDC) power scenarios are still limited to a single communication mode or a rigid hierarchical network design. They lack a unified modeling mechanism for multi-mode communication link quality and terminal energy consumption, which is not combined with the actual topology of the DC field and the operating conditions of the power grid. This results in terminals being unable to achieve intelligent and coordinated switching between power line carrier, wireless, and fiber optic communication methods, easily leading to problems such as network coverage blind spots, communication link congestion, and high terminal energy consumption in some areas. At the same time, existing self-organizing network algorithms are mostly developed for general IoT scenarios and fail to fully consider the dynamic disturbances to the network topology caused by factors unique to HVDC scenarios, such as strong electromagnetic interference, insulation isolation partitions, and equipment maintenance switching. This makes it difficult to quickly complete network cluster structure reconstruction and routing strategy iteration updates. In addition, most low-power communication protocols rely solely on fixed duty cycle mechanisms to achieve energy saving and fail to link the power grid operating status and service priorities to carry out on-demand terminal wake-up control. This makes it impossible to achieve the global optimal configuration of network energy consumption while ensuring high-reliability transmission of power control services, and it is difficult to meet the digital, intelligent, and low-power communication operation requirements of new flexible DC power grids.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a low-power multimode self-organizing network communication method and system based on high-voltage direct current (HVDC) power. This method and system can achieve continuous, stable, reliable, and energy-optimized self-organizing network communication capabilities in complex HVDC power scenarios through the synergistic effects of multimode link modeling, dynamic sensing, adaptive topology, and differentiated low-power routing.

[0006] To achieve the above objectives, one aspect of this application proposes a low-power multimode self-organizing network communication method based on high-voltage direct current (HVDC) power, the method comprising the following steps: Obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; Based on the DC power field equipment topology and the first operating condition parameters, multimode link quality and energy consumption modeling is performed to obtain the multimode link quality and energy consumption model. Real-time acquisition of remaining energy data and first multimode link quality data of each terminal at the first time point to obtain multimode link status data; The terminals are controlled to exchange and integrate the collected multimode link status data through a data interaction mechanism to obtain a regional local network view; The terminals are controlled to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode self-organizing network routing data. The control system filters the target communication mode and relay path based on the multi-mode self-organizing network routing data and the first operating condition parameters. At the same time, the monitoring data and control data are encapsulated into a unified message and forwarded in multiple hops. Duty cycle scheduling and on-demand wake-up control are executed to obtain the terminal wake-up scheduling strategy. Real-time monitoring and collection of the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at the second time point; When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the terminals are controlled to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of the low-power multimode ad hoc network communication.

[0007] Preferably, the step of performing multimode link quality and energy consumption modeling based on the DC power field equipment topology and the first operating condition parameters to obtain a multimode link quality and energy consumption model includes the following steps: Based on the communication methods of power line carrier communication, wireless narrowband communication and fiber optic / Ethernet communication, data is collected for different combinations of DC power field equipment topologies and the first operating condition parameters to obtain multimode link quality data and energy consumption data. The multimode link quality data and the energy consumption data are normalized. The multimode link quality data and the energy consumption data after normalization are correlated and mapped to form a model, thereby obtaining the multimode link quality and energy consumption model.

[0008] Preferably, the real-time acquisition of remaining energy data and first multimode link quality data of each terminal at the first time point to obtain multimode link status data includes the following steps: At the site of the high-voltage direct current power supply, the first multimode link quality data and the remaining energy data of each terminal are continuously collected at the first time point according to the adaptive acquisition cycle associated with the first operating condition parameters, so as to obtain the local multimode link quality data sequence and the remaining energy data sequence. After smoothing and filtering and trend analysis of the local multimode link quality data sequence, the local multimode link quality data sequence and the remaining energy data sequence are jointly encoded to obtain the multimode link status data.

[0009] Preferably, the step of exchanging and integrating the collected multimode link status data through a data interaction mechanism to obtain a regional local network view includes the following steps: The data interaction mechanism adds timestamp information and hop count to each piece of multimode link status data. Multimode link status data whose hop count does not exceed a preset hop count threshold is forwarded between adjacent terminals. At the same time, multimode link status data whose timestamp is earlier than the current storage version is discarded to obtain the target multimode link status data. Based on the target multimode link status data and the comprehensive cost index output by the multimode link quality and energy consumption model, correlation analysis and topology organization are performed to obtain the local network view of the region.

[0010] Preferably, the step of controlling each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode ad hoc network routing data includes the following steps: The control system constructs a weight function by fusing the number of neighboring terminals, the remaining energy data in the local multimode link status data, and the comprehensive cost index output by the multimode link quality and energy consumption model in the local network view of the region. Each terminal is controlled to compete for cluster heads according to the weight function to obtain the basic network cluster structure, wherein the cluster head terminal in the basic network cluster structure has high energy and has at least two effective communication modes. The system controls each terminal to obtain a multi-mode forwarding role by simultaneously enabling power line carrier communication and wireless narrowband communication or fiber optic / Ethernet communication between different clusters, while filtering terminals whose comprehensive cost index reaches a preset threshold. The control system analyzes and calculates each terminal based on the network cluster structure and the multi-mode forwarding role to obtain the multi-mode self-organizing network routing data.

[0011] Preferably, the step of controlling each terminal to analyze and calculate the multimode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multimode ad hoc network routing data further includes the following steps: The control system uses the comprehensive cost index output by the multi-mode link quality and energy consumption model as the path weight to perform adaptation calculations on the multi-mode link and network path, thereby obtaining a set of candidate paths for monitoring data and control data. After controlling each terminal to select a path with a low comprehensive cost index and a preset reliability threshold from the candidate path set for monitoring data, and to select a path from the candidate path set for control data that meets preset energy consumption constraints and whose path hop count does not exceed a preset delay limit, the candidate path sets for monitoring data and control data are encoded and summarized to obtain the multi-mode self-organizing network routing data.

[0012] Preferably, the control of each terminal filters the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. Simultaneously, the monitoring data and control data are encapsulated into a unified message and forwarded via multi-hop. Duty cycle scheduling and on-demand wake-up control are then executed to obtain the terminal wake-up scheduling strategy, including the following steps: The control unit processes the first operating condition parameters to obtain operating condition levels, including normal operating conditions, heavy load operating conditions, or fault / maintenance operating conditions; and sets the duty cycle and wake-up sequence according to the operating condition levels. The system controls each terminal to configure differentiated wake-up duration and wake-up frequency according to the operating condition level, multi-mode forwarding role, and cluster head terminal identity, thereby obtaining the terminal wake-up scheduling strategy.

[0013] Preferably, the step of controlling each terminal to filter based on the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path, and simultaneously encapsulating the monitoring data and control data into a unified message for multi-hop forwarding, and executing duty cycle scheduling and on-demand wake-up control to obtain a terminal wake-up scheduling strategy, further includes the following steps: The control terminal uses the multi-mode self-organizing network routing data and the first operating condition parameters to perform communication adaptation matching and filtering on the monitoring data and the control data respectively, so as to obtain the priority target communication mode and the main relay path; Each terminal is controlled to determine the communication link status by comparing the multi-mode link quality data corresponding to the priority target communication mode with a preset link quality threshold in real time. When the link quality is determined to be lower than the preset link quality threshold, the priority target communication mode and the primary relay path are switched to the backup target communication mode and the backup relay path in the multi-mode self-organizing network routing data.

[0014] Preferably, the real-time monitoring collects the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at a second time point; When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the system controls each terminal to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal, thereby completing the closed-loop operation of the low-power multimode ad hoc network communication. This includes the following steps: By using preset change thresholds, operating condition levels, and terminal state transition judgment conditions, changes in the second multimode link quality data, the second operating condition parameters, and the terminal state at the second time point are determined: When the change in the second multimode link quality data exceeds the preset change threshold, when a terminal undergoes a join / exit / multimode forwarding role status transition, or when the second operating condition parameter changes its operating condition level, the iterative update of the multimode link status data, the regional local network view, and the multimode self-organizing network routing data of each terminal is controlled. Each terminal is controlled to update and increment the version number and configure the expiration timer in each iteration. The multi-mode self-organizing network routing data received by each terminal is verified for version and filtered for timeliness. Only the multi-mode self-organizing network routing data with the highest version number and within the expiration timer limit is retained to obtain the network routing configuration. The terminal wake-up scheduling strategy is adjusted according to the network routing configuration to complete the closed-loop operation of the low-power multi-mode self-organizing network communication.

[0015] To achieve the above objectives, another aspect of this application proposes a low-power multimode self-organizing network communication system based on high-voltage direct current power, comprising: The multimode link modeling unit is used to obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; and to perform multimode link quality and energy consumption modeling based on the DC power field equipment topology and the first operating condition parameters to obtain the multimode link quality and energy consumption model. The link status sensing unit is used to collect the remaining energy data and the first multimode link quality data of each terminal at the first time point in real time to obtain the multimode link status data. A local network construction unit is used to control each terminal to exchange and integrate the collected multimode link status data through a data interaction mechanism to obtain a regional local network view. The cluster structure and route generation unit is used to control each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode self-organizing network routing data. The low-power communication scheduling unit is used to control each terminal to filter according to the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. At the same time, it encapsulates the monitoring data and control data into a unified message and performs multi-hop forwarding, and executes duty cycle scheduling and on-demand wake-up control to obtain the terminal wake-up scheduling strategy. An adaptive update unit is used to monitor and collect the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at a second time point in real time. When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the unit controls each terminal to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of the low-power multimode ad hoc network communication.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a low-power multimode self-organizing network communication method and system based on high-voltage direct current (HVDC) power. This scheme obtains the topology and first operating condition parameters of the DC power field equipment corresponding to each terminal at a first time point, and completes multimode link quality and energy consumption modeling based on these basic parameters, constructing a standardized multimode link quality and energy consumption model. This model can achieve quantitative characterization of multimode communication link quality and energy consumption under fixed operating conditions and topology at the first time point, providing accurate model support for network routing planning. Simultaneously, it collects the remaining energy data and first multimode link quality data of each terminal in real time at the first time point and integrates them to generate multimode link status data, which is then processed through a data interaction mechanism. The exchange and integration of multi-mode link status data is used to obtain a regional local network view. Multi-mode ad hoc network routing data is obtained by analyzing and calculating the multi-mode link quality and energy consumption model and the regional local network view using distributed algorithms. Then, the optimal target communication mode and relay path are selected and matched by combining the multi-mode ad hoc network routing data with the parameters of the first operating condition. Monitoring data and control data are encapsulated into a unified message to achieve reliable multi-hop forwarding. Terminal wake-up scheduling strategy adapted to the first time point operating condition is generated through duty cycle scheduling and on-demand wake-up control. Under the steady-state operation scenario at the first time point, intelligent adaptation of multi-mode communication mode, unified message forwarding and low-power orderly scheduling of terminals can be achieved, effectively improving the resource utilization and energy efficiency of high-voltage DC power field network communication. Simultaneously, continuous real-time collection and monitoring of second multi-mode link quality data, second operating condition parameters, and terminal status at the second time point enables all-weather dynamic perception of link communication quality, on-site operating conditions, and terminal working status. When any dimension of the second multi-mode link quality data, second operating condition parameters, or terminal status fluctuates, iterative updates of multi-mode link status data, regional local network views, and multi-mode self-organizing network routing data can be triggered in a timely manner. Based on the updated global network status, the terminal wake-up scheduling strategy is adaptively adjusted to suit the actual scenario at the second time point. Compared to a fixed static networking method, this enables dynamic networking from the first time point baseline modeling to the second time point. The closed-loop management system, encompassing perception, iterative updates, and adaptive strategy adjustments, effectively adapts to real-world scenarios such as complex electromagnetic interference in high-voltage direct current (HVDC) power fields, operational condition switching, and dynamic changes in terminal status. It ensures the transmission reliability and low-power operation of multi-mode self-organizing network communication under steady-state conditions at the first point in time, while also enabling rapid route reconstruction, communication link switching, and dynamic optimization of wake-up scheduling strategies when link quality, operational conditions, or terminal status change at the second point in time. This avoids problems such as link failures, routing loops, and energy waste, significantly improving the environmental adaptability, transmission stability, overall low-power management capabilities, and self-healing iteration capabilities of multi-mode self-organizing network communication in HVDC power scenarios. Attached Figure Description

[0017] Figure 1This is a flowchart of a low-power multimode self-organizing network communication method based on high-voltage direct current provided in the embodiments of this application; Figure 2 yes Figure 1 Flowchart of step S110; Figure 3 yes Figure 1 Flowchart of step S120; Figure 4 yes Figure 1 Flowchart of step S130; Figure 5 yes Figure 1 Flowchart of step S140; Figure 6 This is a schematic diagram of the structure of a low-power multimode self-organizing network communication system based on high-voltage DC power provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0021] Each terminal: All communication terminals deployed within the high-voltage DC power field, and all network nodes responsible for data acquisition, network interaction, routing and forwarding, and power consumption scheduling.

[0022] Each terminal's local end: refers to the local device side of each terminal, specifically the local entity that independently collects data, executes calculations, and controls control strategies.

[0023] First time point: The baseline initial moment for system initial network modeling, parameter acquisition, and strategy generation.

[0024] The second time point: the subsequent moment during system operation used for status monitoring, parameter comparison, and triggering iterative updates.

[0025] Figure 1 This is an optional flowchart of a low-power multimode self-organizing network communication method based on high-voltage direct current provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S110 to S160.

[0026] Step S110: Obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; perform multi-mode link quality and energy consumption modeling based on the DC power field equipment topology and first operating condition parameters to obtain the multi-mode link quality and energy consumption model. Step S120: Collect the remaining energy data and the first multimode link quality data of each terminal at the first time point in real time to obtain the multimode link status data; Step S130: Control each terminal to exchange and integrate the collected multimode link status data through the data interaction mechanism to obtain a regional local network view; Step S140: Control each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode self-organizing network routing data; Step S150: Control each terminal to filter according to the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. At the same time, encapsulate the monitoring data and control data into a unified message and perform multi-hop forwarding. Then, execute duty cycle scheduling and on-demand wake-up control to obtain the terminal wake-up scheduling strategy. Step S160: Real-time monitoring and collection of the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at the second time point; when the second multimode link quality data, second operating condition parameters, or terminal status change, control each terminal to iteratively update the multimode link status data, regional local network view, and multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of low-power multimode ad hoc network communication.

[0027] Steps S110 to S160 as shown in this embodiment first obtain the DC power field equipment topology and first operating condition parameters corresponding to each terminal at the first time point. Based on the DC power field equipment topology and the first operating condition parameters, multi-mode link quality and energy consumption modeling is performed to construct a multi-mode link quality and energy consumption model. Then, the remaining energy data and first multi-mode link quality data of each terminal at the first time point are collected in real time and integrated to generate multi-mode link status data. Next, each terminal is controlled to exchange and integrate the collected multi-mode link status data through a preset data interaction mechanism to generate a regional local network view. Then, each terminal is controlled to use a distributed algorithm to perform joint analysis and calculation based on the constructed multi-mode link quality and energy consumption model and the regional local network view to solve for multi-mode ad hoc network routing data. After that, each terminal is controlled to use the multi-mode ad hoc network routing data and the multi-mode ad hoc network routing data to solve for multi-mode ad hoc network routing data. The first operating condition parameters are used to filter communication paths and modes, determine the target communication mode and relay path, and encapsulate the field monitoring data and control data into a unified format message for multi-hop forwarding. Duty cycle scheduling and on-demand wake-up control are executed simultaneously to generate a terminal wake-up scheduling strategy adapted to network operation. At the same time, the second multi-mode link quality data, the second operating condition parameters, and the terminal's own operating status are continuously monitored and collected in real time at the second time point for each terminal. When any dimension of the second multi-mode link quality data, the second operating condition parameters, or the terminal status is detected to have changed abnormally, each terminal is immediately controlled to iteratively update and correct the existing multi-mode link status data, the regional local network view, and the multi-mode self-organizing network routing data to adaptively adjust the terminal wake-up scheduling strategy corresponding to its own end, thereby realizing dynamic adaptation and closed-loop stable operation of low-power multi-mode self-organizing network communication in high-voltage DC power scenarios.

[0028] In some embodiments, in step S110, such as Figure 2As shown, in the modeling stage of the low-power multimode self-organizing network communication method for DC power fields, each terminal, based on the acquired DC power field equipment topology and first operating condition parameters, conducts multimode link quality and energy consumption modeling for three communication methods: power line carrier communication, wireless narrowband communication, and fiber optic or Ethernet communication. Modeling first relies on actual high-voltage DC power field environment to collect measured data. By deploying several test terminals on-site, it simulates actual operating scenarios such as different equipment connection methods, different load levels, and different switch switching states, traversing various combinations of DC power field equipment topologies and first operating condition parameters to systematically conduct communication performance and energy consumption tests. The first multimode link quality data selects at least one or more of the following as evaluation indicators: successful transmission rate, average round-trip time, packet loss ratio, retransmission count, and interference alarm count. Energy consumption data is defined as the average power of the terminal transmitting monitoring and control data per unit time, or the energy consumption per transmission of a fixed-length message. To ensure the comprehensiveness and representativeness of the modeling samples, at least ten typical DC power field equipment topologies and at least five first operating condition parameters were selected for cross-combination, covering actual operating scenarios such as different load sections, different pole connection methods, and different maintenance states. Finally, at least fifty sets of first multimode link quality data and corresponding energy consumption data adapted to three communication modes were obtained, laying a sufficient field sample foundation for subsequent normalization processing and model construction.

[0029] After collecting multiple sets of first-mode link quality and energy consumption data, to eliminate the impact of differences in dimensions and magnitudes of indicators, and to achieve horizontal comparison and unified processing among the three communication modes, it is necessary to normalize the collected original first-mode link quality and energy consumption data and construct a multi-dimensional indicator set. This embodiment, combining engineering practice experience and field statistical patterns, defines reasonable upper and lower limit ranges for various original evaluation indicators such as successful transmission rate, average round-trip time, packet loss ratio, retransmission count, interference alarm count, and energy consumption per unit of service volume. Each original measured data item is mapped and converted into a dimensionless value between 0 and 1 according to the corresponding interval rules. When the normalized value approaches 1, it indicates that the corresponding link quality indicator performance is better or the energy consumption level is lower; when the value approaches 0, it indicates poor link quality performance or high energy consumption. Taking power line carrier communication links as an example, under a specific equipment topology and first operating condition parameter combination, if the measured successful transmission rate reaches 98% and the energy consumption per unit of service is at a low level, after normalization, a quality index value of about 0.9 and an energy consumption index value of about 0.2 can be obtained. By integrating and aggregating all normalized single indicators under the same link, the same operating condition, and the same communication mode, a standardized multi-dimensional index set can be formed, which can serve as the standardized input features for subsequent modeling operations.

[0030] Based on the generated multi-dimensional indicator set, the first multi-mode link quality data and energy consumption data are correlated and mapped using samples from this set. A functional relationship is constructed that can simultaneously transform link quality and energy consumption characteristics into a single quantifiable value, and this functional relationship is solidified into a multi-mode link quality and energy consumption model. The comprehensive cost index output by the model can comprehensively represent the overall level of link communication quality and energy consumption on a single numerical dimension, following the evaluation principle that the smaller the value, the better the overall performance of the link while meeting business operation requirements. The modeling process adopts a weighted configuration method, assigning differentiated weight coefficients to the normalized quality and energy consumption indicators. The weight values ​​can be flexibly adapted and configured according to the type of on-site business. For protection and control business scenarios, emphasis is placed on communication reliability and transmission latency performance, with higher weights assigned to reliability and latency-related indicators and medium weights assigned to energy consumption indicators, for example, a reliability weight of 5 and an energy consumption weight of 2. For routine status monitoring business scenarios, the weights of energy consumption indicators are appropriately increased and the weights of latency indicators are decreased to achieve business adaptability optimization. The constructed mapping function relationship can be implemented using a rule comparison table, a segmented combination judgment rule, or by relying on a multi-dimensional index set sample fitting to generate an empirical model. Finally, it is stored in the terminal device or edge control device in the form of a parameter configuration table or a built-in program.

[0031] This embodiment provides the preferred quantization function relationship as follows: In the formula This represents the overall cost index of a multimode link. The normalized link quality index, which represents the range from 0 to 1, is calculated by normalizing various original quality indices. The closer the value is to 1, the better the link quality. The energy consumption normalization index represents the range from 0 to 1. It is calculated from the original energy consumption data. The closer the value is to 1, the higher the energy consumption. This represents a quality indicator weighting coefficient ranging from 0 to 1, used to dynamically balance the evaluation proportions of link quality and energy consumption. In control data service scenarios with stringent latency and reliability requirements, the weighting coefficient can be... The value is set to around 0.7 to prioritize communication link quality; in monitoring data service scenarios centered on energy consumption management, it can be... The value is set to around 0.5 to achieve a balance between link quality and energy consumption.

[0032] The multi-mode link quality and energy consumption model constructed by weighting a linear combination of the above-mentioned normalized indices can simultaneously measure the comprehensive performance of links under different communication modes and topology conditions on a unified numerical scale. During actual terminal operation, the first multi-mode link quality data and energy consumption data collected in real time only need to be normalized to generate a multi-dimensional index set. The built-in multi-mode link quality and energy consumption model can then be called to quickly output the corresponding comprehensive cost index. This index can be directly used as the path weight basis in subsequent cluster structure reconstruction, multi-mode forwarding role allocation, and multi-mode ad hoc network routing data generation processes. This enables quantitative comparability and global optimization selection of three communication methods—power line carrier communication, wireless narrowband communication, and fiber optic / Ethernet communication—under different DC power field equipment topologies and operating conditions, supporting the stable and adaptive operation of low-power multi-mode ad hoc networks.

[0033] In some embodiments, in step S120, such as Figure 3 As shown, in the low-power multimode self-organizing network communication method for DC power fields, each terminal collects its remaining energy data and first multimode link quality data in real time and generates multimode link status data. Firstly, based on the actual operating scenario of the HVDC power field, and combined with the first operating condition parameters, an adaptive acquisition cycle is matched to complete the periodic continuous acquisition of link and energy data. This application divides the operating condition levels of HVDC power fields into at least three categories: normal operating condition, heavy load operating condition, and fault / maintenance operating condition. Differentiated data acquisition cycles are preset for different operating condition levels: the acquisition cycle is set to 60s under normal operating condition, shortened to 10s under heavy load operating condition, and further reduced to 1s under fault / maintenance operating condition. Through the adaptive cycle acquisition mechanism adapted to the operating condition, the data acquisition frequency can be reduced and terminal energy consumption reduced under normal stable operating conditions. Simultaneously, under critical operating conditions such as load fluctuations and fault maintenance, the first multimode link quality data and remaining energy data can be collected with higher time resolution, ensuring the real-time performance and accuracy of status perception in special scenarios. The collected first multimode link quality data includes one or more link quality evaluation indicators such as successful transmission rate, average round-trip time, packet loss ratio, and retransmission count. The remaining energy data can be obtained directly from the terminal's battery level or estimated based on the terminal's long-term average power. During continuous data collection, each terminal sequentially stores the first multimode link quality data collected each time into its local storage area, forming a local multimode link quality data sequence. Simultaneously, the remaining energy data collected each time is stored in time sequence, forming a remaining energy data sequence. For example, if 100 data collections are completed continuously under normal operating conditions, a local multimode link quality data sequence and a remaining energy data sequence, both with a length of 100, can be generated, providing a complete time-series data source for subsequent data processing and feature extraction.

[0034] After each terminal constructs its own multimode link quality data sequence, in order to avoid data spike noise caused by occasional factors such as electromagnetic interference and channel fluctuations, and to accurately discover the steady-state variation pattern of link quality, it is necessary to perform smoothing filtering and trend analysis on the local multimode link quality data sequence. This application adopts a sliding time window method to achieve data smoothing and noise reduction and feature layered extraction. First, a short-term sliding window is constructed by selecting short-term sampling points. For example, the most recent 10 sampling points are selected as a calculation window. The mean or median of various link quality indicators such as successful transmission rate, average round-trip time, and packet loss ratio within the window are calculated. After smoothing calculation, the smooth quality features within the corresponding time window are obtained, which serve as the short-term fluctuation features of link quality, characterizing the subtle fluctuations of link communication status at a short time scale. On this basis, a long-term benchmark window is constructed by selecting sampling data with a longer time domain, such as the most recent 100 sampling points. By calculating the average, maximum, and minimum values ​​of each link quality indicator within the long-term window, long-term variation features that can reflect the long-term operational benchmark level of the link are extracted. By comparing short-term window feature results with long-term window benchmark results, the current link quality status can be accurately determined, distinguishing between three states: normal minor fluctuations, gradual performance degradation, and significant deterioration in communication quality. For example, if the judgment rule is set that the short-term average packet loss ratio is more than 0.1 higher than the long-term average and persists for multiple sliding windows, it can be determined that the link quality is showing a degradation trend. Through a complete processing flow of smoothing filtering and noise reduction, short-term and long-term feature decomposition, and link status determination, a set of quality features that can simultaneously characterize the short-term fluctuation characteristics and long-term evolution patterns of the link is finally obtained, eliminating invalid noise interference and retaining the true link change trend.

[0035] After each terminal completes smoothing filtering and trend analysis of its local multi-mode link quality data sequence to obtain a set of quality features, the extracted short-term fluctuation features and long-term change features are further jointly encoded with the constructed remaining energy data sequence to finally generate multi-mode link status data. Joint encoding involves standardizing and compressing three different dimensions of status information—short-term link features, long-term link features, and terminal remaining energy—according to a unified data structure, enabling a single data transmission to fully carry the terminal's link communication status and remaining energy status. In the specific encoding implementation, a terminal time-series status record can be constructed according to a fixed field structure. The record sequentially configures core fields such as the average short-term window successful transmission rate, the average short-term window round-trip time, the average long-term window packet loss ratio, the average long-term window retransmission count, and the current remaining energy percentage, along with a timestamp and operating condition level identifier. Alternatively, a level-based discretization compression method can be used to divide continuous numerical indicators such as successful transmission rate and remaining energy into multiple level intervals, replacing the original values ​​with level encoding, effectively reducing data transmission bandwidth consumption. The multi-mode link status data generated through joint encoding integrates short-term fluctuation characteristics, long-term change characteristics, and terminal remaining energy information at the data structure level. It can comprehensively depict the communication link status and energy constraint status of the high-voltage direct current power field terminals, providing refined, structured, and low-redundancy basic status data for subsequent data interaction and integration between terminals, construction of regional local network views, cluster structure reconstruction, and accurate calculation of multi-mode self-organizing network routes. It is suitable for the complex electromagnetic environment and low-power networking operation requirements of high-voltage direct current power scenarios.

[0036] In some embodiments, in step S130, such as Figure 4 As shown, each terminal exchanges and integrates the collected multimode link status data through a data interaction mechanism, thereby constructing a local network view. In the pre-processing stage of data interaction and transmission, when each terminal prepares to send its own multimode link status data, it first configures additional identification information for the data to be sent, mainly including two key parameters: timestamp information and hop count. The timestamp information is recorded using the terminal's local clock, employing a complete time identifier format of year, month, day, hour, minute, and second. Its core function is to distinguish different versions of multimode link status data, providing a time basis for subsequent data version comparison and old / new identification. The hop count is used to accurately count the forwarding frequency of a single multimode link status data item between terminal networks. The hop count is incremented by 1 every time data completes a forwarding through a relay terminal, thus quantifying the network propagation range of the data.

[0037] Each terminal is pre-configured with a fixed hop count threshold, for example, set to 3, which serves as the boundary for determining whether to continue forwarding multimode link status data. During data forwarding, the terminal reads the hop count value carried by the received multimode link status data. Only when the hop count value does not exceed the preset hop count threshold is the multimode link status data allowed to continue forwarding to neighboring terminals. If the hop count value reaches or exceeds the preset hop count threshold, the data forwarding process is immediately terminated. This mechanism effectively constrains the spread of multimode link status data throughout the network, prevents the unlimited flooding of massive status data from consuming effective network bandwidth, reduces network resource consumption caused by invalid data transmission, and ensures the rational allocation of communication resources in the DC power field.

[0038] To ensure that all terminals across the network maintain the latest and most valid version of multimode link status data from the same source terminal and to avoid interference from outdated data in network configuration decisions, this application introduces a strict data version control mechanism. When a terminal receives new multimode link status data, it first extracts the timestamp information carried by the data and compares it one by one with the timestamps of the corresponding multimode link status data from the same source terminal already stored in the local database. Following the principle of new versions overwriting old versions, the new data is considered valid and up-to-date only if the timestamp of the received new data is later than the timestamp of the locally stored data. The new data then replaces the existing old data to complete the update. If the timestamp of the new data is earlier than or equal to the timestamp of the locally stored version, the currently received redundant old data is discarded. This version control logic completely eliminates the abnormal situation of old data overwriting new data, significantly reducing redundant data and information conflicts in the network. Simultaneously, the short-term fluctuation characteristics, long-term change characteristics, and terminal remaining energy information contained in the multimode link status data can all maintain timeliness and data reliability within the region under version control, laying a unified and accurate data foundation for subsequent network view construction.

[0039] After multiple rounds of multi-mode link status data interaction, forwarding filtering, and version iteration updates, each terminal retains valid multi-mode link status data that has been filtered and verified, i.e., target multi-mode link status data. Based on this, each terminal, from its own perspective, integrates its own and neighboring terminals' target multi-mode link status data within a preset hop range, extracting multi-mode link adjacency relationships between terminals. Simultaneously, link quality data and energy consumption data under different communication modes are input into a pre-established multi-mode link quality and energy consumption model to solve for the comprehensive cost index corresponding to each link. Using terminal pairs and communication modes as index dimensions, a multi-mode link adjacency table is generated. This adjacency table and the comprehensive cost index of each link are then structurally integrated to form a graph structure representation, ultimately constructing a regional local network view. This regional local network view clearly presents the multi-mode link topology and link cost distribution characteristics within a few hops around a single terminal. The entire construction process does not rely on a central control node and is entirely completed autonomously by the distributed terminals, providing reliable topology and link cost support for subsequent network cluster structure partitioning, multi-mode forwarding role allocation, and the analysis, calculation, and generation of multi-mode self-organizing network routing data.

[0040] In some embodiments, in step S140, such as Figure 5 As shown, each terminal operates as an independent computing entity, without relying on a central control node. This adapts to the complex topology of high-voltage DC power field environments characterized by multi-regional distribution, long transmission distances, and strong electromagnetic interference. Each terminal periodically reads the locally stored regional local network view and its own multi-mode link status data. The regional local network view includes the identifiers of each neighboring terminal, the adjacency relationships of multi-mode links between neighboring terminals, and the comprehensive cost index output by the multi-mode link quality and energy consumption model. The multi-mode link status data includes the terminal's remaining energy data. Each terminal executes the same distributed decision-making rules locally, laying the data and algorithm foundation for a consistent network architecture across the entire network.

[0041] Each terminal extracts the number of its neighbors from the local network view, the remaining energy data from its local multimode link status data, and the comprehensive cost index of adjacent multimode links output by the multimode link quality and energy consumption model. These three core influencing factors are then fused to construct a weighting function. This weighting function is essentially a calculation rule that converts multi-dimensional evaluation factors into a single cluster head score, used to quantify the suitability of a single terminal as a cluster head terminal. From the perspective of suitability principles, the more neighboring terminals a terminal has, the more central it is in the network topology, and the higher its value as a network hub. Higher remaining energy data means it can handle more cross-terminal data forwarding tasks and has energy reserves for long-term stable operation. Lower comprehensive cost index corresponding to multimode links indicates better overall performance in terms of communication quality and operating energy consumption between the terminal and its neighbors. In practical applications, the weighting ratio of each influencing factor can be configured empirically, such as setting the weight of the number of neighboring terminals to 2, the weight of remaining energy data to 3, and the weight of the comprehensive cost index to 2, and calculating the cluster head score of each terminal through a weighted summation method.

[0042] Within a set competition period, each terminal broadcasts its own cluster head score within the local network coverage area and compares it horizontally with the scores of neighboring terminals. The terminal with the highest score is selected as the current cluster head terminal, and the remaining terminals are automatically classified as ordinary cluster member terminals. This completes the cluster head competition and builds the foundation for the network cluster structure. The determined cluster head terminal has the characteristics of sufficient remaining energy, superior topological location, excellent multi-mode link comprehensive performance, and is equipped with at least two effective communication modes, ensuring the stability and endurance of intra-cluster communication.

[0043] After the network cluster structure is built, each cluster head terminal and terminals near the cluster boundary retrieve the local network view of the area, check the distribution of cross-cluster multimode links recorded internally, and carry out the multimode forwarding role screening and configuration work. First, terminals with both power line carrier communication and wireless narrowband communication capabilities, or both power line carrier communication and fiber optic / Ethernet communication capabilities, are selected as candidate terminals. Then, they are sorted and screened according to the comprehensive cost index corresponding to the cross-cluster multimode links. Only when the comprehensive cost index of the cross-cluster links associated with a candidate terminal is lower than the preset index threshold, the candidate terminal is marked as a multimode forwarding role, undertaking the functions of inter-cluster data relay forwarding and multimode communication mode switching. This enables service interoperability and flexible adaptation of communication modes between different network clusters, while strictly controlling link quality and overall energy consumption.

[0044] After determining the basic network cluster structure and multi-mode forwarding role allocation scheme, each terminal conducts path planning with network connectivity, monitoring data transmission reliability, control data transmission latency constraints, and overall network energy consumption balance as joint optimization objectives. This joint optimization objective requires that the network path not only ensures constant communication connectivity for all terminals across the network, but also matches differentiated performance indicators for different service types, while avoiding excessive concentration of forwarding tasks that could cause energy overload for some terminals. In specific applications, the basic constraints are set as a long-term packet loss rate of less than 1% for monitoring data and an end-to-end latency of no more than 100 milliseconds for control data. The comprehensive cost index output by the multi-mode link quality and energy consumption model is used as the network path weight. Multiple feasible transmission paths from the cluster head terminal to other cluster head terminals and network aggregation nodes are traversed and searched, constructing candidate path sets for monitoring data and control data respectively.

[0045] Each terminal employs a differentiated path selection strategy for different service types. For monitoring data, paths with low overall cost indicators and meeting preset transmission reliability thresholds are prioritized. For example, the long-term successful transmission rate of all links on a path is limited to no less than 99%, and a primary path and a backup path are selected based on the principle of minimizing the sum of overall cost indicators. For control data, paths that meet preset energy consumption constraints and whose hop count does not exceed preset latency limits are prioritized. For example, the maximum allowed forwarding hop count is set to 5 hops to ensure low-latency transmission of control commands in multi-mode switching and multi-relay forwarding scenarios. Finally, the selected monitoring data and control data candidate path sets are encoded and summarized according to a unified data structure, fully recording the primary and backup transmission paths corresponding to various services, the cluster head terminals and multi-mode forwarding role terminal identifiers along the path, and the matching communication mode information, ultimately generating standardized multi-mode self-organizing network routing data. Each terminal then performs multi-hop forwarding of messages and communication mode selection based on this routing data, thereby achieving low-power multi-mode self-organizing network communication operation that balances network connectivity, service transmission reliability, control command latency constraints, and overall network energy consumption under complex high-voltage DC power conditions.

[0046] In some steps, such as step S150, each terminal performs comprehensive screening based on multi-mode self-organizing network routing data and first operating condition parameters to determine the target communication mode and relay path that adapts to the service transmission requirements. At the same time, it performs unified message encapsulation on field monitoring data and equipment control data and completes multi-hop forwarding across the entire network. Simultaneously, it implements refined duty cycle scheduling and hierarchical on-demand wake-up control, and finally generates a terminal wake-up scheduling strategy that adapts to the complex operating scenario of DC power fields, so as to realize low-power, high-reliability collaborative transmission of multi-mode communication services.

[0047] At the message forwarding processing level, each terminal periodically queries the locally stored multi-mode self-organizing network routing data to read the primary and backup transmission paths corresponding to monitoring and control services, as well as the communication modes and corresponding relay terminal identifiers for each hop link of each transmission path. This application encapsulates monitoring and control data into a standardized message structure. The message contains a service type field, source terminal identifier, destination terminal identifier, path number, mode number, and payload data, allowing different types of services to share the same data forwarding logic. This simplifies the complexity of message format design, eliminates the configuration and maintenance overhead of multiple forwarding rules, and significantly reduces the computation time and overhead when terminals parse and process different service data. At the same time, the unified message structure provides a unified basis for subsequent duty cycle scheduling and on-demand wake-up control, enabling terminals to use the same wake-up strategy logic to determine whether to process arriving service messages immediately, thus improving the regularity and efficiency of terminal message processing and scheduling control.

[0048] At the duty cycle and wake-up timing configuration level, to adapt to the flexible adjustment requirements of communication interface activity under different operating conditions of DC power plants, each terminal first classifies the collected first operating condition parameters into three fixed levels: normal operation, heavy load operation, and fault or maintenance operation. Each level is then matched with preset, dedicated communication duty cycle parameters and wake-up timing rules. Under the normal operation level, a longer wake-up period and shorter active duration are set, typically configured as a 60-second wake-up period with only 5 seconds of interface activity and the remaining 55 seconds in sleep / energy-saving mode. Under the heavy load operation level, the wake-up period is shortened and the active duration is extended, with a 20-second wake-up period and 8 seconds of interface activity. Under the fault or maintenance operation level, the wake-up period is further compressed to 5 seconds and the interface active duration is set to 3 seconds, ensuring rapid response and transmission of control data such as fault alarms and equipment regulation. By configuring duty cycles differently according to the operating condition level, it can minimize the ineffective energy consumption of monitoring terminals under normal operating conditions, and ensure that the multi-mode communication network has sufficient data response and service transmission capabilities under heavy load and critical fault maintenance conditions, thus achieving a dynamic balance between energy consumption and communication performance.

[0049] At the level of generating differentiated wake-up scheduling strategies, this method combines the functional roles of terminals in multi-mode ad hoc networks, and relies on the operating condition level, multi-mode forwarding role, and cluster head terminal identity to configure differentiated wake-up duration and wake-up frequency for various types of terminals, ultimately forming a complete terminal wake-up scheduling strategy. For ordinary terminals that do not undertake multi-mode forwarding tasks, the interface active duration is further compressed under normal operating conditions, so that they are only responsible for periodic monitoring data reporting, maximizing the saving of terminal energy consumption; for terminals that undertake multi-mode forwarding roles and cluster head management functions, the wake-up frequency is actively increased and the active duration is extended under heavy load operating conditions or fault maintenance operating conditions, so as to complete core tasks such as control message relay and communication mode switching request processing in a smaller time interval; for terminals that carry control data forwarding tasks, a higher message processing active priority is set. Once a control data message is detected to arrive, an early wake-up mechanism can be triggered. Even if the terminal is in a normal sleep stage, it can immediately switch to the working processing state through a low-power interrupt mechanism, strictly meeting the transmission requirements of low latency and high real-time performance of control data.

[0050] At the communication mode and relay path adaptation and selection level, each terminal relies on multi-mode self-organizing network routing data and combines it with real-time first operating condition parameters to conduct service-specific communication adaptation matching and selection for monitoring data and control data. This involves matching the optimal priority target communication mode and main relay path for each type of service. Service adaptation follows a differentiated selection principle: monitoring data prioritizes optimal energy consumption, prioritizing communication modes with lower overall cost indicators in the current local network view. In DC power field areas with weak electromagnetic interference, power line carrier communication is prioritized to reduce transmission energy consumption. Control data prioritizes transmission reliability and latency performance, prioritizing communication modes with high transmission success rates and low round-trip latency in the current network environment. In conventional scenarios, wireless narrowband communication or fiber optic / Ethernet communication is preferred. By matching dedicated communication modes and relay paths for different service types, the high reliability and low latency communication requirements of control data can be met while ensuring low-energy transmission of monitoring data, achieving reasonable allocation and efficient utilization of multi-mode communication resources.

[0051] In terms of automatic cross-mode switching and communication redundancy assurance, each terminal compares the quality data of the first multi-mode link corresponding to the priority target communication mode with the preset link quality threshold in real time, and continuously performs real-time judgment on the communication link status. When a key link indicator is detected to deteriorate below the threshold, such as the service success transmission rate dropping below 0.9, the data packet loss ratio rising above 0.1, or the average round-trip latency exceeding 100ms, it is immediately determined that the current link communication quality does not meet the service transmission requirements. Then, the backup target communication mode and backup relay path pre-stored in the multi-mode self-organizing network routing data are retrieved to automatically complete the seamless switching across communication modes and transmission paths. In practical applications, when the power line carrier communication is affected by on-site electromagnetic interference, causing the link quality to deteriorate, the terminal can automatically switch to wireless narrowband communication. If the wireless narrowband communication latency indicator does not meet the standard, it can further switch to fiber optic or Ethernet communication to complete data transmission. This cross-mode redundancy switching protection mechanism can effectively resist communication fluctuations caused by complex operating conditions such as magnetic field disturbances, equipment switching, and link congestion in high-voltage DC scenarios, ensuring the continuous and stable operation of multi-mode self-organizing network communication and greatly improving the anti-interference capability and communication robustness of the entire DC power field communication system.

[0052] In some embodiments, during step S160, during the operation of low-power multimode ad hoc network communication in a DC power field, each terminal continuously monitors the second multimode link quality data, the second operating condition parameters, and its own operating status in real time at a second time point. This allows them to perceive the dynamic changes in the field communication environment, equipment operating status, and network topology. When a substantial change in relevant parameters is detected, an iterative update process for multimode link status data, regional local network view, and multimode ad hoc network routing data is initiated. Then, the terminal wake-up scheduling strategy is dynamically adjusted based on the updated network and routing information, ultimately achieving closed-loop stable operation of low-power multimode ad hoc network communication. To adapt to the special application requirements of high-voltage DC power scenarios and avoid problems such as excessive terminal computing load, redundant network signaling interaction, and network oscillation caused by irregular and uncontrolled frequent data updates, this application sets strict and clear triggering conditions for the iterative update of multimode link status data, regional local network view, and multimode ad hoc network routing data. The entire network iterative update is only initiated when the specified triggering conditions are met, reducing unnecessary update overhead and resource consumption from the source.

[0053] Regarding the specific judgment logic for triggering iterative updates, this application sets judgment criteria from three dimensions: link quality, terminal status, and operating conditions. For the second multi-mode link quality data, the results of two adjacent data collections are used as the comparison benchmark. Only when the change in link quality exceeds the preset change threshold is it determined that the link status has undergone a substantial change. Typical judgment criteria include quantitative indicators such as a decrease in communication success rate exceeding 0.1, an increase in average round-trip latency exceeding 50 milliseconds, and an increase in packet loss ratio exceeding 0.05. For the terminal status, when the terminal undergoes state transition behaviors between joining the network, leaving the network, and assuming the role of multi-mode forwarding, it is determined that the network topology or forwarding backbone architecture has changed, thus meeting the conditions for triggering iterative updates. For the second operating condition parameters, when the parameter operating level undergoes a cross-level switch, such as switching from normal operating conditions to heavy load operating conditions, or from heavy load operating conditions to fault or maintenance operating conditions, it is determined that the service transmission priority and communication latency requirements have been adjusted, which also triggers the iterative update process. If any one of the above three conditions is met, the entire network iterative update process of multi-mode link status data, regional local network view, and multi-mode self-organizing network routing data will be initiated.

[0054] The iterative update in this application does not involve abandoning the original data and network architecture for a complete rebuild from scratch. Instead, it involves incremental correction and gradual optimization based on existing multimode link status data, regional local network views, and multimode ad hoc network routing data. When a terminal detects that the iterative update trigger condition is met, it first recalculates and generates the latest multimode link status data on its own end and broadcasts the updated multimode link status data to neighboring terminals. After receiving the broadcast data, the neighboring terminals synchronously update their stored regional local network views based on the new link status data, including replacing the comprehensive cost index of the corresponding communication links and updating key information such as the role labels of each terminal in the network. After the regional local network view is updated, the terminal re-performs adaptive cluster structure adjustment and route path calculation based on the updated view information. Modification and optimization of multimode ad hoc network routing data are only performed when there are substantial changes in network topology, link quality, or service requirements that necessitate such modifications. This step-by-step iterative update mode, from multi-mode link status data to regional local network views and then to multi-mode self-organizing network routing data, enables the cluster structure and routing strategy to match the actual operating conditions of the high-voltage DC power field in a timely manner, while avoiding the terminal computing loss and network communication burden caused by large-scale full data recalculation.

[0055] To address the issues of routing loops, excessively long network convergence times, and unstable convergence states caused by parallel iterative updates from multiple terminals in asynchronous distributed networking environments, this method assigns an incrementally increasing version number to each iteration update process and configures an expiration timer for the corresponding generated multi-mode self-organizing network routing data. The version number uses an integer to identify the order of iteration updates, with an initial version number set to 1, and automatically incremented by 1 after each valid iteration update. The expiration timer limits the maximum lifespan of a particular version of routing data that can be recognized, forwarded, and used in the network; an example setting is 120 seconds. When receiving multimode ad hoc network routing data from other terminals, each terminal first performs a version number verification mechanism. Local data replacement is only allowed if the version number of the received routing data is higher than the version number currently stored on the terminal; otherwise, the old version routing information is discarded. After version number verification, a timeliness verification is performed, comparing the time difference between the routing data generation time and the current system time. Only if the time difference does not exceed the expiration timer's set duration is the routing data deemed valid and retained for use; expired routing data is directly discarded. This dual mechanism, combining version number increment control and expiration timer constraints, effectively prevents the risk of old version routing data circulating and forming routing loops in the network. It also ensures that all network routing information can achieve consistent convergence within a limited time. Combined with the network routing configuration obtained after verification and filtering, the terminal wake-up scheduling strategy is dynamically adjusted, ultimately ensuring the overall operational stability and service transmission reliability of low-power multimode ad hoc network communication in high-voltage DC power scenarios.

[0056] The following is a detailed description and explanation of the scheme of this embodiment of the invention, using a specific scenario of the DC field area of ​​a high-voltage direct current converter station: Twelve communication terminals, labeled A1-A12, are deployed around the converter valve area, DC filter field, and smoothing reactor, with A1 designated as the station's access node. The terminals are configured differently according to their communication capabilities: A2, A5, and A8 simultaneously possess three communication modes: power line carrier communication, wireless narrowband communication, and fiber optic or Ethernet communication; A3, A4, A6, A7, A9, A10, A11, and A12 are configured with only two communication capabilities: power line carrier communication and wireless narrowband communication. The service terminals are deployed according to their monitoring functions: A3 is connected to an external temperature monitoring unit, A6 to an external partial discharge monitoring unit, and A9 to an external switch status acquisition unit. In the initial stage of this embodiment, the converter station is in normal operating condition, and the remaining energy range of all communication terminals is maintained between 62% and 95%, providing the basic hardware and operating environment for low-power multi-mode self-organizing network communication.

[0057] This embodiment first utilizes the field equipment topology of the converter valve area, DC filter field, smoothing reactor, and normal first-condition operating parameters within the station to complete the multimode link quality and energy consumption modeling. The model selects successful transmission rate, average round-trip time, packet loss ratio, retransmission count, and unit packet energy consumption as core input indicators. After normalizing each indicator, they are fused and calculated to form a comprehensive cost index, thereby constructing the multimode link quality and energy consumption model. The comprehensive cost of the forwarding link from each service terminal to the access node A1 within the station is obtained through quantitative calculation using the model. Specifically, the comprehensive cost index for A3 monitoring data forwarded to A1 via A2 is 0.31, for A6 monitoring data forwarded to A1 via A5 is 0.29, and for A9 control messages forwarded to A1 via A8 is 0.34, providing a quantitative basis for subsequent network routing selection.

[0058] Under normal operating conditions, each communication terminal sets a 10-second data acquisition cycle, periodically collecting the first multimode link quality data and remaining energy data of its own end. Each terminal retains the data sequence of the most recent 5 acquisition cycles. After smoothing filtering and trend analysis, standardized local multimode link status data is generated. During the multimode link status data exchange process, each terminal synchronously adds a timestamp and hop count value, and sets the network-wide hop count threshold to 3. The terminal executes a data version filtering strategy locally, directly discarding redundant data whose timestamps are earlier than the locally stored version. After completing the data exchange and integration, each terminal generates a local network view of the corresponding coverage area. Based on this, A2, A5, and A8 participated in the cluster head competition by constructing a weight function based on the number of neighboring terminals, remaining energy data, and comprehensive link cost index. After calculation, the weight values ​​of the three were 0.78, 0.81, and 0.76, respectively. Based on this, A2, A5, and A8 were determined as network cluster head terminals. At the same time, cross-cluster forwarding nodes were screened based on communication capabilities and link cost. A11 has more than two cross-cluster communication capabilities, and its comprehensive cost index of 0.37 is lower than the preset threshold of 0.50. Therefore, it was determined to be a network multi-mode forwarding role.

[0059] During the network routing generation phase, a differentiated path selection mechanism is adopted for monitoring data and control data, constructing separate candidate path sets for each. For monitoring data, communication paths with lower overall cost indicators and a success rate of no less than 95% are prioritized; for control data, communication paths with no more than 3 hops and an average round-trip latency of no more than 80ms are prioritized. Service link planning is completed according to the selection rules: temperature monitoring data collected by A3 is relayed to access node A1 within the station via relay A2, with a fixed transmission period of 30 seconds; partial discharge monitoring data collected by A6 is relayed to A1 via relay A5, maintaining a high-frequency reporting period of 10 seconds; switch status control messages generated by A9 are uploaded to A1 via relay A8, and message scheduling and transmission are performed according to control data priority. Simultaneously, the system implements a refined low-power scheduling strategy. Under normal operating conditions, the duty cycle of ordinary terminals is set to 15%, the duty cycle of cluster head terminals is set to 35%, and the duty cycle of role terminals undertaking multi-mode forwarding tasks is set to 40%, achieving a balance in network communication energy efficiency.

[0060] After 20 minutes of stable continuous operation, the communication performance of the power line carrier link used by A6 significantly degraded due to electromagnetic interference in the converter valve area. The link success rate dropped from 0.96 to 0.82, the average round-trip latency increased from 32ms to 95ms, and the packet loss rate increased from 0.02 to 0.09. The terminal detected that the quality data of the second multimode link deviated from the preset link quality threshold in real time, automatically triggering the network parameter iterative update process. A6 re-optimized and generated its own multimode link status data, and distributed the data to A5, A7, and A8 with a new timestamp and version number. After receiving the data, A5, A7, and A8 synchronously updated the local network view, correcting the comprehensive cost index of the A6 power line carrier link from 0.29 to 0.67, and simultaneously calibrating its comprehensive cost index of the wireless narrowband link to 0.38. After performance comparison, the A6 wireless narrowband link has a lower overall cost, a successful transmission rate of 0.94, and an average round-trip latency of 48ms, which meets the transmission requirements of partial discharge monitoring services. The communication mode and relay link were then switched, from the original power line carrier to the A5 relay for uploading, to wireless narrowband to the A5 relay for uploading.

[0061] This network iteration update incremented the multi-mode self-organizing network routing data version number from V12 to V13 and configured a 60-second routing data expiration timer. All terminals across the network implemented a dual filtering mechanism based on routing version and expiration time, retaining only routing data with the highest version number that had not exceeded the expiration timer. Older version routing information was no longer used for packet forwarding, effectively preventing routing loops in asynchronous distributed networking environments and constraining network update convergence time. After link switching was completed, the partial discharge monitoring data of A6 maintained a 10-second reporting cycle. During the subsequent 15 minutes of continuous operation, the average round-trip latency of the link was stably controlled within 51ms, and the packet loss ratio remained below 0.03, effectively ensuring the reliability of service transmission.

[0062] Ten minutes after A6 completed the communication link switch, the converter station's operating condition changed from normal operation to heavy load operation. Based on this change in operating condition, the system initiated adaptive adjustments to the network-wide power consumption and scheduling strategy. Each terminal synchronously corrected its duty cycle parameters and wake-up sequence. The duty cycle of ordinary terminals was increased from 15% to 25%, and the duty cycle of the cluster head terminal was increased from 35% to 55%. A8 and A11, responsible for forwarding control data, were set to priority wake-up status to ensure the real-time transmission priority of control messages. After the strategy adjustment, the switch status control messages sent by A9 could still complete end-to-end transmission within a two-hop range, with an average round-trip delay of only 43ms. This achieved adaptive switching of multi-mode communication links under complex DC field conditions and electromagnetic interference environments in the HVDC converter station, dynamic iteration of network topology, and low-power scheduling closed-loop operation.

[0063] Please see Figure 6 This application also provides a low-power multimode self-organizing network communication system based on high-voltage direct current power, which can implement the above-mentioned method. The system includes: The multimode link modeling unit is used to obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; and to perform multimode link quality and energy consumption modeling based on the DC power field equipment topology and first operating condition parameters to obtain the multimode link quality and energy consumption model. The link status sensing unit is used to collect the remaining energy data and the first multimode link quality data of each terminal at the first time point in real time to obtain the multimode link status data. The local network construction unit is used to control each terminal to exchange and integrate the collected multimode link status data through a data interaction mechanism to obtain a regional local network view; Cluster structure and route generation unit are used to control each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through distributed algorithms to obtain multi-mode self-organizing network routing data; The low-power communication scheduling unit is used to control each terminal to filter according to the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. At the same time, it encapsulates the monitoring data and control data into a unified message and performs multi-hop forwarding, and executes duty cycle scheduling and on-demand wake-up control to obtain the terminal wake-up scheduling strategy. The adaptive update unit is used to monitor and collect the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at the second time point in real time. When the second multimode link quality data, second operating condition parameters, or terminal status change, it controls each terminal to iteratively update the multimode link status data, regional local network view, and multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of low-power multimode ad hoc network communication.

[0064] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0065] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0066] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0067] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0069] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0070] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0071] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0072] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0073] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0074] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A low-power multimode self-organizing network communication method based on high-voltage direct current power, characterized in that, The method includes the following steps: Obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; Based on the DC power field equipment topology and the first operating condition parameters, multimode link quality and energy consumption modeling is performed to obtain the multimode link quality and energy consumption model. Real-time acquisition of remaining energy data and first multimode link quality data of each terminal at the first time point to obtain multimode link status data; The terminals are controlled to exchange and integrate the collected multimode link status data through a data interaction mechanism to obtain a regional local network view; The terminals are controlled to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode self-organizing network routing data. The control system filters the target communication mode and relay path based on the multi-mode self-organizing network routing data and the first operating condition parameters. At the same time, the monitoring data and control data are encapsulated into a unified message and forwarded in multiple hops. Duty cycle scheduling and on-demand wake-up control are executed to obtain the terminal wake-up scheduling strategy. Real-time monitoring and collection of the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at the second time point; When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the terminals are controlled to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of the low-power multimode ad hoc network communication.

2. The method according to claim 1, characterized in that, The step of performing multimode link quality and energy consumption modeling based on the DC power field equipment topology and the first operating condition parameters to obtain the multimode link quality and energy consumption model includes the following steps: Based on the communication methods of power line carrier communication, wireless narrowband communication and optical fiber or Ethernet communication, data is collected for different combinations of DC power field equipment topologies and the first operating condition parameters to obtain multimode link quality data and energy consumption data. The multimode link quality data and the energy consumption data are normalized. The multimode link quality data and the energy consumption data after normalization are correlated and mapped to form a model, thereby obtaining the multimode link quality and energy consumption model.

3. The method according to claim 1, characterized in that, The process of collecting the remaining energy data and first multimode link quality data of each terminal at the first time point in real time to obtain multimode link status data includes the following steps: At the site of the high-voltage direct current power supply, the first multimode link quality data and the remaining energy data of each terminal are continuously collected at the first time point according to the adaptive acquisition cycle associated with the first operating condition parameters, so as to obtain the local multimode link quality data sequence and the remaining energy data sequence. After smoothing and filtering and trend analysis of the local multimode link quality data sequence, the local multimode link quality data sequence and the remaining energy data sequence are jointly encoded to obtain the multimode link status data.

4. The method according to claim 1, characterized in that, The process of exchanging and integrating the collected multi-mode link status data through a data interaction mechanism to obtain a regional local network view includes the following steps: The data interaction mechanism adds timestamp information and hop count to each piece of multimode link status data. Multimode link status data whose hop count does not exceed a preset hop count threshold is forwarded between adjacent terminals. At the same time, multimode link status data whose timestamp is earlier than the current storage version is discarded to obtain the target multimode link status data. Based on the target multimode link status data and the comprehensive cost index output by the multimode link quality and energy consumption model, correlation analysis and topology organization are performed to obtain the local network view of the region.

5. The method according to claim 1, characterized in that, The control of each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode ad hoc network routing data includes the following steps: The control system constructs a weight function by fusing the number of neighboring terminals, the remaining energy data in the local multimode link status data, and the comprehensive cost index output by the multimode link quality and energy consumption model in the local network view of the region. Each terminal is controlled to compete for cluster heads according to the weight function to obtain the basic network cluster structure, wherein the cluster head terminal in the basic network cluster structure has high energy and has at least two effective communication modes. The system controls each terminal to obtain a multi-mode forwarding role by simultaneously enabling power line carrier communication and wireless narrowband communication, fiber optic communication, or Ethernet communication between different clusters, while filtering terminals whose comprehensive cost index reaches a preset threshold. The control system analyzes and calculates each terminal based on the network cluster structure and the multi-mode forwarding role to obtain the multi-mode self-organizing network routing data.

6. The method according to claim 5, characterized in that, The method of controlling each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode ad hoc network routing data also includes the following steps: The control system uses the comprehensive cost index output by the multi-mode link quality and energy consumption model as the path weight to perform adaptation calculations on the multi-mode link and network path, thereby obtaining a set of candidate paths for monitoring data and control data. After controlling each terminal to select a path with a low comprehensive cost index and a preset reliability threshold from the candidate path set for monitoring data, and to select a path from the candidate path set for control data that meets preset energy consumption constraints and whose path hop count does not exceed a preset delay limit, the candidate path sets for monitoring data and control data are encoded and summarized to obtain the multi-mode self-organizing network routing data.

7. The method according to claim 1, characterized in that, The control system filters each terminal based on the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. Simultaneously, it encapsulates monitoring data and control data into a unified message and performs multi-hop forwarding, executing duty cycle scheduling and on-demand wake-up control to obtain a terminal wake-up scheduling strategy, including the following steps: The control unit obtains the operating condition level by classifying the first operating condition parameters. The operating conditions include normal operating condition, heavy load operating condition, or fault or maintenance operating condition. The duty cycle and wake-up sequence are matched and set according to the operating condition level. The system controls each terminal to configure differentiated wake-up duration and wake-up frequency according to the operating condition level, multi-mode forwarding role, and cluster head terminal identity, thereby obtaining the terminal wake-up scheduling strategy.

8. The method according to claim 7, characterized in that, The method of controlling each terminal to filter based on the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path, and simultaneously encapsulating the monitoring data and control data into a unified message for multi-hop forwarding, and executing duty cycle scheduling and on-demand wake-up control to obtain the terminal wake-up scheduling strategy, also includes the following steps: The control terminal uses the multi-mode self-organizing network routing data and the first operating condition parameters to perform communication adaptation matching and filtering on the monitoring data and the control data respectively, so as to obtain the priority target communication mode and the main relay path; Each terminal is controlled to determine the communication link status by comparing the multi-mode link quality data corresponding to the priority target communication mode with a preset link quality threshold in real time. When the link quality is determined to be lower than the preset link quality threshold, the priority target communication mode and the primary relay path are switched to the backup target communication mode and the backup relay path in the multi-mode self-organizing network routing data.

9. The method according to claim 1, characterized in that, The real-time monitoring collects the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at the second time point; When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the system controls each terminal to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal, thereby completing the closed-loop operation of the low-power multimode ad hoc network communication. This includes the following steps: By using preset change thresholds, operating condition levels, and terminal state transition judgment conditions, changes in the second multimode link quality data, the second operating condition parameters, and the terminal state at the second time point are determined: When the change in the second multimode link quality data exceeds the preset change threshold, a terminal joins or leaves, or the multimode forwarding role status transitions, or the second operating condition parameter changes the operating condition level, the iterative update of the multimode link status data, the regional local network view, and the multimode self-organizing network routing data of each terminal is controlled; Each terminal is controlled to update and increment the version number and configure the expiration timer in each iteration. The multi-mode self-organizing network routing data received by each terminal is verified for version and filtered for timeliness. Only the multi-mode self-organizing network routing data with the highest version number and within the expiration timer limit is retained to obtain the network routing configuration. The terminal wake-up scheduling strategy is adjusted according to the network routing configuration to complete the closed-loop operation of the low-power multi-mode self-organizing network communication.

10. A low-power multimode self-organizing network communication system based on high-voltage direct current, characterized in that, include: The multimode link modeling unit is used to obtain the DC power field equipment topology and first operating condition parameters of each terminal at the first time point; Based on the DC power field equipment topology and the first operating condition parameters, multimode link quality and energy consumption modeling is performed to obtain the multimode link quality and energy consumption model. The link status sensing unit is used to collect the remaining energy data and the first multimode link quality data of each terminal at the first time point in real time to obtain the multimode link status data. A local network construction unit is used to control each terminal to exchange and integrate the collected multimode link status data through a data interaction mechanism to obtain a regional local network view. The cluster structure and route generation unit is used to control each terminal to analyze and calculate the multi-mode link quality and energy consumption model and the regional local network view through a distributed algorithm to obtain multi-mode self-organizing network routing data. The low-power communication scheduling unit is used to control each terminal to filter according to the multi-mode self-organizing network routing data and the first operating condition parameters to obtain the target communication mode and relay path. At the same time, it encapsulates the monitoring data and control data into a unified message and performs multi-hop forwarding, and executes duty cycle scheduling and on-demand wake-up control to obtain the terminal wake-up scheduling strategy. An adaptive update unit is used to monitor and collect the second multimode link quality data, second operating condition parameters, and terminal status of each terminal at a second time point in real time. When the second multimode link quality data, the second operating condition parameters, or the terminal status changes, the unit controls each terminal to iteratively update the multimode link status data, the regional local network view, and the multimode ad hoc network routing data to adjust the terminal wake-up scheduling strategy corresponding to each terminal and complete the closed-loop operation of the low-power multimode ad hoc network communication.

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