Satellite internet of things based public network free area power line monitoring system and method thereof

Abstract

This invention discloses a power line monitoring system and method based on satellite Internet of Things (IoT) in areas without public grid coverage, belonging to the field of power system monitoring technology. The system includes monitoring terminal nodes, a satellite IoT constellation, and a ground data processing center. The monitoring terminal nodes are fixedly installed on power line towers or conductors and include sensor modules, a main control unit, a satellite IoT communication module, and a power management module. The satellite IoT constellation consists of several low-Earth orbit communication satellites for data relay. The ground data processing center includes a data receiving server, a data storage and processing platform, an intelligent analysis engine, and a user interface. This invention employs a multi-source data fusion-based comprehensive assessment model for line health, achieving collaborative analysis of electrical and mechanical conditions. This invention solves the problem of power line monitoring in areas without public grid coverage, realizing all-weather, automated, and low-cost intelligent monitoring, significantly improving the safe and stable operation of the power grid.

Description

Technical Field

[0001] This invention relates to the field of power system monitoring technology, and in particular to a power line monitoring system and method for areas without public grid access based on satellite Internet of Things. Background Technology

[0002] my country's power grid is vast, with a wide-ranging transmission and distribution network. Numerous high-voltage transmission and distribution lines traverse complex, uninhabited areas, including towering mountains, expansive grasslands, and primeval forests. A significant proportion of these transmission lines pass through regions with weak or no public grid signal coverage. In these areas, power lines are constantly exposed to complex and variable natural environments, facing various risks such as wildfires, ice accumulation, wind deflection, and geological disasters. Real-time monitoring is crucial for ensuring the safe and stable operation of the power grid.

[0003] Currently, power line monitoring in areas without public grid coverage mainly relies on regular manual inspections and drone inspections. Manual inspections require maintenance personnel to trek through complex terrain to visually inspect the lines, which is inefficient, poses personal safety risks, and cannot provide real-time fault warnings. While drone inspections improve efficiency to some extent, they are still limited by flight radius and endurance, requiring personnel to be near the lines for operation, making continuous 24 / 7 monitoring impossible and resulting in high maintenance costs.

[0004] At the technical level, wireless sensor networks and the Internet of Things (IoT) have seen some application in power monitoring in recent years, such as monitoring systems based on Zigbee and LoRa technologies. However, these systems heavily rely on terrestrial base stations or public mobile communication networks for data transmission and cannot operate independently in areas without public network coverage. To address the communication problem, some research has attempted to use traditional geostationary orbit satellite communication, but its terminal equipment generally suffers from large size, high power consumption, high cost, low data transmission rate, and long latency, making large-scale deployment on power line towers difficult.

[0005] The development of low-Earth orbit satellite IoT technology has provided new possibilities for remote monitoring. These systems offer advantages such as global coverage, miniaturized terminals, low power consumption, and cost. However, directly applying satellite IoT technology to power line monitoring faces multiple challenges: First, power line monitoring requires access to multiple types of sensors, resulting in significant differences in data volume and sampling frequency; second, energy resources are limited in the field, necessitating sophisticated power management strategies; third, satellite communication windows are limited, requiring efficient data compression and transmission optimization mechanisms; and finally, a systematic solution is still lacking for integrating multi-source heterogeneous data to establish a suitable health status assessment model for power lines and achieve effective data-driven decision-making.

[0006] Therefore, there is an urgent need to develop a satellite Internet of Things (IoT)-based power line monitoring system and method for areas without public networks, which can fully utilize the advantages of satellite IoT technology, while solving the special needs of power monitoring scenarios, and realize all-weather, automated, low-cost intelligent monitoring of power line status in remote areas. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a power line monitoring system and method for areas without public network access based on satellite Internet of Things.

[0008] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0009] A satellite-based Internet of Things (IoT) system for monitoring power lines in areas without public grid access includes:

[0010] The monitoring terminal node is fixedly installed on power line towers or conductors, and includes a sensor module, a main control unit, a satellite IoT communication module, and a power management module.

[0011] The satellite Internet of Things constellation consists of several low-Earth orbit communication satellites, used to receive and forward data sent by the monitoring terminal nodes;

[0012] The ground data processing center includes a data receiving server, a data storage and processing platform, an intelligent analysis engine, and a user interface.

[0013] The sensor module is used to collect power line status parameters;

[0014] The main control unit is used to control the sensor's working cycle, preprocess the acquired data, execute local algorithms, and control the communication module.

[0015] The satellite IoT communication module integrates a low-orbit satellite IoT chip and an antenna, and is used to send the data processed by the main control unit to the satellite via a satellite link;

[0016] The power management module includes a solar panel, a battery, and a high-efficiency DC-DC conversion circuit, providing energy to the entire terminal and implementing dynamic power consumption management;

[0017] The data receiving server receives monitoring data relayed by satellite through a ground gateway station;

[0018] The data storage and processing platform parses, cleans, stores, and performs in-depth analysis on the data;

[0019] The intelligent analysis engine runs a line status assessment model to achieve fault warning, trend analysis, and health assessment.

[0020] The user interface, in the form of a web browser or mobile app, displays real-time line status, historical curves, alarm information, and analysis reports to maintenance personnel.

[0021] Furthermore, the power line status parameters collected by the sensor module include conductor temperature, current, sag, vibration frequency, insulator leakage current, images, and videos.

[0022] Furthermore, the main control unit adopts a low-power operating mode, spending most of its time in a deep sleep state, only waking up at a preset acquisition time point or when receiving an external trigger signal, and returning to a low-power state after performing data acquisition and processing tasks.

[0023] Furthermore, the satellite IoT communication module is activated during a predetermined communication window or when triggering conditions are met, searches for available satellites, establishes a connection, and sends out the encapsulated data packets.

[0024] Furthermore, the intelligent analysis engine employs a comprehensive mathematical model for evaluating power line health to assess the status of the power line, where the health assessment value of the i-th monitoring point at time t is... Calculated using the following formula:

[0025]

[0026] in, For electrical condition sub-indicators, For mechanical state sub-indices, , , For the comprehensive weighting coefficient, satisfying .

[0027] Furthermore, the electrical state sub-indicators Calculated using the following formula:

[0028]

[0029] in, , , They represent The conductor temperature, current, and insulator leakage current at any given time; , , It is a normalization function that maps the original data to the interval [0,1]. , , These are the weighting coefficients, and ;

[0030] The temperature normalization function Using Gaussian function form:

[0031]

[0032] in For reference temperature, is the coefficient of standard deviation.

[0033] Furthermore, the mechanical state sub-indicator Calculated using the following formula:

[0034]

[0035] in, , They represent The sag and amplitude of vibration at any given moment; , It is a normalization function that maps the original data to the interval [0,1]. , These are the weighting coefficients, and .

[0036] Furthermore, for a line segment consisting of N monitoring points, its overall health... Calculated using the following formula:

[0037]

[0038] in, The function represents taking the minimum value, reflecting the "barrel effect"; This represents the dispersion of the data at each point within the line segment. This is the dispersion influence coefficient.

[0039] This invention also discloses a method for monitoring power lines in areas without public grids based on satellite Internet of Things, applied to the aforementioned power line monitoring system in areas without public grids, comprising the following steps:

[0040] S1: Parameter configuration and initialization, configuring a unique ID, geographical location, sensor type, data acquisition cycle, and satellite communication window parameters for each monitoring terminal node;

[0041] S2: Low-power collaborative acquisition, the main control unit drives the sensor module to acquire data according to the preset strategy and performs local preprocessing on the data;

[0042] S3: Adaptive satellite communication. When the terminal node is in a predetermined communication window or when the triggering conditions are met, it wakes up the satellite IoT communication module, establishes a satellite connection, and sends data.

[0043] S4: Satellite-to-ground data transmission. The satellite receives data packets and transmits them to the ground gateway station via inter-satellite links or directly, eventually reaching the ground data processing center.

[0044] S5: In-depth data analysis and status assessment. The ground data processing center uses an intelligent analysis engine and a comprehensive mathematical model for line health assessment to analyze and calculate the data.

[0045] S6: Results visualization and early warning. The evaluation results, raw data and alarm information are displayed through the user interface. When the evaluation indicators exceed the safety threshold, alarm information is automatically generated and pushed.

[0046] Furthermore, in step S5, when the line health assessment value is lower than a preset threshold... When this happens, the system triggers an alert of the corresponding level, among which... The value range is 0.6-0.8.

[0047] Compared with the prior art, the advantages of the present invention are as follows:

[0048] 1. By leveraging the global coverage of low-orbit satellite IoT, the problem of power line monitoring in remote, uninhabited areas and areas with no public network signal has been completely solved, achieving comprehensive coverage of power grid monitoring and significantly improving the scope of power grid security protection.

[0049] 2. By adopting a dedicated satellite IoT chip and optimized design, the size of the monitoring terminal is greatly reduced and the cost is significantly lowered, making it suitable for large-scale deployment along power lines and solving the problem that traditional satellite communication terminals are difficult to apply on a large scale.

[0050] 3. Through innovative dynamic power consumption management strategies, intelligent wake-up mechanisms, and high-efficiency power conversion circuits, the monitoring terminal achieves ultra-low power consumption operation, relying solely on small solar cells and batteries to maintain long-term operation, thus solving the problem of limited energy supply in the field.

[0051] 4. The mathematical model for comprehensive assessment of line health proposed in this invention can effectively integrate multi-dimensional monitoring data such as electrical quantities, mechanical quantities, and environmental quantities, overcoming the one-sidedness of single-parameter assessment and improving the accuracy and comprehensiveness of condition assessment.

[0052] 5. By combining local preprocessing with in-depth cloud analysis, the entire process from anomaly detection to fault warning has been automated, which greatly improves the timeliness and accuracy of warnings, buys valuable time for operation and maintenance decisions, and effectively prevents major power accidents.

[0053] 6. An innovative data transmission mechanism combining event triggering and timed reporting was designed, which ensures timely transmission of critical data while minimizing satellite communication frequency, optimizing communication resource utilization efficiency, and extending terminal lifespan.

[0054] 7. The system has realized the transformation from "passive emergency repair" to "proactive prevention", reducing the frequency of manual inspections by more than 70%, reducing the operational risks for maintenance personnel in harsh environments, and avoiding large-scale power outages caused by line faults, which has significant economic and social benefits.

[0055] 8. The monitoring terminal adopts a modular design, which can flexibly configure the type and number of sensors according to the risk characteristics and monitoring needs of different line sections, so as to adapt to the power line monitoring needs of different voltage levels and different geographical environments.

[0056] 9. By combining long-term accumulated line status data with artificial intelligence analysis technology, the line health assessment model can be continuously optimized, providing data support for power grid planning, equipment selection, and operation and maintenance strategy formulation, and promoting the development of the power system towards digitalization and intelligence.

[0057] 10. The system design fully considers extreme environmental factors in the field, and has the characteristics of windproof, rainproof, lightning protection, and resistance to high and low temperatures. It can work stably under various harsh climatic conditions, ensuring the continuity and reliability of monitoring data. Attached Figure Description

[0058] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 This is a structural block diagram of the monitoring terminal node according to an embodiment of the present invention;

[0060] Figure 2 This is a general flowchart of the method of the present invention according to embodiments of the present invention;

[0061] Figure 3 This is a low-power workflow diagram of the monitoring terminal node according to an embodiment of the present invention. Detailed Implementation

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] A power line monitoring system for areas without public network access based on satellite Internet of Things (IoT) includes: monitoring terminal nodes, a satellite IoT constellation, and a ground data processing center;

[0064] like Figure 1 As shown, the monitoring terminal node is fixedly installed on power line poles or conductors, including:

[0065] Sensor module: Used to collect power line status parameters, including conductor temperature, current, sag, vibration frequency, insulator leakage current, and images / videos;

[0066] Main control unit: responsible for controlling the sensor's working cycle, preprocessing acquired data, executing local algorithms, and controlling the communication module;

[0067] Satellite IoT communication module: integrates low-orbit satellite IoT chip and antenna, responsible for sending the data processed by the main control unit to the satellite through the satellite link;

[0068] Power management module: Includes solar panels, batteries and high-efficiency DC-DC conversion circuits, providing power to the entire terminal and implementing dynamic power consumption management;

[0069] Satellite IoT constellation: Composed of several low-Earth orbit communication satellites, it receives data from monitoring terminal nodes and forwards it to ground gateway stations;

[0070] Ground data processing center: includes:

[0071] Data receiving server: Receives monitoring data relayed by satellite via ground gateway station;

[0072] Data storage and processing platform: performs data parsing, cleaning, storage, and in-depth analysis;

[0073] Intelligent analysis engine: Runs a line status assessment model to achieve fault early warning, trend analysis, and health assessment;

[0074] User interface: Displays real-time line status, historical curves, alarm information, and analysis reports to maintenance personnel.

[0075] The monitoring terminal node is the basic unit of the entire system, and its hardware design adopts a modular architecture. In terms of structural design, the outer shell of the monitoring terminal node is made of a combination of high-strength engineering plastics and aluminum alloy, with an IP67 protection rating, which can withstand the effects of harsh environments such as extreme temperatures, high humidity, and strong ultraviolet radiation.

[0076] The sensor module can be flexibly configured according to monitoring needs to collect power line status parameters, including conductor temperature, current, sag, vibration frequency, insulator leakage current, and image / video data. Temperature sensors use non-contact infrared thermometry or contact thermocouples; current sensors use Rogowski coils or Hall effect sensors; sag monitoring uses sensors based on tilt angle or tension measurement; vibration monitoring uses MEMS accelerometers; and miniature cameras can be configured at key nodes for visual monitoring.

[0077] The main control unit (MCU) uses a low-power ARM Cortex-M series microcontroller with a built-in real-time clock and multiple communication interfaces. It is responsible for controlling the sensor's working cycle, preprocessing acquired data, executing local algorithms, and controlling the communication module. The MCU firmware implements a deep sleep mode, waking up only when data acquisition or communication is needed, significantly reducing system power consumption.

[0078] The satellite IoT communication module adopts an integrated design, incorporating a built-in RF chip, power amplifier, and matching circuitry to support low-Earth orbit satellite IoT. It also integrates a dedicated antenna responsible for transmitting data processed by the main control unit to the satellite via the satellite link. The communication module employs adaptive power control technology, dynamically adjusting the transmission power based on satellite signal strength to conserve energy while ensuring communication quality.

[0079] The power management module consists of solar panels, batteries, and a high-efficiency DC-DC conversion circuit. It provides energy to the entire monitoring terminal node and implements dynamic power consumption management. Maximum power point tracking (MPPT) technology is used to improve solar energy conversion efficiency, intelligent charging and discharging strategies protect battery life, and a multi-stage voltage conversion architecture ensures accurate and stable power supply to each module.

[0080] In terms of software implementation, such as Figure 2 As shown, the monitoring terminal node executes a satellite-based Internet of Things (IoT) method for monitoring power lines in areas without public grid access. This includes:

[0081] During the S1 parameter configuration and initialization phase, each monitoring terminal node is configured with parameters such as a unique ID, geographical location, sensor type, data acquisition cycle, and satellite communication window. These parameters can be updated via satellite downlink commands.

[0082] S2 low-power collaborative acquisition phase, such as Figure 3 As shown, the main control unit is in a deep sleep state most of the time. After being woken up at a set time, the main control unit drives the sensor module to collect data according to a preset strategy and performs local preprocessing on the data, including outlier filtering, data compression, and feature extraction, which greatly reduces the amount of data that needs to be transmitted.

[0083] During the S3 adaptive satellite communication phase, the terminal node wakes up the satellite IoT communication module when a predetermined communication window is opened or a trigger condition is met (such as data exceeding a threshold), searches for available satellites, establishes a connection, and sends out the encapsulated data packet. After communication is completed, the RF circuit is immediately shut down, returning to a low-power state.

[0084] The satellite IoT constellation consists of several low-Earth orbit communication satellites responsible for performing S4 satellite-to-ground data transmission tasks. After receiving data packets from monitoring terminal nodes, the satellites transmit them to ground gateway stations via inter-satellite links or directly, and finally deliver them to the ground data processing center.

[0085] The ground data processing center includes a data receiving server, which receives monitoring data relayed by satellites through ground gateway stations and performs data packet parsing, authentication, and integrity checks.

[0086] The data storage and processing platform adopts a distributed architecture to clean and normalize data, and stores it in time-series databases and relational databases, supporting efficient querying and big data analysis.

[0087] The intelligent analysis engine performs deep data analysis and status assessment using S5, realizing the comprehensive line health assessment mathematical model proposed in this invention: For the first... Each monitoring point at time The health assessment value is calculated using the formula.

[0088]

[0089] Perform calculations, where For electrical condition sub-indicators, For mechanical state sub-indices, , , For the comprehensive weighting coefficient, satisfying Electrical status sub-indicators Through formula

[0090]

[0091] Calculation, where , , They represent The conductor temperature, current, and insulator leakage current at any given time. , , It is a normalization function that maps the original data to the interval [0,1] (1 represents the optimal state). For example, the temperature normalization function can be...

[0092]

[0093] in For reference temperature; , , These are the weighting coefficients, and Mechanical condition sub-indices Through formula

[0094]

[0095] Calculation, where , They represent Sag and amplitude of vibration at any given moment , It is a normalization function that maps to the interval [0,1]. , These are the weighting coefficients, and . This reflects the coupling effect between electrical and mechanical conditions; for example, high temperatures may cause increased sag, thus exacerbating health deterioration. For a line segment consisting of N monitoring points, its overall health... Through formula

[0096]

[0097] Calculation, where The function embodies the "barrel effect". This represents the dispersion (e.g., variance) of the data at each point within the line segment. This is the dispersion influence coefficient. and The closer the value is to 1, the better the condition. When the value is below a preset threshold... When the value is set to 0.7, the system triggers an alert of the corresponding level.

[0098] The user interface is responsible for visualizing and alerting S6 results. Presented to operations and maintenance personnel via web or mobile app, it displays real-time line status, historical curves, alarm information, and analysis reports. The interface uses map visualization technology to intuitively display the location and status of each monitoring point, supporting multi-level zooming and data drill-down functions. For different levels of alerts, the system employs a multi-channel notification mechanism, including app push notifications, SMS alerts, and email notifications, ensuring timely response from operations and maintenance personnel.

[0099] During system deployment and implementation, a site survey is first conducted to determine the locations of key monitoring points. Monitoring terminal nodes are then fixedly installed on power line poles or conductors using a non-destructive installation process to avoid damaging the pole structure. After installation, the terminals are remotely configured and calibrated via satellite network. Once the system is operational, a regular maintenance mechanism is established to remotely monitor the terminal's status. When a potential fault is predicted, on-site maintenance is scheduled in advance. For software upgrades, Over-the-Air (OTA) technology is used, enabling remote updates via satellite link without the need for on-site personnel. Through these specific implementation methods, this invention enables 24 / 7 automated monitoring of power lines in remote areas without public network coverage, significantly improving power grid operational safety and maintenance efficiency.

[0100] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A satellite-based Internet of Things (IoT) system for monitoring power lines in areas without public grid access, characterized in that: include: The monitoring terminal node is fixedly installed on power line towers or conductors, and includes a sensor module, a main control unit, a satellite IoT communication module, and a power management module. The satellite Internet of Things constellation consists of several low-Earth orbit communication satellites, used to receive and forward data sent by the monitoring terminal nodes; The ground data processing center includes a data receiving server, a data storage and processing platform, an intelligent analysis engine, and a user interface. The sensor module is used to collect power line status parameters; The main control unit is used to control the sensor's working cycle, preprocess the acquired data, execute local algorithms, and control the communication module. The satellite IoT communication module integrates a low-orbit satellite IoT chip and an antenna, and is used to send the data processed by the main control unit to the satellite via a satellite link; The power management module includes a solar panel, a battery, and a high-efficiency DC-DC conversion circuit, providing energy to the entire terminal and implementing dynamic power consumption management; The data receiving server receives monitoring data relayed by satellite through a ground gateway station; The data storage and processing platform parses, cleans, stores, and performs in-depth analysis on the data; The intelligent analysis engine runs a line status assessment model to achieve fault warning, trend analysis, and health assessment. The user interface, in the form of a web browser or mobile app, displays real-time line status, historical curves, alarm information, and analysis reports to maintenance personnel.

2. The system according to claim 1, characterized in that, The sensor module collects power line status parameters including conductor temperature, current, sag, vibration frequency, insulator leakage current, images, and videos.

3. The system according to claim 1 or 2, characterized in that, The main control unit adopts a low-power operating mode, and is in a deep sleep state most of the time. It is only woken up at the preset acquisition time point or when an external trigger signal is received. After performing data acquisition and processing tasks, it returns to the low-power state.

4. The system according to claim 1, characterized in that, The satellite IoT communication module is activated when a predetermined communication window or when a trigger condition is met, searches for available satellites, establishes a connection, and sends out the encapsulated data packets.

5. The system according to claim 1, characterized in that, The intelligent analysis engine uses a comprehensive mathematical model for line health assessment to evaluate the status of power lines. The health assessment value H_i(t) of the i-th monitoring point at time t is calculated using the following formula: ； in, For electrical condition sub-indicators, For mechanical state sub-indices, , , For the comprehensive weighting coefficient, satisfying .

6. The system according to claim 5, characterized in that, The electrical status sub-indicator Calculated using the following formula: ； in, , , They represent The conductor temperature, current, and insulator leakage current at any given time; , , It is a normalization function that maps the original data to the interval [0,1]. , , These are the weighting coefficients, and ; The temperature normalization function Using Gaussian function form: ； in For reference temperature, is the coefficient of standard deviation.

7. The system according to claim 5 or 6, characterized in that, The mechanical condition sub-index Calculated using the following formula: ； in, , They represent The sag and amplitude of vibration at any given moment; , It is a normalization function that maps the original data to the interval [0,1]. , These are the weighting coefficients, and .

8. The system according to claim 5, characterized in that, For a line segment consisting of N monitoring points, its overall health status Calculated using the following formula: ； in, The function represents taking the minimum value, reflecting the "barrel effect"; This represents the dispersion of the data at each point within the line segment. This is the dispersion influence coefficient.

9. A method for monitoring power lines in areas without public grid access based on satellite Internet of Things, applied to the system described in any one of claims 1-8, characterized in that, Includes the following steps: S1: Parameter configuration and initialization, configuring a unique ID, geographical location, sensor type, data acquisition cycle, and satellite communication window parameters for each monitoring terminal node; S2: Low-power collaborative acquisition, the main control unit drives the sensor module to acquire data according to the preset strategy and performs local preprocessing on the data; S3: Adaptive satellite communication. When the terminal node is in a predetermined communication window or when the triggering conditions are met, it wakes up the satellite IoT communication module, establishes a satellite connection, and sends data. S4: Satellite-to-ground data transmission. The satellite receives data packets and transmits them to the ground gateway station via inter-satellite links or directly, eventually reaching the ground data processing center. S5: In-depth data analysis and status assessment. The ground data processing center uses an intelligent analysis engine and a comprehensive mathematical model for line health assessment to analyze and calculate the data. S6: Results visualization and early warning. The evaluation results, raw data and alarm information are displayed through the user interface. When the evaluation indicators exceed the safety threshold, alarm information is automatically generated and pushed.

10. The method according to claim 9, characterized in that, In step S5, when the line health assessment value is lower than a preset threshold... When this happens, the system triggers an alert of the corresponding level, among which... The value range is 0.6-0.8.

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