Distributed intelligent substation network monitoring system and network time synchronization method

Abstract

The invention discloses a distributed intelligent substation network monitoring system and a network time synchronization method. The monitoring system comprises sensors arranged in a plurality of substations, a data acquisition and processing module, a field monitoring terminal, an execution control mechanism, an industrial personal computer, a display screen, a network communication module, a remote management center and a time synchronization module. The method comprises the following steps: S1, constructing a multi-layer time synchronization network by introducing a plurality of time sources; the PTP time synchronization device is used for time synchronization, network time synchronization is completed by using a timestamp, and high-precision time synchronization is provided; and S2, when the PTP time synchronization device has a fault or the network is unstable. According to the invention, the environmental parameters of the transformer substation and the working parameters of the transformer can be monitored in real time, an accurate data basis is provided for intelligent control of the transformer substation, flexible selection can be realized according to actual conditions, accurate synchronization of system equipment is ensured, and the reliability and stability of system operation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and in particular to a distributed intelligent substation network monitoring system and a network time synchronization method. Background Art

[0002] As a key component of the new generation of power systems, smart substations have greatly improved the efficiency and quality of power production and distribution with their advanced automation control systems. In order to ensure the synchronous operation of all devices, smart substations require precise time synchronization.

[0003] Existing network time synchronization methods, such as GPS time synchronization, NTP time synchronization and PTP time synchronization, have their own advantages, but also have certain limitations. For example, GPS time synchronization requires the device to be able to receive GPS signals, and its application scope is narrow; NTP time synchronization may be affected by network delays, reducing accuracy; although PTP time synchronization has high accuracy, it has high requirements for the configuration of network devices. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned technical problems and to propose a distributed intelligent substation network monitoring system and a network timing method to solve the timing problems existing in the synchronous operation of intelligent substation equipment in the prior art and improve the reliability and stability of the system operation.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A distributed intelligent substation network monitoring system, including sensors, data acquisition and processing modules, field monitoring terminals, execution control mechanisms, industrial computers, display screens, network communication modules, remote management centers, and time synchronization modules arranged in multiple substations;

[0007] The sensor is connected to the data acquisition and processing module, and multiple data acquisition and processing modules are connected to the industrial computer through Profibus-DP and Modbus field buses respectively. The industrial computer is connected to the remote management center through a network communication module. The time synchronization module is used to provide multiple time synchronization methods to ensure accurate synchronization of system equipment.

[0008] Preferably, the sensor includes an environmental parameter acquisition sensor and a transformer operating parameter acquisition sensor, and the environmental parameter acquisition sensor includes a temperature sensor and a humidity sensor.

[0009] Preferably, the network communication module includes a wireless communication interface or a fiber optic communication interface.

[0010] Preferably, the time synchronization module includes a GPS time synchronization device, an NTP server and a PTP time synchronization device.

[0011] Preferably, the data acquisition and processing module uses artificial intelligence algorithms to analyze the collected data, identify potential faults and predict equipment maintenance needs, and generate real-time monitoring reports.

[0012] The present invention also discloses a network time synchronization method, comprising the following steps:

[0013] S1, by introducing multiple time sources, build a multi-level time synchronization network; use PTP time synchronization device for time synchronization, use timestamps to complete network time synchronization, and provide high-precision time synchronization;

[0014] S2, when the PTP time synchronization device fails or the network is unstable, it automatically switches to the NTP server for time synchronization, connects to the NTP server through the Internet, provides high-precision time synchronization, and considers the impact of network delay to optimize the network;

[0015] S3: When the GPS signal is available and both the NTP server and the PTP time synchronization device fail, the GPS time synchronization device is used to synchronize the time, using satellite signals to provide high-precision time synchronization.

[0016] Preferably, a backup timing mechanism is also included. When the master clock is working normally, the boundary clock acts as a slave clock to receive the timing command of the master clock; when the master clock is abnormal, the boundary clock will rise to the master clock and synchronize the time for the timing device to ensure the normal operation of the system equipment.

[0017] Preferably, the boundary clock is a central switch.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. The present invention provides a distributed intelligent substation network monitoring system, which can monitor the environmental parameters and transformer operating parameters of the substation in real time, and provide an accurate data basis for the intelligent control of the substation.

[0020] 2. The network time synchronization method of the present invention combines multiple time synchronization methods such as PTP, NTP and GPS, and can be flexibly selected according to actual conditions to ensure accurate synchronization of system equipment and improve the reliability and stability of system operation.

[0021] 3. The backup timing mechanism of the present invention further improves the reliability of the system. Even if the main clock fails, it can ensure the normal operation of the system equipment and avoid equipment failure or system paralysis caused by timing problems.

[0022] In summary, the present invention can monitor the environmental parameters and transformer operating parameters of the substation in real time, provide an accurate data basis for the intelligent control of the substation, and can flexibly select according to actual conditions to ensure the precise synchronization of system equipment and improve the reliability and stability of system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A module diagram of a distributed intelligent substation network monitoring system proposed by the present invention;

[0024] Figure 2 This is a module diagram of an environmental parameter acquisition sensor in a distributed intelligent substation network monitoring system proposed by the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0026] Reference Figure 1-2 A distributed intelligent substation network monitoring system includes sensors arranged in a plurality of substations, wherein the sensors include environmental parameter acquisition sensors and transformer working parameter acquisition sensors, wherein the environmental parameter acquisition sensors include temperature sensors and humidity sensors, so as to detect the environment in the substation; in addition to basic current, voltage, power factor and other parameters, the transformer working parameter acquisition sensors can also integrate vibration sensors and partial discharge detection sensors to monitor the mechanical stability and insulation status of the transformer, and to give early warning of potential insulation failures or overheating problems;

[0027] Data acquisition and processing module: The module uses artificial intelligence algorithms to analyze the collected data, identify potential faults, predict equipment maintenance needs, and generate real-time monitoring reports. It introduces deep learning algorithms and machine learning models to conduct in-depth mining of massive data to achieve more accurate fault prediction and fault type identification. For example, by training models with historical data, the changing trend of dissolved gas in transformer oil can be predicted to determine the degree of equipment aging or potential fault points.

[0028] More specific explanation: As the core component of modern industrial monitoring and maintenance systems, the data acquisition and processing module plays a vital role. This module integrates advanced artificial intelligence technology and can efficiently process and analyze the massive data collected in real time from various sensors, instruments and monitoring equipment. Its core function is not limited to the simple collection and storage of data, but also to use complex artificial intelligence algorithms such as neural networks, support vector machines, random forests, etc. to deeply analyze the data to identify potential equipment failure modes and accurately predict future maintenance needs.

[0029] To achieve this goal, the data acquisition and processing module is embedded with advanced deep learning algorithms and fine-tuned machine learning models. Deep learning technology, with its powerful feature learning and pattern recognition capabilities, can dig out deep correlations and regularities from massive historical data, which are often difficult to capture with traditional methods. By building a multi-level neural network structure, the module can automatically learn the complex features in the data and continuously optimize the model parameters, thereby achieving high-precision prediction of the trend of equipment status changes. For example, in the power system, by performing deep learning training on the historical monitoring data of dissolved gases (such as hydrogen, methane, ethane, etc.) in transformer oil, the module can accurately predict the future trend of these gases, and then evaluate the degree of insulation aging of the transformer, discover potential overheating, discharge or local fault points in advance, and provide a scientific basis for timely maintenance measures.

[0030] At the same time, the application of machine learning models further enhances the intelligence and adaptability of the system. Through continuous iterative training, the model can optimize itself, improve the ability to identify new types of faults, reduce false positives and false negatives, and ensure accurate and efficient maintenance work. In addition, combined with big data processing technology, the module can process and analyze high-frequency data from multiple sources in real time, generate detailed real-time monitoring reports, and provide decision makers with an intuitive and comprehensive overview of the health status of the equipment, facilitating rapid response and formulation of effective maintenance strategies.

[0031] Edge computing capability: Integrate edge computing technology in the data acquisition and processing module to reduce data transmission delays and improve system response speed. Edge nodes can initially process data and only upload key information to the cloud or remote management center to reduce network burden;

[0032] More specific explanation: Edge computing capability, as a key technology in the field of modern data processing, has brought changes to the data acquisition and processing module. In this innovative framework, edge computing technology is seamlessly integrated into the data acquisition and processing module, aiming to fundamentally reduce the delay of data transmission, significantly improve the overall response speed of the system, and ensure the real-time and effectiveness of data processing.

[0033] Specifically, edge computing achieves preliminary data processing and analysis by deploying intelligent computing nodes (edge ​​nodes) at the edge of the network, that is, close to the data source or user end. These edge nodes have powerful data processing capabilities and can pre-process, filter and compress the collected data in real time, so that only the refined key information, abnormal data or emergency alarms are uploaded to the cloud or remote management center. This strategy not only greatly reduces the burden of network transmission and reduces data traffic costs, but also ensures the rapid delivery of key data, which wins valuable time for subsequent decision-making and fault response.

[0034] In addition, the introduction of edge computing technology also enhances the security and privacy protection of the system. Since sensitive data is initially processed at the edge node, only desensitized or encrypted key information is transmitted, which greatly reduces the risk of data being intercepted or abused during transmission. At the same time, the distributed deployment of edge nodes also improves the robustness and fault tolerance of the system. Even if some nodes fail, it will not affect the normal operation of the entire system and the continuity of data processing.

[0035] In the data acquisition and processing module, the integration of edge computing technology also promotes the optimization of resource allocation and energy efficiency. By intelligently allocating computing tasks, edge nodes can efficiently handle most routine data processing needs and call cloud resources only when necessary, thereby reducing overall energy consumption and operating costs.

[0036] In summary, the integration of edge computing technology in the data acquisition and processing module not only significantly improves the system's real-time response capability and data processing efficiency, but also enhances the system's security, robustness and energy efficiency. This technological innovation has brought new development opportunities to many fields such as industrial Internet of Things, smart cities, and telemedicine, and promoted the process of digital transformation and intelligent upgrading.

[0037] The execution control mechanism is connected with the data acquisition and processing module, the on-site monitoring terminal and the inter-synchronization system;

[0038] On-site monitoring terminal: The on-site monitoring terminal is a camera installed in the substation. The on-site monitoring terminal uses a high-definition smart camera with functions such as face recognition and license plate recognition. It is not only used for daily monitoring, but also can assist in security management, such as personnel entry and exit management, intrusion detection, etc. Infrared thermal imaging cameras are added for environmental monitoring at night or in bad weather to promptly detect equipment overheating or abnormal heating;

[0039] On-site monitoring terminals, as a key link in the intelligent management and safety protection system of substations, play a vital role. These monitoring devices carefully deployed inside the substations use advanced high-definition intelligent camera technology, which not only greatly improves the clarity and detail capture capabilities of the monitoring images, but also integrates multiple intelligent functions to meet the complex and ever-changing on-site monitoring needs.

[0040] With its excellent image processing capabilities, the high-definition smart camera can capture and transmit high-definition video images in real time, providing operation and maintenance personnel with a full field view. On this basis, the camera also integrates two advanced functions: face recognition and license plate recognition. Face recognition technology uses advanced algorithms to accurately identify and compare facial features, effectively realizing the identity verification and permission management of personnel entering and leaving the substation, which not only improves the level of security management, but also simplifies the personnel entry and exit process. The license plate recognition function can automatically identify and record the license plate numbers of vehicles entering and leaving, providing strong support for vehicle management, visitor tracking and rapid response in emergency situations.

[0041] In addition, in order to meet the monitoring needs at night or in bad weather conditions, infrared thermal imaging cameras are also added to the on-site monitoring terminals. This special type of camera can use the principle of infrared radiation to penetrate darkness and haze and capture the temperature distribution information on the surface of objects. By monitoring the temperature changes on the surface of the equipment in real time, the infrared thermal imaging camera can promptly detect potential safety hazards such as overheating or abnormal heating of the equipment, providing valuable early warning information for operation and maintenance personnel, helping to prevent safety accidents such as fire and short circuit.

[0042] In summary, the on-site monitoring terminal, with its advanced technologies such as high-definition smart cameras, face recognition, license plate recognition and infrared thermal imaging, not only meets the basic needs of daily monitoring of substations, but also plays an important role in security management, personnel entry and exit management, intrusion detection and environmental monitoring, etc., providing a solid technical guarantee for the safe and efficient operation of substations.

[0043] Execution control mechanism: The execution control mechanism is the central processor, which adopts a distributed control strategy. Each substation or key equipment area is equipped with an independent execution control unit, which works in conjunction with the central processor to achieve more flexible and rapid control response;

[0044] The executive control mechanism, as the nerve center of the power monitoring and management system, is composed of a high-performance central processing unit (CPU). This design not only ensures that the system has powerful data processing and decision-making capabilities, but also further improves the flexibility and response speed of the system by adopting advanced distributed control strategies.

[0045] Under the distributed control framework, each substation or key equipment area is equipped with an independent execution control unit (ECU). These ECUs, as field-level intelligent controllers, directly connect and monitor various types of power equipment and sensors in the area, and can collect equipment operation data, environmental parameters and fault alarm information in real time, and respond quickly and perform corresponding control operations according to preset logical rules or instructions from the central processor.

[0046] The central processor and each ECU realize information exchange and collaborative work through a high-speed and reliable communication network. The advantage of this distributed architecture is that it can disperse the control logic and decision-making to each ECU, reducing the burden on the central processor and improving the parallel processing capability of the system. At the same time, since the ECU is directly deployed on-site, it can sense and respond to changes in equipment status more quickly, thereby significantly shortening the execution time of control instructions and improving the overall response speed of the system.

[0047] In addition, the distributed control strategy also enhances the reliability and fault tolerance of the system. Even if a certain ECU fails, it will not affect the normal operation of other ECUs or the central processor, ensuring the continuous and stable operation of the system. At the same time, through the centralized monitoring and management of ECUs by the central processor, the global optimization and resource allocation of the entire power monitoring and management system can be achieved, further improving the overall efficiency of the system.

[0048] In summary, the executive control agency adopts a distributed control strategy, equips each substation or key equipment area with an independent executive control unit, and works in conjunction with the central processor to achieve more flexible and rapid control response, providing a solid foundation for the intelligent and automated operation of the power monitoring and management system.

[0049] The industrial computer is the control device of the entire system;

[0050] Display screen, the display screen can be touch-controlled, and the operation of the equipment can be controlled, etc.;

[0051] A network communication module, the network communication module comprising a wireless communication interface or an optical fiber communication interface for connecting to an external communication device or a connection line;

[0052] Remote management center: The remote management center is connected to external computers through a network communication module, and can remotely control the industrial computer;

[0053] A time synchronization module, wherein the time synchronization module includes a GPS time synchronization device, an NTP server and a PTP time synchronization device;

[0054] The sensor is connected to the data acquisition and processing module, and multiple data acquisition and processing modules are connected to the industrial computer through Profibus-DP and Modbus field buses respectively. The industrial computer is connected to the remote management center through a network communication module. The time synchronization module is used to provide multiple time synchronization methods to ensure accurate synchronization of system equipment.

[0055] The present invention also discloses a network time synchronization method, comprising the following steps:

[0056] S1, by introducing multiple time sources, build a multi-level time synchronization network; use PTP time synchronization device for time synchronization, use timestamps to complete network time synchronization, and provide high-precision time synchronization;

[0057] S2, when the PTP time synchronization device fails or the network is unstable, it automatically switches to the NTP server for time synchronization, connects to the NTP server through the Internet, provides high-precision time synchronization, and considers the impact of network delay to optimize the network;

[0058] S3: When the GPS signal is available and both the NTP server and the PTP time synchronization device fail, the GPS time synchronization device is used to synchronize the time, using satellite signals to provide high-precision time synchronization.

[0059] The present invention also includes a backup time synchronization mechanism. When the master clock works normally, the boundary clock acts as a slave clock to receive the time synchronization command of the master clock; when the master clock is abnormal, the boundary clock will rise to the master clock and synchronize the time for the time-granted device to ensure the normal operation of the system equipment; wherein, the boundary clock is a central switch.

[0060] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A distributed intelligent substation network monitoring system, characterized in that: It includes sensors, data acquisition and processing modules, field monitoring terminals, execution control mechanisms, industrial computers, display screens, network communication modules, remote management centers, and time synchronization modules installed in multiple substations; The sensor is connected to the data acquisition and processing module, and multiple data acquisition and processing modules are connected to the industrial computer through Profibus-DP and Modbus field buses respectively. The industrial computer is connected to the remote management center through a network communication module. The time synchronization module is used to provide multiple time synchronization methods to ensure accurate synchronization of system equipment.

2. A distributed intelligent substation network monitoring system according to claim 1, characterized in that: The sensors include an environmental parameter acquisition sensor and a transformer operating parameter acquisition sensor, and the environmental parameter acquisition sensor includes a temperature sensor and a humidity sensor.

3. A distributed intelligent substation network monitoring system according to claim 1, characterized in that: The network communication module includes a wireless communication interface or an optical fiber communication interface.

4. A distributed intelligent substation network monitoring system according to claim 1, characterized in that: The time synchronization module includes a GPS time synchronization device, an NTP server and a PTP time synchronization device.

5. A distributed intelligent substation network monitoring system according to claim 1, characterized in that: The data acquisition and processing module uses artificial intelligence algorithms to analyze the collected data, identify potential faults and predict equipment maintenance needs, and generate real-time monitoring reports.

6. A network time synchronization method, characterized in that: The distributed intelligent substation network monitoring system applied to claims 1-5 comprises the following steps: S1, by introducing multiple time sources, build a multi-level time synchronization network; use PTP time synchronization device for time synchronization, use timestamps to complete network time synchronization, and provide high-precision time synchronization; S2, when the PTP time synchronization device fails or the network is unstable, it automatically switches to the NTP server for time synchronization, connects to the NTP server through the Internet, provides high-precision time synchronization, and considers the impact of network delay to optimize the network; S3: When the GPS signal is available and both the NTP server and the PTP time synchronization device fail, the GPS time synchronization device is used to synchronize the time, using satellite signals to provide high-precision time synchronization.

7. A network time synchronization method according to claim 6, characterized in that: It also includes a backup timing mechanism. When the master clock is working normally, the boundary clock acts as a slave clock to receive the timing commands from the master clock. When the master clock is abnormal, the boundary clock will rise to the master clock and synchronize the timing for the timing device to ensure the normal operation of the system equipment.

8. A network time synchronization method according to claim 7, characterized in that: The boundary clock is a central switch.

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