Location monitoring system and method for partial discharge of distribution transformer

Abstract

The invention discloses a distribution transformer partial discharge positioning monitoring system and method, a low voltage side and a high voltage side of a distribution transformer are respectively connected with a voltage sensor, the low voltage side of the distribution transformer is connected with a current sensor, the voltage sensor and the current sensor are connected with an edge calculation module, and the edge calculation module is connected with an intelligent fusion terminal. The edge calculation module is used for collecting and processing signals and uploading the signals to the intelligent fusion terminal, the insulation state of the distribution transformer can be continuously monitored in real time, the partial discharge phenomenon can be more accurately positioned and monitored, and therefore potential safety hazards are prevented from developing into serious faults. The risk of equipment faults can be reduced, stable operation of a power system is guaranteed, and large-area power failure or more serious safety accidents caused by the equipment faults are prevented.

Description

Technical Field

[0001] The invention belongs to the technical field of distribution transformers, and in particular relates to a distribution transformer partial discharge positioning monitoring system and method. Background Art

[0002] The partial discharge signal is very weak when it is generated inside the transformer, and is subject to electromagnetic interference from the transformer itself and other equipment, which makes it difficult to accurately capture and identify the real partial discharge signal during online monitoring. The complexity of the transformer winding structure further exacerbates the attenuation and distortion of the signal, reduces the signal-to-noise ratio of the monitoring signal, and increases the difficulty of analysis.

[0003] Currently, commonly used partial discharge monitoring methods such as pulse current method and ultrasonic sensor method face many challenges in online monitoring. For example, although the pulse current method has high sensitivity for offline measurement, it is easily affected by electromagnetic interference at the operating equipment site and cannot perform live detection. The ultrasonic sensor method needs to solve the attenuation and reflection problems of the signal during propagation inside the transformer, as well as distinguish the impact of different types of acoustic wave signals such as mechanical vibration and noise on the monitoring results.

[0004] Designing and installing a suitable hardware signal acquisition system including sensors, front-end systems, etc. is the key to ensuring the effectiveness of online monitoring. However, due to the complexity of the transformer structure and the particularity of the operating environment, it becomes particularly difficult to select suitable monitoring points and installation locations. The performance of hardware equipment such as sensitivity and anti-interference ability also directly affects the accuracy and reliability of the monitoring results. The partial discharge online monitoring system needs to collect, process and analyze a large amount of status data. However, due to the large amount of data and strong noise interference, data processing and analysis are difficult. The online monitoring system requires long-term operation and maintenance to ensure its stability and reliability. However, due to the limitations of factors such as system complexity and the skill level of operation and maintenance personnel, operation and maintenance management is difficult. Therefore, there is an urgent need for a distribution transformer partial discharge positioning monitoring system and method to solve the problem that partial discharge of distribution transformers cannot be monitored online. Summary of the invention

[0005] The purpose of the present invention is to overcome the problem that partial discharge of a distribution transformer cannot be monitored online, and a partial discharge positioning monitoring system and method for a distribution transformer are proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme:

[0007] A partial discharge positioning monitoring system for a distribution transformer, wherein the low-voltage side and the high-voltage side of the distribution transformer are respectively connected with voltage sensors, the low-voltage side of the distribution transformer is connected with a current sensor, the voltage sensor and the current sensor are connected to an edge computing module, and the edge computing module is connected to an intelligent fusion terminal.

[0008] Furthermore, the high-voltage side of the distribution transformer is connected to the high-voltage side capacitor divider, the low-voltage side of the distribution transformer is connected to the low-voltage side capacitor divider, and the high-voltage side capacitor divider and the low-voltage side capacitor divider are connected to the edge computing module.

[0009] Furthermore, the low-voltage side of the distribution transformer is connected to a current transformer, and the current transformer is connected to the edge computing module.

[0010] Furthermore, the intelligent converged terminal is connected to the IoT management platform.

[0011] Furthermore, the edge computing module includes an AD converter, an FPGA and an ARM processor.

[0012] A method for positioning and monitoring partial discharge of a distribution transformer comprises the following steps: a voltage sensor is used to collect voltage signals on the low-voltage side and the high-voltage side of the distribution transformer, a current sensor is used to collect current signals on the low-voltage side of the distribution transformer, an edge computing module obtains voltage signals and current signals for processing and uploads the processing results to an intelligent fusion terminal.

[0013] Furthermore, a high-voltage side capacitor divider is configured on the high-voltage side of the distribution transformer to collect the high-voltage side voltage signal, and a low-voltage side capacitor divider is configured on the low-voltage side of the distribution transformer to collect the low-voltage side voltage signal of the distribution transformer. The edge computing module obtains the high-voltage side voltage signal and the low-voltage side voltage signal through the high-voltage side capacitor divider and the low-voltage side capacitor divider, processes them and uploads the processing results to the intelligent fusion terminal. A current transformer is configured on the low-voltage side of the distribution transformer to collect the low-voltage side current signal of the distribution transformer. The edge computing module obtains the low-voltage side current signal through the current transformer, processes it and uploads the processing results to the intelligent fusion terminal.

[0014] Furthermore, the intelligent fusion terminal uploads the processing results to the IoT management platform.

[0015] Furthermore, the AD converter in the edge computing module quantizes the signals of the high-voltage side capacitor divider and the low-voltage side capacitor divider to obtain a quantized sensor signal, the FPGA in the edge computing module collects, stores and filters the quantized sensor signal to obtain a processed sensor signal, and the ARM in the edge computing module extracts features from the processed sensor signal and performs communication protocols to the outside.

[0016] Furthermore, the edge computing module obtains the voltage signal and the current signal for processing and uploads the processing results to the intelligent fusion terminal to locate the fault. Specifically, when a fault occurs inside the distribution transformer, the polarity of the high-voltage side capacitor divider is opposite to that of the low-voltage side capacitor divider; when a fault occurs outside the distribution transformer, the polarity of the high-voltage side capacitor divider is the same as that of the low-voltage side capacitor divider.

[0017] Compared with the prior art, the present invention has the following beneficial technical effects:

[0018] The present invention proposes a distribution transformer partial discharge positioning monitoring system, which configures a high-voltage side capacitor voltage divider on the high-voltage side of the distribution transformer to monitor the high-voltage side voltage, and configures a low-voltage side capacitor voltage divider on the low-voltage side of the distribution transformer to monitor the voltage on the low-voltage side of the distribution transformer. The edge computing module collects and processes the signal and uploads it to the intelligent fusion terminal, which can monitor the insulation state of the distribution transformer in real time and continuously, and can more accurately locate and monitor partial discharge phenomena, thereby avoiding potential safety hazards from developing into serious faults. It can reduce the risk of equipment failure, ensure the stable operation of the power system, and prevent large-scale power outages or more serious safety accidents caused by equipment failure.

[0019] The present invention proposes a distribution transformer partial discharge positioning monitoring system, which converts the signals of the sensors connected to the high-voltage side and the low-voltage side of the distribution transformer through the architecture of ADC+FPGA+ARM and uploads them to the intelligent fusion terminal, so that the system has the function of partial discharge positioning, and can accurately point out the specific location where the discharge occurs, which helps maintenance personnel to quickly locate and handle faults, reduce the time and difficulty of troubleshooting, and understand the loss status and life prediction of the equipment through regular monitoring and analysis of partial discharge data, so as to formulate preventive maintenance plans in a targeted manner. It helps to discover and deal with problems such as aging and damage of equipment in advance, and avoid high maintenance costs and power outage losses caused by sudden equipment failures. Accurate positioning and early warning functions enable maintenance personnel to use time and resources more efficiently, reduce unnecessary inspections and maintenance work, and improve operation and maintenance efficiency.

[0020] The present invention proposes a distribution transformer partial discharge positioning monitoring system, which can provide rich data analysis and reporting functions through the Internet of Things management platform, including key information such as the type, intensity, and development trend of partial discharge, which helps users understand the operating status of the equipment, evaluate the health status and remaining life of the equipment, and provide strong support for management decisions. Through in-depth analysis and mining of partial discharge data, refined management of the equipment can be achieved. Users can formulate more scientific and reasonable operation and maintenance strategies and plans based on the actual conditions and needs of the equipment. By timely discovering and handling partial discharge problems, energy waste and increased emissions caused by equipment failures can be avoided. The partial discharge monitoring system also helps to monitor pollution problems of power equipment. By monitoring pollutants such as gases and particles generated by partial discharge, pollution problems of equipment can be discovered and handled in a timely manner to reduce the impact on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings in the specification are used to provide further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0022] Figure 1 The present invention is a structural diagram of a distribution transformer partial discharge positioning monitoring system.

[0023] Among them, 1 is a distribution transformer, 21 is a high-voltage side capacitor divider, 22 is a low-voltage side content divider, 3 is a current transformer, 4 is an edge computing module, and 5 is an intelligent fusion terminal. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described 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, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment 1

[0027] See also Figure 1 A partial discharge positioning monitoring system for a distribution transformer, wherein the low-voltage side and the high-voltage side of the distribution transformer 1 are respectively connected with voltage sensors, the low-voltage side of the distribution transformer 1 is connected with a current sensor, the voltage sensor and the current sensor are connected to an edge computing module 4, and the edge computing module 4 is connected to an intelligent fusion terminal 5.

[0028] Intelligent converged terminal refers to a terminal device that uses new technologies, new materials, and new processes to integrate multiple functions. It can collect, process, transmit, and control a variety of data and information, and provide users with convenient, efficient, and intelligent services. It integrates multiple technologies and functions to meet different scenarios and needs. It has the ability to learn, make decisions, and optimize independently to improve work efficiency and accuracy. It supports multiple communication protocols and interfaces to achieve interconnection between devices. It can collect, process, and transmit large amounts of data and information to provide strong support for decision-making.

[0029] Intelligent converged terminals play an important role in the power industry. They are used for intelligent operation and maintenance, remote monitoring, data collection and other functions of the power grid to improve the efficiency and stability of the power grid. They include core hardware components such as processors, memory, sensors, and communication modules, which provide powerful computing and communication capabilities for the equipment. They are responsible for the resource management and task scheduling of the equipment, and provide a stable operating environment for upper-level applications, including application software such as data collection, processing, transmission and control, to realize the intelligent functions of the equipment.

[0030] Preferably, the high-voltage side of the distribution transformer 1 is connected to the high-voltage side capacitor divider 21, the low-voltage side of the distribution transformer 2 is connected to the low-voltage side capacitor divider 22, the high-voltage side capacitor divider 21 and the low-voltage side capacitor divider 22 are connected to the edge computing module 4, and the low-voltage side of the distribution transformer 1 is connected to the current transformer 3, and the current transformer 3 is connected to the edge computing module 4.

[0031] Capacitive voltage divider is a measuring device made by the principle of voltage division of capacitors in series, mainly used to measure AC high voltage. The working principle of capacitive voltage divider is based on the capacitive reactance characteristics of capacitors in AC circuits. When AC voltage is applied to capacitors in series, each capacitor will distribute a part of the voltage according to its capacitive reactance value, thereby achieving a voltage division effect. Compared with ordinary resistive voltage dividers, capacitive voltage dividers have greater voltage resistance and are not easy to break down, so they are more suitable for measuring high voltage.

[0032] The frequency response effect of the capacitor voltage divider makes it suitable for AC circuits, but the response time value is larger than that of the resistor voltage divider, so it is rarely used in the measurement of impulse voltage. The capacitor voltage divider has a simple structure and relatively low installation cost. The capacitor voltage divider has the advantages of wide bandwidth, fast response speed, and good stability, and is particularly suitable for the measurement of fast pulse signals.

[0033] The current transformer is an instrument that converts a large current on the primary side into a small current on the secondary side for measurement. It works on the principle of electromagnetic induction. When the current on the high current side of the primary side passes through the coil, a magnetic field is generated in the closed iron core, and then a current is induced in the winding on the low current side of the secondary side. The magnitude of the induced current is proportional to the current on the primary side and inversely proportional to the number of turns of the secondary coil. According to Faraday's law of electromagnetic induction, the current transformer is mainly composed of a closed iron core and a winding. The number of turns of the primary winding is very small, and it is connected in series in the circuit of the current to be measured; the number of turns of the secondary winding is large, and it is connected in series in the measuring instrument and the protection circuit. When working, the secondary circuit of the current transformer is always closed, and the impedance of the series coil of the measuring instrument and the protection circuit is very small, making the working state of the current transformer close to a short circuit. The main function of the current transformer is to convert high current into low current for easy measurement and protection. At the same time, it can also play the role of electrical isolation to protect the safety of measuring instruments and personnel.

[0034] Preferably, the intelligent fusion terminal 5 is connected to the Internet of Things management platform.

[0035] The IoT management platform is a comprehensive platform that integrates IoT device connection, data collection, processing, analysis and application services. The IoT management platform can realize the connection and management of various IoT devices, including device registration, configuration, status monitoring, remote control and other functions, to ensure that the devices can operate stably and reliably. It supports a variety of communication protocols and interfaces, such as LoRa, NB-IoT, Wi-Fi, etc., to meet the needs of different devices and scenarios. The platform can collect data generated by various IoT devices in real time, and process and analyze them to convert raw data into valuable information. It provides efficient data storage and query mechanisms to support rapid processing and access of large-scale data sets. It supports a variety of data analysis tools and algorithms, such as real-time analysis, pattern recognition, anomaly detection, etc. The platform can integrate various application services, such as remote monitoring, intelligent control, early warning and prediction, etc., to meet different business needs. It provides a rich API interface and SDK toolkit to facilitate developers to quickly develop and deploy IoT applications.

[0036] Preferably, the edge computing module 4 includes an AD converter, an FPGA and an ARM processor.

[0037] AD converter is a circuit device used to convert analog signals such as voltage and current into digital signals for processing and storage in digital systems. "A" stands for "Analog", which refers to the analog signal to be converted; "D" stands for "Digital", which refers to the digital signal output after conversion. AD converter converts analog signals into digital signals through four processes: sampling, holding, quantization and encoding. The specific process includes: sampling the analog signal at a certain time interval, then comparing the sampled value with a series of standard digital signals, and finally outputting the corresponding digital quantity through quantization and encoding.

[0038] FPGA is a product further developed on the basis of programmable devices such as PAL, GAL, CPLD, etc. It appears as a semi-custom circuit in the field of application-specific integrated circuits ASIC, which not only solves the shortcomings of custom circuits, but also overcomes the shortcomings of the limited number of gate circuits of the original programmable devices.

[0039] FPGA chips contain a large number of logic gates and triggers. Users can configure these logic gates and triggers through programming to achieve specific logic functions. FPGAs are highly flexible and programmable and can be customized and optimized according to different application requirements. FPGAs have very powerful parallel processing capabilities and can handle multiple tasks at the same time, which gives them a significant advantage in processing high-speed, large-data applications.

[0040] The basic working principle of FPGA is to realize user-defined logic functions through internal programmable logic blocks and input and output blocks. Users can program and configure by using special FPGA development tools such as Xilinx's ISE, Vivado or Altera's Quartus. Development tools usually provide graphical programming interfaces and hardware description language HDL programming methods, and users can choose the appropriate programming method according to their needs.

[0041] ARM processor, full name Advanced RISC Machine, is a low-power, low-cost RISC RISC computer microprocessor. ARM processor adopts RISC design with simple instruction set, low power consumption and high performance. It supports Thumb16-bit / ARM 32-bit dual instruction set, which is well compatible with 8-bit / 16-bit devices and provides all the advantages of 32-bit system. ARM processor uses a large number of registers, and the instruction execution speed is faster. Most data operations are completed in registers, which improves the execution efficiency. The fixed-length instruction format is adopted to facilitate pipeline operation execution and improve data processing capabilities.

[0042] The ARM processor is responsible for processing complex software algorithms and task scheduling, while the FPGA is responsible for high-speed data processing and hardware acceleration. This combination can give full play to the advantages of both, improve the overall performance of the system and reduce power consumption. FPGA and ARM can be integrated in the same SoC system-level core), with faster internal communication rate, high hardware integration and smaller size. The combination of ARM and FPGA can be extended through FPGA to meet the needs of multiple interface resources. The combination of FPGA hardware programmability and ARM software programmability can shorten the product development cycle and reduce the cost of listing.

[0043] The ADC is responsible for quickly converting analog signals into digital signals, the FPGA performs high-speed parallel processing of digital signals, and the ARM performs complex control and algorithm calculations. The three work together to achieve high-performance data processing.

[0044] Embodiment 2

[0045] A method for positioning and monitoring partial discharge of a distribution transformer comprises the following steps: a voltage sensor is used to collect voltage signals on the low-voltage side and the high-voltage side of the distribution transformer 1; a current sensor is used to collect current signals on the low-voltage side of the distribution transformer 1; an edge computing module 4 obtains the voltage signal and the current signal for processing and uploads the processing results to an intelligent fusion terminal 5.

[0046] A high-voltage side capacitor divider 21 is configured on the high-voltage side of the distribution transformer 1 to collect the high-voltage side voltage signal. A low-voltage side capacitor divider 22 is configured on the low-voltage side of the distribution transformer 1 to collect the low-voltage side voltage signal of the distribution transformer 1. The edge computing module 4 obtains the high-voltage side voltage signal and the low-voltage side voltage signal through the high-voltage side capacitor divider 21 and the low-voltage side capacitor divider 22, processes the signals and uploads the processing results to the intelligent fusion terminal 5. A current transformer 3 is configured on the low-voltage side of the distribution transformer 1 to collect the low-voltage side current signal of the distribution transformer 1. The edge computing module 4 obtains the low-voltage side current signal through the current transformer 3 to process the signals and uploads the processing results to the intelligent fusion terminal 5.

[0047] The intelligent fusion terminal 5 uploads the processing results to the IoT management platform.

[0048] Preferably, the AD converter in the edge computing module 4 quantizes the signals of the high-voltage side capacitor divider 21 and the low-voltage side capacitor divider 22 to obtain a quantized sensor signal, the FPGA in the edge computing module 4 collects, stores and filters the quantized sensor signal to obtain a processed sensor signal, and the ARM in the edge computing module 4 extracts features from the processed sensor signal and performs communication protocols to the outside.

[0049] The edge computing module 4 acquires the voltage signal and the current signal for processing and uploads the processing results to the intelligent fusion terminal 5 to locate the fault specifically: when a fault occurs inside the distribution transformer 1, the polarity of the high-voltage side capacitor divider 21 is opposite to that of the low-voltage side capacitor divider 22; when a fault occurs outside the distribution transformer 2, the polarity of the high-voltage side capacitor divider 21 is the same as that of the low-voltage side capacitor divider 22.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A distribution transformer partial discharge positioning monitoring system, characterized in that: The low voltage side and the high voltage side of the distribution transformer (1) are respectively connected to voltage sensors, the low voltage side of the distribution transformer (1) is connected to a current sensor, the voltage sensor and the current sensor are connected to an edge computing module (4), and the edge computing module (4) is connected to an intelligent fusion terminal (5).

2. A distribution transformer partial discharge location monitoring system according to claim 1, characterized in that: The high-voltage side of the distribution transformer (1) is connected to a high-voltage side capacitor voltage divider (21), the low-voltage side of the distribution transformer (2) is connected to a low-voltage side capacitor voltage divider (22), and the high-voltage side capacitor voltage divider (21) and the low-voltage side capacitor voltage divider (22) are connected to an edge computing module (4).

3. A distribution transformer partial discharge location monitoring system according to claim 1, characterized in that: The low-voltage side of the distribution transformer (1) is connected to a current transformer (3), and the current transformer (3) is connected to an edge computing module (4).

4. A distribution transformer partial discharge location monitoring system according to claim 1, characterized in that: The intelligent fusion terminal (5) is connected to the Internet of Things management platform.

5. A distribution transformer partial discharge location monitoring system according to claim 1, characterized in that: The edge computing module (4) includes an AD converter, an FPGA and an ARM processor.

6. A method for localizing and monitoring partial discharge of a distribution transformer, characterized in that: The method comprises the following steps: the low-voltage side and the high-voltage side of the distribution transformer (1) collect voltage signals through voltage sensors, the low-voltage side of the distribution transformer (1) collects current signals through current sensors, and an edge computing module (4) obtains the voltage signal and the current signal for processing and uploads the processing results to an intelligent fusion terminal (5).

7. A method for localizing and monitoring partial discharge of a distribution transformer according to claim 6, characterized in that: A high-voltage side capacitor voltage divider (21) is configured on the high-voltage side of the distribution transformer (1) to collect the high-voltage side voltage signal; a low-voltage side capacitor voltage divider (22) is configured on the low-voltage side of the distribution transformer (1) to collect the low-voltage side voltage signal of the distribution transformer (1); the edge computing module (4) obtains the high-voltage side voltage signal and the low-voltage side voltage signal through the high-voltage side capacitor voltage divider (21) and the low-voltage side capacitor voltage divider (22), processes the signals, and uploads the processing results to the intelligent fusion terminal (5); a current transformer (3) is configured on the low-voltage side of the distribution transformer (1) to collect the low-voltage side current signal of the distribution transformer (1); the edge computing module (4) obtains the low-voltage side current signal through the current transformer (3), processes the signals, and uploads the processing results to the intelligent fusion terminal (5).

8. A method for localizing and monitoring partial discharge of a distribution transformer according to claim 7, characterized in that The intelligent fusion terminal (5) uploads the processing results to the IoT management platform.

9. A method for localizing and monitoring partial discharge of a distribution transformer according to claim 7, characterized in that: The AD converter in the edge computing module (4) quantizes the signals of the high-voltage side capacitor voltage divider (21) and the low-voltage side capacitor voltage divider (22) to obtain a quantized sensing signal, the FPGA in the edge computing module (4) collects, stores and filters the quantized sensing signal to obtain a processed sensing signal, and the ARM in the edge computing module (4) extracts features from the processed sensing signal and performs communication protocol to the outside.

10. A method for localizing and monitoring partial discharge of a distribution transformer according to claim 7, characterized in that: The edge computing module (4) obtains the voltage signal and the current signal for processing and uploads the processing result to the intelligent fusion terminal (5) to locate the fault. Specifically, when a fault occurs inside the distribution transformer (1), the polarity of the high-voltage side capacitor divider (21) and the low-voltage side capacitor divider (22) are opposite; when a fault occurs outside the distribution transformer (2), the polarity of the high-voltage side capacitor divider (21) and the low-voltage side capacitor divider (22) are the same.

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