Transformer winding deformation live monitoring device for GIS substation

Abstract

The utility model discloses a transformer winding deformation live-line monitoring device for a GIS transformer substation, and belongs to the technical field of winding deformation monitoring. Comprising a signal generation module, a feedback protection module, a sensor module, a weak high-frequency signal processing module, a signal acquisition module and a diagnostic analysis module, the feedback protection module comprises a change-over switch and a feedback unit; the sensor module comprises an excitation sensor and a response sensor, a measuring coil is wound on a magnetic core of the excitation sensor, and a measuring coil and an anti-interference coil are wound on a magnetic core of the response sensor; the weak high-frequency signal processing module comprises a filtering unit, an integrating unit and an amplifying unit; the signal generation module, the change-over switch, the feedback unit, the excitation sensor, the response sensor, the filtering unit, the integration unit, the amplification unit, the signal acquisition module and the diagnostic analysis module are connected in sequence.

Description

Technical Field

[0001] This utility model relates to the field of winding deformation monitoring technology, and in particular to a live monitoring device for transformer winding deformation in GIS substations. Background Technology

[0002] To improve the reliability of the power grid, my country's power industry is vigorously promoting the intelligent, digital, and information-based development of equipment. For transformers, winding deformation is one of the important causes of serious accidents such as inter-turn short circuits and insulation breakdown. Timely detection of local deformation is an effective means to avoid these accidents. However, people's understanding of the mapping relationship between the internal winding deformation of transformers and external measurable characteristics is not yet thorough enough. Current diagnostic methods generally have low sensitivity and accuracy, and live-line testing technology is generally not mature enough. In practice, offline testing is still the main method.

[0003] Currently, commonly used methods for detecting winding deformation include the low-voltage short-circuit impedance method and the frequency response analysis method (FRA). These two methods are included in the mandatory winding deformation testing procedures by the State Grid Corporation of China before transformers leave the factory and are put into operation, and the original test data must be retained. Among them, the frequency response method has advantages such as high accuracy and ease of use in detecting transformer winding deformation. Furthermore, compared to the short-circuit impedance method, the frequency response curve used in FRA contains much richer information and has higher sensitivity, thus it is widely used.

[0004] The power industry standard DL / T911-2016, "Frequency Response Analysis Method for Power Transformer Winding Deformation," clarifies the offline detection method for transformer winding deformation using the frequency response method. The diagnostic technique of the frequency response analysis method is based on the horizontal or vertical comparison of frequency response amplitude curves. The horizontal comparison method compares the three-phase windings on each side of the same transformer. When the spectral characteristics of the three phases are inconsistent, the spectral characteristics of the windings of transformers of the same model produced in the same period from the same manufacturer are used for judgment. If the consistency among the three phases of transformers produced in the same period is good, it is preliminarily determined that the transformer winding has deformed. The vertical analysis method compares the amplitude-frequency characteristics of the transformer currently recorded with those recorded during normal operation. If the difference between the two exceeds a certain level, it can be preliminarily determined that the winding has deformed. However, the offline detection of transformer winding deformation currently faces the following problems in practice:

[0005] (1) Offline detection of transformer winding deformation requires de-energizing and disconnecting the transformer. In actual operation, the transformer cannot be easily stopped.

[0006] (2) Transformer winding deformation has a cumulative effect, and the offline detection interval is long, making it impossible to detect defects in a timely manner;

[0007] (3) Since there are no clear requirements for the output signal, offline testing depends on the technical level and work experience of the testing personnel.

[0008] In response to the shortcomings of offline detection, live-line monitoring has become increasingly popular in recent years. Transformer windings in live operation not only carry large currents and high potentials, but are also directly electrically connected to other equipment in the substation and overhead transmission lines. Existing offline detection methods cannot be directly applied to operating transformers. Therefore, it is essential to solve the problem of how to inject an excitation signal into the high-potential windings and obtain a response signal from them. Some researchers use coils to inject sweep frequency excitation signals from the winding neutral point or bushing root, and measure the current response signal from the bushing root. However, this method has significant limitations: if the transformer neutral point is not grounded, the sensor cannot be installed; installing the sensor at the bushing root requires a power outage, which is inefficient and time-consuming. New explorations and improvements are needed to determine the injection and measurement locations for frequency response signals in online monitoring of transformer winding deformation.

[0009] For grounding outgoing cables in GIS substations, it was previously believed that injecting frequency response signals from this location would be unlikely to yield a measurable result. However, compared to measurements at the bushing root, the operating space is larger, sensor installation is more convenient, and unlike the limitations imposed by the large insulation distance at the bushing root, live installation is possible at the outgoing cable location, making it economical. Therefore, it is possible to attempt frequency response signal injection and measurement from the outgoing cables of GIS substations, construct relevant network transfer functions, and perform live detection of transformer winding deformation.

[0010] To address the aforementioned issues, it is necessary to design a transformer winding deformation monitoring device for GIS substations that has strong anti-interference capabilities and can be installed and operated under energized conditions to meet practical needs. Utility Model Content

[0011] The purpose of this utility model is to address the shortcomings of existing technologies by proposing a live monitoring device for transformer winding deformation in GIS substations, comprising a signal generation module, a feedback protection module, a sensor module, a weak high-frequency signal processing module, a signal acquisition module, and a diagnostic analysis module;

[0012] The feedback protection module includes a switching switch and a feedback unit; the sensor module includes an excitation sensor and a response sensor; the weak high-frequency signal processing module includes a filtering unit, an integration unit, and an amplification unit.

[0013] The signal generation module, switching switch, feedback unit, excitation sensor, response sensor, filtering unit, integration unit, amplification unit, signal acquisition module, and diagnostic analysis module are connected in sequence.

[0014] Both the excitation sensor and the response sensor are Rogowski coil sensors with open and closed operation, and the sensor core material is iron-based microcrystalline material.

[0015] Excitation and response sensors are installed at the end of the terminal compartment of each phase cable on the high-voltage side.

[0016] Each circuit element in the filtering unit, integration unit, and amplification unit is equipped with a shielding layer.

[0017] The feedback unit is a unidirectional feedback parallel resonant device.

[0018] The switch is a periodic switching switch.

[0019] The beneficial effects of this utility model are as follows:

[0020] 1. The monitoring device can be installed under power without interrupting the power supply to monitor the operating status of the transformer windings, which is economical and reliable.

[0021] 2. The monitoring device can continuously measure the transformer in operation, obtaining more accurate and reliable data.

[0022] 3. The monitoring device can diagnose early faults in transformer windings and provide early warnings before the faults worsen, enabling scientifically planned maintenance work.

[0023] 4. The monitoring device can provide a comprehensive understanding of the equipment's historical usage, allowing for full utilization of its lifespan within the context of asset management. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the structure of the transformer winding deformation live monitoring device for GIS substations according to this utility model;

[0025] Figure 2 A schematic diagram of the sensor layout scheme for monitoring transformer winding deformation in a GIS substation;

[0026] Figure 3 Magnetic field distribution cloud maps at different installation distances;

[0027] Figure 4 This is a schematic diagram of interference shielding for signal processing circuits.

[0028] Figure 5 This is a schematic diagram of the principle for detecting deformation in the windings of a live transformer.

[0029] Figure 6(a) shows the frequency response curves of excitation and response being in phase;

[0030] Figure 6(b) shows the frequency response curves of the excitation and response being out of phase. Detailed Implementation

[0031] This utility model proposes a live monitoring device for transformer winding deformation in GIS substations. The following description, in conjunction with the accompanying drawings and specific embodiments, further illustrates this utility model.

[0032] Figure 1 This is a schematic diagram of the structure of the transformer winding deformation live monitoring device for GIS substations according to this utility model. The device includes a signal generation module, a feedback protection module, a sensor module, a weak high-frequency signal processing module, a signal acquisition module, and a diagnostic analysis module. The feedback protection module includes a switching switch and a feedback unit. The sensor module includes an excitation sensor and a response sensor, both of which are Rogowski coil sensors based on the magnetic field coupling principle. The excitation sensor has a measuring coil wound on its magnetic core, with one end grounded and the other end serving as the input terminal. The response sensor has a measuring coil and an anti-saturation coil wound on its magnetic core, with one end of the measuring coil grounded and the other end serving as the output terminal. The anti-saturation coils of each response sensor are connected in parallel, and a small impedance Z is connected in series at each port of the anti-saturation coil. Both the excitation and response sensors are open-ended, with openings at both ends. The sensor housing and the break in the magnetic core are fastened with screws, and the coil breaks are connected via aviation connector wires. The weak high-frequency signal processing module includes a filtering unit, an integration unit, and an amplification unit; the signal generation module, switching switch, feedback unit, excitation sensor, response sensor, filtering unit, integration unit, amplification unit, signal acquisition module, and diagnostic analysis module are connected sequentially. The specific monitoring steps are as follows:

[0033] 1. Install three excitation sensors at the end of each phase cable terminal compartment on the high-voltage side, at a height of 210cm above the ground; install three response sensors at the end of each phase cable terminal compartment on the high-voltage side, at a height of 255cm above the ground. For detailed layout instructions, please refer to [link to relevant documentation]. Figure 2 The installation process is as follows:

[0034] (1) Place the two half excitation sensors of each phase at the end of the cable terminal compartment of each phase on the high voltage side, connect the aviation plug connection line, merge the sensors, and tighten the interface screws.

[0035] (2) Place the two half-response sensors of each phase at the end of the cable terminal compartment of each phase on the high voltage side. The current metal sheath grounding wire of the response sensor is wrapped together with the cable body in the center of the sensor. Figure 3 The magnetic field distribution cloud maps are shown at different installation distances. Based on simulation analysis and field experimental experience, if the distance between the response sensor and the excitation sensor is too small, their magnetic fields may couple, affecting the online measurement of the frequency response signal. The height difference between the response sensor and the excitation sensor should not be less than 30 cm.

[0036] (3) Connect the anti-saturation coils of the three-phase response sensor in parallel with the cable, ensure that the parallel interface is securely connected, connect the aviation plug connection lines of each phase, merge the sensors, and tighten the sensor interface screws.

[0037] (4) The input end of the excitation sensor is connected to the signal generation module via a cable, and the output end of the response sensor is connected to the weak high-frequency signal processing module via a cable. After the wiring is completed, the measurement is performed.

[0038] 2. The signal generation module injects a 160V sweep frequency voltage signal into the winding of the A-phase excitation sensor via a multi-phase switching switch. The sweep frequency range is 1kHz-1MHz. Utilizing the principle of magnetic field coupling, the A-phase excitation sensor couples the signal into the winding, generating an induced current signal in the winding. The A, B, and C three-phase response sensors extract the induced current signal generated in the winding based on magnetic field coupling. For details on the live detection principle, please refer to the appendix. Figure 5 .

[0039] 3. The weak high-frequency signal processing module processes the output voltage signal of the response sensor. The frequency response signal first passes through a high-pass filter to remove power frequency noise, and then passes through a low-pass filter to remove high-frequency noise above 1MHz. Subsequently, the composite integrator circuit processes the low-frequency and high-frequency bands, improving the sensitivity of signals from 1kHz to 10kHz and 900kHz to 1MHz, making the measurement frequency band flatter. Finally, the signal enters the amplifier, which first amplifies it by 10 times, and then the second-stage amplifier can adjust the amplification by 10-100 times, amplifying the frequency response signal from tens to hundreds of microvolts to the millivolt level. Figure 4 This is a schematic diagram of interference shielding for signal processing circuits.

[0040] 4. The signal acquisition module acquires the signals processed by the weak high-frequency signal processing module, acquires signals from all sensors simultaneously, and transmits the acquired data to the diagnostic analysis module for further analysis after classification and processing.

[0041] 5. The diagnostic analysis module calculates the signal network transfer function and constructs the network transfer function H for the case where the neutral point of the three-phase transformer is not grounded based on the port voltage and current relationship.

[0042]

[0043] Where j is the imaginary number, ω is the angular frequency, and H(ω) is the magnitude of the transfer function at frequency ω, which is used as the vertical axis of the frequency response curve (amplitude-frequency curve).

[0044] With the excitation sensor input voltage U S (Excitation signal) is used as a reference, and the output voltage signal U of the response sensor is used as a reference. X1 Combined, in the formula k T Represents the response sensor output voltage UX1 The voltage U generated by the sensing system X2 The proportional coefficient between them contains the gain information of the weak signal processing circuit. X represents one of the three phases A, B and C. The generated frequency response function images are shown in Figure 6(a) and Figure 6(b).

[0045] The signal generation module applies an excitation signal to the phase A excitation sensor. At this time, all three phase response sensors output signals. The frequency response curves generated by the network function H formed by each phase are denoted as Aa, Ab, and Ac, respectively.

[0046] 6. When the multi-phase switching switch is switched to phase B, the signal generation module injects a 160V sweep frequency voltage signal into the winding of the phase B excitation sensor. The sweep frequency range is 1kHz-1MHz. Repeat steps 2-5 to generate frequency response curves Ba, Bb, and Bc.

[0047] 7. When the multiphase switching switch is switched to phase C, the signal generation module injects a 160V sweep frequency voltage signal into the winding of the phase C excitation sensor. The sweep frequency range is 1kHz-1MHz. Repeat steps 2-5 to generate frequency response curves Ca, Cb, and Cc.

[0048] The generated frequency response curves are used for diagnostic analysis using correlation coefficients. The relevant calculations and processing are as follows:

[0049] Assuming X(k) and Y(k) are the frequency response amplitude sequences of the transformer under normal operating conditions and under winding deformation fault conditions, respectively, the characteristic function is calculated as follows:

[0050] First, calculate the standard deviation of the two sequences:

[0051]

[0052] Where k = 0, 1, 2, ..., N-1, is the number of sampling frequency points, and N is the total number of sampling frequency points;

[0053] The covariance of the two sequences is:

[0054]

[0055] The normalized covariance coefficients of the two sequences are:

[0056]

[0057] The relevant coefficients that meet the requirements of the project are:

[0058]

[0059] As shown in the above formula, the correlation coefficient between two identical curves is 10, and the greater the difference, the smaller the correlation coefficient.

[0060] A longitudinal comparison of the frequency response curves of three-phase windings at the same voltage level was performed. Changes in the frequency response characteristics of the winding's characteristic function were determined through characteristic indices, and a comprehensive analysis was conducted using multiple characteristic indices. The characteristic value used was R. LF (low-frequency correlation coefficient), R MF (Mid-frequency correlation coefficient), R HF (High-frequency band correlation coefficient), R (whole frequency band correlation coefficient).

[0061] The generated frequency response curves were compared with the online database, which refers to the live-line testing data collected during the initial commissioning phase of the transformer. The results obtained using the correlation coefficient method are detailed in Table 1.

[0062] Table 1. Calculation results of eigenvalues ​​of the frequency response curve of network function H.

[0063]

[0064] Referring to the diagnostic criteria of the correlation coefficient method in the power industry standard DL / T911-2016 "Frequency Response Analysis Method for Winding Deformation of Power Transformers", it can be seen that all three phase windings of the transformer are in normal winding condition with no deformation. From the above analysis, it can be concluded that the monitoring device of this utility model can realize uninterrupted monitoring of the transformer winding operation status, which is economical and reliable; it can also perform continuous measurement of energized transformers, obtaining more accurate and reliable data.

Claims

1. A live-line monitoring device for transformer winding deformation in a GIS substation, characterized in that, It includes a signal generation module, a feedback protection module, a sensor module, a weak high-frequency signal processing module, a signal acquisition module, and a diagnostic analysis module; The feedback protection module includes a switching switch and a feedback unit; the sensor module includes an excitation sensor and a response sensor; the weak high-frequency signal processing module includes a filtering unit, an integration unit, and an amplification unit. The signal generation module, switching switch, feedback unit, excitation sensor, response sensor, filtering unit, integration unit, amplification unit, signal acquisition module, and diagnostic analysis module are connected in sequence.

2. The transformer winding deformation live-line monitoring device for GIS substations according to claim 1, characterized in that, Both the excitation sensor and the response sensor are Rogowski coil sensors with open and closed operation, and the sensor core material is iron-based microcrystalline material.

3. The transformer winding deformation live-line monitoring device for GIS substations according to claim 2, characterized in that, Excitation and response sensors are installed at the end of the terminal compartment of each phase cable on the high-voltage side.

4. The transformer winding deformation live-line monitoring device for GIS substations according to claim 1, characterized in that, Each circuit element in the filtering unit, integration unit, and amplification unit is equipped with a shielding layer.

5. The transformer winding deformation live-line monitoring device for GIS substations according to claim 1, characterized in that, The feedback unit is a unidirectional feedback parallel resonant device.

6. The transformer winding deformation live-line monitoring device for GIS substations according to claim 1, characterized in that, The switching switch is a periodic switching switch.

Images