A grounding system for a high-voltage switchgear

Abstract

The present invention discloses a grounding system for a high-voltage switchgear, which relates to the technical field of power systems and solves the problems of poor resistance stability and poor safety in the grounding system of existing high-voltage switchgears. The present invention includes a real-time detection module, an adaptive grounding resistance adjustment module, a high-frequency transient suppression module, a fault detection and isolation module, a grounding current control module, and a telemetry module. The present invention ensures the stability of the grounding resistance under different environmental conditions by connecting multiple sections of controllable resistors in series with the grounding path and automatically adjusting the resistance value in combination with the environmental compensation model. The high-frequency transient suppression module detects and quickly responds to the arc re-ignition to effectively suppress the generation of overvoltage. The fault detection and isolation module monitors the grounding current in real time to prevent the further spread of faults, improving the reliability and safety of the system. The present invention greatly improves the resistance stability and safety of the existing grounding system.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and more particularly to a grounding system for a high-voltage switchgear cabinet. Background Art

[0002] With the rapid development of the power industry, as an important device in the power system, the safety and reliability of high-voltage switchgear cabinets have been increasingly emphasized. During the process of power transmission and distribution, as a key link to ensure the safety of equipment and personnel, the technical level and performance requirements of the grounding system of high-voltage switchgear cabinets are constantly improving. In the construction of modern power grids, the optimization and improvement of the grounding system of high-voltage switchgear cabinets have become the focus of attention in the power industry;

[0003] Currently, the grounding system of high-voltage switchgear cabinets generally adopts a metal-enclosed structure, and the internal space uses air or insulating gas as the insulating medium. The grounding system ensures effective grounding during equipment maintenance or faults and prevents electric shock accidents by fixedly installing a grounding switch and setting a mechanical interlock device between the grounding switch and the circuit breaker. At the same time, the grounding system also needs to meet certain requirements for resistance and conductance to achieve the rapid conduction and dispersion of current. However, with the expansion of the power grid scale and the increase in power load, higher requirements are put forward for the performance of the grounding system of high-voltage switchgear cabinets.

[0004] In the grounding system of high-voltage switchgear cabinets, the grounding resistance is one of the key indicators of the grounding system performance. However, due to the changes in the physical and chemical properties of the soil (such as humidity, temperature, salt content, etc.), the grounding resistance may change over time and environmental conditions. This change may cause the grounding system to be unable to provide sufficient protection in some cases; in addition, grounding protection is an important measure to prevent equipment failures and electric shock accidents. However, for the grounding method of ungrounded neutral point or grounded through an arc suppression coil, its limitations are particularly obvious. Although this grounding method can effectively limit the large current during single-phase grounding, the problem of arc reignition overvoltage cannot be ignored. The arc reignition overvoltage may put higher requirements on the insulation level of the equipment, thereby increasing the equipment cost and manufacturing difficulty. In addition, frequent overvoltages may accelerate equipment aging, shorten the service life of the equipment, and further increase the operation and maintenance costs. Secondly, during a single-phase grounding fault, the grounding system needs to quickly and accurately control the grounding current to prevent equipment damage and power supply interruption. However, some grounding systems perform poorly in controlling the grounding current. This may cause the protection device to malfunction due to excessive current or be insensitive due to too small current, thus unable to cut off the fault circuit in time and increasing the risk of the system.

[0005] Therefore, a grounding system for a high-voltage switchgear cabinet is needed to solve the above problems. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention discloses a grounding system for a high-voltage switchgear, aiming to improve the stability and safety of the existing grounding system of high-voltage switchgear.

[0007] To achieve the above technical effects, the present invention adopts the following technical solutions:

[0008] A grounding system for a high-voltage switchgear, comprising:

[0009] A real-time detection module, used for real-time monitoring of the grounding resistance and changes in environmental factors beside the grounding system, and outputting the grounding resistance change value and environmental factors to the adaptive grounding resistance adjustment module and the telemetry module; the environmental factors include soil humidity and temperature;

[0010] The adaptive grounding resistance adjustment module, used for dynamically adjusting the grounding resistance according to the grounding resistance change value and environmental factors; the adaptive grounding resistance adjustment module connects multiple sections of controllable resistors in series with the grounding path, and the adaptive grounding resistance adjustment module constructs a resistance compensation value mapping model based on the environmental sensitivity index and the cross-correlation coefficient, and controls the resistance value through a dynamic resistance value control algorithm; the resistance compensation value mapping model includes an environmental factor quantization unit, a resistance influence analysis unit, a compensation value calculation unit, and an output feedback unit;

[0011] A high-frequency transient suppression module, used for suppressing high-frequency transient overvoltage caused by arc restriking;

[0012] A fault detection and isolation module, used for detecting the grounding current, isolating the faulty circuit, and transmitting the fault signal to the telemetry module;

[0013] A grounding current control module, used for controlling the grounding current;

[0014] The telemetry module, used for providing remote monitoring of the grounding system status; the telemetry module transmits the grounding system indicators to the remote terminal through wireless communication; the grounding system indicators include grounding resistance, current, soil resistivity, and temperature data;

[0015] The output end of the real-time detection module is connected to the input ends of the adaptive grounding resistance adjustment module and the telemetry module; the output ends of the high-frequency transient suppression module, the fault detection and isolation module, and the grounding current control module are connected to the input end of the telemetry module; the output end of the fault detection and isolation module is connected to the input end of the grounding current control module.

[0016] As a further technical solution of the present invention, the real-time detection module monitors the grounding resistance in real time through the grounding resistance detection unit; the grounding resistance detection unit supplies power to the grounding resistance through a constant current source circuit configured by an operational amplifier and an LDO voltage regulator, and detects the voltage drop across the grounding resistance through a differential amplifier. The voltage signal is converted into a digital signal by an analog-to-digital converter; the constant current source circuit ensures that the current remains constant throughout the detection process through a negative feedback mechanism, eliminating the error caused by power supply fluctuations; the differential amplifier consists of two symmetrical operational amplifiers, which respectively detect the voltages at both ends of the grounding resistance, and eliminate noise interference through differential output; the grounding resistance detection module also sends the calculated change value of the grounding resistance to the adaptive grounding resistance adjustment module and the telemetry module through the serial communication protocol SPI.

[0017] As a further technical solution of the present invention, the adaptive grounding resistance adjustment module receives and processes the digital signal of the grounding resistance detection module through a microcontroller. The microcontroller processes the digital signal output by the grounding resistance detection module through an FIR filter and a moving average filter, and calculates the change value of the grounding resistance by the least squares method; according to the calculated change value of the grounding resistance, the adaptive grounding resistance adjustment module then realizes the amplification of the PWM signal and the drive of the controllable resistor array through a PWM drive circuit; the controllable resistor array consists of multiple controllable resistor units, and each controllable resistor unit is connected in series in the grounding path. The on-state of each controllable resistor unit is controlled and adjusted through a PWM signal to realize the dynamic adjustment of the grounding resistance value; the adaptive grounding resistance adjustment module also realizes the real-time monitoring of the change value of the grounding resistance through a closed-loop feedback circuit, and performs real-time feedback adjustment on the change value of the grounding resistance through a dynamic resistance value control algorithm.

[0018] As a further technical solution of the present invention, the PWM drive circuit includes an input unit, an amplification unit, a drive stage unit, a protection unit, and an isolation unit; the input unit locks the state of the input signal through an input buffer; the amplification unit amplifies the amplitude of the PWM signal through a high-gain operational amplifier; the drive stage unit generates a current to drive the controllable resistor array through a power transistor; the protection unit protects the circuit from abnormal conditions through a current-limiting resistor, a clamping diode, and a transient voltage suppressor; the isolation unit electrically isolates between the main control circuit and the drive circuit through an optocoupler.

[0019] As a further technical solution of the present invention, the working method of the dynamic resistance value control algorithm includes the following steps:

[0020] Step 1: Construct a resistance value mapping matrix where, T n , RH n , I n , V nand FT n respectively represent the temperature, humidity, current, voltage and fault type code of the high-voltage switchgear at the nth sampling moment; and noise suppression is performed through a weighted moving average filter;

[0021] Step 2: Based on the resistance value mapping matrix E, calculate the dynamic resistance value demand through a multivariable nonlinear function; the multivariable nonlinear function obtains the weight vector θ and the feature mapping function G n (E), map the environmental parameters to the high-dimensional feature space to calculate the grounding resistance value; the feature mapping function constructs the feature mapping through the polynomial kernel function and the activation function; the formula expression for the multivariable nonlinear function to calculate the dynamic resistance value demand is:

[0022]

[0023] In formula (1), M represents the highest degree of the polynomial term; P represents the number of cross terms, used to control the complexity of the feature mapping function; G n (E) represents the feature mapping function, used to map the nth row vector of the resistance value mapping matrix to the high-dimensional feature space; θ represents the weight vector, used to map the output of the feature mapping function to the dynamic resistance value demand; μ c represents the coefficient in the polynomial kernel function and the cross term, used to adjust the shape and complexity of the feature mapping function; indexset l represents the parameter index set involved in the lth cross term; E n represents the nth row vector of the resistance value mapping matrix;

[0024] Step 3: Construct the state matrix of the controllable resistance array where S n represents the switch state of the nth controllable resistance unit; and based on the current state S n and the dynamic resistance value demand phi(E n ), determine the optimal PWM duty cycle setting through the fitness function F ij (S n ); the formula expression of the fitness function is:

[0025]

[0026] In formula (2), L represents a solution, that is, a set of PWM duty cycle settings; h, γ and ε respectively represent the weight coefficients of the error term, the safety penalty term and the stability penalty term, used to balance the importance of different optimization objectives; P ij (L) represents the safety penalty term of the solution L; R a represents the predicted value of the grounding resistance of the nth sample by the deep learning model; R pUnder solution L, the actual grounding resistance value of the nth sample; δ ij (L) represents the stable penalty term of solution L; N represents the number of samples within the evaluation period; phi(E n ) represents the dynamic resistance value requirement; T represents the length of the evaluation time period, which is used to measure the calculation range of the cumulative error;

[0027] Step 4: Control the conduction state of the controllable resistor array through a PWM signal to adjust the grounding resistance value; during the control process, monitor the system state and environmental changes in real time, and compare the actual grounding resistance value with the predicted value in Step 2. If an error occurs, adjust the control strategy through a feedback mechanism; the adjustment includes modifying the PWM duty cycle setting, adjusting the search parameters of the genetic algorithm, or retraining the dynamic resistance value demand model; the feedback mechanism generates and adjusts the duty cycle of the PWM signal through a PID controller according to the resistance value error; the calculation formula is:

[0028]

[0029] In formula (3), A t is the control parameter of the step growth rate, which is used to limit the growth speed of the step; μ j represents the adjustment threshold, which is used to judge whether adaptive adjustment is required; ΔS is the adjustment step, which represents the adjustment amount of the PWM duty cycle setting; w t represents the current error; sign represents the sign function, which is used to determine the adjustment direction; K P 、K i and K d represent the proportional, integral, and differential gains of the PID controller respectively.

[0030] As a further technical solution of the present invention, the environmental factor quantification unit establishes a mathematical model between environmental parameters and quantification indicators through a statistical quantification method. The statistical quantification method describes the mapping relationship between environmental parameters and quantification indicators through a non-linear model, and minimizes the difference between the predicted value and the actual value through regression analysis to solve the model parameters; the resistance influence analysis unit fits the non-linear mapping between environmental parameters and resistance changes through a support vector machine and a neural network; the support vector machine uses a kernel function to map the input data into a high-dimensional space and finds the optimal hyperplane to maximize the classification interval; the neural network realizes the approximation and prediction of complex functions through a multi-layer network structure and a backpropagation algorithm; based on the results of the resistance influence analysis, the compensation value calculation unit dynamically calculates and outputs a resistance compensation value using Gaussian process regression and the gradient descent method; the Gaussian process regression is based on the prior assumption of a Gaussian process, describes the correlation between input variables through a kernel function, and calculates the predicted value using Bayesian inference; the gradient descent method is used to fine-tune the compensation value considering the requirements of system stability and real-time performance; the output feedback unit transmits the calculated resistance compensation value to the adaptive grounding resistance adjustment module in real time through a communication protocol and an API interface, and receives system status feedback; the output end of the environmental factor quantification unit is connected to the input end of the resistance influence analysis unit; the output end of the resistance influence analysis unit is connected to the input end of the compensation value calculation unit; the output end of the compensation value calculation unit is connected to the input end of the output feedback unit.

[0031] As a further technical solution of the present invention, the high-frequency transient suppression module shunts the transient voltage suppression diode on the grounding path. When an overvoltage occurs, the transient voltage suppression diode conducts; the high-frequency transient suppression module includes a detection and response unit, an energy absorption unit, and a filtering and stabilization unit; the detection and response unit uses a high-bandwidth analog front end and fast Fourier transform to monitor the voltage waveform of the power system in real time. Once a high-frequency transient is detected, the conduction state of the transient voltage suppression diode is switched to direct the transient current to a preset safe path. The detection and response unit also provides an immediate voltage clamp through a metal oxide varistor; when a high-frequency transient occurs, the energy absorption unit stores energy through a capacitor bank and converts the stored electrical energy into heat energy through a positive temperature coefficient thermistor and dissipates it into the environment; the energy absorption unit also releases the stored energy through a gas discharge tube; the filtering and stabilization unit shunts a multi-stage LC filtering network in the circuit, and the multi-stage LC filtering network filters out redundant frequency components through a surface acoustic wave filter; the filtering and stabilization unit also optimizes the energy release process through an adaptive tuning mechanism; the adaptive tuning mechanism evaluates the fitness of the cut-off frequency and bandwidth through a particle swarm optimization algorithm to tune the value of the objective function; during the parameter adjustment process, the adaptive tuning mechanism also simulates the response of the filter to the transient voltage waveform through finite element analysis to evaluate the energy absorption and release effects.

[0032] As a further technical solution of the present invention, the fault detection and isolation module monitors the grounding current through a current transformer. When a current exceeding the threshold is detected, the fault detection and isolation module transmits the signal to the isolation circuit through a high-speed optocoupler, triggers the solid-state relay to cut off the power supply, and encapsulates the fault information into a data packet through the communication interface circuit RS-485 and transmits it to the telemetry module; the fault detection and isolation module includes a current detection unit, a signal processing unit, an isolation execution unit, and a communication unit; the current detection unit outputs a voltage signal proportional to the current through a Rogowski coil and adjusts the gain and offset of the current transformer through a self-calibration circuit; the self-calibration circuit periodically generates a known current signal as a reference, compares the reference signal and the output signal of the current transformer, and detects and adjusts the gain and offset of the current transformer; the signal processing unit identifies the fault characteristic signal parameters through fast Fourier transform and wavelet transform; the fault characteristic signal parameters include harmonic distortion rate, amplitude mutation amount, and phase jump parameter; once a fault signal is detected, the isolation execution unit cuts off the connection between the fault circuit and the main system through a silicon-controlled rectifier, and after the isolation operation is completed, transmits the fault information to the telemetry module through the communication unit.

[0033] As a further technical solution of the present invention, the ground current control module limits the ground current through a self-resetting fuse PPTC, and adjusts the current limiting value through a current feedback loop; the current feedback loop includes a current sensor, a comparator, a control logic unit and a drive circuit; the current sensor is used to capture the current signal in the ground line in real time and convert the current signal into an electrical signal; the comparator is used to compare the detected current value with a preset safety threshold to determine whether it is necessary to adjust the ground current. If adjustment is required, the control logic unit generates an adjustment control signal through an adaptive PID controller based on the deviation between the current ground current and the target current, and adjusts the working state of the self-resetting fuse PPTC through the drive circuit.

[0034] The beneficial effects of the present invention are as follows:

[0035] 1. The present invention monitors the ground resistance and environmental factors (such as soil humidity and temperature) in real time through a real-time monitoring module and an adaptive ground resistance adjustment module, and transmits the data to the adaptive ground resistance adjustment module. The adaptive ground resistance adjustment module dynamically adjusts the ground resistance according to these data. By connecting multiple sections of controllable resistors in series with the ground path and combining with an environmental compensation model, the resistance value is automatically adjusted to ensure that the ground resistance remains stable under different environmental conditions. The problem that the ground resistance fluctuates with the environment is solved, and the adaptability and reliability of the system are improved.

[0036] 2. The present invention detects and quickly responds to arc re-ignition through a high-frequency transient suppression module, and effectively suppresses the generation of overvoltage through a fast cut-off and recovery circuit. Protect the insulation level of the equipment, reduce the equipment cost and manufacturing difficulty, extend the service life of the equipment, and reduce the operation and maintenance cost. The problem of overvoltage caused by arc re-ignition is solved, and the safety and stability of the system are improved.

[0037] 3. The present invention uses a fault detection and isolation module to monitor the ground current in real time. Once a single-phase ground fault is detected, the isolation mechanism is immediately activated to quickly cut off the fault circuit. Prevent the further spread of the fault and protect other normally operating circuits. The problem of untimely fault detection and isolation is solved, and the reliability and safety of the system are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings, where:

[0039] Figure 1This is the overall architecture diagram of the grounding system of a high-voltage switchgear according to the present invention;

[0040] Figure 2 This is the workflow framework diagram of the grounding system of a high-voltage switchgear according to the present invention;

[0041] Figure 3 This is the workflow framework diagram of the high-frequency transient suppression module according to the present invention;

[0042] Figure 4 This is the working flowchart of the resistance compensation value mapping model according to the present invention;

[0043] Figure 5 This is the workflow framework diagram of the fault detection and isolation module according to the present invention. Specific embodiments

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] As Figures 1 - 5 shown, a grounding system of a high-voltage switchgear includes;

[0046] A real-time detection module for real-time monitoring of changes in the grounding resistance and environmental factors beside the grounding system, and outputting the grounding resistance change value and environmental factors to the adaptive grounding resistance adjustment module and the telemetry module; the environmental factors include soil humidity and temperature; the real-time detection module monitors the grounding resistance in real time through a grounding resistance detection unit; the grounding resistance detection unit supplies power to the grounding resistance through a constant current source circuit configured by an operational amplifier and an LDO voltage regulator, and detects the voltage drop across the grounding resistance through a differential amplifier, and the voltage signal is converted into a digital signal through an analog-to-digital converter; the constant current source circuit ensures that the current remains constant throughout the detection process through a negative feedback mechanism, eliminating the error of power supply fluctuations; the differential amplifier consists of two symmetric operational amplifiers, respectively detecting the voltages at both ends of the grounding resistance, and eliminating noise interference through differential output; the grounding resistance detection module also sends the calculated grounding resistance change value to the adaptive grounding resistance adjustment module and the telemetry module through the serial communication protocol SPI.

[0047] In specific implementations, an operational amplifier is used to provide high gain and low output impedance, and an LDO voltage regulator is used to provide a stable power supply voltage. The constant current source circuit ensures that the current remains constant throughout the detection process through a negative feedback mechanism, eliminating errors caused by power supply fluctuations. The inverting input terminal of the operational amplifier is connected to a reference voltage source, and the non-inverting input terminal is connected to one end of a grounded resistor. The LDO voltage regulator provides a stable power supply voltage, ensuring the stable operation of the circuit under different environmental conditions. The negative feedback mechanism forms a feedback loop through a resistor and a grounded resistor, keeping the output current constant. The constant current source circuit ensures the stability of the current during the detection process, eliminates the influence of power supply fluctuations on the measurement results, and improves the accuracy and reliability of the measurement.

[0048] The differential amplifier consists of two symmetrical operational amplifiers, which respectively detect the voltages across the grounding resistor and eliminate noise interference through differential output. The differential amplifier can amplify the difference between two input signals while suppressing common-mode noise. The two symmetrical operational amplifiers are respectively connected to both ends of the grounding resistor, and the output signals are connected to the analog-to-digital converter through the differential output terminals. The input terminals of the differential amplifier are matched by precision resistors to ensure the balance of the two input signals, thus effectively eliminating noise interference. The differential amplifier improves the signal-to-noise ratio of the signal, ensures the measurement accuracy in a complex electromagnetic environment, and reduces the influence of external interference on the measurement results. The analog-to-digital converter ADC converts the analog signal into a digital signal through the sampling and quantization processes. The sampling process discretizes the continuous analog signal, and the quantization process converts the discrete analog signal into a digital code. The resolution of the ADC determines the accuracy of the converted digital signal. Finally, the grounding resistor detection module sends the calculated change value of the grounding resistor to the adaptive grounding resistor adjustment module and the telemetry module through the SPI interface. The master device sends the clock signal through the SCLK line, sends data through the MOSI line, receives data through the MISO line, and the SS line controls the selection of the slave device. In the actual working state, the working process of the grounding resistor detection unit is as follows: The constant current source circuit and the differential amplifier are initialized to ensure that the circuit is in a stable state. The LDO voltage regulator provides a stable power supply voltage, the operational amplifier enters the working state, and the input terminals of the differential amplifier are matched by precision resistors to ensure the balance of the two input signals. The constant current source circuit provides a constant current for the grounding resistor, and the differential amplifier detects the voltage drop across the grounding resistor. The differential amplifier transmits the voltage signal to the analog-to-digital converter through the differential output terminal. The analog-to-digital converter converts the analog voltage signal into a digital signal and calculates the value of the grounding resistor through internal calculation. The grounding resistor detection module sends the calculated change value of the grounding resistor to the adaptive grounding resistor adjustment module and the telemetry module through the SPI interface. The master device sends the clock signal through the SCLK line, sends data through the MOSI line, receives data through the MISO line, and the SS line controls the selection of the slave device. During the data transmission process, the system monitors the change of the grounding resistor in real time and transmits the data to the central processing unit for further processing and analysis. The central processing unit dynamically adjusts the grounding resistor through the adaptive grounding resistor adjustment module according to the received change value of the grounding resistor. The adaptive grounding resistor adjustment module automatically adjusts the resistance value by connecting multiple sections of controllable resistors in series with the grounding path and combining the environmental compensation model to ensure that the grounding resistor remains stable under different environmental conditions.

[0049] Compared with the same type of hardware, the constant current source circuit ensures that the current remains constant throughout the detection process through a negative feedback mechanism, eliminating the error caused by power supply fluctuations. The differential amplifier eliminates noise interference through differential output, improving the signal-to-noise ratio of the signal. These designs ensure the high precision and stability of the ground resistance detection. The symmetric design and differential output mode of the differential amplifier effectively eliminate common-mode noise and improve the anti-interference ability of the system. In a complex electromagnetic environment, the system can still maintain high-precision measurement results. Through the SPI protocol, the ground resistance detection module can transmit data to the adaptive ground resistance adjustment module and the telemetry module at high speed and reliably. The full-duplex communication mode of the SPI protocol simplifies the data transmission process and improves the communication efficiency and reliability of the system. In addition, the LDO voltage regulator provides a stable power supply voltage to ensure the stable operation of the circuit under different environmental conditions. The low-power design extends the service life of the system and improves the reliability of the system. The high-gain and low-output impedance characteristics of the operational amplifier and the differential amplifier further improve the performance of the system. Among them, the parameters of the operational amplifier are: bandwidth: 10 MHz, input bias current: 1 pA, power supply voltage range: 2.7V to 36V; the parameters of the LDO voltage regulator are: output voltage: 3.3V, maximum output current: 800 mA, quiescent current: 5 μA; the parameters of the differential amplifier are: gain range: 1 to 10000, bandwidth: 1 MHz, power supply voltage range: 2.7V to 36V; the parameters of the analog-to-digital converter are: resolution: 16 bits, sampling rate: 860 SPS, power supply voltage range: 2.0V to 5.5V; the clock frequency of the serial communication protocol SPI1 is 10 MHz, and the data transmission rate is 10 Mbps.

[0050] An adaptive grounding resistance adjustment module is used to dynamically adjust the grounding resistance according to the change value of the grounding resistance and environmental factors; the adaptive grounding resistance adjustment module connects multiple sections of controllable resistors in series with the grounding path, and the adaptive grounding resistance adjustment module constructs a resistance compensation value mapping model based on the environmental sensitive period index and the cross-correlation coefficient, and controls the resistance value through a dynamic resistance value control algorithm; the resistance compensation value mapping model includes an environmental factor quantization unit, a resistance influence analysis unit, a compensation value calculation unit and an output feedback unit; the adaptive grounding resistance adjustment module receives and processes the digital signal of the grounding resistance detection module through a microcontroller, and the microcontroller processes the digital signal output by the grounding resistance detection module through a FIR filter and a moving average filter, and calculates the change value of the grounding resistance by the least square method; according to the calculated change value of the grounding resistance, the adaptive grounding resistance adjustment module then realizes the amplification of the PWM signal and the drive of the controllable resistor array through a PWM drive circuit; the controllable resistor array is composed of multiple controllable resistor units, each controllable resistor unit is connected in series in the grounding path, and the on-state of each controllable resistor unit is controlled and adjusted through a PWM signal to realize the dynamic adjustment of the grounding resistance value; the adaptive grounding resistance adjustment module also realizes the real-time monitoring of the change value of the grounding resistance through a closed-loop feedback circuit, and performs real-time feedback adjustment on the change value of the grounding resistance through a dynamic resistance value control algorithm.

[0051] In specific implementation, the microcontroller receives the digital signal from the ground resistance detection module through the SPI or I2C interface. The internally integrated FIR filter and moving average filter preprocess the received digital signal to remove noise and interference. Subsequently, the change value of the ground resistance is calculated by the least squares method. The FIR filter is a digital filter that realizes signal filtering by performing convolution operations on the input signal. The FIR filter performs weighted summation on the input signal through a set of predefined coefficients to filter out high-frequency noise and interference. The FIR filter has a linear phase characteristic and can maintain the integrity of the signal. The moving average filtering smooths the signal fluctuations by averaging the data within a certain window. The moving average filter averages the data within a fixed-length window. Each time new data arrives, the data within the window is updated and the new average value is calculated. The moving average filtering can smooth the short-term fluctuations of the signal, improve the signal stability, and reduce the influence of instantaneous interference. The least squares method is a mathematical optimization method that fits the best linear relationship by minimizing the sum of the squares of the errors. The least squares method fits a straight line by fitting a series of data points, making the sum of the squares of the distances from all data points to this straight line the smallest. In this module, the least squares method is used to calculate the change value of the ground resistance. The PWM drive circuit controls the amplitude of the signal by changing the pulse width to drive the controllable resistance array. The PWM drive circuit generates a PWM signal through the microcontroller, which is amplified by a power amplifier and then drives the controllable resistance array. The on-state of each controllable resistance unit is controlled by the PWM signal. By changing the duty cycle of the PWM signal, the on-time of each controllable resistance unit is adjusted, thereby realizing the dynamic adjustment of the ground resistance. The PWM drive circuit can accurately control the on-state of each controllable resistance unit to achieve high-precision and real-time adjustment of the ground resistance. The controllable resistance array consists of multiple controllable resistance units. Each controllable resistance unit is connected in series in the grounding path. By controlling and adjusting the on-state of each controllable resistance unit through the PWM signal, the dynamic adjustment of the ground resistance value is realized. Each controllable resistance unit consists of a fixed resistor and a controllable switch (such as a MOSFET). The PWM signal adjusts the equivalent resistance value of the resistance unit by controlling the on and off of the switch. Multiple resistance units are connected in series to form an adjustable resistance array. The controllable resistance array can achieve high-precision and highly flexible resistance adjustment to ensure the stability of the ground resistance under different environmental conditions. The closed-loop feedback circuit is used to monitor the change value of the ground resistance in real time and perform real-time feedback adjustment on the change value of the ground resistance through the dynamic resistance value control algorithm. The closed-loop feedback circuit monitors the change value of the ground resistance in real time through a feedback sensor and feeds the monitored value back to the microcontroller. The microcontroller adjusts the duty cycle of the PWM signal through the dynamic resistance value control algorithm to achieve real-time adjustment of the ground resistance.The closed-loop feedback circuit can monitor and adjust the grounding resistance in real time, ensuring the stability and reliability of the system, and improving the response speed and control accuracy of the system.

[0052] Under the actual working conditions, the working process of the adaptive grounding resistance adjustment module is as follows: The microcontroller continuously receives and processes the digital signals of the grounding resistance detection module, and the FIR filter and the moving average filter continuously perform signal preprocessing. The PWM drive circuit and the controllable resistance array adjust the conduction state of each controllable resistance unit according to the PWM signal generated by the microcontroller to keep the grounding resistance stable. The closed-loop feedback circuit monitors the change value of the grounding resistance in real time to ensure the stability and reliability of the system. When the microcontroller detects that the change value of the grounding resistance exceeds the preset range, it adjusts the duty cycle of the PWM signal through the dynamic resistance value control algorithm to drive the controllable resistance array to adjust the grounding resistance. The closed-loop feedback circuit monitors the adjusted grounding resistance value in real time to ensure that the adjusted resistance value meets the expectations. At this time, the system enters the resistance adjustment and feedback state to ensure the real-time adjustment and stability of the grounding resistance. Under different environmental conditions, the microcontroller adjusts the grounding resistance in real time according to the change of environmental factors through the dynamic resistance value control algorithm. The closed-loop feedback circuit ensures the self-adaptability and stability of the system, and improves the adaptability and reliability of the system. The system enters the environmental adaptation and self-adaptive adjustment state to ensure the stability of the grounding resistance under different environmental conditions.

[0053] Compared with the same type of hardware, the present invention removes noise and interference through the FIR filter and the moving average filter to ensure the high precision and stability of the signal. The least squares method can accurately calculate the change value of the grounding resistance, improving the precision and reliability of the system. In addition, the PWM drive circuit can accurately control the conduction state of each controllable resistance unit to achieve the high-precision and real-time adjustment of the grounding resistance. The closed-loop feedback circuit ensures the fast response and high sensitivity of the system, improving the control precision and response speed of the system. Secondly, through the dynamic resistance value control algorithm, the system can adjust the grounding resistance in real time according to the change of environmental factors to ensure the self-adaptability and environmental adaptability of the system. The closed-loop feedback circuit ensures the stability and reliability of the system, improving the adaptability and reliability of the system. At the same time, through the cooperation with the telemetry module, the operation and maintenance personnel can monitor the state of the grounding resistance in real time through the remote terminal, take maintenance measures in time, reduce the fault response time, and improve the reliability and safety of the system.

[0054] Furthermore, the environmental factor quantification unit establishes a mathematical model between environmental parameters and quantification indicators through a statistical quantification method. The statistical quantification method describes the mapping relationship between environmental parameters and quantification indicators through a non-linear model, and minimizes the difference between the predicted value and the actual value through regression analysis to solve the model parameters. The resistance impact analysis unit fits the non-linear mapping between environmental parameters and resistance changes through a support vector machine and a neural network. The support vector machine uses a kernel function to map the input data into a high-dimensional space and finds the optimal hyperplane to maximize the classification margin. The neural network realizes the approximation and prediction of complex functions through a multi-layer network structure and a backpropagation algorithm. Based on the results of the resistance impact analysis, the compensation value calculation unit dynamically calculates and outputs the resistance compensation value using Gaussian process regression and the gradient descent method. The Gaussian process regression is based on the prior assumption of a Gaussian process, describes the correlation between input variables through a kernel function, and calculates the predicted value using Bayesian inference. The gradient descent method is used to fine-tune the compensation value considering the requirements of system stability and real-time performance. The output feedback unit transmits the calculated resistance compensation value to the adaptive grounding resistance adjustment module in real time through a communication protocol and an API interface, and receives the system status feedback. The output end of the environmental factor quantification unit is connected to the input end of the resistance impact analysis unit. The output end of the resistance impact analysis unit is connected to the input end of the compensation value calculation unit. The output end of the compensation value calculation unit is connected to the input end of the output feedback unit.

[0055] In the grounding system of high-voltage switchgear, the environmental factor quantification unit establishes a mathematical model between environmental parameters and quantification indexes through statistical quantification methods. The statistical quantification method describes the mapping relationship between environmental parameters (such as temperature, humidity, current, voltage, etc.) and quantification indexes through a non-linear model, and minimizes the difference between the predicted value and the actual value through regression analysis to solve the model parameters. The resistance influence analysis unit fits the non-linear mapping between environmental parameters and resistance changes through support vector machine (SVM) and neural network. SVM uses a kernel function to map input data to a high-dimensional space and finds the optimal hyperplane to maximize the classification margin. Commonly used kernel functions include linear kernel, polynomial kernel and Gaussian kernel. The neural network realizes the approximation and prediction of complex functions through a multi-layer network structure and backpropagation algorithm. The neural network includes an input layer, a hidden layer and an output layer, and adjusts the weights through the backpropagation algorithm to minimize the loss function. The resistance influence analysis unit can accurately fit the non-linear relationship between environmental parameters and resistance changes, providing a reliable basis for the calculation of compensation values. The compensation value calculation unit dynamically calculates and outputs the resistance compensation value by using Gaussian process regression (GPR) and gradient descent method. GPR is based on the prior assumption of Gaussian process, describes the correlation between input variables through a kernel function, and calculates the predicted value using Bayesian inference. Commonly used kernel functions include squared exponential kernel and Matern kernel. The gradient descent method is used to fine-tune the compensation value considering the requirements of system stability and real-time performance. By iteratively updating the weights, the loss function is minimized. The compensation value calculation unit can dynamically calculate and output the resistance compensation value to ensure the stability of the grounding resistance under different environmental conditions. The output feedback unit transmits the calculated resistance compensation value to the adaptive grounding resistance adjustment module in real time through a communication protocol and API interface, and receives the system status feedback. The output feedback unit exchanges data with the adaptive grounding resistance adjustment module through a standard communication protocol (such as Modbus or CAN) and API interface to ensure the real-time transmission and feedback of data. The output feedback unit can realize real-time data transmission and system status feedback to ensure the stability and reliability of the system.

[0056] Under actual working conditions, such as Figure 4As shown in the figure, the working process of the resistance compensation value mapping model is as follows: Environmental factor quantification: Use statistical quantification methods to establish a mathematical model between environmental parameters and quantification indicators. Then, minimize the difference between the predicted value and the actual value through regression analysis to solve the model parameters. Next, use support vector machines and neural networks to fit the non-linear mapping between environmental parameters and resistance changes. Based on the results of the resistance impact analysis, use Gaussian process regression and gradient descent methods to dynamically calculate the resistance compensation value. Finally, transmit the calculated resistance compensation value to the adaptive grounding resistance adjustment module in real time and receive the system status feedback. Specifically, first, the environmental factor quantification unit continuously collects environmental parameters, establishes a mathematical model between environmental parameters and quantification indicators through statistical quantification methods, and outputs the quantification indicators. The resistance impact analysis unit fits the non-linear mapping between environmental parameters and resistance changes through support vector machines and neural networks and outputs the fitting results. The compensation value calculation unit dynamically calculates and outputs the resistance compensation value using Gaussian process regression and gradient descent methods to ensure the stability of the grounding resistance. The output feedback unit transmits the resistance compensation value to the adaptive grounding resistance adjustment module in real time through communication protocols and API interfaces and receives the system status feedback to ensure the stability and reliability of the system. When the environmental parameters change, the environmental factor quantification unit updates the quantification indicators in real time, the resistance impact analysis unit refits the non-linear mapping between environmental parameters and resistance changes, the compensation value calculation unit recalculates the resistance compensation value, and the output feedback unit transmits the new resistance compensation value in real time to ensure the real-time adjustment of the grounding resistance. The system enters the environmental change and adjustment state to ensure the stability of the grounding resistance under different environmental conditions. When the system detects a fault, the environmental factor quantification unit incorporates the fault type code into the quantification indicators, the resistance impact analysis unit refits the non-linear mapping between environmental parameters and resistance changes, the compensation value calculation unit recalculates the resistance compensation value, and the output feedback unit transmits the new resistance compensation value in real time to ensure the real-time adjustment of the grounding resistance. The system enters the fault detection and response state to ensure the stability of the grounding resistance in case of a fault.

[0057] Compared with the same type of hardware, through statistical quantization methods and non-linear models, the environmental factor quantization unit of the present invention can convert complex environmental parameters into easily processed quantization indicators, providing accurate data support for subsequent resistance impact analysis. Through support vector machines and neural networks, the resistance impact analysis unit can accurately fit the non-linear relationship between environmental parameters and resistance changes, providing a reliable basis for compensation value calculation. Through Gaussian process regression and gradient descent methods, the compensation value calculation unit can dynamically calculate and output the resistance compensation value, ensuring the stability of the grounding resistance under different environmental conditions. Secondly, through real-time data transmission and system status feedback, the output feedback unit can ensure the fast response and high sensitivity of the system. Through Gaussian process regression and gradient descent methods, the compensation value calculation unit can adjust the resistance compensation value in real time, ensuring the fast response and high sensitivity of the system. Through the environmental factor quantization unit and the resistance impact analysis unit, the system can comprehensively consider various environmental factors and system parameters, ensuring the stability of the grounding resistance under different environmental conditions. Through the compensation value calculation unit and the output feedback unit, the system can adjust the resistance compensation value in real time, ensuring the self-adaptability and environmental adaptability of the system. At the same time, through standard communication protocols and API interfaces, the output feedback unit can achieve real-time data transmission and system status feedback, ensuring the efficient communication and remote monitoring of the system. Operation and maintenance personnel can monitor the status of the grounding resistance in real time through a remote terminal, take maintenance measures in a timely manner, reduce the fault response time, and improve the reliability and safety of the system.

[0058] In a specific embodiment, the hardware operating environment of the resistance compensation value mapping model in the grounding system of a high-voltage switchgear needs to meet the following requirements: The operating temperature range should be from -20°C to 70°C to adapt to different environmental conditions. The storage temperature range should be from -40°C to 85°C to ensure the storage safety of the device under extreme temperatures. The relative humidity should be between 10% and 90% without condensation to prevent device damage caused by excessive humidity. The input voltage range should be 220V ± 10%, and the frequency should be 50 / 60Hz to ensure stable power supply. The power supply fluctuation should not exceed ±5% to avoid system failures caused by unstable power supplies. The device should comply with the EMC (Electromagnetic Compatibility) standard to ensure normal operation in an electromagnetic environment without interference. The device should be able to withstand vibrations with a frequency of 10Hz to 500Hz and an amplitude of 0.075mm to ensure stable operation in an industrial environment. The experimental equipment includes a high-voltage switchgear model HSK-1000; a microcontroller: model STM32F407; environmental sensors: a temperature sensor DS18B20, a humidity sensor DHT22, a current sensor LEM LAH 50-P, a voltage sensor ACS712; a controllable resistor array: 10 controllable resistor units, each unit consisting of a MOSFET (IRF540N) and a 10Ω fixed resistor; a PWM drive circuit: a power amplifier LM2902, a switching circuit IRF540N; a data acquisition system: an NI LabVIEW data acquisition card; the experimental platform is the Windows 10 operating system, MATLAB R2021a;

[0059] Based on the above hardware operating environment, under the same environmental conditions, the experimental group and the control group are tested separately. The experimental group uses the resistance compensation value mapping model to dynamically adjust the grounding resistance. The control group uses the traditional fixed resistor adjustment method without dynamic adjustment. Environmental parameters (temperature, humidity, current, voltage) and grounding resistance values are collected. And the grounding resistance values and system stability of each group under different environmental conditions are recorded; The experimental data are recorded as shown in Table 1:

[0060] Table 1 Comparison Table of Experimental Data

[0061]

[0062] As can be seen from Data Table 2, in the experimental group, under different environmental conditions, the error of the grounding resistance always remained within 0.2 Ω, while the error of the control group gradually increased and reached a maximum of 2.2 Ω. This indicates that the resistance compensation value mapping model can significantly improve the accuracy of the grounding resistance. Additionally, the system stability score of the experimental group always remained above 8.6, while the system stability score of the control group gradually decreased and dropped to a minimum of 1.0. This indicates that the resistance compensation value mapping model can significantly improve the system stability. Secondly, the experimental group could maintain good performance under different environmental conditions, while the performance of the control group significantly decreased when the environment changed greatly. This indicates that the resistance compensation value mapping model has strong environmental adaptability.

[0063] A high-frequency transient suppression module for suppressing high-frequency transient overvoltage caused by arc re-ignition; the high-frequency transient suppression module connects a transient voltage suppression diode in parallel on the grounding path, and when overvoltage occurs, the transient voltage suppression diode conducts; the high-frequency transient suppression module includes a detection and response unit, an energy absorption unit, and a filtering and stabilization unit; the detection and response unit uses a high-bandwidth analog front end and fast Fourier transform to monitor the voltage waveform of the power system in real time. Once high-frequency transients are detected, it switches the conduction state of the transient voltage suppression diode to direct the transient current to a preset safe path. The detection and response unit also provides immediate voltage clamping through a metal oxide varistor; when high-frequency transients occur, the energy absorption unit stores energy through a capacitor bank and converts the stored electrical energy into heat energy through a positive temperature coefficient thermistor and dissipates it into the environment; the energy absorption unit also releases the stored energy through a gas discharge tube; the filtering and stabilization unit connects a multi-stage LC filter network in parallel in the circuit, and the multi-stage LC filter network filters out redundant frequency components through a surface acoustic wave filter; the filtering and stabilization unit also optimizes the energy release process through an adaptive tuning mechanism; the adaptive tuning mechanism evaluates the fitness of the cut-off frequency and bandwidth through a particle swarm optimization algorithm to tune the value of the objective function; during the parameter adjustment process, the adaptive tuning mechanism also simulates the response of the filter to the transient voltage waveform through finite element analysis to evaluate the energy absorption and release effects.

[0064] In a specific implementation, a transient voltage suppression diode (TVS) is a fast-response semiconductor device that can quickly conduct when an overvoltage is detected, directing the transient current to a preset safe path to protect the circuit from damage caused by overvoltage. The TVS diode is connected in parallel to the ground path. When an overvoltage is detected, the TVS diode quickly conducts, directing the transient current to the ground wire, thereby clamping the voltage within a safe range. The TVS diode has a low clamping voltage and a high response speed, and can conduct within a few nanoseconds. The detection and response unit uses a high-bandwidth analog front end and fast Fourier transform (FFT) to monitor the voltage waveform of the power system in real time. Once a high-frequency transient is detected, the conduction state of the TVS diode is immediately switched. Specifically, the high-bandwidth analog front end can capture high-frequency transient signals, and the fast Fourier transform algorithm performs frequency-domain analysis on the captured signals to identify transient components. The detection and response unit controls the conduction state of the TVS diode through a high-speed comparator and a drive circuit. A metal oxide varistor (MOV) provides immediate voltage clamping to further enhance the protection effect. The detection and response unit can monitor and respond to transient overvoltages in real time, ensuring that the TVS diode conducts in the shortest possible time to protect the circuit from damage caused by overvoltage. The energy absorption unit stores energy through a capacitor bank and converts the stored electrical energy into heat energy and dissipates it into the environment through a positive temperature coefficient thermistor (PTC). In addition, the energy absorption unit also releases the stored energy through a gas discharge tube (GDT). The capacitor bank is connected in parallel to the circuit and is used to absorb transient energy. The PTC thermistor has an increased resistance at high temperatures, converting the stored electrical energy into heat energy and dissipating it into the environment. The GDT breaks down at high voltages and releases the stored energy. These components work together to ensure the effective absorption and release of energy. The energy absorption unit can effectively absorb and release transient energy, protect the circuit from the impact of overvoltage, and extend the service life of the equipment. The filtering and stabilization unit connects a multi-stage LC filtering network in parallel to the circuit and filters out redundant frequency components through a surface acoustic wave filter (SAW). The filtering and stabilization unit also optimizes the energy release process through an adaptive tuning mechanism. The multi-stage LC filtering network is used to filter out high-frequency noise, and the SAW filter is used to further filter out redundant frequency components. The adaptive tuning mechanism evaluates the fitness of the cut-off frequency and bandwidth through the particle swarm optimization algorithm (PSO) and tunes the value of the objective function. Finite element analysis (FEA) simulates the response of the filter to the transient voltage waveform and evaluates the energy absorption and release effects. The filtering and stabilization unit can effectively filter out high-frequency noise and optimize the energy release process.

[0065] In actual operation, the working mode of the high-frequency transient suppression module is as follows: Figure 3As shown: The high-frequency transient suppression module first uses a high-bandwidth analog front-end and fast Fourier transform (FFT) to monitor the voltage waveform of the power system in real time. Once a high-frequency transient is detected, by switching the conduction state of the transient voltage suppression diode, the transient current is directed to a safe path, and a metal oxide varistor is used for voltage clamping. When a high-frequency transient occurs, energy is stored by a capacitor bank, and the electrical energy is converted into heat energy and dissipated through a positive temperature coefficient thermistor, or the energy is released through a gas discharge tube. A multistage LC filter network and a surface acoustic wave filter are connected in parallel in the circuit to filter out redundant frequency components. Finally, the particle swarm optimization algorithm is used to evaluate the fitness of the filter parameters (cutoff frequency and bandwidth), and finite element analysis is used to simulate the response of the filter to the transient voltage waveform to optimize the energy release process. Specifically, first, the detection response unit is initialized, and the high-bandwidth analog front-end starts to monitor the voltage waveform of the power system. The TVS diode and MOV are in a standby state, ready to respond to transient overvoltage. The capacitor bank and PTC thermistor of the energy absorption unit are in a charging state, and the GDT is in a non-breakdown state. The multistage LC filter network and SAW filter of the filter stabilization unit are in a working state, and the adaptive tuning mechanism is initialized. Then, the detection response unit monitors the voltage waveform in real time through the high-bandwidth analog front-end. Once a high-frequency transient is detected, the fast Fourier transform algorithm performs a frequency-domain analysis on the captured signal to identify the transient components. The high-speed comparator and drive circuit immediately switch the conduction state of the TVS diode to direct the transient current to the ground wire. The MOV provides immediate voltage clamping to further enhance the protection effect. The capacitor bank of the energy absorption unit absorbs the transient energy, and the PTC thermistor converts the stored electrical energy into heat energy and dissipates it into the environment. The GDT breaks down under high voltage to release the stored energy. These components work together to ensure the effective absorption and release of energy, protecting the circuit from overvoltage shocks. Finally, the multistage LC filter network and SAW filter of the filter stabilization unit filter out high-frequency noise to optimize the signal quality. The adaptive tuning mechanism evaluates the fitness of the cutoff frequency and bandwidth through the particle swarm optimization algorithm and tunes the value of the objective function. Finite element analysis simulates the response of the filter to the transient voltage waveform to evaluate the energy absorption and release effects.

[0066] Compared with the same type of hardware, the detection and response unit adopts a high-bandwidth analog front end and fast Fourier transform, which can monitor and respond to transient overvoltages in real time, ensure that the TVS diode conducts in the shortest time, and protect the circuit from overvoltage damage. The MOV provides instant voltage clamping to further enhance the protection effect. The energy absorption unit effectively absorbs and releases transient energy through the cooperation of capacitor banks, PTC thermistors, and GDTs, protects the circuit from the impact of overvoltage, and extends the service life of the equipment. These components work together to ensure the effective management and release of energy. In addition, the filtering and stabilization unit adopts a multi-stage LC filtering network and SAW filters to effectively filter out high-frequency noise and optimize the signal quality. The adaptive tuning mechanism evaluates the fitness of the cut-off frequency and bandwidth through the particle swarm optimization algorithm and tunes the value of the objective function. Finite element analysis simulates the response of the filter to the transient voltage waveform, evaluates the energy absorption and release effects, and ensures the stability and reliability of the system. Through efficient energy management and filtering technologies, the system can maintain high reliability in a complex electromagnetic environment. The adaptive tuning mechanism ensures the continuous optimization of the system, reduces maintenance costs, and extends the service life of the equipment. Among them, the parameters of the transient voltage suppression diode (TVS): maximum clamping voltage: 220V, maximum peak pulse power: 600W, response time: 1ns; parameters of the metal oxide varistor (MOV): rated voltage: 220V, maximum energy absorption: 20J, response time: 25ns; parameters of the capacitor bank: capacitance value: 10 μF, withstand voltage: 500V, temperature range: -55°C to +125°C; parameters of the positive temperature coefficient thermistor (PTC): rated voltage: 200V, rated current: 1A, temperature range: -40°C to +125°C; parameters of the gas discharge tube (GDT): rated voltage: 220V, maximum discharge current: 10kA, response time: 1μs; parameters of the surface acoustic wave filter (SAW): center frequency: 2.5GHz, bandwidth: 100MHz, insertion loss: 3dB; parameters of the multi-stage LC filtering network: cut-off frequency: 500kHz, bandwidth: 100kHz, insertion loss: 1dB.

[0067] The fault detection and isolation module is used to detect the ground current, isolate the faulty circuit, and transmit the fault signal to the telemetry module; the fault detection and isolation module monitors the ground current through a current transformer. When a current exceeding the threshold is detected, the fault detection and isolation module transmits the signal to the isolation circuit through a high-speed optocoupler, triggers the solid-state relay to cut off the power supply, and encapsulates the fault information into a data packet through the communication interface circuit RS-485 and transmits it to the telemetry module; the fault detection and isolation module includes a current detection unit, a signal processing unit, an isolation execution unit, and a communication unit; the current detection unit outputs a voltage signal proportional to the current through a Rogowski coil and adjusts the gain and offset of the transformer through a self-calibration circuit; the self-calibration circuit periodically generates a known current signal as a reference, compares the reference signal with the output signal of the transformer, and detects and adjusts the gain and offset of the transformer; the signal processing unit identifies the fault characteristic signal parameters through fast Fourier transform and wavelet transform; the fault characteristic signal parameters include harmonic distortion rate, amplitude mutation amount, and phase jump parameter; once a fault signal is detected, the isolation execution unit cuts off the connection between the faulty circuit and the main system through a silicon-controlled rectifier. After the isolation operation is completed, the fault information is transmitted to the telemetry module through the communication unit.

[0068] In a specific implementation, the self-calibration circuit periodically generates a known current signal as a reference, compares the reference signal with the output signal of the transformer, and detects and adjusts the gain and offset of the transformer. The self-calibration circuit includes a reference signal generator, a comparator, and an adjustment circuit. The signal processing unit identifies the fault characteristic signal parameters through fast Fourier transform (FFT) and wavelet transform (Wavelet Transform), including harmonic distortion rate, amplitude mutation amount, and phase jump parameter. The FFT algorithm converts the time-domain signal into a frequency-domain signal and identifies the harmonic components in the signal. The wavelet transform, through multi-resolution analysis, identifies the mutation and transient components in the signal. The signal processing unit implements these algorithms through a high-speed processor (such as DSP or FPGA) to ensure real-time processing and analysis. FFT and wavelet transform can accurately identify the fault characteristic signal, improve the accuracy and sensitivity of fault detection, ensure the detection of faults at an early stage, and reduce the damage of faults to the system. When the signal processing unit detects a fault signal, the isolation execution unit transmits the signal to the solid-state relay (SSR) through a high-speed optocoupler, triggering the SCR to cut off the power supply. The combination of SCR and SSR ensures the rapid isolation of the faulty circuit, protects the main system from the impact of faults, and improves the safety and reliability of the system. The communication unit includes an RS-485 transceiver and a communication protocol processor.

[0069] Under the actual working conditions, such as Figure 5As shown in the figure, the working process of the fault detection and isolation module is as follows: First, the grounding current is monitored through a current transformer. When the current exceeds the preset threshold, it is judged as a fault. Then, the fault signal is transmitted to the isolation circuit through a high-speed optocoupler. The solid-state relay is triggered to cut off the power supply. And the fault information is encapsulated into a data packet through the communication interface circuit. Finally, the fault information data packet is transmitted to the telemetry module through RS-485. Specifically, the current detection unit is initialized, and the Rogowski coil starts to detect the grounding current. The self-calibration circuit generates a reference signal to adjust the gain and offset of the transformer. The signal processing unit is initialized to prepare for signal processing. The isolation execution unit and the communication unit are initialized to prepare for responding to the fault signal. The current detection unit outputs a voltage signal proportional to the current through the Rogowski coil, and the self-calibration circuit regularly generates a reference signal to adjust the gain and offset of the transformer. The signal processing unit analyzes the voltage signal in real time through FFT and wavelet transform algorithms to identify the fault characteristic signal parameters, including the harmonic distortion rate, the amplitude mutation amount, and the phase jump parameter. Once the signal processing unit detects a fault signal exceeding the threshold, the isolation execution unit transmits the signal to the solid-state relay through a high-speed optocoupler, triggering the SCR to cut off the connection between the fault circuit and the main system. After the isolation operation is completed, the communication unit encapsulates the fault information into a data packet through the RS-485 interface and transmits it to the telemetry module. The communication unit communicates with the telemetry module through the RS-485 interface to transmit the fault information to the remote monitoring center. The operation and maintenance personnel can view the fault information in real time through the remote terminal, take maintenance measures in a timely manner, reduce the fault response time, and improve the reliability and safety of the system.

[0070] Compared with the same type of hardware, the current detection unit adopts a Rogowski coil and a self-calibration circuit, ensuring high-precision and long-term stability of current detection. The self-calibration circuit adjusts the gain and offset of the current transformer by periodically generating a reference signal, improving the reliability of fault detection. The signal processing unit analyzes the voltage signal in real time through FFT and wavelet transform algorithms to identify the parameters of the fault characteristic signal. These algorithms can accurately identify the fault characteristics, improving the sensitivity and accuracy of fault detection. The isolation execution unit ensures the rapid isolation of the faulty circuit through a high-speed optocoupler and a solid-state relay, protecting the main system from the impact of faults. The communication unit encapsulates the fault information into data packets through the RS-485 interface and transmits it to the telemetry module. The RS-485 interface has the ability of long-distance transmission and multi-point communication, ensuring that the fault information can be transmitted to the remote monitoring center in time, facilitating remote monitoring and management by the operation and maintenance personnel. This not only improves the communication efficiency of the system but also reduces the operation and maintenance costs. In addition, through efficient fault detection and isolation technologies, the system can maintain high reliability in a complex electromagnetic environment. The optimized design of the self-calibration circuit and the communication unit ensures the long-term stability and reliability of the system, reduces the maintenance cost, and extends the service life of the equipment. Among them, the Rogowski coil adopts Rogowski-1000, parameters: coil diameter: 100 mm, frequency range: 10 Hz to 1 MHz, output voltage: 1 mV / A; in the self-calibration circuit, the parameters of the reference signal generator: temperature coefficient: 0.075% / °C, output current: 1 μA to 1 mA; the parameters of the comparator: operating voltage: 2 V to 36 V, response time: 1 μs; the signal processing unit adopts TMS320F28335, parameters: main frequency: 150 MHz, memory: 128 KB Flash, 32 KB RAM; the parameters of the solid-state relay (SSR): rated voltage: 240 VAC, rated current: 12 A, response time: 10 μs; the parameters of the silicon-controlled rectifier (SCR): rated voltage: 1200 V, rated current: 100 A, response time: 5 μs; the parameters of the high-speed optocoupler: operating voltage: 5 V, response time: 100 ns; the parameters of the RS-485 transceiver: operating voltage: 3.3 V to 5.5 V, data transmission rate: 2.5 Mbps; the parameters of the communication protocol processor: main frequency: 72 MHz, memory: 64 KB Flash, 20 KB RAM.

[0071] The ground current control module is used to control the ground current; the ground current control module limits the ground current through a self-resetting fuse PPTC and adjusts the current limiting value through a current feedback loop; the current feedback loop includes a current sensor, a comparator, a control logic unit and a drive circuit; the current sensor is used to capture the current signal in the ground line in real time and convert the current signal into an electrical signal; the comparator is used to compare the detected current value with a preset safety threshold to determine whether the ground current needs to be adjusted. If adjustment is required, the control logic unit generates an adjustment control signal through an adaptive PID controller based on the deviation between the current ground current and the target current, and adjusts the working state of the self-resetting fuse PPTC through the drive circuit;

[0072] In specific implementation, a self-resetting fuse (PPTC) is a positive temperature coefficient thermistor that can rapidly heat up when the current exceeds a predetermined value, increasing the resistance value to limit the current. When the current returns to normal, the PPTC will automatically reset and return to the low-resistance state. In practice, the PPTC is connected in parallel to the grounding path. When the current exceeds the predetermined value, the PPTC rapidly heats up, the resistance value increases, and the current is limited. When the current returns to normal, the PPTC cools down and the resistance value returns to the low-resistance state. The PPTC can respond rapidly during current overload, protecting the circuit from overcurrent damage. At the same time, it has a self-resetting function, eliminating the need to replace the fuse, improving the reliability and maintenance convenience of the system. In the current feedback loop, the current sensor continuously captures the current signal in the grounding line and converts the current signal into an electrical signal. The comparator compares the detected current value with a preset safety threshold to determine whether the grounding current needs to be adjusted. If adjustment is required, the control logic unit generates an adjustment control signal through an adaptive PID controller based on the deviation between the current grounding current and the target current, and adjusts the operating state of the PPTC through the drive circuit. The current feedback loop ensures precise control of the grounding current, improving the stability and safety of the system. Under actual operating conditions, the workflow of the grounding current control module is as follows: The current sensor continuously monitors the current signal in the grounding line, and the comparator compares the detected current value with the preset safety threshold. If the current value is within the safe range, the control logic unit and the drive circuit remain in a standby state, the PPTC is in a low-resistance state, and the grounding current flows normally. When the current sensor detects that the grounding current exceeds the preset safety threshold, the comparator outputs a high-level signal indicating that the grounding current needs to be adjusted. The control logic unit generates an adjustment control signal through an adaptive PID controller based on the deviation between the current grounding current and the target current. The drive circuit controls the operating state of the PPTC according to the generated adjustment control signal, and the PPTC rapidly heats up, increasing the resistance value to limit the current. At this time, the system enters the current overload response state to ensure rapid limitation of the grounding current and protect the circuit from overcurrent damage. When the current returns to normal, the PPTC cools down, the resistance value returns to the low-resistance state, and the grounding current resumes normal flow. The control logic unit and the drive circuit continue to monitor and adjust the grounding current to ensure the stability and safety of the system. The system enters the current recovery and self-resetting state to ensure the normal operation of the circuit.

[0073] Compared with the same type of hardware, the adaptive PID controller can dynamically adjust the control parameters according to the real-time state of the system, improve the control accuracy and stability, and ensure the precise control of the grounding current. In addition, the PPTC can respond quickly when the current is overloaded, protecting the circuit from overcurrent damage. The control logic unit and the drive circuit ensure the effective transmission and execution of the control signal, improving the system's response speed and control accuracy. Secondly, the PPTC has a self-resetting function. When the current returns to normal, the PPTC will automatically reset and return to the low-resistance state without the need to replace the fuse, improving the system's reliability and maintenance convenience. At the same time, through cooperation with the telemetry module, the operation and maintenance personnel can monitor the status of the grounding current in real time through the remote terminal, take maintenance measures in a timely manner, reduce the fault response time, and improve the reliability and safety of the system.

[0074] The telemetry module is used to provide remote monitoring of the grounding system status; the telemetry module transmits the grounding system indicators to the remote terminal through wireless communication; the grounding system indicators include grounding resistance, current, soil resistivity, and temperature data;

[0075] In specific implementation, as Figure 2 shown, the real-time detection module is responsible for monitoring the grounding resistance and environmental factors, and sending the data to the adaptive grounding resistance adjustment module and the telemetry module. The adaptive grounding resistance adjustment module adjusts the grounding path according to the received data. The telemetry module is responsible for transmitting the data to the remote terminal through wireless communication. The high-frequency transient suppression module directly sends a suppression signal to the grounding path. When the fault detection and isolation module detects a fault, it sends a fault signal to the telemetry module and an isolation signal to the grounding path. The grounding current control module sends a control signal to the grounding path as needed.

[0076] Furthermore, the PWM drive circuit includes an input unit, an amplification unit, a drive stage unit, a protection unit, and an isolation unit; the input unit locks the state of the input signal through an input buffer; the amplification unit amplifies the amplitude of the PWM signal through a high-gain operational amplifier; the drive stage unit generates a current to drive the controllable resistor array through a power transistor; the protection unit protects the circuit from abnormal conditions through a current-limiting resistor, a clamping diode, and a transient voltage suppressor; the isolation unit electrically isolates between the main control circuit and the drive circuit through an optocoupler. Furthermore, the working method of the dynamic resistance control algorithm includes the following steps: Step 1, construct a resistance mapping matrix where, T n , RH n , I n , V n and FT nrespectively represent the temperature, humidity, current, voltage and fault type coding of the high-voltage switchgear at the nth sampling moment; and noise suppression is carried out through a weighted moving average filter;

[0077] Step 2: Based on the resistance value mapping matrix E, calculate the dynamic resistance value demand through a multi-variable non-linear function; the multi-variable non-linear function obtains the weight vector θ and the feature mapping function G through neural network training n (E), map the environmental parameters to the high-dimensional feature space to calculate the grounding resistance value; the feature mapping function constructs the feature mapping through the polynomial kernel function and the activation function; the formula expression for the multi-variable non-linear function to calculate the dynamic resistance value demand is:

[0078]

[0079] In formula (1), M represents the highest degree of the polynomial term; P represents the number of cross terms, which is used to control the complexity of the feature mapping function; G n (E) represents the feature mapping function, which is used to map the nth row vector of the resistance value mapping matrix to the high-dimensional feature space; θ represents the weight vector, which is used to map the output of the feature mapping function to the dynamic resistance value demand; μ c represents the coefficient in the polynomial kernel function and the cross term, which is used to adjust the shape and complexity of the feature mapping function; indexset l represents the parameter index set involved in the lth cross term; E n represents the nth row vector of the resistance value mapping matrix;

[0080] Step 3: Construct the state matrix of the controllable resistance array where S n represents the switch state of the nth controllable resistance unit; and based on the current state S n and the dynamic resistance value demand phi(E n ), determine the optimal PWM duty cycle setting through the fitness function F ij (S n ); the formula expression of the fitness function is:

[0081]

[0082] In formula (2), L represents a solution, that is, a set of PWM duty cycle settings; h, γ and ε respectively represent the weight coefficients of the error term, the safety penalty term and the stability penalty term, which are used to balance the importance of different optimization objectives; P ij (L) represents the safety penalty term of the solution L; R a represents the predicted grounding resistance value of the nth sample by the deep learning model; R p is the actual grounding resistance value of the nth sample under the solution L; δ ij(L) represents the stable penalty term of solution L; N represents the number of samples within the evaluation period; phi(E n ) represents the dynamic resistance value requirement; T represents the length of the evaluation time period, which is used to measure the calculation range of the cumulative error;

[0083] Step 4: Control the conduction state of the controllable resistor array through the PWM signal to adjust the grounding resistance value; during the control process, the system state and environmental changes are monitored in real time, and the actual grounding resistance value is compared with the predicted value in Step 2. If an error occurs, the control strategy is adjusted through a feedback mechanism; the adjustment includes modifying the PWM duty cycle setting, adjusting the search parameters of the genetic algorithm, or retraining the dynamic resistance value demand model; the feedback mechanism generates and adjusts the duty cycle of the PWM signal through a PID controller according to the resistance value error; the calculation formula is:

[0084]

[0085] In formula (3), A t is the control parameter of the step size growth rate, which is used to limit the growth speed of the step size; μ j represents the adjustment threshold, which is used to determine whether adaptive adjustment is required; ΔS is the adjustment step size, which represents the adjustment amount of the PWM duty cycle setting; w t represents the current error; sign represents the sign function, which is used to determine the adjustment direction; K P 、K i and K d respectively represent the proportional, integral, and differential gains of the PID controller.

[0086] In specific implementation, the working process of the dynamic resistance value control algorithm is as follows: The environmental factor quantization unit continuously collects environmental parameters to form a resistance value mapping matrix E. The weighted moving average filter suppresses the noise of the resistance value mapping matrix to improve the stability and accuracy of the data. In the dynamic resistance value demand calculation stage, the dynamic resistance value demand phi(E n ) is calculated through a multivariable nonlinear function. The fitness function determines the optimal PWM duty cycle setting, and the PWM drive circuit controls the conduction state of the controllable resistor array to maintain the stability of the grounding resistance. The closed-loop feedback circuit monitors the change value of the grounding resistance in real time to ensure the stability and reliability of the system. When the environmental factors change, the environmental factor quantization unit updates the resistance value mapping matrix E in real time. In the dynamic resistance value demand calculation stage, the dynamic resistance value demand phi(E n)。The fitness function re - determines the optimal PWM duty cycle setting, and the PWM drive circuit adjusts the conduction state of the controllable resistor array to ensure real - time adjustment of the grounding resistance. The closed - loop feedback circuit monitors the adjusted grounding resistance value in real - time to ensure that the adjusted resistance value meets the expectations. At this time, the system enters the environmental change and adjustment state to ensure real - time adjustment and stability of the grounding resistance. When the system detects a fault, the environmental factor quantization unit incorporates the fault type code into the resistance value mapping matrix E. In the dynamic resistance value demand calculation stage, the dynamic resistance value demand phi(E n )。The fitness function re - determines the optimal PWM duty cycle setting, and the PWM drive circuit adjusts the conduction state of the controllable resistor array to ensure real - time adjustment of the grounding resistance. The closed - loop feedback circuit monitors the adjusted grounding resistance value in real - time to ensure that the adjusted resistance value meets the expectations. At this time, the system enters the fault detection and response state to ensure real - time adjustment and stability of the grounding resistance.

[0087] Compared with the same - type hardware, through multi - variable non - linear functions and neural network training, the dynamic resistance value control algorithm of the present invention can accurately calculate the dynamic resistance value demand, improving the accuracy and stability of the system. Through the PID controller and the closed - loop feedback mechanism, the system can adjust the grounding resistance in real - time to ensure the high precision and stability of the system. Through the weighted moving average filter and the fitness function, the system can quickly respond to environmental changes and fault detection, improving the response speed and sensitivity of the system. Through the PID controller and the closed - loop feedback mechanism, the system can adjust the grounding resistance in real - time to ensure the fast response and high sensitivity of the system. Through the environmental factor quantization unit and the resistance influence analysis unit, the system can comprehensively consider various environmental factors and system parameters to ensure the stability of the grounding resistance under different environmental conditions. Through the dynamic resistance value control algorithm and the closed - loop feedback mechanism, the system can adjust the grounding resistance in real - time to ensure the self - adaptability and environmental adaptability of the system. Through cooperation with the telemetry module, the operation and maintenance personnel can monitor the status of the grounding resistance in real - time through the remote terminal, take maintenance measures in a timely manner, reduce the fault response time, and improve the reliability and safety of the system.

[0088] In specific implementation, the hardware working environment of the dynamic resistance value control algorithm includes: high - voltage switchgear: model HSK - 1000; micro - controller: model STM32F407; environmental sensors: temperature sensor DS18B20, humidity sensor DHT22, current sensor LEM LAH 50 - P, voltage sensor ACS712; controllable resistor array: 10 controllable resistor units, each unit consisting of a MOSFET (IRF540N) and a 10Ω fixed resistor; PWM drive circuit: power amplifier LM2902, switch circuit IRF540N; data acquisition system: NI LabVIEW data acquisition card; experimental platform: Windows 10 operating system, MATLABR2021a;

[0089] Based on the above hardware environment, environmental sensors are used to collect environmental parameters such as temperature, humidity, current, and voltage in real time, and ground current and voltage are collected through current sensors and voltage sensors. The collected data is transmitted to the microcontroller and preprocessed through a weighted sliding average filter. Based on the resistance value mapping matrix, the dynamic resistance value requirement is calculated through a multivariable non-linear function. The optimal PWM duty cycle setting is determined through the fitness function to control the conduction state of the controllable resistor array. The PID controller generates and adjusts the duty cycle of the PWM signal according to the resistance value error, monitors the system state and environmental changes in real time, verifies the effectiveness of the dynamic resistance value control algorithm in the grounding system of high-voltage switchgear, and evaluates its performance and stability under different environmental conditions. The experimental data is recorded as shown in Table 2:

[0090] Table 2 Experimental Data Record Table

[0091]

[0092] As can be seen from the table, with the change of environmental parameters, the error between the predicted resistance value and the actual resistance value always remains within 0.2 Ω, indicating that the dynamic resistance value control algorithm has high precision. In the case where the fault type code is 1, the error still remains within 0.2 Ω, indicating that the algorithm can also maintain good performance in case of faults. The output of the PID controller gradually adjusts with the change of environmental parameters, ensuring the real-time adjustment of the grounding resistance. In case of faults, the PID output increases slightly, indicating that the algorithm can respond to faults in a timely manner and adjust the grounding resistance. The total fitness value of the fitness function is always low, indicating that the algorithm can maintain good performance under different environmental conditions. In case of faults, the safety penalty term increases slightly, but the total fitness value still remains at a low level, indicating that the algorithm can also maintain stability in case of faults. Therefore, significant results have been achieved in the application of the dynamic resistance value control algorithm in the grounding system of high-voltage switchgear. The experimental results show that under different environmental conditions, the error between the predicted resistance value and the actual resistance value always remains within 0.2 Ω. In addition, the PID controller can adjust the duty cycle of the PWM signal in real time to ensure the real-time adjustment of the grounding resistance. Secondly, the total fitness value of the fitness function is always low, indicating that the algorithm can maintain good performance under different environmental conditions. At the same time, in case of faults, the algorithm can respond to faults in a timely manner, adjust the grounding resistance, and ensure the stability and safety of the system.

[0093] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easily understood by those skilled in the art that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims

1. A grounding system for a high-voltage switchgear, characterized in that: The system includes: A real-time detection module, which is used to monitor the changes of the grounding resistance and the environmental factors beside the grounding system in real time, and output the grounding resistance change value and the environmental factors to the adaptive grounding resistance adjustment module and the telemetry module; the environmental factors include soil humidity and temperature; The adaptive grounding resistance adjustment module, which is used to dynamically adjust the grounding resistance according to the grounding resistance change value and the environmental factors; the adaptive grounding resistance adjustment module connects multiple sections of controllable resistors in series with the grounding path, the adaptive grounding resistance adjustment module constructs a resistance compensation value mapping model based on the environmental sensitive period index and the cross-correlation coefficient, and controls the resistance value through a dynamic resistance value control algorithm; the resistance compensation value mapping model includes an environmental factor quantization unit, a resistance influence analysis unit, a compensation value calculation unit and an output feedback unit; A high-frequency transient suppression module, which is used to suppress the high-frequency transient overvoltage caused by the arc restrike; A fault detection and isolation module, which is used to detect the grounding current, isolate the fault circuit, and transmit the fault signal to the telemetry module; A grounding current control module, which is used to control the grounding current; The telemetry module, which is used to provide remote monitoring of the grounding system status; the telemetry module transmits the grounding system indicators to the remote terminal through wireless communication; the grounding system indicators include grounding resistance, current, soil resistivity and temperature data; The output end of the real-time detection module is connected to the input ends of the adaptive grounding resistance adjustment module and the telemetry module; the output ends of the high-frequency transient suppression module, the fault detection and isolation module and the grounding current control module are connected to the input end of the telemetry module; the output end of the fault detection and isolation module is connected to the input end of the grounding current control module.

2. The grounding system of a high-voltage switchgear according to claim 1, characterized in that: The real-time detection module monitors the grounding resistance in real time through a grounding resistance detection unit; the grounding resistance detection unit supplies power to the grounding resistance through a constant current source circuit configured by an operational amplifier and an LDO voltage regulator, and detects the voltage drop across the grounding resistance through a differential amplifier, and the voltage signal is converted into a digital signal through an analog-to-digital converter; the constant current source circuit ensures that the current remains constant throughout the detection process through a negative feedback mechanism, eliminating the error caused by power supply fluctuations; the differential amplifier consists of two symmetrical operational amplifiers, which respectively detect the voltages at both ends of the grounding resistance, and eliminate noise interference through differential output; the grounding resistance detection unit also sends the calculated grounding resistance change value to the adaptive grounding resistance adjustment module and the telemetry module through the serial communication protocol SPI.

3. The grounding system of a high-voltage switchgear according to claim 2, characterized in that: The adaptive grounding resistance adjustment module receives and processes the digital signal of the grounding resistance detection unit through a microcontroller, the microcontroller processes the digital signal output by the grounding resistance detection unit through a FIR filter and a moving average filter, and calculates the change value of the grounding resistance through the least squares method; According to the calculated change value of the grounding resistance, the adaptive grounding resistance adjustment module then realizes the amplification of the PWM signal and the driving of the controllable resistor array through the PWM driving circuit; the controllable resistor array is composed of multiple controllable resistor units, and each controllable resistor unit is connected in series in the grounding path. The on-state of each controllable resistor unit is controlled and adjusted through the PWM signal to realize the dynamic adjustment of the grounding resistance value; the adaptive grounding resistance adjustment module also realizes the real-time monitoring of the grounding resistance change value through the closed-loop feedback circuit, and performs real-time feedback adjustment on the grounding resistance change value through the dynamic resistance value control algorithm.

4. The grounding system of a high-voltage switchgear according to claim 3, characterized in that: The PWM driving circuit includes an input unit, an amplification unit, a driving stage unit, a protection unit, and an isolation unit; the input unit locks the state of the input signal through an input buffer; the amplification unit amplifies the amplitude of the PWM signal through a high-gain operational amplifier; the driving stage unit generates a current to drive the controllable resistor array through a power transistor; the protection unit protects the circuit from abnormal conditions through a current-limiting resistor, a clamping diode, and a transient voltage suppressor; The isolation unit electrically isolates between the main control circuit and the driving circuit through an optocoupler.

5. The grounding system of a high-voltage switchgear according to claim 3, characterized in that: The working method of the dynamic resistance value control algorithm includes the following steps: Step 1: Construct a resistance mapping matrix , where , , , and respectively represent the temperature, humidity, current, voltage and fault type code of the high-voltage switchgear at the th sampling moment; and noise suppression is performed through a weighted moving average filter; Step 2: Based on the resistance value mapping matrix , calculate the dynamic resistance value requirement through a multi-variable non-linear function; the weight vector and the feature mapping function of the multi-variable non-linear function are obtained through neural network training, map the environmental parameters to a high-dimensional feature space to calculate the grounding resistance value; the feature mapping function constructs a feature mapping through a polynomial kernel function and an activation function; the formula expression for the multi-variable non-linear function to calculate the dynamic resistance value requirement is: （1） In formula (1), represents the highest degree of the polynomial term; represents the number of cross terms, which is used to control the complexity of the feature mapping function; represents the feature mapping function, which is used to map the th row vector of the resistance value mapping matrix to a high-dimensional feature space; represents the weight vector, which is used to map the output of the feature mapping function to the dynamic resistance value requirement; represents the coefficients in the polynomial kernel function and the cross terms, which are used to adjust the shape and complexity of the feature mapping function; represents the th set of parameter indices involved in the cross term; represents the th row vector of the resistance value mapping matrix; Step 3: Construct the state matrix of the controllable resistor array , where represents the switch state of the th controllable resistor unit; and based on the current state and the dynamic resistance value requirement , the optimal PWM duty cycle setting is determined through the fitness function . The formula expression of the fitness function is as follows: （2） In formula (2), represents a solution, that is, a set of PWM duty ratio settings; , and respectively represent the weight coefficients of the error term, the safety penalty term, and the stability penalty term, which are used to balance the importance of different optimization objectives; represents the safety penalty term of the solution ; represents the predicted value of the grounding resistance of the -th sample by the deep learning model; Under the solution , the actual grounding resistance value of the -th sample; represents the stability penalty term of the solution ; represents the number of samples within the evaluation period; represents the dynamic resistance value requirement; represents the length of the evaluation time period, which is used to measure the calculation range of the cumulative error; Step 4: Control the on-state of the controllable resistor array through the PWM signal to adjust the grounding resistance value; during the control process, the system state and environmental changes are monitored in real time, and the actual grounding resistance value is compared with the predicted value in Step 2. If an error occurs, the control strategy is adjusted through the feedback mechanism; the adjustment includes modifying the PWM duty cycle setting, adjusting the search parameters of the genetic algorithm, or retraining the dynamic resistance value demand model; the feedback mechanism generates and adjusts the duty cycle of the PWM signal according to the resistance error through a PID controller; the calculation formula is: （3） In formula (3), is the control parameter for the step growth rate, used to limit the growth speed of the step; represents the adjustment threshold, used to determine whether adaptive adjustment is required; is the adjustment step, representing the adjustment amount of the PWM duty cycle setting; represents the current error; represents the sign function, used to determine the adjustment direction; and and represent the proportional, integral, and derivative gains of the PID controller, respectively.

6. The grounding system of a high-voltage switchgear according to claim 1, characterized in that: The environmental factor quantization unit establishes a mathematical model between the environmental parameters and the quantization index through a statistical quantization method. The statistical quantization method describes the mapping relationship between the environmental parameters and the quantization index through a non-linear model, and minimizes the difference between the predicted value and the actual value through regression analysis to solve the model parameters; the resistance influence analysis unit fits the non-linear mapping between the environmental parameters and the resistance change through a support vector machine and a neural network; the support vector machine uses a kernel function to map the input data to a high-dimensional space and finds the optimal hyperplane to maximize the classification interval; the neural network realizes the approximation and prediction of complex functions through a multi-layer network structure and a backpropagation algorithm. Based on the results of the resistance influence analysis, the compensation value calculation unit dynamically calculates and outputs the resistance compensation value using Gaussian process regression and the gradient descent method; Gaussian process regression is based on the prior assumption of a Gaussian process, describes the correlation between input variables through a kernel function, and calculates the predicted value using Bayesian inference; the gradient descent method is used to fine-tune the compensation value considering the system stability and real-time requirements. The output feedback unit transmits the calculated resistance compensation value to the adaptive grounding resistance adjustment module in real time through a communication protocol and an API interface, and receives system status feedback; the output end of the environmental factor quantification unit is connected to the input end of the resistance influence analysis unit; The output end of the resistance influence analysis unit is connected to the input end of the compensation value calculation unit; the output end of the compensation value calculation unit is connected to the input end of the output feedback unit.

7. The grounding system of a high-voltage switchgear according to claim 1, characterized in that: The high-frequency transient suppression module connects a transient voltage suppression diode in parallel on the grounding path. When an overvoltage occurs, the transient voltage suppression diode conducts; the high-frequency transient suppression module includes a detection and response unit, an energy absorption unit, and a filtering and stabilization unit; The detection and response unit uses a high-bandwidth analog front end and fast Fourier transform to monitor the voltage waveform of the power system in real time. Once a high-frequency transient is detected, it switches the conduction state of the transient voltage suppression diode to direct the transient current to a preset safe path. The detection and response unit also provides immediate voltage clamping through a metal oxide varistor; when a high-frequency transient occurs, the energy absorption unit stores energy through a capacitor bank and converts the stored electrical energy into heat energy through a positive temperature coefficient thermistor and dissipates it into the environment. The energy absorption unit also releases the stored energy through a gas discharge tube; the filtering and stabilization unit connects a multi-stage LC filter network in parallel in the circuit, and the multi-stage LC filter network filters out redundant frequency components through a surface acoustic wave filter; the filtering and stabilization unit also optimizes the energy release process through an adaptive tuning mechanism; the adaptive tuning mechanism evaluates the fitness of the cut-off frequency and bandwidth through a particle swarm optimization algorithm to tune the value of the objective function; During the parameter adjustment process, the adaptive tuning mechanism also simulates the response of the filter to the transient voltage waveform through finite element analysis to evaluate the energy absorption and release effects.

8. The grounding system of a high-voltage switchgear according to claim 1, characterized in that: The fault detection and isolation module monitors the grounding current through a current transformer. When a current exceeding the threshold is detected, the fault detection and isolation module transmits the signal to the isolation circuit through a high-speed optocoupler, triggers a solid-state relay to cut off the power supply, and encapsulates the fault information into a data packet through a communication interface circuit RS-485 and transmits it to the telemetry module; the fault detection and isolation module includes a current detection unit, a signal processing unit, an isolation execution unit, and a communication unit; the current detection unit outputs a voltage signal proportional to the current through a Rogowski coil and adjusts the gain and offset of the transformer through a self-calibration circuit; The self-calibration circuit periodically generates a known current signal as a reference, compares the reference signal with the output signal of the transformer, and detects and adjusts the gain and offset of the transformer; the signal processing unit identifies the fault characteristic signal parameters through fast Fourier transform and wavelet transform; The fault characteristic signal parameters include harmonic distortion rate, amplitude mutation amount, and phase jump parameter; once a fault signal is detected, the isolation execution unit cuts off the connection between the fault circuit and the main system through a silicon-controlled rectifier, and after the isolation operation is completed, transmits the fault information to the telemetry module through the communication unit.

9. The grounding system of a high-voltage switchgear according to claim 1, characterized in that: The grounding current control module limits the grounding current through a self-resetting fuse PPTC and adjusts the current limiting value through a current feedback loop; the current feedback loop includes a current sensor, a comparator, a control logic unit, and a drive circuit; the current sensor is used to capture the current signal in the grounding line in real time and convert the current signal into an electrical signal; the comparator is used to compare the detected current value with a preset safety threshold to determine whether it is necessary to adjust the grounding current. If adjustment is required, the control logic unit generates an adjustment control signal through an adaptive PID controller based on the deviation between the current grounding current and the target current, and adjusts the working state of the self-resetting fuse PPTC through the drive circuit.

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