Grounding transformer-based arc suppression coil dynamic compensation switching method

Abstract

The application relates to the technical field of power protection, and discloses a grounding transformer arc suppression coil dynamic compensation switching method. The method comprises the following steps: acquiring photovoltaic system zero sequence voltage, zero sequence current and line impedance in real time through a multi-branch collector to obtain a power grid operation state parameter set; identifying an internal photovoltaic fault through a fault direction discrimination algorithm according to the phase relationship between the zero sequence current and the zero sequence voltage; inputting a fault confirmation signal into an arc suppression coil inductance adjustment system, and dynamically calculating compensation inductance parameters according to the capacitive current at the fault point; and adjusting the inductance of the arc suppression coil through a thyristor-controlled hierarchical reactor combination to make the inductive current and the capacitive current offset each other, so that the grounding arc is extinguished. The application solves the technical problems that the traditional arc suppression coil cannot distinguish between internal and external photovoltaic faults, the compensation parameters are fixed, and the response speed is slow, and improves the accuracy of grounding fault processing and the dynamic response capability of compensation switching.

Description

A method for dynamic compensation switching based on grounding transformer arc suppression coil Technical Field

[0001] This application relates to the field of power protection technology, and in particular to a dynamic compensation switching method based on the arc suppression coil of a grounding transformer. Background Technology

[0002] Traditional photovoltaic power generation systems primarily rely on arc suppression coils with fixed parameters to handle neutral point grounding faults. These coils generate inductive current to compensate for capacitive grounding currents in the system. When a single-phase grounding fault occurs, the arc is naturally extinguished by the mutual cancellation of inductive and capacitive currents. Existing arc suppression coil systems use preset inductance parameters. The basic parameters of the arc suppression coil are determined based on the grid's rated capacity and operating conditions. The arc suppression coil is connected to the grid neutral point via a grounding transformer. Under normal operating conditions, the arc suppression coil is in standby mode. When a grounding fault signal is detected, it is activated to compensate for the fault current.

[0003] Existing arc suppression coil systems suffer from significant technical shortcomings, primarily due to the lack of an automatic measurement system. This prevents real-time measurement of the grid-to-ground capacitance current and displacement voltage. When grid operation or parameters change, the capacitance current must be estimated manually, resulting in large estimation errors and an inability to effectively control residual current and suppress arc overvoltage. Traditional arc suppression coils employ a fixed number of adjustment stages based on voltage levels, leading to a limited number of stages and large differential currents, resulting in severely insufficient compensation accuracy. Furthermore, the tuning process requires power outages and coil withdrawal, disrupting the continuity of arc suppression compensation and causing excessively slow response times. In case of system anomalies or accidents, insufficient adjustment time can easily lead to loss of control. Many operating arc suppression coils have insufficient capacity, forcing them to operate under undercompensated conditions for extended periods. Due to the lack of damping resistors, they form a series resonant circuit with the grid-to-ground capacitance. Under undercompensation, a grid disconnection fault can easily trigger a full-compensation state, generating voltage resonance. This type of overvoltage is more harmful to power system insulation than arc-to-ground overvoltage.

[0004] The fundamental problem with existing arc suppression coil technology lies in its lack of fault direction identification capability and dynamic parameter adjustment mechanism. It cannot distinguish between internal and external faults in photovoltaic systems, leading to blind and inefficient compensation strategies. Traditional fixed parameter configurations cannot adapt to the dynamic changes in the operating conditions of photovoltaic power generation systems. In particular, when fluctuations in photovoltaic output cause changes in grid parameters, the preset arc suppression coil parameters cannot provide optimal compensation, thus affecting the timeliness and accuracy of fault handling. More critically, existing technology lacks fault identification algorithms tailored to the characteristics of photovoltaic systems, and cannot determine the specific location and nature of the fault based on the phase relationship of zero-sequence electrical quantities. This technological limitation directly restricts the optimization of arc suppression coil compensation effects and the improvement of grid operation safety. Summary of the Invention

[0005] This application provides a dynamic compensation switching method based on grounding transformer arc suppression coil, which solves the technical problems of traditional arc suppression coils being unable to distinguish between internal and external photovoltaic faults, having fixed compensation parameters, and having slow response speed. This method improves the accuracy of grounding fault handling and the dynamic response capability of compensation switching.

[0006] Firstly, this application provides a dynamic compensation switching method based on the arc suppression coil of a grounding transformer, the method comprising:

[0007] The zero-sequence voltage, zero-sequence current and line impedance of the photovoltaic system are collected and processed in real time by the multi-branch collectors connected to the main control unit to obtain a set of grid operation status parameters.

[0008] Based on the phase relationship between zero-sequence current and zero-sequence voltage in the set of power grid operating status parameters, the single-phase grounding fault is identified internally and externally using a fault direction discrimination algorithm to obtain a photovoltaic internal fault confirmation signal.

[0009] The internal fault confirmation signal of the photovoltaic system is input to the arc suppression coil inductance adjustment system. The inductance value of the arc suppression coil is dynamically calculated based on the capacitive current at the fault point to obtain the compensation inductance parameters.

[0010] Based on the aforementioned compensation inductance parameters, the inductance of the arc suppression coil is adjusted by a combination of thyristor-controlled graded reactors, so that the inductive current generated by the arc suppression coil cancels out the capacitive current at the fault point, thus achieving the extinguishing of the grounding arc.

[0011] Optionally, the multi-branch data acquisition unit connected through the main control unit performs real-time acquisition and processing of the zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system, including:

[0012] Branch 1 collector, branch 2 collector, and branch 3 collector are respectively connected to their respective photovoltaic branches;

[0013] Each branch data acquisition unit is equipped with an independent A / D conversion module, and the sampling frequency is set to 10kHz;

[0014] The main control unit establishes a communication connection with each branch collector through the grounding transformer controller to form a multi-branch parallel monitoring network, which records the amplitude and phase information of the zero-sequence component in real time; it establishes a power grid-to-ground capacitance current database to store the capacitance current variation law under different operating conditions and obtains a set of power grid operating status parameters.

[0015] Optionally, the fault direction discrimination algorithm performs internal and external identification processing for single-phase ground faults as follows:

[0016] The zero-sequence voltage and zero-sequence current in the power grid operating state parameter set are preprocessed using the sliding window technique, with each window containing 20 sampling points;

[0017] The fundamental component is extracted by fast Fourier transform, and the phase difference between the zero-sequence current and the zero-sequence voltage is calculated. When the angle between the zero-sequence current and the zero-sequence voltage is within the range of 0 to 150 degrees, the positive internal fault identification result of the photovoltaic system is generated.

[0018] When the angle of the zero-sequence current lagging behind the zero-sequence voltage is within the range of -150 degrees to 0 degrees, a reverse external fault identification result is generated; based on the positive internal fault identification result of the photovoltaic system, the photovoltaic internal fault confirmation signal is output.

[0019] Optionally, the process by which the arc suppression coil inductance adjustment system dynamically calculates the arc suppression coil inductance value based on the capacitive current at the fault point is as follows:

[0020] The required compensation capacity is calculated based on the maximum active power of the photovoltaic system, the power factor before compensation, and the target power factor.

[0021] The target inductance value of the arc suppression coil is determined by the system angular frequency and the equivalent capacitance value.

[0022] Verify the constraint that the arc suppression coil capacity does not exceed 20% of the transformer's rated capacity; confirm that the zero-sequence voltage drop generated by the zero-sequence current flowing through the arc suppression coil in the transformer does not exceed 10% of the rated phase voltage; and generate the compensation inductance parameters based on the constraint.

[0023] Optionally, the process of adjusting the inductance of the arc suppression coil using a thyristor-controlled graded reactor combination is as follows:

[0024] The coarse-adjustment reactor group receives the compensation inductance parameters and completes the adjustment of the basic inductance value within 5ms;

[0025] The fine-tuning reactor group achieves continuous fine-tuning of the inductance through PWM control, completing the fine-tuning process within 15ms;

[0026] The compensation effect verification module completes the compensation effect detection within 10ms; the total response time of the coarse adjustment reactor group, the fine adjustment reactor group, and the compensation effect verification module is controlled within 30ms.

[0027] The inductance adjustment during the total response time enables the inductive current generated by the arc suppression coil to cancel out the capacitive current at the fault point.

[0028] Optionally, the coordinated control process of the coarse-adjustment reactor group and the fine-adjustment reactor group is as follows:

[0029] The coarse-adjustment reactor group includes multi-stage thyristor switching reactors, and the fine-adjustment reactor group adopts controllable saturated reactors;

[0030] The compensated residual current is monitored in real time through a closed-loop control system; when the residual current exceeds a preset threshold, the fine-tuning reactor group automatically performs inductance fine-tuning; ensuring that the mutual cancellation effect of the inductive current and capacitive current is maintained within the set range.

[0031] Optionally, an adjustable damping resistor is connected in series in the arc suppression coil circuit to suppress series resonance overvoltage; the value of the adjustable damping resistor is determined according to the ratio of inductance to capacitance; when the system is detected to enter a resonance state, the adjustable damping resistor is automatically activated.

[0032] Optionally, the extinction status of the grounding arc is confirmed by the following verification indicators:

[0033] The voltage of the faulty phase has recovered to more than 95% of the rated voltage;

[0034] The voltage of the non-faulty phase remains within 105% of the rated voltage;

[0035] The deviation between the product of zero-sequence voltage and zero-sequence current is controlled within 2% of the rated zero-sequence voltage.

[0036] The technical solution provided in this application utilizes a multi-branch data acquisition unit connected to the main control unit to collect and process the zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system in real time. This overcomes the technical deficiency of traditional arc suppression coils lacking an automatic measurement system, enabling continuous monitoring and data-driven management of grid operating parameters. It eliminates the error problem of manually estimating capacitive current and establishes a grid-to-ground capacitive current database, providing a reliable data foundation for dynamic compensation. The fault direction discrimination algorithm, which performs internal and external identification processing for single-phase ground faults, solves the fundamental problem of traditional technologies being unable to distinguish fault locations. By analyzing the phase relationship between zero-sequence current and zero-sequence voltage, it accurately identifies internal and external photovoltaic faults, avoiding the blindness of compensation strategies and significantly improving the targeting and effectiveness of fault handling. The arc suppression coil inductance adjustment system, which dynamically calculates the inductance value based on the capacitive current at the fault point, completely changes the limitations of fixed parameter configuration in traditional arc suppression coils. It achieves precise matching between compensation parameters and actual fault conditions, solving the technical problems of few stages, large stage difference currents, and low compensation accuracy. Real-time calculation ensures the optimal correspondence between compensation capacity and fault current. The technology of using a thyristor-controlled graded reactor combination for inductance adjustment enables a fast response within 30ms, solving the technical problems of traditional arc suppression coil tuning requiring power outages and having slow response speeds. Through the coordinated control of coarse and fine adjustment, the accuracy and speed of inductance adjustment are ensured, enabling the inductive current generated by the arc suppression coil to be precisely canceled out with the capacitive current at the fault point, thus ensuring the reliable extinguishing of the grounding arc.

[0037] The fault direction discrimination algorithm plays a crucial role in the grounding protection application of photovoltaic power generation systems. By combining sliding window technology and fast Fourier transform, the algorithm achieves accurate analysis of the phase relationship of zero-sequence current. Its core contribution lies in establishing a fault type identification mechanism based on phase difference range. When the zero-sequence current leads the zero-sequence voltage by 0 to 150 degrees, it is determined to be an internal photovoltaic fault. When the zero-sequence current lags the zero-sequence voltage by -150 to 0 degrees, it is determined to be an external fault. This algorithm design is specifically optimized for the electrical characteristics of photovoltaic systems and has higher anti-interference ability and discrimination accuracy compared with traditional amplitude comparison methods. The dynamic inductance calculation algorithm demonstrates significant technical advantages in the optimization of arc suppression coil parameters. By calculating the maximum active power of the photovoltaic system in real time and the relationship between the power factor before and after compensation, the required compensation capacity is determined. Combined with the system angular frequency and equivalent capacitance value, the target inductance value is accurately calculated. The algorithm considers engineering constraints such as arc suppression coil capacity constraints and zero-sequence voltage drop limits, ensuring the engineering feasibility of the calculation results. The contribution of this algorithm in the application of dynamic compensation in photovoltaic power generation systems lies in realizing the real-time matching of compensation parameters with the system operating state, which significantly improves the stability and reliability of the compensation effect. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 is a schematic diagram of an embodiment of the dynamic compensation switching method based on the arc suppression coil of the grounding transformer in this application;

[0040] Figure 2 is a schematic diagram of the system architecture of the dynamic compensation switching method based on the grounding transformer arc suppression coil in the embodiments of this application. Detailed Implementation

[0041] This application provides a dynamic compensation switching method based on a grounding transformer arc suppression coil. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0042] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to Figure 1. One embodiment of the dynamic compensation switching method based on the grounding transformer arc suppression coil in this application includes:

[0043] The zero-sequence voltage, zero-sequence current and line impedance of the photovoltaic system are collected and processed in real time by the multi-branch collectors connected to the main control unit to obtain a set of grid operation status parameters.

[0044] Based on the phase relationship between zero-sequence current and zero-sequence voltage in the set of power grid operating status parameters, the single-phase grounding fault is identified internally and externally using a fault direction discrimination algorithm to obtain the photovoltaic internal fault confirmation signal.

[0045] The internal fault confirmation signal of the photovoltaic system is input to the arc suppression coil inductance adjustment system. The inductance value of the arc suppression coil is dynamically calculated based on the capacitive current at the fault point to obtain the compensation inductance parameters.

[0046] Based on the compensation inductance parameters, the inductance of the arc suppression coil is adjusted by a combination of graded reactors controlled by thyristors, so that the inductive current generated by the arc suppression coil cancels out the capacitive current at the fault point, thus achieving the extinguishing of the grounding arc.

[0047] It is understood that the executing entity of this application can be a dynamic compensation switching system based on the arc suppression coil of a grounding transformer, or it can be a terminal or a server; no specific limitation is made here. This application's embodiment uses a server as the executing entity for illustration.

[0048] Specifically, the implementation process of the dynamic compensation switching method based on the grounding transformer arc suppression coil first establishes communication connections with branch collectors 1, 2, and 3 through the main control unit. Each collector is equipped with an independent A / D conversion module to synchronously acquire the zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system. The main control unit, acting as the data aggregation center, receives raw electrical parameter data from the three branch collectors, with a sampling frequency set to 10kHz to ensure rapid response to transient changes in the power grid. Each branch collector acquires the amplitude and phase information of the zero-sequence component through high-precision sensors, forming a data structure containing timestamps, amplitudes, and phase angles, and establishing a set of power grid operating status parameters. This parameter set not only records real-time data but also constructs a database of power grid-to-ground capacitance current, storing the variation patterns of capacitance current under different operating conditions, forming a historical data reference benchmark.

[0049] After receiving the set of power grid operating status parameters, the fault direction discrimination algorithm first uses a sliding window technique to preprocess the zero-sequence voltage and zero-sequence current. Each sliding window contains a data sequence of 20 consecutive sampling points. The sliding window technique smooths the data within the time window, eliminates instantaneous noise interference, and extracts stable electrical parameter features. The Fast Fourier Transform algorithm performs frequency domain transformation on the time-domain data within the window, separates the fundamental component from the composite signal, and calculates the phase difference between the zero-sequence current and zero-sequence voltage. When the phase difference calculation shows that the zero-sequence current leads the zero-sequence voltage by an angle within the range of 0 to 150 degrees, the discrimination algorithm determines it as a positive internal fault in the photovoltaic system and generates a positive internal fault identification result for the photovoltaic system. Conversely, when the zero-sequence current lags the zero-sequence voltage by an angle within the range of -150 degrees to 0 degrees, it is identified as a reverse external fault. Based on the positive internal fault identification result of the photovoltaic system, the algorithm outputs a photovoltaic internal fault confirmation signal, triggering the subsequent dynamic compensation switching process.

[0050] Upon receiving a fault confirmation signal from the photovoltaic system, the arc suppression coil inductance adjustment system immediately initiates a dynamic inductance value calculation program. The program first reads three key parameters: the photovoltaic system's maximum active power, the power factor before compensation, and the target power factor. It then calculates the required reactive power compensation capacity using the power factor compensation formula. Based on the system's angular frequency and equivalent capacitance, the inductance adjustment system determines the target inductance value of the arc suppression coil using the inductance calculation formula. During the calculation process, the system verifies two important constraints: the arc suppression coil capacity must not exceed 20% of the transformer's rated capacity, and the zero-sequence voltage drop generated by the zero-sequence current flowing through the arc suppression coil within the transformer must not exceed 10% of the rated phase voltage. After the constraints are verified, the dynamic calculation program outputs the compensation inductance parameters, which include the target inductance value, adjustment range, and adjustment accuracy requirements.

[0051] After receiving the compensation inductance parameters, the thyristor-controlled graded reactor assembly initiates a three-stage inductance adjustment process. The first stage, the coarse-tuning reactor group, comprises multiple thyristor-switched reactors. It performs a wide-range inductance adjustment based on the target value in the compensation inductance parameters, rapidly switching the base inductance value within a 5ms time window. The second stage, the fine-tuning reactor group, employs controllable saturated reactor technology, using PWM pulse width modulation control to achieve continuous fine-tuning of the inductance value, completing the fine adjustment process within 15ms. The third stage, the compensation effect verification module, monitors the residual current and voltage recovery after adjustment in real time, completing a quantitative evaluation of the compensation effect within 10ms. The coordinated control of these three stages ensures the total response time is kept within 30ms, allowing the inductive current generated by the arc suppression coil to cancel out the capacitive current at the fault point, ultimately extinguishing the grounding arc.

[0052] In one specific embodiment, a multi-branch data acquisition unit connected to the main control unit performs real-time acquisition and processing of the zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system, including:

[0053] Branch 1 collector, branch 2 collector, and branch 3 collector are respectively connected to their respective photovoltaic branches;

[0054] Each branch data acquisition unit is equipped with an independent A / D conversion module, and the sampling frequency is set to 10kHz;

[0055] The main control unit establishes a communication connection with each branch acquisition unit through the grounding transformer controller, forming a multi-branch parallel monitoring network to record the amplitude and phase information of the zero-sequence component in real time; it also establishes a power grid-to-ground capacitance current database to store the capacitance current variation patterns under different operating conditions and obtain a set of power grid operating status parameters.

[0056] Specifically, Branch 1 data collector is dedicated to acquiring zero-sequence voltage, zero-sequence current, and line impedance data for the first photovoltaic branch. It converts the high-voltage side electrical signals into low-voltage signals suitable for processing by the A / D conversion module using voltage and current transformers. Branch 2 and Branch 3 data collectors employ the same signal conditioning circuits, corresponding to the second and third photovoltaic branches respectively, forming a three-way parallel data acquisition architecture. Each branch data collector's built-in A / D conversion module uses a 16-bit resolution analog-to-digital converter with a sampling frequency set to 10kHz, meaning that each electrical parameter is digitally sampled 10,000 times per second, thereby capturing rapidly changing signals during grid operation.

[0057] After the A / D conversion module converts the analog signal into a digital signal, the built-in digital signal processor performs preliminary processing on the raw sampled data, including digital filtering, signal amplification, and zero-drift compensation. The digital filtering process uses a low-pass filter to eliminate high-frequency noise interference, the signal amplification stage adjusts the signal amplitude according to a preset gain coefficient, and the zero-drift compensation function eliminates DC offset errors introduced by the sensor and conversion circuit. The processed digital signal is transmitted to the central control unit via the CAN bus protocol. The CAN bus uses differential signal transmission, which provides strong anti-interference capabilities and reliable data transmission.

[0058] The main control unit acts as the data aggregation and processing center, establishing communication connections with the three branch data collectors through the grounding transformer controller. The grounding transformer controller has built-in multiple communication interfaces, supporting simultaneous data exchange with multiple data collectors. The communication protocol adopts a master-slave mode. The main control unit, acting as the master station, periodically sends data request commands to each branch data collector. The data collectors, acting as slave stations, respond to the requests and upload the collected electrical parameter data. During data transmission, each data packet includes a timestamp, data collector identifier, parameter type, and numerical information. The timestamp ensures time synchronization of data from different branches, the data collector identifier distinguishes the data source, and the parameter type indicates whether it is zero-sequence voltage, zero-sequence current, or line impedance data.

[0059] The multi-branch parallel monitoring network is established based on a real-time data exchange and status synchronization mechanism. The central control unit sends a synchronization signal to all branch collectors every 100 milliseconds to ensure that each collector samples data at the same time, avoiding data analysis errors caused by sampling time differences. The amplitude and phase information of the zero-sequence component are extracted using digital signal processing algorithms. Amplitude calculation employs the root mean square algorithm to perform statistical analysis on the sampled data, while phase information is determined by zero-crossing detection and correlation analysis algorithms to determine the signal's phase angle. Amplitude data is stored in RMS form, and phase data is recorded in angle value form; together, they constitute the description of the zero-sequence component.

[0060] The establishment of the power grid-to-ground capacitive current database involves three stages: data classification, storage, and indexing. Data classification categorizes the collected capacitive current data into four states based on operating conditions: normal operation, light load operation, heavy load operation, and fault operation. Data for each state is stored independently, forming a sub-database. The storage structure adopts a time-series database format, recording the variation patterns of capacitive current in chronological order, while also associating it with corresponding operating condition parameters, including influencing factors such as load level, ambient temperature, and humidity. The indexing mechanism establishes a multi-dimensional index system based on time, operating condition type, and parameter range, supporting rapid retrieval of historical data under specific conditions.

[0061] The formation process of the power grid operation status parameter set involves correlating real-time acquired data with historical databases. Real-time data directly reflects the current state, while historical data serves as the benchmark for trend analysis and anomaly detection. The parameter set is stored using a multi-dimensional array structure: the first dimension represents the time series, the second represents the branch number, the third represents the parameter type, and the fourth represents the numerical value and status identifier. The status identifier includes data validity, data quality level, and anomaly flags. Data validity indicates whether the acquired data is within the normal range, the data quality level reflects the reliability of the data, and the anomaly flag indicates whether any anomalies have been detected.

[0062] Figure 2 is a schematic diagram of the system architecture of the dynamic compensation switching method based on the grounding transformer arc suppression coil in this embodiment of the application. As shown in Figure 2, the system architecture includes a grounding transformer, an arc suppression coil, a compensation system, and a multi-branch acquisition network. DL0 represents the main control unit, and DL1, DL2, and DL3 represent the branch 1 collector, branch 2 collector, and branch 3 collector, respectively. Each branch collector establishes a communication connection with the main control unit through the grounding transformer controller, forming a multi-branch parallel monitoring network. The grounding transformer is connected to the neutral point of the power grid through the arc suppression coil. The series resistor R in the arc suppression coil circuit is used for damping control, and the capacitor C represents the equivalent capacitance of the power grid to ground. Each branch collector monitors the zero-sequence voltage, zero-sequence current, and line impedance parameters of the corresponding photovoltaic branch in real time, and transmits the acquired data to the main control unit for fault direction determination and compensation parameter calculation, realizing rapid identification and dynamic compensation switching control of single-phase grounding faults in the photovoltaic system.

[0063] In one specific embodiment, the process of the fault direction discrimination algorithm performing internal and external identification processing for single-phase ground faults is as follows:

[0064] The sliding window technique is used to preprocess the zero-sequence voltage and zero-sequence current in the set of power grid operating state parameters. Each window contains 20 sampling points.

[0065] The fundamental component is extracted by fast Fourier transform, and the phase difference between the zero-sequence current and the zero-sequence voltage is calculated. When the angle between the zero-sequence current and the zero-sequence voltage is within the range of 0 to 150 degrees, the positive internal fault identification result of the photovoltaic system is generated.

[0066] When the angle of the zero-sequence current lagging behind the zero-sequence voltage is within the range of -150 degrees to 0 degrees, a reverse external fault identification result is generated; based on the positive internal fault identification result of the photovoltaic system, a photovoltaic internal fault confirmation signal is output.

[0067] Specifically, the zero-sequence voltage and zero-sequence current in the power grid operating state parameter set are preprocessed using the sliding window technique. The sliding window technique is a time-domain signal processing method that continuously moves a fixed-length data window across the time series, with each window containing 20 consecutive sampling points. Since the sampling frequency is 10kHz, each window corresponds to a 2-millisecond time span, and the data within the window represents the instantaneous changes in zero-sequence voltage and zero-sequence current during that time period. The sliding window's step size is set to one sampling point, meaning that after each window movement, the oldest data point is discarded, and the newest data point is added, forming a continuously updated data processing flow. The data preprocessing process includes outlier detection and smoothing filtering. Outlier detection identifies abnormal data by comparing the deviation of the current data point from other data points within the window, while smoothing filtering uses a moving average method to eliminate random noise interference in subsequent analysis.

[0068] The Fast Fourier Transform (FFT) algorithm receives preprocessed window data and converts the time-domain signal into a frequency-domain signal for spectral analysis. The core principle of the FFT algorithm is based on the fast computation method of the Discrete Fourier Transform (DFT). It decomposes the N-point DFT into multiple smaller-scale transformation operations using a divide-and-conquer strategy, significantly reducing computational complexity. The algorithm performs a butterfly operation on the zero-sequence voltage data from 20 sampling points. The butterfly operation is the basic computational unit of the FFT, achieving frequency domain transformation through complex multiplication and addition. The transformation result contains the spectral information of the zero-sequence voltage signal, where the fundamental component corresponds to the 50Hz power frequency. The algorithm extracts the amplitude and phase information of the fundamental component using a peak detection method. The zero-sequence current data undergoes the same FFT processing flow to obtain the amplitude and phase parameters of the fundamental component. During the fundamental component extraction process, the algorithm performs peak search on the spectral data, identifying the frequency point with the largest amplitude as the fundamental frequency. The corresponding complex value contains the amplitude and phase information of the fundamental frequency.

[0069] The phase difference calculation process is based on mathematical operations using the complex representations of the fundamental components of the zero-sequence current and zero-sequence voltage. The phase angle of the complex number is calculated using the arctangent function, and the phase difference is obtained by subtracting the phase angle of the zero-sequence voltage from the phase angle of the zero-sequence current. The sign and magnitude of the phase difference calculation result directly reflect the leading or lagging relationship between the zero-sequence current and the zero-sequence voltage. When the calculated phase difference is positive, it indicates that the zero-sequence current leads the zero-sequence voltage; when the phase difference is negative, it indicates that the zero-sequence current lags behind the zero-sequence voltage. The algorithm judges the angular range of the phase difference value. When the phase difference is within the range of 0 to 150 degrees, the discrimination logic generates a forward internal fault identification result for the photovoltaic system, based on the electrical characteristic that the zero-sequence current leads the zero-sequence voltage during a forward internal fault. When the phase difference is within the range of -150 degrees to 0 degrees, the discrimination logic generates a reverse external fault identification result, corresponding to the electrical phenomenon that the zero-sequence current lags behind the zero-sequence voltage during an external fault.

[0070] The result of the forward internal fault identification in the photovoltaic system serves as the trigger condition for subsequent processing. When the algorithm detects this identification result, it immediately outputs a photovoltaic internal fault confirmation signal. The photovoltaic internal fault confirmation signal is in digital form and includes a fault type identifier, fault time, and fault branch information. The fault type identifier distinguishes forward internal faults from other fault types, the fault time records the accurate timestamp of the fault detection, and the fault branch information indicates the specific photovoltaic branch number where the fault occurred. The generation process of the confirmation signal also includes continuity verification; the algorithm requires the analysis results of three consecutive sliding windows to all point to the same fault type before outputting a confirmation signal, avoiding misjudgments caused by transient interference.

[0071] When a positive internal fault occurs in a photovoltaic system, the zero-sequence voltage and zero-sequence current satisfy the following relationship: ;

[0072] in Represents zero-sequence voltage. Represents zero-sequence current. This represents the zero-sequence impedance of the photovoltaic branch. When a reverse external fault occurs in the photovoltaic system, the zero-sequence voltage and zero-sequence current satisfy the following relationship: ;

[0073] in Indicates the zero-sequence impedance of the power supply. This represents the zero-sequence impedance of the line. Based on these two mathematical relationships, the phase difference is calculated using complex number operations, through... The function calculates the phase angle difference between the zero-sequence current and the zero-sequence voltage. During a forward internal fault, the phase difference satisfies... The phase difference satisfies the following during a reverse external fault: The numerical range of the phase difference directly corresponds to the fault type determination result.

[0074] In one specific embodiment, the process by which the arc suppression coil inductance adjustment system dynamically calculates the arc suppression coil inductance value based on the capacitive current at the fault point is as follows:

[0075] The required compensation capacity is calculated based on the maximum active power of the photovoltaic system, the power factor before compensation, and the target power factor.

[0076] The target inductance value of the arc suppression coil is determined by the system angular frequency and the equivalent capacitance value.

[0077] Verify the constraint that the arc suppression coil capacity does not exceed 20% of the transformer's rated capacity; confirm that the zero-sequence voltage drop generated by the zero-sequence current flowing through the arc suppression coil in the transformer does not exceed 10% of the rated phase voltage; generate compensation inductance parameters based on the constraint conditions.

[0078] Specifically, the required compensation capacity is calculated using three key parameters: the maximum active power of the photovoltaic system, the power factor before compensation, and the target power factor. The maximum active power of the photovoltaic system is obtained from the set of grid operating state parameters. This parameter reflects the power output capability of the photovoltaic system under full load operation and is collected in real time by a power measurement device and transmitted to the inductive regulation system. The power factor before compensation is calculated by measuring the ratio of active power to reactive power output by the photovoltaic system. The power factor value directly reflects the balance between capacitive and inductive loads in the grid. The target power factor is preset according to grid operating requirements, usually set to a value close to 1 to achieve power factor correction. The compensation capacity calculation adopts the power triangle principle, determining the required compensation capacity by calculating the difference in reactive power before and after compensation. The calculation process involves inverse cosine function operations and trigonometric function transformations, converting the power factor into a phase angle before vector calculation.

[0079] The determination of the system angular frequency and equivalent capacitance value is based on a comprehensive analysis of the basic parameters of the power grid and the characteristic parameters of the photovoltaic system. The system angular frequency is equal to twice pi multiplied by the power frequency of 50 Hz, resulting in a fixed value of 314 radians per second. This parameter serves as the basic frequency parameter for calculating the inductance of the arc suppression coil. The calculation of the equivalent capacitance value is more complex, requiring consideration of the parallel effect of the ground capacitance of each branch of the photovoltaic system. The total equivalent capacitance value is obtained by parallel calculation of the ground capacitance values ​​of branch 1, branch 2, and branch 3. The ground capacitance value is obtained by measuring the capacitance under normal operating conditions of the photovoltaic system using a capacitance measuring device. The measurement process employs the AC impedance method, measuring the capacitive impedance by applying an AC signal of known frequency and amplitude, and then calculating the capacitance value based on the inverse relationship between impedance and capacitance. The calculation of the target inductance value of the arc suppression coil is based on the series resonance principle. Complete compensation is achieved when the inductive reactance of the arc suppression coil is equal to the equivalent capacitive reactance of the system. The target inductance value is equal to 1 divided by the product of the square of the system angular frequency and the equivalent capacitance value.

[0080] The constraint verification process includes capacity constraints and voltage drop constraints. Capacity constraint verification is achieved by comparing the ratio of the arc suppression coil capacity to the transformer's rated capacity. The arc suppression coil capacity equals the arc suppression coil inductance multiplied by the system angular frequency, then multiplied by the square of the rated voltage. The transformer's rated capacity is obtained from the transformer's nameplate parameters. The calculated ratio must be less than 20% to meet the constraint conditions. The voltage drop constraint verification process is more complex, requiring the calculation of the voltage drop across the transformer's zero-sequence impedance caused by the zero-sequence current flowing through the arc suppression coil. The magnitude of the zero-sequence current is equal to the capacitive current at the fault point. The transformer's zero-sequence impedance is obtained through transformer parameter calculation or actual measurement. The zero-sequence voltage drop is calculated using Ohm's law; the zero-sequence current is multiplied by the transformer's zero-sequence impedance to obtain the voltage drop value. The ratio of this value to the rated phase voltage must be less than 10% to meet the operating requirements.

[0081] The generation process of the compensation inductance parameters integrates the above calculation results and constraint verification results to form a parameter set that includes the target inductance value, adjustment range, and safety margin. The target inductance value is a theoretical calculation result, the adjustment range takes into account the fluctuation range of power grid parameters in actual operation, and the safety margin ensures that the arc suppression coil can still operate normally under extreme conditions. The parameter generation process also includes a dynamic adjustment mechanism. When a change in power grid parameters is detected, the inductance regulation system automatically recalculates the compensation inductance parameters to ensure the continuous effectiveness of the compensation effect.

[0082] It should be noted that the calculation of the target inductance value of the arc suppression coil is based on the principle of series resonance compensation, and the target inductance value is obtained through the formula... Confirmed, among which Indicates the target inductance value. Represents the system's angular frequency. This represents the equivalent capacitance of the power grid. System angular frequency. ,in For a power frequency of 50Hz, the equivalent capacitance value is... The compensation capacity is obtained through parallel calculation of the capacitance to ground of each photovoltaic branch. The power factor correction formula is used for the compensation capacity calculation.

[0083] in Indicates the required compensation capacity. This indicates the maximum active power of the photovoltaic system. This represents the power factor angle before compensation. This represents the target power factor angle. The damping resistance value is calculated based on the critical damping condition, and the resistance value is obtained through the formula... Confirmed, among which L represents the damping resistance value, C represents the arc suppression coil inductance value, and C represents the grid capacitance to ground value.

[0084] In one specific embodiment, the process of adjusting the inductance of the arc suppression coil using a thyristor-controlled graded reactor combination is as follows:

[0085] The coarse-adjustment reactor group receives the compensation inductance parameters and completes the adjustment of the basic inductance value within 5ms;

[0086] The fine-tuning reactor group achieves continuous fine-tuning of the inductance through PWM control, completing the fine-tuning process within 15ms;

[0087] The compensation effect verification module completes the compensation effect detection within 10ms; the total response time of the coarse adjustment reactor group, the fine adjustment reactor group, and the compensation effect verification module is controlled within 30ms.

[0088] By adjusting the inductance during the total response time, the inductive current generated by the arc suppression coil and the capacitive current at the fault point are mutually canceled out.

[0089] Specifically, the coarse-adjustment reactor group receives compensation inductance parameters and adjusts the base inductance value. The coarse-adjustment reactor group comprises multiple stages of thyristor-switched reactors, each with a different inductance value. Coarse adjustment control of the inductance value is achieved through binary encoding. The compensation inductance parameters include three key data points: the target inductance value, the current inductance value, and the adjustment step size. The coarse-adjustment controller first calculates the difference between the target and current inductance values, and then determines the reactor combinations to be switched on or off based on the inductance values ​​of each reactor stage. The switching decision employs an optimization algorithm, finding the combination with the smallest difference from the target inductance value by traversing all reactor combination schemes. The switching command is transmitted to each stage of the thyristor switch via digital signals. Upon receiving the switching command, the thyristor switch executes the switching action at the AC voltage zero-crossing point to avoid arcing and inrush current during the switching process. The data flow of the entire coarse-adjustment process includes five stages: parameter reception, difference calculation, combination optimization, command generation, and execution confirmation. Data buffering and state mechanisms ensure the continuity and reliability of data processing between these stages. The 5-millisecond settling time constraint requires the controller to use a high-speed digital signal processor with a clock frequency set above 100 MHz to ensure that complex combinatorial optimization algorithms can complete calculations and output results within the time limit.

[0090] After receiving the coarse adjustment completion signal, the fine-tuning reactor group initiates the continuous fine-tuning process of PWM control. PWM control is an application of pulse width modulation technology, which continuously controls the controllable saturated reactor by adjusting the duty cycle of the pulse signal. The inductance value of the controllable saturated reactor has a non-linear relationship with the control current; a small change in the control current causes a continuous change in the inductance value. The PWM controller calculates the required control current value based on the residual error between the target inductance value and the inductance value after coarse adjustment. The control current calculation uses a lookup table method and a linear interpolation algorithm. The lookup table method is based on a pre-established table of correspondence between inductance values ​​and control currents, while the linear interpolation algorithm handles the numerical calculations between table intervals, ensuring that the control accuracy reaches the level of one-thousandth of the inductance value. The PWM signal generation process includes three steps: carrier signal generation, modulation signal calculation, and pulse width determination. The carrier signal adopts a triangular wave form with a frequency set to 20 kHz. The modulation signal is calculated in real time according to the control current requirement, and the pulse width is determined by comparing the amplitude relationship between the modulation signal and the carrier signal. The data feedback mechanism of the fine-tuning process monitors the adjustment effect in real time through an inductance value measurement device. This device employs impedance analysis, applying a test signal of known frequency and amplitude to the controllable saturated reactor. The inductance value is calculated by measuring the phase and amplitude of the response signal. The measurement result is compared with the target value to generate an error signal, which is then input to the PWM controller to form a closed-loop control system. The 15-millisecond fine-tuning time includes multiple iterative adjustment processes, each with a 3-millisecond cycle, comprising four stages: measurement, calculation, adjustment, and verification. Five iterative adjustments ensure that the inductance value adjustment accuracy meets the compensation requirements.

[0091] The compensation effect verification module initiates a rapid detection program after inductor adjustment. The detection process includes three aspects: residual current measurement, voltage recovery detection, and phase relationship verification. Residual current measurement obtains the adjusted zero-sequence current value through a zero-sequence current transformer and compares it with the capacitive current before the fault. Ideally, the residual current should be close to zero under ideal compensation conditions; in practical engineering, residual current controlled within 5% of the capacitive current is considered successful compensation. Voltage recovery detection monitors changes in the voltage of the faulty phase and the voltage of the non-faulty phases. The degree of recovery of the faulty phase voltage directly reflects the compensation effect, while the stability of the non-faulty phase voltage reflects the impact of the compensation process on other parts of the power grid. Phase relationship verification analyzes the phase difference between the adjusted zero-sequence voltage and zero-sequence current. A phase difference close to zero indicates that the inductive current and capacitive current are essentially canceled out; the degree of deviation from zero quantifies the compensation accuracy. The verification algorithm employs a multi-parameter comprehensive evaluation method, weighting the residual current, voltage recovery, and phase relationship indicators according to weighting coefficients to obtain a comprehensive evaluation score. If the score exceeds a preset threshold, compensation is confirmed as successful; if the score is below the threshold, a secondary adjustment program is triggered. The 10-millisecond detection time is achieved through parallel processing technology, with data acquisition and analysis performed simultaneously for the three detection items, and finally the results are summarized to form a comprehensive evaluation result.

[0092] The overall response time control mechanism uses a timing coordinator to uniformly manage the working timing of the three processing modules. The timing coordinator receives the internal fault confirmation signal from the photovoltaic system as a start trigger, and simultaneously sends start commands and time synchronization signals to the coarse-adjustment reactor group, the fine-adjustment reactor group, and the compensation effect verification module. Each module is equipped with a real-time clock and a countdown timer to ensure that its respective data processing tasks are completed within the specified time. The timing coordinator continuously monitors the execution status of each module, and when the total execution time approaches the 30-millisecond limit, it forcibly terminates the current adjustment process and outputs the current optimal result. The 30-millisecond time constraint solves the problem of slow response speed of traditional arc suppression coils. The rapid response capability ensures that compensation is put into operation in a timely manner after a fault occurs, avoiding further damage to the power grid caused by the continued burning of the grounding arc.

[0093] In one specific embodiment, the coordinated control process of the coarse-adjustment reactor group and the fine-adjustment reactor group is as follows:

[0094] The coarse-adjustment reactor group includes multi-stage thyristor switching reactors, while the fine-adjustment reactor group uses controllable saturated reactors.

[0095] The residual current after compensation is monitored in real time through a closed-loop control system. When the residual current exceeds the preset threshold, the fine-tuning reactor group automatically performs inductance fine-tuning to ensure that the mutual cancellation effect of inductive current and capacitive current is maintained within the set range.

[0096] Specifically, the coordinated control process of the coarse-adjustment reactor group and the fine-adjustment reactor group establishes a two-layer inductance regulation architecture based on the dynamic compensation switching method of the grounding transformer arc suppression coil. The coarse-adjustment reactor group includes multi-stage thyristor-switched reactors as the main means of large-range inductance regulation. Each stage of the thyristor-switched reactor is connected to reactor components with different inductance values. The on and off states of the thyristors are controlled by digital control signals to realize the activation and deactivation of the reactors. The multi-stage thyristor-switched reactors adopt a binary weight configuration. The first stage corresponds to the basic inductance unit, the second stage corresponds to twice the basic inductance unit, the third stage corresponds to four times the basic inductance unit, and so on to form a binary inductance regulation system. The control logic calculates the required adjustment amount based on the difference between the target inductance value and the current inductance value, and then converts the adjustment amount into a binary code. Each binary bit corresponds to the state of a stage of thyristor-switched reactor, with a high level indicating activation and a low level indicating deactivation. After receiving the binary control code, the thyristor switch controller generates a corresponding trigger pulse sequence. The trigger pulse is issued at the moment when the AC voltage crosses zero, ensuring that the thyristor is turned on or off when the current is zero, thus avoiding arcing and impact phenomena during the switching process.

[0097] The fine-tuning reactor bank uses a controllable saturated reactor to achieve continuous fine-tuning of the inductance value. The controllable saturated reactor consists of an iron-core reactor and a DC control winding. The magnitude of the DC current flowing through the DC control winding determines the magnetic saturation degree of the iron core, thus changing the equivalent inductance value of the reactor. There is a non-linear relationship between the control current and the inductance value. When the control current is small, the iron core is in the linear operating region, and the inductance value remains relatively large. As the control current increases, the iron core gradually enters the saturation region, and the inductance value decreases accordingly. The control current is calculated based on a pre-established inductance-current characteristic curve, obtained through experimental measurements. The inductance values ​​corresponding to different control currents are recorded, forming a lookup table data structure. The fine-tuning controller looks up the corresponding control current value based on the residual inductance error after coarse adjustment. When the error value falls within the range of data points in the table, a linear interpolation algorithm is used to calculate the precise control current value.

[0098] The data processing of the closed-loop control system involves real-time monitoring of the compensation effect through a residual current detection device. This device includes a zero-sequence current transformer and a signal conditioning circuit. The zero-sequence current transformer is installed in the arc suppression coil circuit to detect the actual current flowing through the coil. The signal conditioning circuit amplifies, filters, and performs analog-to-digital conversion on the weak signal output from the transformer to obtain a digitized current value. Residual current calculation is achieved through vector operations. The detected inductive current is vector-subtracted from the known capacitive current to obtain the amplitude and phase information of the residual current. The magnitude of the residual current directly reflects the quality of the compensation effect; a smaller amplitude indicates a better compensation effect. The phase information reflects the nature of the residual current; a leading phase indicates that the capacitive component is dominant, while a lagging phase indicates that the inductive component is dominant.

[0099] The preset threshold is set based on the requirements for safe operation of the power grid and the standards for arc suppression effect. It is usually set to five percent of the capacitive current amplitude before the fault. When the residual current exceeds this threshold, the automatic fine-tuning program of the fine-tuning reactor group is triggered. The fine-tuning program first analyzes the nature of the residual current to determine whether it is capacitive overcompensation or inductive undercompensation, and then calculates the required inductance adjustment. The adjustment calculation adopts a proportional-integral control algorithm. The proportional term determines the adjustment range based on the current error magnitude, and the integral term determines the adjustment direction based on the historical error accumulation. The two terms are combined to form the control output. The control output is converted into the control current increment of the controllable saturated reactor, and the inductance value is fine-tuned by modifying the DC control current.

[0100] The process of maintaining the mutual cancellation effect of inductive and capacitive currents is achieved through continuous monitoring and dynamic adjustment. The monitoring period is set to one-tenth of the grid fundamental cycle, i.e., once every 2 milliseconds. Each monitoring obtains the current residual current value and compares it with the set range. The set range includes an upper threshold and a lower threshold. The upper threshold corresponds to the maximum allowable residual current value, and the lower threshold corresponds to the minimum compensation accuracy requirement. When the residual current is within the set range, the current adjustment state is maintained; when the residual current exceeds the set range, the corresponding adjustment program is activated. The execution priority of the adjustment program is determined according to the degree of deviation. Minor deviations are fine-tuned using a fine-tuning reactor group, while severe deviations are jointly adjusted by activating both the coarse-tuning reactor group and the fine-tuning reactor group.

[0101] In one specific embodiment, an adjustable damping resistor is connected in series in the arc suppression coil circuit to suppress series resonance overvoltage; the value of the adjustable damping resistor is determined according to the ratio of inductance to capacitance; when the system is detected to enter a resonance state, the adjustable damping resistor is automatically engaged.

[0102] The extinction state of the grounding arc is confirmed by the following verification indicators: the voltage of the faulted phase recovers to more than 95% of the rated voltage; the voltage of the non-faulted phase remains within 105% of the rated voltage; and the deviation of the product of zero-sequence voltage and zero-sequence current is controlled within 2% of the rated zero-sequence voltage.

[0103] Specifically, the activation of the damping resistor is precisely controlled through a resonance detection algorithm and a resistance value calculation program. The resonance detection algorithm continuously monitors the voltage and current waveforms in the arc suppression coil circuit, identifying the occurrence of series resonance through frequency domain analysis. A resonance state is determined when the voltage amplitude abnormally increases and the current phase is nearly in phase with the voltage phase. The calculation of the adjustable damping resistor value is based on the inductance-capacitance ratio, employing a resistance calculation method under critical damping conditions. The resistance value is equal to the square root of twice the inductance-capacitance ratio. This calculation process requires real-time acquisition of the current inductance value of the arc suppression coil and the equivalent capacitance value of the power grid. The inductance value is obtained through an inductance measurement device, which applies a high-frequency test signal to the arc suppression coil and analyzes the response characteristics to derive the inductance value. The capacitance value is obtained through parallel calculation of the capacitance to ground of each photovoltaic branch. After the resistance value calculation is completed, the adjustable damping resistor controller adjusts the activation combination of the resistor array according to the calculation results. The resistor array contains multiple resistor units with different resistance values, and the series and parallel combinations of these units are controlled by relay switches to achieve the desired resistance value. When the resonance detection algorithm confirms that a resonance state has been detected, the control signal immediately triggers the automatic switching procedure of the damping resistor. The switching process is executed at the current zero crossing point to avoid the generation of inrush current.

[0104] The verification process of the ground arc extinction state is achieved through the data collection and analysis of three key indicators. For the detection of the fault phase voltage recovery, a high-precision voltage transformer is used to monitor the real-time value of the fault phase voltage and compare it with the rated voltage for calculation. The voltage recovery rate is calculated by dividing the current voltage amplitude by the rated voltage amplitude to obtain a percentage value. When this percentage reaches or exceeds 95, it is confirmed that the fault phase voltage recovery index is qualified. The detection of the non-fault phase voltage maintenance monitors the voltage amplitude changes of the other two phases simultaneously to prevent overvoltage impact on the non-fault phases during the compensation process. The ratio of the non-fault phase voltage to the rated voltage needs to be controlled within the range of 0.95 to 1.05 to be considered qualified. The calculation process of the product deviation between the zero-sequence voltage and the zero-sequence current is more complex. It is necessary to collect the instantaneous values of the zero-sequence voltage and the zero-sequence current simultaneously and perform a product operation. The product result represents the magnitude of the zero-sequence power. In the ideal compensation state, the zero-sequence power should be close to zero. The deviation calculation is obtained by dividing the difference between the actual zero-sequence power and the theoretical zero value by the rated zero-sequence voltage to get a percentage deviation. When this deviation value is controlled within 2%, it is confirmed that the zero-sequence power index is qualified.

[0105] The data processing of the verification indicators adopts a multi-channel synchronous acquisition and real-time calculation architecture. The data acquisition channels include the fault phase voltage channel, the non-fault phase voltage channel, the zero-sequence voltage channel, and the zero-sequence current channel. Each channel uses an independent A / D converter to ensure the synchronization and accuracy of data acquisition. The acquired data is first processed by digital filtering to eliminate high-frequency noise interference, and then the effective value calculation and phase analysis are performed to obtain the amplitude and phase information of each parameter. The calculation process of the fault phase voltage recovery rate includes three steps: amplitude extraction, reference comparison, and percentage conversion. The amplitude extraction uses the root mean square algorithm to perform statistical calculations on the sampled data. The reference comparison divides the extracted amplitude by the pre-stored rated voltage value. The percentage conversion multiplies the division result by 100 to obtain the recovery rate value. The data processing of the non-fault phase voltage maintenance detection uses a range judgment algorithm. The algorithm first calculates the ratio of the non-fault phase voltage to the rated voltage, and then judges whether this ratio falls within the preset qualified range. When it exceeds the range, an unqualified signal is output and the deviation value is recorded. The calculation of the zero-sequence power deviation uses an instantaneous power integration algorithm. The algorithm performs a time integration operation on the product of the zero-sequence voltage and the zero-sequence current to obtain the average power value. The difference between the average power and the zero value is the power deviation. The ratio of the deviation value to the rated zero-sequence voltage forms the final percentage deviation index.

[0106] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic compensation switching method based on the arc suppression coil of a grounding transformer, characterized in that, The method includes: real-time acquisition and processing of zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system through multi-branch acquisition devices connected to the main control unit to obtain a set of grid operating status parameters; based on the phase relationship between zero-sequence current and zero-sequence voltage in the set of grid operating status parameters, internal and external identification processing of single-phase grounding faults is performed using a fault direction discrimination algorithm to obtain a photovoltaic internal fault confirmation signal, including: the process of internal and external identification processing of single-phase grounding faults using the fault direction discrimination algorithm is as follows: data preprocessing of zero-sequence voltage and zero-sequence current in the set of grid operating status parameters is performed using sliding window technology, with each window containing 20 sampling points; the fundamental component is extracted by fast Fourier transform, and the phase difference between zero-sequence current and zero-sequence voltage is calculated; when the angle of zero-sequence current leading zero-sequence voltage is within the range of 0 to 150 degrees, a positive internal fault identification result of the photovoltaic system is generated; when the angle of zero-sequence current lagging zero-sequence voltage is within the range of -150 degrees to 0 degrees, a reverse internal fault identification result is generated. External fault identification results; based on the positive internal fault identification results of the photovoltaic system, output the internal fault confirmation signal of the photovoltaic system; input the internal fault confirmation signal of the photovoltaic system to the arc suppression coil inductance adjustment system, and dynamically calculate the inductance value of the arc suppression coil according to the capacitive current at the fault point to obtain the compensation inductance parameters, including: calculating the required compensation capacity according to the maximum active power of the photovoltaic system, the power factor before compensation, and the target power factor; determining the target inductance value of the arc suppression coil through the system angular frequency and equivalent capacitance value; verifying the constraint condition that the arc suppression coil capacity does not exceed 20% of the rated capacity of the transformer; confirming that the zero-sequence voltage drop generated by the zero-sequence current flowing through the arc suppression coil in the transformer does not exceed 10% of the rated phase voltage; generating the compensation inductance parameters based on the constraint condition; based on the compensation inductance parameters, adjusting the inductance of the arc suppression coil through a thyristor-controlled graded reactor combination, so that the inductive current generated by the arc suppression coil and the capacitive current at the fault point can cancel each other out, and the grounding arc is extinguished.

2. The method according to claim 1, characterized in that, The multi-branch data acquisition unit connected through the main control unit performs real-time acquisition and processing of the zero-sequence voltage, zero-sequence current, and line impedance of the photovoltaic system. This includes: branch 1 data acquisition unit, branch 2 data acquisition unit, and branch 3 data acquisition unit are respectively connected to the corresponding photovoltaic branch; each branch data acquisition unit is equipped with an independent A / D conversion module, and the sampling frequency is set to 10kHz; the main control unit establishes a communication connection with each branch data acquisition unit through the grounding transformer controller to form a multi-branch parallel monitoring network, and records the amplitude and phase information of the zero-sequence component in real time; a power grid-to-ground capacitance current database is established to store the capacitance current variation law under different operating conditions, and obtain a set of power grid operating status parameters.

3. The method according to claim 1, characterized in that, The process of adjusting the inductance of the arc suppression coil by the thyristor-controlled graded reactor group is as follows: the coarse-adjustment reactor group receives the compensation inductance parameters and completes the adjustment of the basic inductance value within 5ms; the fine-adjustment reactor group realizes continuous fine-tuning of the inductance through PWM control and completes the fine-tuning process within 15ms. The compensation effect verification module completes the compensation effect detection within 10ms; the total response time of the coarse adjustment reactor group, the fine adjustment reactor group and the compensation effect verification module is controlled within 30ms; the inductance adjustment within the total response time enables the inductive current generated by the arc suppression coil to cancel out the capacitive current at the fault point.

4. The method according to claim 3, characterized in that, The coordinated control process of the coarse-adjustment reactor group and the fine-adjustment reactor group is as follows: the coarse-adjustment reactor group includes multi-stage thyristor switching reactors, and the fine-adjustment reactor group adopts controllable saturated reactors; the residual current after compensation is monitored in real time through a closed-loop control system; when the residual current exceeds a preset threshold, the fine-adjustment reactor group automatically performs inductance fine-tuning; ensuring that the mutual cancellation effect of the inductive current and capacitive current is maintained within the set range.

5. The method according to claim 1, characterized in that, Also includes: An adjustable damping resistor is connected in series in the arc suppression coil circuit to suppress series resonance overvoltage; the value of the adjustable damping resistor is determined according to the ratio of inductance to capacitance; when the system is detected to enter a resonance state, the adjustable damping resistor is automatically activated.

6. The method according to claim 1, characterized in that, The extinction state of the grounding arc is confirmed by the following verification indicators: the voltage of the faulted phase recovers to more than 95% of the rated voltage; the voltage of the non-faulted phase remains within 105% of the rated voltage; and the deviation of the product of zero-sequence voltage and zero-sequence current is controlled within 2% of the rated zero-sequence voltage.

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