Three-phase voltage type pwm rectifier control system with adaptive dynamic response optimization

Abstract

The application discloses a three-phase voltage type PWM rectifier control system with adaptive dynamic response optimization, and relates to the technical field of power electronics.The application comprises a monitoring module, a prediction module, a dynamic adjustment module, an execution module, a parallel compensation module and a cycle determination module; the monitoring module is used for monitoring the grid voltage, current and load change in real time through a sensor; voltage sensors, current sensors and power sensors are installed at the input end and the output end of the three-phase voltage type PWM rectifier, so that the voltage, current and power change of the grid can be comprehensively monitored; the application significantly improves the response speed and accuracy of the system to the grid voltage fluctuation and load change; the prediction module uses an advanced algorithm to analyze the short-term change trend of the grid and load, so that the system can timely adjust the control strategy, thereby maintaining the stability of the DC side voltage and improving the power quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power electronics, specifically a three-phase voltage-type PWM rectifier control system with adaptive dynamic response optimization. BACKGROUND

[0002] Existing three-phase voltage-type PWM rectifier control systems are widely used in situations requiring high power factor, low harmonic pollution, and bidirectional energy flow. These systems can effectively regulate output DC voltage and current by precisely controlling the switching state of the rectifier, adapting to grid voltage fluctuations and load changes. However, traditional rectifier control systems have limitations in dynamic response, especially in complex grid conditions or sudden load changes, which may not adjust the output in time, affecting system stability and power quality.

[0003] Although existing technologies meet the basic needs of power electronic systems to some extent, there are still some key problems. First, the dynamic response speed of traditional control systems is often insufficient to cope with rapidly changing grid environments, leading to DC side voltage fluctuations and affecting system stability. Second, the system is complex in parameter design and control strategy selection, requiring a large number of experiments and simulations to determine, which increases the difficulty and cost of system design. In addition, the performance of existing systems in grid imbalance or harmonic pollution needs to be improved, and circulating current problems may occur when operating in parallel, affecting system efficiency.

[0004] To solve the above-mentioned defects, the technical scheme is provided. SUMMARY

[0005] The present application aims to solve the limitations of existing three-phase voltage-type PWM rectifier control systems in dynamic response, grid adaptability, and power quality, and proposes a three-phase voltage-type PWM rectifier control system with adaptive dynamic response optimization.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] The three-phase voltage-type PWM rectifier control system with adaptive dynamic response optimization comprises:

[0008] A monitoring module for real-time monitoring of grid voltage, current, and load changes through sensors;

[0009] A prediction module for running a prediction algorithm using collected data to analyze short-term trends in grid and load changes;

[0010] A dynamic adjustment module for calculating control parameter adjustments based on prediction results and generating PWM control signals;

[0011] The execution module is configured to input the PWM control signal into the rectifier and adjust the working state of the rectifier in response to changes in the power grid and the load.

[0012] The parallel compensation module is configured to monitor the DC side voltage of the parallel compensation circuit in real time and intervene in energy compensation as soon as the voltage is detected to be out of the preset range.

[0013] The cycle determination module is configured to adjust and compensate the frequency according to the system response feedback.

[0014] Further, the monitoring module monitors the power grid voltage, current and load change in real time through the sensor in the following specific steps:

[0015] The voltage, current and power sensors are installed at the input and output ends of the rectifier to comprehensively monitor the power grid parameters.

[0016] The data acquisition system is started to collect sensor data in real time, amplify, filter and analog-digital convert the original signal, and synchronize the sensor data for eliminating noise and adapting to digital processing.

[0017] The conditioned signal is transmitted to the central processing unit to execute the real-time monitoring algorithm and monitor the power grid state.

[0018] The monitoring data is stored for use by the historical analysis and prediction module, and the abnormality detection algorithm is run to immediately issue a warning when the power grid parameters are detected to be abnormal.

[0019] The sensors and data links are regularly self-checked to ensure the accuracy and reliability of the monitoring system.

[0020] Further, the specific operation steps of regularly self-checking the sensors and data links in the monitoring module are as follows:

[0021] The self-checking frequency, inspection items and parameters are determined, and the self-checking is performed according to the preset order.

[0022] The power supply, circuit and interface states of the sensors and data acquisition cards are checked, the response accuracy of the sensors is tested by using a standard signal source, zero point calibration and range linearity test are performed to ensure that the sensor output is proportional to the input.

[0023] The sensor accuracy is verified by comparing the measured value with the theoretical value, the denoising effect of the filter is tested to see whether it meets the standard, and the conversion accuracy and sampling rate of the analog-digital converter are verified.

[0024] The data of different sensors or the same sensor at different times are compared to ensure consistency and repeatability, and the communication stability and data integrity between the sensors and the processing unit are checked.

[0025] Run diagnostic programs to verify the correctness of data processing and transmission logic, simulate faults, test alarm and response mechanisms, record self-test results, and perform corresponding maintenance and calibration.

[0026] Further, the specific operation steps of the prediction module analyzing the short-term change trend of the power grid and the load are as follows:

[0027] Convert three-phase voltage and current data to two-phase stationary coordinate system through mathematical transformation, and use software phase-locked loop to obtain synchronization information;

[0028] Based on the working model of the rectifier, a prediction model is constructed to describe the trend of system state change;

[0029] Select time series analysis, machine learning or model predictive control algorithm for prediction, and optimize parameters according to prediction error;

[0030] Run the prediction algorithm, combine current and historical data, and predict the change of power grid voltage, current and load in the short term;

[0031] Analyze the prediction results, evaluate the potential fluctuations or mutations of the power grid and the load, and determine whether the control strategy needs to be adjusted;

[0032] Feedback the prediction results to the dynamic adjustment module to provide data support for control parameter adjustment;

[0033] According to the actual response of the system, calibrate the prediction model, analyze the reasons for the prediction deviation, and optimize it.

[0034] Further, the specific operation steps of the prediction module according to the actual response of the system to calibrate the prediction model, analyze the reasons for the prediction deviation, and optimize it are as follows:

[0035] Collect actual operation data and compare with prediction results, quantify prediction deviation, analyze statistical characteristics of deviation, and identify deviation mode;

[0036] Adjust model parameters according to analysis results, including coefficients, weights and optimization targets, and evaluate the impact of parameter adjustment on prediction accuracy;

[0037] Use new parameters to retrain the model, adapt to changes in power grid and load, evaluate the prediction accuracy of the calibrated model, ensure the improvement effect, apply the calibrated model to real-time prediction, and fine-tune according to feedback;

[0038] Record calibration activities, including parameter adjustment and effect, and analyze the root causes of prediction deviation;

[0039] According to the results of cause analysis, optimize the model structure and algorithm, continuously monitor the model performance, and regularly perform iterative optimization.

[0040] Further, the period determination module adjusts and compensates the frequency according to the system response feedback, and the specific operation steps are as follows:

[0041] The dynamic response parameters of the monitoring system include:

[0042] Output DC voltage: monitor the stability and deviation of the DC side voltage, and quantify the stability by the deviation, and record the deviation as the voltage deviation value;

[0043] Total harmonic distortion of input AC current: measure the quality of current waveform, and quantify it by total harmonic distortion, recorded as harmonic loss value;

[0044] Power factor: evaluate the phase difference between input current and voltage;

[0045] Symmetry of current waveform: monitor the balance degree of three-phase current, and quantify it by balance degree percentage;

[0046] Variation rate of load current: obtain a group of values by the variation of load current at different times, calculate the variance of the group of values, recorded as electric variation value, and use the electric variation value as the measure of the variation rate of load current;

[0047] After normalizing the voltage deviation value, harmonic loss value, phase difference, balance degree percentage and electric variation value, the combined judgment value is calculated by the formula, and the combined judgment value is used as the standard of system response feedback;

[0048] The combined judgment value is compared with the preset several combined judgment value intervals, and the several combined judgment value intervals correspond to different adjustment and compensation frequencies, and when the combined judgment value interval is determined, the corresponding adjustment and compensation frequency is determined, and the determined adjustment and compensation frequency is used for corresponding data monitoring.

[0049] Further, the dynamic adjustment module calculates the control parameter adjustment according to the prediction result, and the specific operation steps of generating PWM control signal are as follows:

[0050] Obtain the power grid and load change prediction provided by the prediction module, set the power factor, harmonic content and DC side voltage stability control target;

[0051] Apply control algorithm to calculate the duty cycle, frequency and phase parameters of PWM signal, generate PWM control signal according to the calculation result, and use it to adjust the rectifier state;

[0052] Combine the real-time data of the monitoring module, continuously optimize the control parameters, send the PWM control signal to the execution module, execute accurate control, receive the feedback information of the monitoring module, and correct the corresponding control parameters.

[0053] Further, the execution module inputs the PWM control signal into the rectifier, adjusts the working state of the rectifier, and the specific operation steps are as follows:

[0054] The PWM control signal is received from the dynamic adjustment module, the corresponding control parameters are parsed, the IGBT and MOSFET devices are driven to perform switching operation according to the PWM signal, the operation of the power device is ensured to be synchronized with the power grid, the input current and DC voltage of the rectifier are controlled;

[0055] The feedback data of the monitoring module is used to dynamically adjust the PWM signal and optimize the performance of the rectifier;

[0056] The protection mechanism is executed to protect the rectifier;

[0057] The state of the power device is monitored, the operation data is collected, and the monitoring and dynamic adjustment modules are fed back;

[0058] The execution effect is evaluated to ensure that it meets the control target and forms a continuous control cycle.

[0059] Further, the protection mechanism in the execution module is as follows:

[0060] The safety threshold parameters of overcurrent, short circuit and overheating are determined, the current, voltage and temperature are continuously monitored to ensure that they do not exceed the safety threshold;

[0061] The monitoring parameters are programmed to automatically start protection when they exceed the threshold, and overcurrent, short circuit and overheating protection circuits are deployed to ensure rapid response;

[0062] Fault detection and protection actions are monitored and executed by software, faults are identified by fault identification algorithm, and shutdown device, circuit disconnection or load reduction protection actions are executed;

[0063] When the protection is triggered, an alarm is sent and an indication is given on the user interface.

[0064] Further, the specific operation steps of the parallel compensation module for energy compensation are as follows:

[0065] The DC side voltage is continuously monitored by the sensor, the real-time monitored DC side voltage is compared with the preset safety range, and when the DC side voltage exceeds the range, the energy compensation mechanism is started;

[0066] The parallel capacitor or reactor is adjusted to absorb or provide reactive power, and in the compensation process, the generation of harmonics is suppressed, and the monitoring module and the execution module are coordinated to ensure system response consistency;

[0067] An automatic control logic is set, a manual operation interface is provided, the compensation result is fed back to the monitoring module and the dynamic adjustment module, and the system performance is evaluated and adjusted.

[0068] Compared with the prior art, the present application has the following advantages:

[0069] The present application significantly improves the response speed and accuracy of the system to grid voltage fluctuations and load changes. The prediction module uses advanced algorithms to analyze the short-term trends of the grid and load, ensuring that the system can adjust the control strategy in time to maintain the stability of the DC side voltage and improve power quality.

[0070] The present application, the execution module combines real-time monitoring data to dynamically adjust the PWM control signal, realizes the accurate control to the rectifier working state, simultaneously, through the implementation protection mechanism, such as overcurrent, short circuit and overheat protection, ensures that the rectifier can safely run under abnormal condition, not only improves the operation efficiency of the system, also greatly enhances the safety and reliability of the system, and the intervention of parallel compensation module further optimizes the stability of DC side voltage, simultaneously restrains the possible generated harmonic, guarantees the clean and efficient operation of the grid.

[0071] The present application also has a periodic self-checking function. The monitoring module periodically checks the sensors and data link to ensure the accuracy and reliability of the monitoring system, simplifies the maintenance work and reduces human errors. The cycle determination module automatically sets the adjustment frequency of the PWM according to the actual response of the system, reducing the need for manual intervention and improving the intelligence level of the system. The system continuously learns and calibrates itself to optimize control parameters, ensuring high efficiency and adaptability in long-term operation. BRIEF DESCRIPTION OF DRAWINGS

[0072] For the convenience of those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0073] Figure 1 The present application is a system block diagram. DETAILED DESCRIPTION

[0074] The technical solutions of the present application will be described below in conjunction with embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0075] It should be understood that the terms "include" and "contain" used in the specification and claims of the present disclosure indicate the presence of the described features, whole, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof.

[0076] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0077] like Figure 1 As shown, the adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system includes a monitoring module, a prediction module, a dynamic adjustment module, an execution module, a parallel compensation module, and a period determination module.

[0078] The monitoring module is used to monitor changes in grid voltage, current, and load in real time via sensors;

[0079] Voltage sensors, current sensors, and power sensors are installed at the input and output terminals of a three-phase voltage-source PWM rectifier to comprehensively monitor changes in the voltage, current, and power of the power grid. Data acquisition is initiated, and the sensors collect data on the grid voltage, current, and load power in real time, ensuring that the data acquisition frequency meets the requirements of the system's dynamic response.

[0080] The acquired raw signals are conditioned, including amplification, filtering, and analog-to-digital conversion, to eliminate noise and obtain signals suitable for digital processing. Data from all sensors is synchronized in time for subsequent processing and analysis. The conditioned signal data is then transmitted to a central processing unit (CPU), such as a microcontroller or digital signal processor (DSP), where real-time monitoring algorithms are implemented to continuously monitor changes in grid voltage, current, and load, ensuring timely detection of any grid anomalies. The monitored data is stored in the system for use by historical data analysis and prediction modules. An anomaly detection algorithm is implemented; if grid voltage or current exceeds the preset normal operating range, an immediate warning is issued, and preparations are made to trigger subsequent predictions and adjustments. The installed sensors and transmission links undergo regular self-testing to ensure their accuracy and reliability. The specific process is as follows:

[0081] Develop a detailed self-check plan and process, including the frequency of self-check, the items and parameters of the check, etc. Check the hardware status of the sensor and data acquisition card, including power supply, connection line, interface, etc. Test the sensor using a known signal source to ensure that the sensor can accurately measure and respond to the given signal. Calibrate the zero point of the sensor to ensure that the output of the sensor is zero or a preset reference value when there is no signal input. Gradually increase the input signal to the maximum range of the sensor and check whether the output of the sensor is proportional to the input to ensure the linearity of the range. Verify the accuracy and resolution of the sensor by comparing the output of the sensor with the theoretical value or the measured value of the calibration device. Check whether the filter in the signal conditioning process can effectively filter out noise to ensure signal quality.

[0082] Test the analog-to-digital converter (ADC) to ensure that its conversion accuracy and sampling rate meet the system requirements. Compare the data collected by different sensors or the same sensor at different times to ensure the consistency and repeatability of the data. Check the communication link between the sensor and the central processing unit, including the stability of wireless or wired connection and the integrity of data transmission. Run diagnostic software or scripts to test the software of the data acquisition system and check whether the logic of data processing and transmission is correct. Simulate abnormal signals or fault conditions to check whether the alarm and response mechanism of the system is working properly. Record the problems found during the self-checking process and the maintenance measures to provide a reference for future maintenance and upgrading. According to the self-checking results and the manufacturer's recommendations, regularly maintain and calibrate the sensor and data acquisition system.

[0083] The prediction module is used to run prediction algorithms using collected data to analyze short-term trends in the power grid and load;

[0084] Convert three-phase grid voltage and input current data to two-phase stationary coordinate system through mathematical transformation (such as 3 / 2 transformation) to simplify subsequent processing. Use software phase-locked loop technology to obtain the position angle of the grid voltage to provide necessary synchronization information for current prediction and control. According to the working principle and mathematical model of the rectifier, construct a model suitable for the prediction module, which can describe the trend of system state. Pre-set prediction algorithms, including time series analysis, machine learning or model predictive control (MPC), etc. to predict short-term changes in the power grid and load. Optimize the parameters of the prediction model and algorithm according to the prediction error and system performance requirements to improve the prediction accuracy.

[0085] The running prediction algorithm uses current and historical data to predict the changes in grid voltage, current, and load in the next control cycle. The prediction results are analyzed to determine whether there are potential grid fluctuations or load mutations, and whether the control strategy needs to be adjusted in advance. The prediction results are fed back to the dynamic adjustment module to provide a basis for adjusting the control parameters, ensuring that the rectifier can respond to changes in the grid and load in a timely manner. At the same time, the prediction model is calibrated according to the actual system response to analyze the causes of prediction deviation and optimize it for more accurate prediction. The specific process is as follows:

[0086] After the prediction algorithm runs, the rectifier's running data under actual grid conditions, including voltage, current, and power parameters, are collected. The prediction results are compared and analyzed with the actual system response data to find the deviation between the predicted and actual values. Statistical analysis of the deviation data, including the size, direction, distribution, and other characteristics of the deviation, is performed to identify the pattern and rules of the deviation. Based on the deviation analysis results, it is determined whether the prediction model needs to be calibrated, as well as the specific direction and degree of calibration. The parameters of the prediction model, such as the coefficients of time series models, the weights of machine learning models, and the optimization objectives of model predictive control, are adjusted for sensitivity analysis to evaluate the impact of model parameter adjustment on prediction accuracy, ensuring that parameter adjustment can significantly reduce prediction deviation.

[0087] The prediction model is retrained using the adjusted parameters to adapt to new grid and load conditions. The retrained model is evaluated to verify whether the calibration has improved the accuracy of the prediction. The calibrated model is applied to online prediction to monitor the prediction effect in real time and make further fine-tuning based on system feedback. The details of all calibration activities, including adjusted parameters, calibration effects, and any observed changes in model behavior, are recorded for in-depth analysis of the causes of prediction deviation, which may include model structure deficiencies, data quality issues, external disturbances, etc. Based on the results of the deviation cause analysis, the model is optimized, which may include improving the model structure, enhancing data preprocessing, introducing new prediction algorithms, etc. The performance of the prediction model is continuously monitored, and the model is iteratively optimized regularly based on changes in grid and load conditions.

[0088] The dynamic adjustment module is used to calculate control parameter adjustments based on the prediction results and generate PWM control signals.

[0089] Receiving grid and load change prediction data from the prediction module, which includes information such as predicted grid voltage changes, load current changes, etc., defining performance indicators such as power factor, harmonic content, DC side voltage stability, etc. according to system requirements, and setting corresponding control targets; using prediction data and performance indicators, calculate the required control parameter adjustment value through control algorithm (such as PID control, fuzzy control, neural network control, etc.), these control parameters may include PWM modulation signal duty cycle, frequency, phase, etc.

[0090] According to the calculated control parameters, generate corresponding PWM control signals, which will be used to control the power devices of the rectifier to adjust the working state of the rectifier; then obtain the real-time data obtained by the monitoring module, and continuously optimize the control parameters according to the latest monitoring data and prediction results to ensure that the rectifier control system quickly responds to the actual changes of the grid and load;

[0091] The generated PWM control signals are transmitted to the execution module to adjust the switching state of the power devices of the rectifier, so as to realize accurate control of the working state of the rectifier; after the execution module adjusts the working state of the rectifier, the monitoring module will monitor the grid voltage, current and load changes in real time, and feed back these information to the dynamic adjustment module for necessary correction and adjustment.

[0092] The execution module is used to input PWM control signals to the rectifier and adjust the working state of the rectifier to respond to grid and load changes;

[0093] First, receive the PWM control signals generated by the dynamic adjustment module, which contain all the information needed to adjust the working state of the rectifier, analyze the PWM control signals and extract the key parameters needed to control the rectifier, such as switching time of switching devices, duty cycle of PWM wave, etc.; according to the analyzed PWM control signals, drive power devices (such as IGBT, MOSFET, etc.) to switch, these operations will directly affect the input current and DC side voltage of the rectifier, ensure that the switching operation of the power device is synchronized with the grid to avoid invalid switching actions and potential damage;

[0094] According to the real-time data feedback by the monitoring module, dynamically adjust the PWM control signal to realize accurate control of the working state of the rectifier; implement protection mechanisms such as overcurrent protection, short circuit protection and overheat protection to ensure the safe operation of the rectifier under abnormal conditions, the specific steps are as follows:

[0095] The parameters of the protection measures, including the thresholds of overcurrent, short circuit and overheating, are determined, the current, voltage and temperature of the power device are monitored in real time to ensure that they are below the protection thresholds, and the protection logic is set in the execution module. When the monitored parameters exceed the preset thresholds, the protection mechanism is automatically triggered, and the preset hardware protection circuits, such as overcurrent protection circuit, short circuit protection circuit and overheating protection circuit, are ensured to respond quickly in abnormal conditions. According to the real-time monitoring of the power device by the software protection program and the execution of the protection action, the fault detection algorithm is used to quickly identify the fault type when an abnormal condition is detected, and the protection action is executed, such as shutting down the power device, disconnecting the circuit or reducing the load, etc. In the case of serious abnormal conditions, system isolation is performed to ensure that the fault does not spread to other parts, and an alarm signal is sent when the protection measures are triggered, and the corresponding indication is provided on the user interface.

[0096] The execution module monitors the working state and possible abnormal conditions of the power device while adjusting the working state of the rectifier, collects the running state information of the power device, including current, voltage, etc., and feeds back these information to the monitoring module and dynamic adjustment module; the execution result is evaluated to ensure that the working state of the rectifier meets the expected control target, and a continuous cycle process is formed through the operation of the execution module to continuously receive new control signals and respond to adapt to the continuous changes of the power grid and the load.

[0097] The parallel compensation module is used to monitor the DC side voltage in real time, and once the voltage is detected to exceed the preset range, it immediately intervenes to compensate energy;

[0098] The DC side voltage is monitored in real time by high sensitivity sensors to ensure that any change in voltage can be responded in time, and the monitored DC side voltage is compared with the preset safe range to judge whether the voltage exceeds the normal working interval; once the DC side voltage is detected to exceed the preset range, the energy compensation mechanism is immediately started to maintain voltage stability, and the parallel compensation device, such as parallel capacitor or parallel reactor, is controlled to absorb or provide necessary reactive power by adjusting its working state, so as to compensate the DC side voltage;

[0099] While performing reactive power compensation, attention should be paid to suppress possible harmonics to ensure that power quality is not affected, and the parallel compensation module needs to work with other modules in the system, such as monitoring module, execution module, etc., to ensure the consistency and effectiveness of the whole system response; the preset automatic control logic is used to realize unattended operation, and the manual intervention interface is provided for operation when necessary, and necessary protection measures, such as overload protection, short circuit protection, etc., are implemented during the compensation process to ensure system safety, and the compensated data is fed back to the monitoring module and dynamic adjustment module for further system performance evaluation and adjustment.

[0100] The period determination module is used for adjusting and compensating the frequency according to the system response feedback;

[0101] The dynamic response parameters of the monitoring system are monitored, including:

[0102] The output DC voltage: the stability and deviation of the DC side voltage are monitored, and the stability is quantified by the deviation, and the deviation is recorded as the voltage deviation value; the total harmonic distortion (THD) of the input AC current: the quality of the current waveform is measured, and the total harmonic distortion (THD) is quantified, recorded as the harmonic loss value, and when the THD is higher, the frequency of the adjustment PWM strategy needs to be improved to reduce the harmonic; the power factor: the phase difference between the input current and the voltage is evaluated, and the low power factor may need to adjust the PWM control to improve the power quality; the symmetry of the current waveform: the balance degree of the three-phase current is monitored, and the balance degree percentage is quantified, and the asymmetric current waveform may need to adjust the PWM frequency to achieve balance; the change rate of the load current: the fast-changing load may need faster response time, which can be achieved by adjusting the PWM frequency, and the change of the load current is obtained through different time to get a group of values, and the variance of the group of values is calculated, recorded as the electric variable value, and the electric variable value is used as the measure of the change rate of the load current;

[0103] The voltage deviation value, the harmonic loss value, the phase difference, the balance degree percentage and the electric variable value are respectively marked as yo, xw, wg, pb and db, and the normalized processing is put into the following formula:

[0104] To get the combined judgment value HPZ, wherein The preset weight coefficients of the voltage deviation value, the harmonic loss value, the phase difference, the balance degree percentage and the electric variable value are respectively; and the combined judgment value obtained is used as the standard for measuring the system response feedback; the combined judgment value HPZ obtained is compared with a plurality of preset combined judgment value intervals, and different adjustment and compensation frequencies are set corresponding to the plurality of combined judgment value intervals, when the combined judgment value interval to which the combined judgment value HPZ belongs is determined, the corresponding adjustment and compensation frequency is determined, and the corresponding data monitoring is performed at the determined adjustment and compensation frequency.

[0105] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details, nor limit the application to the specific embodiments. Obviously, many modifications and changes can be made according to the content of the present application. The embodiments are selected and described in detail in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited by the claims and their entire scope and equivalents.

Claims

1. A three-phase voltage-source PWM rectifier control system with adaptive dynamic response optimization, characterized in that, include: The monitoring module is used to monitor changes in grid voltage, current, and load in real time through sensors; The forecasting module is used to run forecasting algorithms based on the collected data to analyze short-term trends in the power grid and load. The specific operation steps are as follows: The three-phase voltage and current data are transformed into a two-phase stationary coordinate system through mathematical transformation, and synchronization information is obtained using a software phase-locked loop. Based on the rectifier's working model, a predictive model is constructed to describe the trend of system state changes. Choose time series analysis, machine learning, or model predictive control algorithms for prediction, and optimize parameters based on prediction errors; Run the prediction algorithm and combine current and historical data to predict changes in grid voltage, current and load in the short term; Analyze the forecast results, assess potential fluctuations or abrupt changes in the power grid and load, and determine whether the control strategy needs to be adjusted. The prediction results are fed back to the dynamic adjustment module to provide data support for adjusting the control parameters; Based on the actual system response, calibrate the prediction model, analyze the causes of prediction deviations, and optimize it. The dynamic adjustment module is used to calculate and adjust control parameters based on the prediction results and generate PWM control signals. The specific operation steps are as follows: Obtain power grid and load change predictions provided by the prediction module, and set power factor, harmonic content, and DC side voltage stability control targets; The application control algorithm calculates the duty cycle, frequency, and phase parameters of the PWM signal, and generates a PWM control signal based on the calculation results to adjust the rectifier state. By combining real-time data from the monitoring module, the control parameters are continuously optimized, and the PWM control signal is sent to the execution module to perform precise control. The module also receives feedback information from the monitoring module and performs corresponding control parameter corrections. The execution module is used to input PWM control signals into the rectifier and adjust the rectifier's operating state in response to changes in the power grid and load. The parallel compensation module is used to monitor the DC-side voltage in real time in the parallel compensation circuit. Once the voltage exceeds the preset range, it immediately intervenes to perform energy compensation. The specific operation steps are as follows: The DC-side voltage is continuously monitored by sensors, and the real-time monitored DC-side voltage is compared with a preset safety range. When the DC-side voltage exceeds the range, the energy compensation mechanism is activated. Adjusting parallel capacitors or reactors absorbs or provides reactive power, suppresses harmonic generation during compensation, and works in conjunction with monitoring and execution modules to ensure consistent system response. Automatic control logic is set up, while a manual operation interface is provided. The compensation results are fed back to the monitoring module and the dynamic adjustment module for system performance evaluation and adjustment. The period determination module is used to adjust and compensate for the set frequency based on the system response feedback. The specific operation steps are as follows: The dynamic response parameters of the monitoring system include: Output DC voltage: Monitor the stability and deviation of the DC side voltage, quantify the stability through the deviation, and record the deviation as the voltage bias value; Total harmonic distortion of input AC current: measures the quality of the current waveform and is quantified by total harmonic distortion, denoted as harmonic distortion value; Power factor: Evaluates the phase difference between the input current and voltage; Symmetry of current waveform: Monitor the balance of three-phase current and quantify it as a percentage of balance. The rate of change of load current: The change of load current is obtained by taking a set of values ​​over different time periods, calculating the variance of the set of values, and recording it as the electrical change value. This electrical change value is used as a measure of the rate of change of load current. The obtained bias value, harmonic loss value, phase difference, balance percentage and electrical change value are then normalized and calculated using a formula to obtain the combined judgment value, which is then used as the standard for measuring the system response feedback. The obtained combined judgment value is compared with several preset combined judgment value intervals. Different adjustment and compensation frequencies are set for each of the several combined judgment value intervals. Once the combined judgment value interval to which the combined judgment value belongs is determined, the corresponding adjustment and compensation frequency is determined, and the corresponding data monitoring is carried out at the determined adjustment and compensation frequency.

2. The adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system according to claim 1, characterized in that, The specific steps of the monitoring module in real-time monitoring of grid voltage, current, and load changes via sensors are as follows: Voltage, current, and power sensors are installed at the input and output terminals of the rectifier to achieve comprehensive monitoring of grid parameters; Start the data acquisition system to collect sensor data in real time, amplify, filter and convert the raw signal to digital, synchronize the data of each sensor, and use it to eliminate noise and adapt to digital processing; The conditioned signal is transmitted to the central processing unit to execute real-time monitoring algorithms and monitor the power grid status. It stores monitoring data for use by historical analysis and prediction modules, runs anomaly detection algorithms, and immediately issues warnings when abnormal power grid parameters are detected. Regularly perform self-tests on sensors and data links to ensure the accuracy and reliability of the monitoring system.

3. The adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system according to claim 2, characterized in that, The specific steps for the monitoring module to periodically perform self-checks on the sensors and data links are as follows: Define the self-test frequency, test items, and parameters, and execute them in the preset order; Check the power supply, wiring, and interface status of the sensor and data acquisition card; test the sensor's response accuracy using a standard signal source; perform zero-point calibration and range linearity testing to ensure that the sensor output is proportional to the input. By comparing the measured values ​​with the theoretical values, the accuracy of the sensor is verified, the noise reduction effect of the filter is checked to see if it meets the standard, and the conversion accuracy and sampling rate of the analog-to-digital converter are verified. Compare data from different sensors or the same sensor at different times to ensure consistency and repeatability, and check the communication stability and data integrity between the sensor and the processing unit; Run diagnostic programs to verify the correctness of data processing and transmission logic, simulate faults, test alarm and response mechanisms, record self-test results, and perform corresponding maintenance and calibration.

4. The adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system according to claim 1, characterized in that, The specific steps of the prediction module in calibrating the prediction model, analyzing the causes of prediction deviations, and optimizing it based on the actual system response are as follows: Collect actual operational data and compare it with the prediction results to quantify the prediction deviation, analyze the statistical characteristics of the deviation, and identify the deviation pattern. Adjust the model parameters based on the analysis results, including coefficients, weights and optimization objectives, and evaluate the impact of parameter adjustments on prediction accuracy; The model is retrained using new parameters to adapt to changes in the power grid and load. The accuracy of the calibrated model is evaluated to ensure the improvement. The calibrated model is then applied to real-time forecasting and fine-tuned based on feedback. Record calibration activities, including parameter adjustments and effects, and analyze the root causes of prediction deviations; Based on the root cause analysis results, optimize the model structure and algorithm, continuously monitor model performance, and conduct iterative optimizations periodically.

5. The adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system according to claim 1, characterized in that, The execution module inputs the PWM control signal to the rectifier and adjusts the rectifier's operating state to respond to changes in the power grid and load. The specific operation steps are as follows: The system receives PWM control signals from the dynamic adjustment module, parses the corresponding control parameters, and drives IGBT and MOSFET devices to perform switching operations based on the PWM signals, ensuring that the operation of power devices is synchronized with the power grid and controlling the rectifier input current and DC voltage. By utilizing feedback data from the monitoring module, the PWM signal is dynamically adjusted to optimize rectifier performance; Protective measures are implemented through protection mechanisms to ensure rectifier safety; Monitor the status of power devices, collect operating data, and feed it back to the monitoring and dynamic adjustment module; Evaluate the effectiveness of implementation to ensure compliance with control objectives and establish a continuous control cycle.

6. The adaptive dynamic response optimized three-phase voltage-source PWM rectifier control system according to claim 5, characterized in that, The protection mechanism process in the execution module is as follows: Define the safety threshold parameters for overcurrent, short circuit, and overheating, and continuously monitor current, voltage, and temperature to ensure that they do not exceed the safety thresholds; Program the execution module to automatically activate protection when monitored parameters exceed thresholds, deploy overcurrent, short circuit, and overheat protection circuits to ensure rapid response; The software monitors and executes fault detection and protection actions, identifies faults through fault identification algorithms, and executes protection actions such as shutting down devices, disconnecting circuits, or reducing load. An alarm is triggered when protection is activated, and a notification is displayed on the user interface.

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