Inverter Dynamic Control Method Applicable to Grid-Connected Photovoltaic Power Resources

Abstract

This application relates to the field of inverter control technology, specifically to an inverter dynamic control method applicable to the grid connection of photovoltaic power resources. The method includes: collecting voltage signals, current signals, equivalent inductance, and inverter filter capacitors; performing frequency division processing on the voltage signals and current signals by frequency, and transmitting the separated signal components to different control layer modules respectively; constructing an objective function of the MPC algorithm based on the change characteristics of the separated high-frequency signal components to output a high-frequency compensation amount; dynamically adjusting the bandwidth of the ESO in the ILADRC algorithm based on the grid equivalent inductance and the inverter filter capacitor to obtain a low-frequency compensation amount; weighting all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain a comprehensive control amount; and performing dynamic control on the inverter. This application aims to control the inverter through multi-band collaboration.

Description

Technical Field

[0001] This application relates to the field of inverter control technology, and specifically to an inverter dynamic control method applicable to grid connection of photovoltaic power resources. Background Art

[0002] Grid connection of photovoltaic power resources means that after converting the direct current generated by a solar photovoltaic power generation system into alternating current, through specific technologies and equipment, it is connected to the public power grid to achieve the coordinated operation of solar power generation and the power grid, enabling solar power generation to provide power for the power grid and meet the electricity demand of users. The main function of an inverter is to convert direct current into alternating current, which plays a crucial role in a photovoltaic power generation system and is one of the key devices for realizing photovoltaic grid connection.

[0003] There are various disturbances in a photovoltaic inverter system, referring to all uncertain factors or interference signals that can affect the normal operation of the system, the quality of the output electric energy, and the control performance. According to the frequency range, they can be divided into high-frequency disturbances and low-frequency disturbances. High-frequency disturbances will cause high-frequency harmonics to appear in the output current and voltage waveforms, resulting in poor power quality, and may also make it difficult for the output signal of the inverter to synchronize with the grid signal, leading to unstable phenomena during the grid connection process; low-frequency disturbances will cause changes in the output power of the solar panels, thereby causing fluctuations in the output power of the inverter, and may also slow down the dynamic response of the photovoltaic grid-connected system, taking a longer time to return to a stable state. Summary of the Invention

[0004] In view of the above, it is necessary to provide an inverter dynamic control method applicable to grid connection of photovoltaic power resources to solve the above problems.

[0005] An embodiment of this application provides an inverter dynamic control method applicable to grid connection of photovoltaic power resources, and the method includes:

[0006] A data acquisition layer for acquiring voltage signals, current signals, equivalent inductance, and inverter filter capacitors;

[0007] A frequency domain segmentation layer connected to the data acquisition layer for frequency-dividing the voltage signal and the current signal through frequency, and transmitting the separated signal components to different control layer modules respectively;

[0008] A composite control layer connected to the frequency domain segmentation layer, including an MPC module and an ILADRC module;

[0009] The MPC module is used to construct an objective function of the MPC algorithm based on the change characteristics of the separated high-frequency signal components, and output a high-frequency compensation amount using the MPC algorithm;

[0010] The ILADRC module is used to dynamically adjust the bandwidth of the ESO in the ILADRC algorithm based on the equivalent inductance of the power grid and the filter capacitor of the inverter, and combine the separated low-frequency signal components to obtain the low-frequency compensation amount using the ILADRC algorithm;

[0011] The coordinated control layer, connected to the composite control layer, is used to weight all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain the comprehensive control amount;

[0012] The output execution layer, connected to the coordinated control layer, is used to dynamically control the inverter based on the comprehensive control amount.

[0013] Among them, the frequency division processing of the voltage signal and the current signal by frequency is specifically as follows:

[0014] Based on the equivalent inductance of the power grid and the filter capacitor of the inverter, calculate the cut-off frequency;

[0015] Divide the voltage signal after filtering that is greater than the cut-off frequency into a voltage high-frequency component, and divide the voltage signal less than or equal to the cut-off frequency into a voltage low-frequency component;

[0016] Divide the current signal after filtering that is greater than the cut-off frequency into a current high-frequency component, and divide the current signal less than or equal to the cut-off frequency into a current low-frequency component.

[0017] Among them, the specific formula for the cut-off frequency is: , where represents the cut-off frequency, , respectively represent the equivalent inductance of the power grid and the filter capacitor of the inverter.

[0018] Among them, the construction of the objective function of the MPC algorithm based on the change characteristics of the separated high-frequency signal components, the specific formula is: ; in the formula, F represents the objective function of the MPC algorithm; N represents the prediction horizon N; represents the change amount of the control input voltage high-frequency component at the k-th moment; represents the change amount of the control input current high-frequency component at the k-th moment; represents norm; represents the preset weight coefficient.

[0019] Among them, the change amount of the voltage high-frequency component is specifically the difference between the control input voltage high-frequency components at adjacent moments.

[0020] Among them, the formula for dynamically adjusting the bandwidth of the ESO in the ILADRC algorithm is: , where represents the ESO bandwidth, represents the equivalent inductance of the power grid, represents the filter capacitor of the inverter.

[0021] Among them, the low-frequency compensation amount obtained by using the ILADRC algorithm is specifically as follows:

[0022] Taking the low-frequency component of the voltage and the low-frequency component of the current as the input of the ILADRC algorithm, and dynamically adjusting according to the bandwidth of the ESO to obtain the low-frequency compensation amount.

[0023] Among them, the weighting of all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain the comprehensive control amount is specifically as follows:

[0024] Taking the high-frequency energy ratio as the weight, weighting the sum value of all high-frequency compensation amounts and the sum value of all low-frequency compensation amounts to obtain the comprehensive control amount.

[0025] Among them, the high-frequency energy ratio is specifically the ratio of the energy of the high-frequency component of all signals to the total energy.

[0026] Among them, the dynamic control of the inverter is specifically as follows:

[0027] Generating a driving signal for the inverter switching tube according to the comprehensive control amount output by the cooperative control layer, and using the generated driving signal to control the switching state of the inverter switching tube.

[0028] This application has at least the following beneficial effects:

[0029] This application first divides high-frequency noise and low-frequency disturbances through the frequency-domain segmentation layer, effectively suppresses high-frequency disturbances such as switching noise using the MPC module, makes the high-frequency components in the electric energy purer, reduces the interference to other electrical equipment, and improves the overall power quality; uses the ILADRC module to focus on dealing with low-frequency disturbances such as changes in light intensity and low-frequency changes in load, ensures the stability and reliability of the electric energy in the medium and low frequency bands, and reduces the problems of voltage fluctuation and flicker; through multi-band cooperative control, comprehensively processes disturbances in different frequency bands, avoiding the influence of the coupling between disturbances on the performance of the inverter; finally, using the cooperative control strategy, according to the changes in parameters such as the grid impedance, by dynamically adjusting the output weights of the MPC and ILADRC, ensures that the inverter can operate stably under different grid conditions, improves the adaptability and robustness of the inverter to the weak grid environment, and can utilize solar energy resources more effectively compared with traditional single control methods, improves the overall conversion efficiency of the photovoltaic power generation system, and enables the system to operate more efficiently under different lighting and load conditions. Description of the Drawings

[0030] Figure 1 is a flowchart of the inverter dynamic control method applicable to the grid connection of photovoltaic power resources provided by this application;

[0031] Figure 2 Schematic diagram of components of the inverter dynamic control method provided for this application and applicable to grid connection of photovoltaic power resources. Detailed implementation manners

[0032] In the description of the embodiments of this application, words such as "exemplary", "or", "for example", etc. are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Precisely, using words such as "exemplary", "or", "for example", etc. aims to present relevant concepts in a specific manner.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used in the description of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0034] In addition, it should be noted that the terms "first", "second" in this application and its drawings are used to distinguish similar objects and are not used to describe a specific order or sequence. For the methods disclosed in the embodiments of this application or the methods shown in the flowcharts, including one or more steps for implementing the methods, without departing from the scope of protection of this application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0036] This application proposes an inverter dynamic control method applicable to grid connection of photovoltaic power resources, which is applied to the field of inverter control technology. Refer to the attached Figure 1 , schematic diagram of components of the inverter dynamic control method applicable to grid connection of photovoltaic power resources. Refer to the attached Figure 2 , the method is implemented through the following components:

[0037] (1) Data acquisition layer: collect voltage signals, current signals, equivalent inductance, and inverter filter capacitors.

[0038] The data acquisition layer consists of a voltage sensor, a current sensor, an inductance sensor, and a capacitance sensor.

[0039] Voltage sensors are respectively installed at the DC bus of the inverter, the AC side output terminal, and the common connection point, responsible for collecting voltage signals at these locations. The voltage sensor at the DC bus of the inverter can monitor the change of the bus voltage in real time and detect unstable voltage fluctuations in a timely manner; the voltage sensors located at the AC side output terminal of the inverter and the common connection point can collect grid voltage signals, which can not only obtain basic information such as the amplitude and phase of the voltage, but also detect abnormal conditions such as harmonics therein.

[0040] Current sensors are installed on the AC side output line of the inverter to collect grid-connected current signals, which contain harmonic components and current fluctuations caused by load changes, grid faults, etc.

[0041] In this embodiment, the sampling frequency of all sensors is 50 kHz. Since the subsequent processing of the voltage signals at each location is the same, the voltage signal on the DC bus side is taken as an example, and is processed in combination with the signals obtained by other sensors.

[0042] (2) Frequency domain segmentation layer: The voltage signal and the current signal are divided by frequency.

[0043] The multi-band filter bank is used to divide the voltage signal and the current signal obtained by the data acquisition layer according to frequency. The multi-frequency filter bank includes a second-order Butterworth high-pass filter (High-Pass Filter, HPF) and a second-order Butterworth low-pass filter (Low-Pass Filter, LPF), and is divided according to the cut-off frequency. Among them, the high-pass filter and the low-pass filter are in parallel configuration.

[0044] In this embodiment, the formula for the cut-off frequency of the filter bank is , where represents the cut-off frequency, , respectively represent the equivalent inductance of the grid and the filter capacitor of the inverter.

[0045] In the formula for the cut-off frequency, and constitute an LC resonance circuit structure, so the cut-off frequency of the filter bank can be regarded as the product of a preset value and the natural resonance frequency in the LC resonance circuit. In this embodiment, the preset value is taken as , and the implementer can adjust it according to the actual situation.

[0046] In this embodiment, the voltage signals greater than the cut-off frequency after filtering are classified as voltage high-frequency components, and the voltage signals less than or equal to the cut-off frequency are classified as voltage low-frequency components; the current signals greater than the cut-off frequency after filtering are classified as current high-frequency components, and the current signals less than or equal to the cut-off frequency are classified as current low-frequency components.

[0047] The frequency-domain segmentation layer guides the disturbance signals of different frequencies to the corresponding control layers for processing respectively, realizing the separate control of high-frequency and low-frequency disturbances, and improving the pertinence and effectiveness of control.

[0048] (3)The composite control layer includes an MPC module and an ILADRC module; MPC module: Based on the change characteristics of the separated high-frequency signal components, construct the objective function of the MPC algorithm, and use the MPC algorithm to output the high-frequency compensation amount; ILADRC module: Dynamically adjust the bandwidth of the ESO in the ILADRC algorithm based on the equivalent inductance of the power grid and the filter capacitor of the inverter, and combine the separated low-frequency signal components to obtain the low-frequency compensation amount using the ILADRC algorithm.

[0049] Inverters for grid-connected photovoltaic power are indeed affected by various disturbances of different frequencies, and these disturbances may come from different sources, such as grid fluctuations, light changes, load changes, etc. Some existing control methods usually only focus on disturbances in specific frequency bands, resulting in them being less effective or unable to comprehensively improve the performance of the inverter when dealing with multi-band disturbances.

[0050] A Model Predictive Control (MPC) controller is introduced to handle high-frequency disturbances and optimize the overall performance of the inverter for grid-connected photovoltaic power; while the Improved Linear Active Disturbance Rejection Control (ILADRC) algorithm is only effective in the medium and low frequency bands and cannot handle high-frequency interference. This application considers combining the MPC algorithm with the ILADRC algorithm to effectively address the multi-band disturbance problem in the inverter.

[0051] MPC module: The MPC algorithm realizes high-frequency disturbance suppression based on a discrete-time state-space model. Its core is to predict the behavior of the inverter in multiple future control periods through rolling optimization and solve the optimal control quantity to minimize the objective function. MPC belongs to well-known technology and its specific content will not be elaborated. In this embodiment, the necessary parameter settings are as follows:

[0052] The objective function is to minimize the high-frequency disturbance energy, and the formula is: , where F represents the objective function of the MPC algorithm; N represents the prediction horizon N, which is set to 6 control periods in this embodiment, and is 60 , represents the change amount of the high-frequency component of the control input voltage at the k-th moment, that is, the difference between the high-frequency components of the corresponding voltages at the k-th and (k - 1)-th moments; represents the change amount of the high-frequency component of the control input current at the k-th moment, that is, the difference between the high-frequency components of the corresponding currents at the k-th and (k - 1)-th moments; represents norm; represents a preset weight coefficient.

[0053] It should be noted that in a three-phase power generation system, this value is a vector containing three components. Taking the norm is to quantify and amplify the influence of the change amount of the control input. The square operation of the norm enables even a small change amount to have a certain influence on the objective function, and the larger the change amount, the greater the contribution to the objective function. In this way, when optimizing the objective function, it will prompt the change of the control input to be as small as possible, thereby making the control process more stable, reducing unnecessary energy loss and equipment wear, and improving the stability and reliability of the inverter.

[0054] In addition, it should be noted that is used to adjust the importance of the current change amount part in the objective function: When it is greater than or equal to 1, it indicates that more attention is paid to the stability of the current, and the objective function will tend to reduce the change amount of the current; When it is less than 1, relatively more attention is paid to the change amount of the control input, and a certain degree of current fluctuation may be allowed in exchange for a more optimal adjustment of the control input. Based on this, in this embodiment takes a value of 1, and the implementer can adjust the size according to the actual situation.

[0055] The MPC algorithm will predict the future situation according to the current state and the model, continuously solve this objective function, obtain the optimal control input at each moment, so as to achieve efficient and stable control of the inverter, and finally output the high-frequency compensation amount, that is, the duty cycle adjustment amount, with a range of -10% to +10%. It should be noted that if it exceeds this range, saturation processing is performed.

[0056] The constraint conditions are a switch frequency upper limit of 20 kHz and a current harmonic less than 3%.

[0057] High-frequency disturbances change rapidly, requiring the control strategy to have a fast response ability. The MPC algorithm can predict the future states of the inverter in multiple moments in advance by establishing a prediction model. In each control cycle, it can quickly calculate the optimal control input according to the prediction results and the set goals, so as to quickly respond to high-frequency disturbances, effectively suppress high-frequency noises and high-frequency disturbances such as harmonics near the switching frequency.

[0058] ILADRC module: ILADRC is an improved linear active disturbance rejection control module, which is optimized on the basis of traditional ADRC, simplifies parameter adjustment and improves control performance. The ILADRC algorithm belongs to the well-known technology, and the specific content will not be elaborated here. In this embodiment, the necessary parameter settings are as follows:

[0059] An improved Extended State Observer (ESO) is used, and the bandwidth of the ESO can be dynamically adjusted according to the grid impedance. The formula is: , where represents the ESO bandwidth, represents the equivalent inductance of the grid, represents the inverter filter capacitor.

[0060] It should be noted that by dynamically adjusting the ESO bandwidth according to the grid impedance, it can adapt to the changes of the grid impedance in real time, track the state changes faster, better estimate the total disturbance, ensure stable operation under different grid impedance conditions, and enhance the adaptability of the inverter to external environmental changes.

[0061] In the low-frequency band, the ESO can accurately estimate the mid- and low-frequency disturbance signals caused by factors such as grid voltage fluctuations and load changes. These estimated values can be used in the disturbance rejection compensation law to adjust the control input to offset the impact of the disturbance on the inverter.

[0062] The ILADRC algorithm uses a linear function to replace the traditional non-linear tracking method, reduces the computational complexity, generates a transient process signal, suppresses the impact of rapid jumps in the input signal on the inverter, and finally outputs a low-frequency compensation amount, that is, the voltage loop compensation amount, with a range of -5V to +5V. If it exceeds this range, saturation processing is performed; it should be noted that this range is a preset range used to control the stability and response ability of the inverter, and the implementer can adjust it according to the actual situation.

[0063] Mid- and low-frequency disturbances usually have uncertainty and complexity, such as changes in light intensity, slow changes in grid voltage and frequency, etc. These disturbances are difficult to accurately model and predict. ILADRC has strong robustness and anti-interference ability. It can estimate and compensate the unknown disturbances in the inverter in real time, and can effectively suppress various uncertain disturbances in the mid- and low-frequency bands, ensuring the stability of the inverter and the accuracy of the output.

[0064] When facing dynamic processes such as load changes and grid faults, the ILADRC can quickly adjust the control output, enabling the inverter to have good dynamic response performance in the medium and low frequency bands. It can accelerate the dynamic response speed of the inverter by real-time estimating and compensating for disturbances, reduce the overshoot and adjustment time of the inverter during the dynamic process, enable the photovoltaic grid-connected inverter to quickly and stably adapt to various working conditions changes in the medium and low frequency bands, and improve the reliability and operating efficiency of the inverter.

[0065] (4) Cooperative control layer: Weigh all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain a comprehensive control amount.

[0066] The final output of the cooperative control layer is , where represents the comprehensive control amount, with a range of -12V to +12V, represents the high-frequency energy ratio, that is, the ratio of the energy of the high-frequency components of all signals to the total energy, represents the sum value of all high-frequency compensation amounts output by the MPC, represents the sum value of all low-frequency compensation amounts output by the ILADRC.

[0067] It should be understood that the high-frequency energy ratio can dynamically adjust the output weights of the high-frequency band MPC module and the low-frequency band ILADRC module. When the high-frequency energy ratio is relatively high, the control effect of the MPC module is increased; conversely, when the high-frequency energy ratio is low, the role of the ILADRC module is relatively strengthened, so as to achieve cooperative control in multiple frequency bands and ensure that the inverter can maintain good performance and stability under different working conditions.

[0068] (5) Output execution layer: Dynamically control the inverter based on the comprehensive control amount.

[0069] Generate the drive signal for the inverter switching tubes according to the comprehensive control amount output by the cooperative control layer. The key parameters are: carrier frequency 10kHz (triangle wave), dead time 2 (set based on the IGBT switching characteristics), modulation method SPWM, modulation ratio range 0.2 to 0.9. Finally, drive pulse signals will be output to complete the dynamic control of the inverter.

[0070] The present application provides a dynamic control method for an inverter applicable to grid connection of photovoltaic power resources. The method includes: First, the high-frequency noise and low-frequency disturbances are segmented through a frequency-domain segmentation layer, and the MPC module is used to effectively suppress high-frequency disturbances such as switching noise, making the high-frequency components in the electric energy purer, reducing interference to other electrical equipment, and improving the overall power quality; The ILADRC module is used to focus on dealing with low-frequency disturbances such as changes in light intensity and low-frequency changes in load, ensuring the stability and reliability of the electric energy in the medium and low frequency bands, and reducing problems of voltage fluctuations and flicker; Through multi-band collaborative control, disturbances in different frequency bands are comprehensively processed, avoiding the influence of the mutual coupling between disturbances on the performance of the inverter; Finally, using a collaborative control strategy, according to changes in parameters such as grid impedance, by dynamically adjusting the output weights of the MPC and ILADRC, it is ensured that the inverter can operate stably under different grid conditions, improving the adaptability and robustness of the inverter to a weak grid environment. Compared with traditional single control methods, it can make more effective use of solar energy resources, improve the overall conversion efficiency of the photovoltaic power generation system, and enable the system to operate more efficiently under different light and load conditions.

[0071] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the block may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, which may depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description. Sometimes, there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, which may depend on the functions involved. Each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0072] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application 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 described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A dynamic control method for an inverter applicable to grid connection of photovoltaic power resources, characterized in that, This method is implemented through the following components: The data acquisition layer is used to acquire voltage signals, current signals, equivalent inductance, and inverter filter capacitors; The frequency domain segmentation layer is connected to the data acquisition layer and is used to perform frequency division processing on voltage signals and current signals by frequency, and transmit the separated signal components to different control layer modules respectively; The composite control layer is connected to the frequency domain segmentation layer and includes an MPC module and an ILADRC module; The MPC module is used to construct the objective function of the MPC algorithm based on the change characteristics of the separated high-frequency signal components, and output the high-frequency compensation amount using the MPC algorithm; The ILADRC module is used to dynamically adjust the bandwidth of the ESO in the ILADRC algorithm based on the grid equivalent inductance and the inverter filter capacitor, and combine the separated low-frequency signal components to obtain the low-frequency compensation amount using the ILADRC algorithm; The cooperative control layer is connected to the composite control layer and is used to weight all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain the comprehensive control amount; The output execution layer is connected to the cooperative control layer and is used to dynamically control the inverter based on the comprehensive control amount.

2. The dynamic control method for an inverter applicable to grid connection of photovoltaic power resources according to claim 1, characterized in that, The frequency division processing of voltage signals and current signals by frequency is specifically as follows: Based on the equivalent inductance of the grid and the inverter filter capacitor, calculate the cut-off frequency; Divide the filtered voltage signal greater than the cut-off frequency into voltage high-frequency components, and divide the voltage signal less than or equal to the cut-off frequency into voltage low-frequency components; Divide the filtered current signal greater than the cut-off frequency into current high-frequency components, and divide the current signal less than or equal to the cut-off frequency into current low-frequency components.

3. The dynamic control method for an inverter applicable to grid connection of photovoltaic power resources according to claim 2, wherein The specific formula for the cut-off frequency is as follows: , where represents the cut-off frequency, , respectively represent the equivalent inductance of the power grid and the inverter filter capacitor.

4. The dynamic control method of the inverter applicable to grid connection of photovoltaic power resources according to claim 1, wherein Based on the change characteristics of the separated high-frequency signal components, construct the objective function of the MPC algorithm. The specific formula is as follows: ; where F represents the objective function of the MPC algorithm; N represents the prediction horizon N; represents the change amount of the high-frequency component of the controlled input voltage at the k-th moment; represents the change amount of the high-frequency component of the controlled input current at the k-th moment; represents norm; represents the preset weight coefficient.

5. The inverter dynamic control method applicable to grid connection of photovoltaic power resources according to claim 4, characterized in that, The change amount of the voltage high-frequency component is specifically the difference between the control input voltage high-frequency components at adjacent moments.

6. The dynamic control method for an inverter applicable to grid connection of photovoltaic power resources according to claim 1, characterized in that, The formula for dynamically adjusting the bandwidth of the ESO in the ILADRC algorithm is as follows: , where represents the ESO bandwidth, represents the equivalent inductance of the power grid, represents the inverter filter capacitor.

7. The dynamic control method of the inverter applicable to the grid connection of photovoltaic power resources according to claim 1, characterized in that, The obtaining of the low-frequency compensation amount using the ILADRC algorithm is specifically as follows: Use the voltage low-frequency component and the current low-frequency component as the input of the ILADRC algorithm, and dynamically adjust according to the group width of the ESO to obtain the low-frequency compensation amount.

8. The dynamic control method of the inverter applicable to grid connection of photovoltaic power resources according to claim 1, characterized in that, The weighting of all the obtained high-frequency compensation amounts and low-frequency compensation amounts to obtain the comprehensive control amount is specifically as follows: Use the high-frequency energy ratio as the weight to weight the sum of all high-frequency compensation amounts and the sum of all low-frequency compensation amounts to obtain the comprehensive control amount.

9. The dynamic control method of the inverter applicable to grid connection of photovoltaic power resources according to claim 8, characterized in that, The high-frequency energy ratio is specifically the ratio of the energy of the high-frequency components of all signals to the total energy.

10. The inverter dynamic control method applicable to grid connection of photovoltaic power resources according to claim 1, characterized in that, The dynamic control of the inverter is specifically as follows: Generate the drive signal of the inverter switching tube according to the comprehensive control amount output by the cooperative control layer, and use the generated drive signal to control the switching state of the inverter switching tube.

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