Rectification control method and system of bidirectional photovoltaic energy storage inverter

Abstract

This application relates to the field of photovoltaic energy storage rectification control technology, specifically to a rectification control method and system for a bidirectional photovoltaic energy storage inverter. The method includes: acquiring electrical parameters, photovoltaic cell parameters, and environmental data for each acquisition cycle of the bidirectional photovoltaic energy storage inverter; analyzing the peak distribution of the spectrum of each electrical parameter to determine significant peaks; and studying the frequency correlation of significant peaks in adjacent acquisition cycles to obtain a harmonic variation sequence. Through autocorrelation analysis and amplitude distribution characteristics, combined with environmental monitoring data, the harmonic fluctuation index for each acquisition cycle is calculated. Based on this, the MPPT control algorithm is used to determine the maximum power point, and the disturbance step size and frequency of the MPPT control are adjusted according to the harmonic fluctuation index to optimize the rectification control of the photovoltaic energy storage inverter, thereby improving control efficiency and reducing harmonic pollution.

Description

Technical Field

[0001] This application relates to the field of photovoltaic energy storage rectification control technology, specifically to a rectification control method and system for a bidirectional photovoltaic energy storage inverter. Background Technology

[0002] Photovoltaic power generation relies on natural conditions, and its output exhibits significant fluctuations and unpredictability, severely threatening the stability of power supply. In this context, energy storage systems play a crucial role in balancing supply and demand and smoothing power fluctuations through peak shaving and valley filling mechanisms. Bidirectional photovoltaic energy storage inverters, as core devices capable of simultaneously achieving AC / DC conversion and energy storage charging / discharging, play an indispensable role in this process. However, with the increasing proportion of renewable energy sources, the rectification control of energy storage systems faces unprecedented challenges. Specifically, harmonics are a significant factor in the rectification control of photovoltaic energy storage inverters; harmonic hazards not only reduce energy storage quality but also damage electrical equipment.

[0003] Existing technologies typically employ filter construction to filter harmonics, but this method is primarily suitable for relatively stable AC power sources. When photovoltaic power generation is introduced into the power system, environmental fluctuations necessitate frequent Maximum Power Point Tracking (MPPT) adjustments. These adjustments introduce new, uncontrollable harmonics. These dynamically changing harmonic components are difficult for existing methods to effectively address, leading to a decline in the energy storage quality of the energy storage system and ultimately threatening the stability and security of the power system. Summary of the Invention

[0004] In view of the above, it is necessary to provide a rectification control method and system for a bidirectional photovoltaic energy storage inverter to solve the above problems.

[0005] The first aspect of this application provides a rectification control method for a bidirectional photovoltaic energy storage inverter, the method comprising:

[0006] Acquire electrical parameters, photovoltaic cell parameters, and environmental data for each acquisition cycle of the bidirectional photovoltaic energy storage inverter;

[0007] For each acquisition cycle, significant peaks are identified based on the peak distribution characteristics of the spectrum of each electrical parameter. The correlation between the frequency distributions corresponding to the significant peaks obtained in adjacent acquisition cycles is analyzed to obtain the harmonic variation sequence. Autocorrelation analysis is performed on each electrical parameter in each acquisition cycle. Based on the difference characteristics between the autocorrelation results of two adjacent acquisition cycles, combined with the amplitude distribution corresponding to the significant peaks and the similarity characteristics between the harmonic variation sequence and the various environmental monitoring data collected, the harmonic fluctuation index of each acquisition cycle is determined.

[0008] The MPPT control algorithm is used to obtain the maximum power point of each acquisition cycle based on the photovoltaic cell parameters and all environmental data. The perturbation step size and perturbation frequency of the MPPT control algorithm are adjusted based on the obtained maximum power point and the harmonic fluctuation coefficient to perform rectification control on the photovoltaic energy storage inverter.

[0009] Preferably, the process of determining the significant peak value specifically includes:

[0010] For each acquisition cycle, all peak values ​​in the spectrum of each electrical parameter are thresholded, and peak values ​​greater than the threshold are considered significant peak values.

[0011] Preferably, the specific process for obtaining the harmonic variation sequence is as follows:

[0012] The sequence of frequencies corresponding to all significant peaks obtained in each acquisition cycle is taken as the frequency sequence;

[0013] For each acquisition cycle and all previous acquisition cycles, calculate the differences between the frequency sequences of all adjacent acquisition cycles, and denote the sequence formed by all the differences as the harmonic variation sequence.

[0014] Preferably, the step of determining the harmonic fluctuation index for each acquisition cycle specifically involves:

[0015] For each acquisition cycle, the sequence of significant peaks corresponding to integer multiples of the fundamental frequency is denoted as the harmonic amplitude sequence, and the proportion of negative elements in the first-order difference sequence of the harmonic amplitude sequence is obtained.

[0016] Analyze the similarity between the variation characteristics of various environmental data and the element distribution of the harmonic variation sequence in each acquisition cycle, and determine the first average value for each acquisition cycle;

[0017] For each acquisition cycle and all previous acquisition cycles, the lag difference for each acquisition cycle is determined by combining the differences in the autocorrelation analysis results of all electrical parameters in all adjacent acquisition cycles.

[0018] Analyze the distribution of significant peak values ​​of all electrical parameters in each acquisition cycle and the distribution characteristics of their corresponding frequencies to determine the distribution values ​​of harmonic components of electrical parameters in each acquisition cycle;

[0019] The negative correlation mapping result of the quantity proportion of each acquisition cycle, and the positive fusion result of the first average value, the hysteresis difference, and the distribution value of the electrical parameter harmonic components, are used as the harmonic fluctuation coefficient of each acquisition cycle.

[0020] Preferably, determining the first average value for each collection cycle specifically involves:

[0021] Obtain the first-order difference sequence of various environmental data sequences, calculate the mean similarity between the harmonic variation sequence of each acquisition cycle and the first-order difference sequence corresponding to various environmental data, and determine the first average value for each acquisition cycle.

[0022] Preferably, determining the lag difference for each acquisition cycle specifically involves:

[0023] The upper quartile of all peak values ​​in the autocorrelation analysis results of each electrical parameter in each acquisition cycle is used as the threshold. The sequence of hysteresis values ​​corresponding to all autocorrelation coefficients greater than the threshold is used as the hysteresis sequence of each electrical parameter.

[0024] For each acquisition cycle and all previous acquisition cycles, calculate the distance metric between the hysteresis sequences of various electrical parameters between two adjacent acquisition cycles, and record the average of the distance metrics obtained for all electrical parameters as the second average.

[0025] The mean of the second average values ​​of all two adjacent acquisition periods is denoted as the hysteresis difference.

[0026] Preferably, determining the electrical parameter harmonic component distribution value for each acquisition cycle specifically involves:

[0027] Obtain the percentage of amplitude of each significant peak in the spectrum of various electrical parameters for each acquisition cycle, corresponding to all significant peaks, and multiply it by the frequency corresponding to each significant peak.

[0028] The multiplication results of various electrical parameters are accumulated to obtain the harmonic component distribution measure of each electrical parameter. The mean of the harmonic component distribution measures of all electrical parameters is used as the harmonic component distribution value of the electrical parameters in each acquisition cycle.

[0029] Preferably, the specific formula for adjusting the disturbance step size of MPPT control is as follows: In the formula, , For MPPT number The, the The perturbation step size is adjusted for each acquisition cycle. It is the first Normalized results of harmonic fluctuation coefficients for each acquisition cycle. It is the first The voltage value corresponding to the maximum power point in each sampling cycle. For the first The average voltage of the photovoltaic cells in each collection cycle; e represents the natural constant.

[0030] Preferably, the specific formula for adjusting the disturbance frequency of MPPT control is as follows: In the formula, It is the MPPT control number The perturbation frequency per acquisition cycle , These are the minimum and maximum values ​​of the initially set disturbance frequency. It is the first Normalized results of harmonic fluctuation coefficients for each acquisition cycle. It is the first The voltage value corresponding to the maximum power point in each sampling cycle. For the first The average voltage of photovoltaic cells over a collection period.

[0031] Secondly, embodiments of this application also provide a rectification control system for a bidirectional photovoltaic energy storage inverter, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0032] This application has at least the following beneficial effects:

[0033] This application first calculates the harmonic fluctuation coefficient based on the harmonic variations in the power system. This index quantifies the characteristics of harmonics from different sources, helping to enhance the identification of harmonic pollution caused by MPPT control. Then, by combining the harmonic fluctuation coefficient with MPPT control on the photovoltaic power generation side, adaptive disturbance step size and disturbance frequency are adjusted. This adjustment method helps to achieve a dynamic balance between power system harmonic pollution control and photovoltaic system power generation efficiency based on changes in harmonic pollution. Through this approach, combining the identification of harmonic pollution caused by MPPT control with adaptive adjustment of MPPT control parameters, the dynamic harmonic pollution generated by MPPT control is reduced, i.e., the content of unpredictable harmonic components in the power system is reduced. This enhances the quality of harmonic filtering used by the photovoltaic energy storage inverter during rectification control in the energy storage process, achieving a higher-quality photovoltaic energy storage inverter rectification control method. Attached Figure Description

[0034] Figure 1 A block diagram of a rectification control method for a bidirectional photovoltaic energy storage inverter provided in one embodiment of this application;

[0035] Figure 2 This is a flowchart illustrating the process of obtaining the harmonic fluctuation coefficient according to one embodiment of this application. Detailed Implementation

[0036] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application's specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0038] It should also be noted that the terms "first" and "second" in this application and its accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The methods disclosed in the embodiments of this application or the methods shown in the flowcharts include one or more steps for implementing the method. Without departing from the scope of protection of this application, the execution order of multiple steps can be interchanged, and some steps can also be deleted.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0040] The following description, in conjunction with the accompanying drawings, details the specific scheme of the rectification control method and system for a bidirectional photovoltaic energy storage inverter provided in this application.

[0041] Please see Figure 1 The document illustrates a flowchart of the rectification control method for a bidirectional photovoltaic energy storage inverter according to an embodiment of this application. The method includes:

[0042] Step 1: Obtain electrical parameters, photovoltaic cell parameters, and environmental data for each data acquisition cycle of the bidirectional photovoltaic energy storage inverter.

[0043] At the output end of the photovoltaic (PV) panel, voltage and current sensors are used to collect PV cell parameters, including PV cell voltage and current data, at a data acquisition frequency of 10 kHz for 1 second per acquisition. At the AC side of the PV grid connection, voltage and current sensors are used to collect electrical parameters, including power system voltage and current data, at a data acquisition frequency of 10 kHz for 1 second per acquisition. A PV monitoring system is used to collect environmental data for PV power generation, including temperature, humidity, wind speed, and solar irradiance data, at a acquisition frequency of 1 Hz. All collected data are normalized. Within each acquisition cycle, the collected electrical parameters are compiled into voltage and current sequences according to the acquisition order, and the collected PV cell parameters are compiled into PV cell voltage and current sequences according to the acquisition order. All environmental data collected across all acquisition cycles are compiled into various environmental sequences, including temperature, humidity, wind speed, and solar irradiance sequences.

[0044] Step 2: For each acquisition cycle, based on the peak distribution characteristics of the spectrum of each electrical parameter, determine the significant peaks; analyze the correlation between the frequency distributions corresponding to the significant peaks obtained in adjacent acquisition cycles to obtain the harmonic variation sequence; perform autocorrelation analysis on each electrical parameter in each acquisition cycle, and based on the difference characteristics between the autocorrelation results of two adjacent acquisition cycles, combined with the amplitude distribution corresponding to the significant peaks and the similarity characteristics between the harmonic variation sequence and the various environmental monitoring data collected, determine the harmonic fluctuation index for each acquisition cycle.

[0045] When performing rectifier control for bidirectional photovoltaic energy storage inverters, harmonic components in the power system have a significant impact on the quality of rectifier control. Excessive harmonics can not only affect the energy storage conversion efficiency but also potentially damage power equipment. Therefore, harmonic filtering first requires analyzing the changes in harmonic components. In a normal power system, since harmonics are caused by the load, their frequencies are often integer multiples of the fundamental frequency, and they are primarily low-frequency harmonics. This means that as the harmonic frequency increases, the harmonic amplitude tends to decrease. Secondly, harmonic frequencies typically exhibit the same periodicity as the fundamental frequency. Finally, because the operating state of the load in the power system is usually stable, the harmonic components in the power system are relatively stable, and environmental changes have a relatively small impact on harmonics.

[0046] When MPPT control induces harmonic generation, the following factors contribute to this: Firstly, MPPT adjustment is caused by environmental changes and thus exhibits a degree of randomness. Secondly, the non-linear adjustment process introduces numerous high-frequency and interharmonic harmonics, and the amplitude of these harmonics does not show a trend with frequency changes. Thirdly, these harmonics arise from fluctuations caused by MPPT adjustment, which generate corresponding harmonic variations. Since MPPT control is instantaneous, these harmonics have a relatively short duration but occur frequently. Finally, because MPPT control is influenced by environmental factors, these harmonics show a strong correlation with environmental changes.

[0047] With the first Taking the data from the first collection period as an example, the data from the first collection period will be used to collect the data from the second collection period The voltage and current sequences from each acquisition cycle are used as inputs to perform a Fast Fourier Transform (FFT) to obtain the corresponding spectrum. In the spectrum, all peaks are segmented using the Otsu threshold method to obtain a segmentation threshold. Peaks exceeding the segmentation threshold are marked as significant peaks. The frequencies corresponding to these significant peaks are then arranged in ascending order to form a frequency sequence. For the previous... For each acquisition cycle, the difference between the frequency sequences of all adjacent acquisition cycles is calculated, and the sequence formed by all differences is denoted as the harmonic variation sequence. It should be noted that in this embodiment, the difference between sequences is calculated using DTW distance. Among significant peaks, the peaks corresponding to integer multiples of the fundamental frequency are arranged in order of frequency magnitude to form a harmonic amplitude sequence.

[0048] Then respectively for the first Autocorrelation analysis is performed on the voltage and current sequences from each acquisition period, and the corresponding autocorrelation function graphs are output. In each autocorrelation function graph, the upper quartile of all peak values ​​is used as a threshold, and autocorrelation coefficients with peak values ​​greater than the threshold are considered significant autocorrelation coefficients. The lags corresponding to all significant autocorrelation coefficients are then arranged in order of magnitude to form a lag sequence. The Fast Fourier Transform, Otsu thresholding, and autocorrelation analysis are well-known techniques and will not be elaborated further.

[0049] Based on the above analysis, the harmonic fluctuation coefficient is calculated to measure the degree to which the harmonic components in the power system are affected by the MPPT control of photovoltaic power generation.

[0050] Specifically, for each acquisition cycle, the percentage of negative elements in the first-order difference sequence of the harmonic amplitude sequence is obtained; the percentage obtained in the i-th acquisition cycle is denoted as... .

[0051] The similarity between the harmonic variation sequence of each acquisition cycle and the first-order difference sequences of various environmental sequences is calculated, and then the average of all obtained similarity values ​​is denoted as the first average value. In this embodiment, the similarity between sequences is calculated using the Pearson correlation coefficient, and the first average value of the i-th acquisition cycle is denoted as... .

[0052] For each acquisition cycle and all preceding acquisition cycles, the distance metric between the hysteresis sequences of various electrical parameters in two adjacent acquisition cycles is calculated, and the average of the distance metrics obtained for all electrical parameters is denoted as the second average. The mean of the second averages of all two adjacent acquisition cycles is denoted as the hysteresis difference. In this embodiment, the distribution difference between sequences is calculated using the DTW distance, and the hysteresis difference obtained in the i-th acquisition cycle is denoted as... .

[0053] The percentage of amplitude of each significant peak in the spectrum of various electrical parameters for each acquisition cycle is obtained, and multiplied by the frequency corresponding to each significant peak. The multiplication results of various electrical parameters are accumulated to obtain the harmonic component distribution measure of each electrical parameter. The mean of the harmonic component distribution measures of all electrical parameters is taken as the harmonic component distribution value of the electrical parameters for each acquisition cycle. In this embodiment, the harmonic component distribution value of the electrical parameters in the i-th acquisition cycle is denoted as... .

[0054] The negative correlation mapping result of the quantity proportion in each acquisition cycle, combined with the positive fusion result of the first average value, the hysteresis difference, and the distribution value of the harmonic components of the electrical parameters, is used as the harmonic fluctuation coefficient for each acquisition cycle. In this embodiment, the negative correlation mapping result of the variables is calculated using the reciprocal of the variables, and the positive fusion of multiple variables is calculated using a multiplication method. Specifically, : Indicates the first Harmonic fluctuation coefficient for each acquisition cycle.

[0055] The flowchart for obtaining the harmonic fluctuation coefficient is as follows: Figure 2 As shown.

[0056] Understandably, when MPPT control adjustments introduce harmonics or have a minimal impact, the harmonics in the power system are primarily caused by electrical loads. The amplitude of these harmonics decreases with increasing harmonic frequency. Secondly, low-frequency harmonics constitute a larger proportion and have relatively larger amplitudes, while high-frequency harmonics and interharmonics have smaller amplitudes and proportions. Furthermore, harmonic variations caused by electrical loads are relatively less affected by environmental fluctuations. Finally, because the operating state of electrical loads is typically stable, the changes in harmonic components acquired at different sampling times exhibit relatively high stability, resulting in a smaller harmonic fluctuation coefficient. Conversely, the greater the impact of MPPT control adjustments on harmonics in the power system, the larger the corresponding harmonic fluctuation coefficient.

[0057] Step 3: Apply the MPPT control algorithm to the photovoltaic cell parameters and all environmental data for each acquisition cycle to obtain the maximum power point for each acquisition cycle. Based on the obtained maximum power point and the harmonic fluctuation coefficient, adjust the perturbation step size and perturbation frequency of the MPPT control algorithm to perform rectification control on the photovoltaic energy storage inverter.

[0058] The harmonic fluctuation coefficient measures the degree to which harmonics in a power system are affected by the maximum power point tracking (MPPT) control adjustments of photovoltaic (PV) power generation. Typically, the purpose of MPPT control adjustments is to ensure that PV cells operate at their optimal operating point, thereby improving the power generation efficiency of the PV system. However, to achieve this goal, MPPT control needs to be frequently adjusted according to environmental changes, which can significantly impact the power quality of the power system. Therefore, after quantifying the impact of PV MPPT control adjustments on harmonics in the power system, the MPPT control process needs to be optimized to achieve a dynamic balance between harmonic pollution control and PV power generation efficiency.

[0059] Using all environmental sequences and photovoltaic cell parameter sequences obtained in each acquisition cycle as inputs, MPPT control is employed to output the maximum power point obtained during this control, i.e., the optimal operating point. MPPT control is a well-known technique and will not be elaborated upon further. During MPPT control, the perturbation step size and perturbation frequency are key parameters affecting the oscillations caused by MPPT control and ensuring photovoltaic power generation efficiency. The initial perturbation step size... The recommended value range is: In this embodiment, the value is 0.1V. When the disturbance step size is too large, it will improve the efficiency of reaching the optimal operating point, but the large adjustment will also cause the MPPT control to generate large oscillations, introducing more harmonic components into the power system. When the disturbance frequency is large, the MPPT control will also need to be adjusted frequently, thus introducing more harmonics into the power system. However, when the disturbance step size or disturbance frequency is small, it will affect the efficiency of photovoltaic power generation to reach the optimal operating point. Therefore, a balance needs to be struck between the two.

[0060] Based on the above analysis, the perturbation step size and perturbation frequency are adaptively adjusted to achieve a dynamic balance between the harmonic components of the power system and the power generation efficiency of the photovoltaic system.

[0061] First, adjust the perturbation step size: : , For MPPT number The, the The perturbation step size is adjusted for each acquisition cycle. It is the first Normalized results of harmonic fluctuation coefficients for each acquisition cycle. It is the first The voltage value corresponding to the maximum power point in each sampling cycle. For the first The average voltage of the photovoltaic cells over several adjustment periods, where e represents the natural constant; The open-circuit voltage proportional coefficient method can be used to determine the open-circuit voltage proportional coefficient method, which is a well-known technique and will not be elaborated further. The normalization method adopts the maximum and minimum value normalization method.

[0062] Adjust the disturbance frequency: : It is the MPPT control number The perturbation frequency per acquisition cycle , These are the minimum and maximum values ​​of the initially set disturbance frequency. , The values ​​are 1Hz and 20Hz respectively.

[0063] Understandably, when MPPT control has a greater impact on harmonic fluctuations within the power system, a smaller disturbance step size and frequency should be used to reduce harmonic pollution caused by MPPT control. This, in turn, reduces the harmonic impact of the photovoltaic energy storage inverter during energy storage rectification control and improves the quality of rectification control. Conversely, when the conversion efficiency of photovoltaic power generation is low, a larger disturbance step size and frequency are required to improve the efficiency of photovoltaic power generation, ensure a sufficient power supply for the power system, and thus guarantee the stability of the power supply during energy storage rectification control. This avoids negative impacts on the conversion efficiency of the energy storage device and the safety of the power equipment caused by large fluctuations in the power supply.

[0064] The MPPT control process for photovoltaic power generation in the power system is adaptively optimized based on the adjusted perturbation step size and frequency, thereby reducing harmonic fluctuations in the entire power system. Then, a filter is used to filter the remaining harmonic components in the power system, and the filtered AC power is rectified and converted into DC power, thus enabling the charging and energy storage of the photovoltaic energy storage inverter. This completes the rectification control of the photovoltaic energy storage inverter. The construction of the filter is a well-known technology in the power field, and the specific process will not be elaborated further.

[0065] Based on the same inventive concept as the above methods, this application also provides a rectification control system for a bidirectional photovoltaic energy storage inverter, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above methods.

[0066] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending 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 reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0067] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects; modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some technical features, without causing the essence of the corresponding technical solutions to deviate from the scope of the technical solutions in the embodiments of this application, should all be included within the protection scope of this application.

Claims

1. A rectification control method of a bidirectional photovoltaic energy storage inverter, characterized in that, The method includes: Acquire electrical parameters, photovoltaic cell parameters, and environmental data for each acquisition cycle of the bidirectional photovoltaic energy storage inverter; For each acquisition cycle, significant peaks are identified based on the peak distribution characteristics of the spectrum of each electrical parameter. The correlation between the frequency distributions corresponding to the significant peaks obtained in adjacent acquisition cycles is analyzed to obtain the harmonic variation sequence. Autocorrelation analysis is performed on each electrical parameter in each acquisition cycle. Based on the difference characteristics between the autocorrelation results of two adjacent acquisition cycles, combined with the amplitude distribution corresponding to the significant peaks and the similarity characteristics between the harmonic variation sequence and the various environmental monitoring data collected, the harmonic fluctuation coefficient of each acquisition cycle is determined. The MPPT control algorithm is applied to the photovoltaic cell parameters and all environmental data for each acquisition cycle to obtain the maximum power point for each acquisition cycle. Based on the obtained maximum power point and the harmonic fluctuation coefficient, the perturbation step size and perturbation frequency of the MPPT control algorithm are adjusted to perform rectification control on the photovoltaic energy storage inverter. The specific process for obtaining the harmonic variation sequence is as follows: The sequence of frequencies corresponding to all significant peaks obtained in each acquisition cycle is taken as the frequency sequence; For each acquisition cycle and all previous acquisition cycles, calculate the differences between the frequency sequences of all adjacent acquisition cycles, and denote the sequence formed by all the differences as the harmonic variation sequence; The specific steps for determining the harmonic fluctuation coefficient for each acquisition cycle are as follows: For each acquisition cycle, the sequence of significant peaks corresponding to integer multiples of the fundamental frequency is denoted as the harmonic amplitude sequence, and the proportion of negative elements in the first-order difference sequence of the harmonic amplitude sequence is obtained. Analyze the similarity between the variation characteristics of various environmental data and the element distribution of the harmonic variation sequence in each acquisition cycle, and determine the first average value for each acquisition cycle; For each acquisition cycle and all previous acquisition cycles, the lag difference for each acquisition cycle is determined by combining the differences in the autocorrelation analysis results of all electrical parameters in all adjacent acquisition cycles. Analyze the distribution of significant peak values ​​of all electrical parameters in each acquisition cycle and the distribution characteristics of their corresponding frequencies to determine the distribution values ​​of harmonic components of electrical parameters in each acquisition cycle; The negative correlation mapping result of the quantity proportion of each acquisition cycle, and the positive fusion result of the first average value, the hysteresis difference, and the distribution value of the electrical parameter harmonic components, are used as the harmonic fluctuation coefficient of each acquisition cycle. The specific formula for adjusting the perturbation step of the MPPT control is: ; wherein, , is the perturbation step adjusted by the MPPT in the first th and the first th collection period, is the normalized result of the harmonic fluctuation coefficient in the first th collection period, is the voltage value corresponding to the maximum power point in the first th collection period, is the average voltage of the photovoltaic cell in the first th collection period; and e represents the natural constant. The specific formula for adjusting the disturbance frequency of MPPT control is as follows: In the formula, It is the MPPT control number The perturbation frequency per acquisition cycle , These are the minimum and maximum values ​​of the initially set disturbance frequency. It is the first Normalized results of harmonic fluctuation coefficients for each acquisition cycle. It is the first The voltage value corresponding to the maximum power point in each sampling cycle. For the first The average voltage of photovoltaic cells over a collection period.

2. The rectification control method for a bidirectional photovoltaic energy storage inverter as described in claim 1, characterized in that, The process of determining significant peak values ​​is as follows: For each acquisition cycle, all peak values ​​in the spectrum of each electrical parameter are thresholded, and peak values ​​greater than the threshold are considered significant peak values.

3. The rectification control method for a bidirectional photovoltaic energy storage inverter as described in claim 1, characterized in that, The determination of the first average value for each collection cycle is specifically as follows: Obtain the first-order difference sequence of various environmental data sequences, calculate the mean similarity between the harmonic variation sequence of each acquisition cycle and the first-order difference sequence corresponding to various environmental data, and determine the first average value for each acquisition cycle.

4. The rectification control method for a bidirectional photovoltaic energy storage inverter as described in claim 1, characterized in that, The determination of the lag difference for each acquisition cycle is specifically as follows: The upper quartile of all peak values ​​in the autocorrelation analysis results of each electrical parameter in each acquisition cycle is used as the threshold. The sequence of hysteresis values ​​corresponding to all autocorrelation coefficients greater than the threshold is used as the hysteresis sequence of each electrical parameter. For each acquisition cycle and all previous acquisition cycles, calculate the distance metric between the hysteresis sequences of various electrical parameters between two adjacent acquisition cycles, and record the average of the distance metrics obtained for all electrical parameters as the second average. The mean of the second average values ​​of all two adjacent acquisition periods is denoted as the hysteresis difference.

5. The rectification control method for a bidirectional photovoltaic energy storage inverter as described in claim 1, characterized in that, The determination of the electrical parameter harmonic component distribution value for each acquisition cycle is specifically as follows: Obtain the percentage of amplitude of each significant peak in the spectrum of various electrical parameters for each acquisition cycle, corresponding to all significant peaks, and multiply it by the frequency corresponding to each significant peak. The multiplication results of various electrical parameters are accumulated to obtain the harmonic component distribution measure of each electrical parameter. The mean of the harmonic component distribution measures of all electrical parameters is used as the harmonic component distribution value of the electrical parameters in each acquisition cycle.

6. A rectification control system for a bidirectional photovoltaic energy storage inverter, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.

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