Photovoltaic inverter harmonic suppression and power grid electric energy quality collaborative optimization method

Abstract

The invention discloses a photovoltaic inverter harmonic suppression and power grid electric energy quality collaborative optimization method, and relates to the technical field of power systems, and the method comprises the following steps: obtaining a photovoltaic inverter output current wave, and marking the current wave as a real-time detection wave; acquiring a first historical data point based on normal current waves in the power grid; obtaining a screening coordinate point based on the first historical data point; acquiring a reference periodic wave based on the screened coordinate points; constructing a real-time detection length based on the real-time detection wave and the reference waveform; acquiring a historical detection length based on the normal waves without harmonic waves; obtaining a detection length threshold based on the historical detection length; classifying the real-time detection waves based on the real-time detection length and the detection length threshold, and performing different operations on different types of real-time detection waves; the method is used for solving the problems that in the prior art, whether harmonic waves appear or not is judged through frequency, amplitude and other data, data comparison is tedious, and the accuracy of a judgment result is low.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization method. BACKGROUND

[0002] With the acceleration of global energy transformation, photovoltaic power generation as a core component of renewable energy, the rapid switching action of photovoltaic inverters, nonlinear control characteristics and interaction with grid impedance, will inject harmonic current into the grid, causing voltage waveform distortion, seriously threatening the safe and stable operation of the grid and the normal work of various electrical equipment; such interference not only reduces the power quality of the grid, but also can have a negative impact on grid stability and equipment life; therefore, it is necessary to determine whether harmonics occur and to suppress harmonics; In order to prevent the injection of harmonic current into the grid, it is necessary to determine whether the current injected into the grid is distorted, and the existing method is to analyze and determine the AC output of the photovoltaic inverter to determine whether harmonics occur; generally, the frequency and amplitude of the AC output of the photovoltaic inverter are compared, because multiple data are compared, if multiple data are on the edge of abnormality, although the current is normal from each data, but the overall current may have been abnormal, so the data comparison is tedious and the accuracy of the judgment result is low, for example, the patent application with publication number CN119496136A discloses a multi-dimensional time sequence photovoltaic grid-connected harmonic current prediction control method, which determines whether harmonics occur by comparing frequency and amplitude data, making data comparison tedious and the accuracy of the judgment result low, that is, the existing technology determines whether harmonics occur by comparing frequency and amplitude data, resulting in tedious data comparison and low accuracy of the judgment result. SUMMARY

[0003] The present application aims to at least solve one of the technical problems in the prior art, obtain a photovoltaic inverter output current wave, marked as a real-time detection wave; obtain a first historical data point based on a normal current wave in the grid; obtain a screening coordinate point based on the first historical data point; obtain a reference periodic wave based on the screening coordinate point; construct a real-time detection length based on the real-time detection wave and the reference waveform; obtain a historical detection length based on a normal wave without harmonics; obtain a detection length threshold based on the historical detection length; classify the real-time detection wave based on the real-time detection length and the detection length threshold, and perform different operations on different kinds of real-time detection waves, to solve the problem of tedious data comparison and low accuracy of the judgment result in the existing technology by comparing frequency and amplitude data to determine whether harmonics occur.

[0004] To achieve the above-mentioned purpose, the present application provides a photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization method, comprising the following steps: Obtaining a photovoltaic inverter output current wave, marked as a real-time detection wave; Obtaining a first historical data point based on a normal current wave in a power grid; Obtaining a screening coordinate point based on the first historical data point; Obtaining a reference periodic wave based on the screening coordinate point; Constructing a real-time detection length based on the real-time detection wave and the reference wave; Obtaining a historical detection length based on a normal wave without harmonics; Obtaining a detection length threshold based on the historical detection length; Classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves.

[0005] Further, obtaining a first historical data point based on a normal current wave in a power grid comprises the following sub-steps: Obtaining a first number of periodic waveforms in the normal current wave in the power grid, marked as historical periodic waves; Establishing a plane rectangular coordinate system with the horizontal axis value as time and the vertical coordinate as current value, marked as a historical current coordinate system; Making the starting points of the historical periodic waves coincide with the origin of the historical current coordinate system; Drawing a second number of evenly spaced data points on each historical periodic wave, marked as first historical data points.

[0006] Further, obtaining a screening coordinate point based on the first historical data point comprises the following sub-steps: Obtaining the vertical coordinates of the first historical data points with equal horizontal coordinates, marked as historical vertical coordinates; Obtaining the range of the historical vertical coordinates, marked as a first overall range; Dividing the first overall range into a third number of ranges, marked as first divided ranges; Obtaining the frequency of the historical vertical coordinates in each first divided range, marked as first divided frequencies; Sorting the first divided frequencies from left to right according to the minimum value of the corresponding first divided range from small to large.

[0007] Further, obtaining a screening coordinate point based on the first historical data point further comprises the following sub-steps: Obtaining the sum of the first frequencies, marked as a first sum frequency; Dividing the first sum frequency by the third number to obtain a value, marked as a first evenly divided frequency; Setting a first abnormal proportion; multiplying the first evenly divided frequency by the first abnormal proportion to obtain a value, marked as a first abnormal threshold; Marking the first divided frequencies less than the first abnormal threshold as first abnormal frequencies; If the first frequency on the left side is the first abnormal frequency, the first abnormal frequency on the left side is deleted, and the first abnormal frequency is continuously deleted to the right until the first abnormal frequency on the left side is not deleted; after stopping, the minimum value of the first division range corresponding to the first abnormal frequency on the left side is obtained, which is marked as the first vertical coordinate value; If the first frequency on the right side is the first abnormal frequency, the first abnormal frequency on the right side is deleted, and the first abnormal frequency is continuously deleted to the left until the first abnormal frequency on the right side is not deleted; after stopping, the maximum value of the first division range corresponding to the first abnormal frequency on the right side is obtained, which is marked as the second vertical coordinate value; The first historical data point between the first vertical coordinate value and the second vertical coordinate value is obtained, which is marked as the screening coordinate point.

[0008] Further, the reference periodic waveform based on the screening coordinate point comprises the following sub-steps: Obtain the screening coordinate point of each same horizontal coordinate; All screening coordinate points are functionally fitted to obtain a function, which is marked as a reference periodic wave.

[0009] Further, the real-time detection length based on the real-time detection wave and the reference waveform comprises the following sub-steps: Obtain each periodic wave in the real-time detection wave, which is marked as a real-time detection periodic wave; The starting points of the real-time detection periodic wave and the reference periodic wave are coincided; Draw the sixth number of coordinate points with equal interval paths on the real-time detection periodic wave, which are marked as first detection coordinate points; The first detection coordinate points are marked with sequence numbers according to the horizontal coordinates of the first detection coordinate points from small to large, which are marked as first sequence numbers; the first sequence numbers are positive integers starting from 1; Draw the sixth number of coordinate points with equal interval paths on the reference periodic wave, which are marked as second detection coordinate points; The second detection coordinate points are marked with sequence numbers according to the horizontal coordinates of the second detection coordinate points from small to large, which are marked as second sequence numbers; the second sequence numbers are positive integers starting from 1; The first detection coordinate points and the second detection coordinate points with the same first sequence numbers and second sequence numbers are connected to obtain line segments, which are marked as interval line segments; The length between the interval line segments is obtained, which is marked as the real-time detection length.

[0010] Further, the historical detection length based on the normal wave without harmonic comprises the following sub-steps: Obtain the periodic wave of the fourth number of normal waves without harmonic, which is marked as a second historical periodic wave; The second historical periodic wave is regarded as a real-time detection periodic wave to obtain a real-time detection length, which is marked as a historical detection length.

[0011] Further, obtaining the detection length threshold based on the historical detection length comprises the following sub-steps: obtaining a range of the historical detection length, which is marked as a second overall range; the second overall range is evenly divided into a fifth number of ranges, which are marked as second divided ranges; obtaining a frequency of the historical detection length in each second divided range, which is marked as a second divided frequency; the second divided frequencies are sorted from left to right according to the minimum values of the corresponding second divided ranges from small to large.

[0012] Further, obtaining the detection length threshold based on the historical detection length further comprises the following sub-steps: obtaining a sum of the second frequencies, which is marked as a second sum frequency; dividing the second sum frequency by the fifth number to obtain a value, which is marked as a second average frequency; setting a second abnormality proportion; multiplying the second average frequency by the second abnormality proportion to obtain a value, which is marked as a second abnormality threshold; marking the second divided frequencies less than the second abnormality threshold as second abnormal frequencies; if the rightmost second divided frequency is a second abnormal frequency, deleting the rightmost second abnormal frequency, continuously deleting the second abnormal frequencies to the left until the rightmost second abnormal frequency is not a second abnormal frequency, and then stopping; after stopping, obtaining the maximum value of the second divided range corresponding to the rightmost second abnormal frequency, which is marked as a detection length threshold.

[0013] Further, classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves comprises the following sub-steps: if the real-time detection length is greater than the detection length threshold, marking the real-time detection wave as a first kind of real-time wave; if the real-time detection length is not greater than the detection length threshold, marking the real-time detection wave as a second kind of real-time wave; if it is the first kind of real-time wave, eliminating the harmonic of the current output by the photovoltaic inverter before inputting it into the power grid; if it is the second kind of real-time wave, directly inputting the current output by the photovoltaic inverter into the power grid.

[0014] The beneficial effects of the present application are: the present application obtains a photovoltaic inverter output current wave, which is marked as a real-time detection wave; obtains first historical data points based on normal current waves in the power grid; obtains screening coordinate points based on the first historical data points; obtains a reference periodic wave based on the screening coordinate points; constructs a real-time detection length based on the real-time detection wave and the reference waveform; obtains a historical detection length based on normal waves without harmonics; obtains a detection length threshold based on the historical detection length; classifies the real-time detection wave based on the real-time detection length and the detection length threshold, and performs different operations on different types of real-time detection waves, the advantage being that the comparison data is reduced, and the accuracy of the judgment result is improved. The present application constructs a real-time detection length based on a real-time detection wave and a reference waveform, and the advantage is that whether a harmonic appears is judged based on the real-time detection length, the comparison data is reduced, and the accuracy of the judgment result is improved. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The step flowchart of the method of the present application is shown in the figure. Figure 2 The schematic diagram of the reference periodic wave of the present application is shown in the figure. Figure 3 The schematic diagram of one interval line segment of the present application is shown in the figure. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0017] Embodiment 1, please refer to Figure 1 The present application provides a photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization method, which comprises the following steps: Step S1, obtaining a photovoltaic inverter output current wave, which is marked as a real-time detection wave.

[0018] Step S2, obtaining first historical data points based on normal current waves in the power grid; step S2 comprises the following substeps: Step S201, obtaining a first number of periodic waveforms in the normal current wave in the power grid, which is marked as a historical periodic wave; the first number of historical periodic waves obtain more accurate waveforms, for example, the first number is set to 100; Step S202, establishing a plane rectangular coordinate system with the horizontal axis value as time and the vertical coordinate as current value, which is marked as a historical current coordinate system; Step S203, making the starting points of the historical periodic waves coincide with the origin of the historical current coordinate system; Step S204, a second number of evenly spaced data points on each historical periodic wave are plotted, marked as first historical data points; a second number of first historical data points are obtained. For example, the second number is 20, for the convenience of obtaining the waveform of each historical periodic wave.

[0019] Step S3, a screening coordinate point is obtained based on the first historical data points; step S3 includes the following sub-steps: Step S301, the ordinate of the first historical data point with the same abscissa is obtained, marked as a historical ordinate; Step S302, the range of the historical ordinate is obtained, marked as a first overall range; Step S303, the first overall range is evenly divided into a third number of ranges, marked as a first divided range; a third number of first divided ranges are obtained. For example, the third number is 10, for the convenience of observing the distribution of the historical ordinate; Step S304, the frequency of the historical ordinate in each first divided range is obtained, marked as a first divided frequency; Step S305, the first divided frequencies are sorted from left to right in ascending order according to the minimum value of the corresponding first divided range.

[0020] Step S306, the sum of the first frequencies is obtained, marked as a first sum frequency; Step S307, the first sum frequency is divided by the third number to obtain a value, marked as a first average frequency; Step S308, a first abnormality proportion is set; the product of the first average frequency and the first abnormality proportion is obtained, marked as a first abnormality threshold; the first abnormality threshold is used to obtain smaller first divided frequencies, so the first abnormality proportion is set to be smaller. For example, the first abnormality proportion is 0.2; Step S309, the first divided frequencies less than the first abnormality threshold are marked as first abnormal frequencies; In actual application, the first sum frequency is obtained as 100; the first average frequency is calculated as 100÷10=10; the first abnormality threshold is calculated as 10×0.2=2; then the first abnormality threshold is 2; the first divided frequencies less than 2 are marked as first abnormal frequencies.

[0021] Step S310, if the leftmost first divided frequency is a first abnormal frequency, the leftmost first abnormal frequency is deleted, and the first abnormal frequencies are continuously deleted to the right until the leftmost is not a first abnormal frequency; after stopping, the minimum value of the first divided range corresponding to the leftmost first abnormal frequency is obtained, marked as a first ordinate value; the first ordinate value is used to screen out too small historical ordinates, so that the subsequent obtained historical ordinate range is more accurate, and the subsequent obtained reference periodic wave is more accurate; Step S311, if the first division frequency on the rightmost side is the first abnormal frequency, the first abnormal frequency on the rightmost side is deleted, and the first abnormal frequency is continuously deleted to the left until the first abnormal frequency on the rightmost side is not the first abnormal frequency, and then the deletion is stopped; after the deletion is stopped, the maximum value of the first division range corresponding to the first abnormal frequency on the rightmost side is obtained, and the maximum value is marked as a second vertical coordinate value; the second vertical coordinate value is used to filter out a too large historical vertical coordinate, so that the range of the subsequently obtained historical vertical coordinate is more accurate, and then the subsequently obtained reference cycle wave is more accurate.

[0022] Step S312, the first historical data point between the first vertical coordinate value and the second vertical coordinate value is obtained, and the first historical data point is marked as a screening coordinate point. In practical application, please refer to Figure 2 the drawing, the obtained screening coordinate point.

[0023] Step S4, a reference cycle wave is obtained based on the screening coordinate point; step S4 includes the following sub-steps: Step S401, the screening coordinate point of each same horizontal coordinate is obtained; Step S402, all the screening coordinate points are functionally fitted to obtain a function, and the function is marked as a reference cycle wave; the reference cycle wave is closer to the fluctuation of the normal current; In practical application, please refer to Figure 3 the drawing, the obtained reference cycle wave.

[0024] Step S5, a real-time detection length is constructed based on the real-time detection wave and the reference wave; step S5 includes the following sub-steps: Step S501, each cycle wave in the real-time detection wave is obtained, and the cycle wave is marked as a real-time detection cycle wave; Step S502, the starting points of the real-time detection cycle wave and the reference cycle wave are made to coincide; the coincidence is convenient for comparison; Step S503, a sixth number of coordinate points with equal interval paths are drawn on the real-time detection cycle wave, and the coordinate points are marked as first detection coordinate points; the greater the sixth number is set, the better, for example, the sixth number is 20; Step S504, the first detection coordinate points are marked with sequence numbers in the order from small to large according to the horizontal coordinates of the first detection coordinate points, and the sequence numbers are marked as first sequence numbers; the first sequence numbers are positive integers starting from 1; Step S505, a sixth number of coordinate points with equal interval paths are drawn on the reference cycle wave, and the coordinate points are marked as second detection coordinate points; the sixth number is set to be consistent to facilitate the first detection coordinate points and the second detection coordinate points; Step S506, the second detection coordinate points are marked with sequence numbers in the order from small to large according to the horizontal coordinates of the second detection coordinate points, and the sequence numbers are marked as second sequence numbers; the second sequence numbers are positive integers starting from 1; Step S507, connecting the first detection coordinate point with the second detection coordinate point to obtain a line segment, marked as an interval line segment, when the first sequence number is the same as the second sequence number; Step S508, obtaining the length between the interval line segments, marked as a real-time detection length; the real-time detection length is the same as the distance at the same position, and the greater the real-time detection length, the more it indicates that it is not close to the reference periodic wave; the real-time detection length can be used to judge the real-time detection periodic wave, and the comparison data such as frequency and assignment can be reduced; the real-time detection length is the actual distance of the drawing size.

[0025] In practical application, please refer to Figure 3 As shown in the figure, an interval line segment is obtained; the obtained real-time detection length is 5 cm.

[0026] Step S6, obtaining a historical detection length based on a normal wave without harmonic; step S6 includes the following sub-steps: Step S601, obtaining a periodic wave of a fourth number of normal waves without harmonic, marked as a second historical periodic wave; the fourth number of second historical periodic waves is to obtain the maximum value of the real-time detection length when there is no harmonic; therefore, the fourth number should not be too small, for example, the fourth number is 100; Step S602, obtaining a real-time detection length by regarding the second historical periodic wave as a real-time detection periodic wave, marked as a historical detection length.

[0027] Step S7, obtaining a detection length threshold value based on the historical detection length; step S7 includes the following sub-steps: Step S701, obtaining a range of the historical detection length, marked as a second overall range; Step S702, dividing the second overall range into a fifth number of ranges uniformly, marked as a second divided range; the fifth number of second divided ranges is to observe the distribution of the historical detection length, for example, the fifth number is 10; Step S703, obtaining the frequency of the historical detection length in each second divided range, marked as a second divided frequency; Step S704, sorting the second divided frequencies from left to right in ascending order according to the minimum value of the corresponding second divided range.

[0028] Step S705, obtaining the sum of the second frequencies, marked as a second sum frequency; Step S706, dividing the second sum frequency by the fifth number to obtain a value, marked as a second average frequency; Step S707, setting a second abnormal proportion; multiplying the second average frequency by the second abnormal proportion to obtain a value, marked as a second abnormal threshold value; the second abnormal threshold value is to obtain a smaller second divided frequency, so the second abnormal proportion should not be too large, for example, the second abnormal proportion is 0.2; Step S708, marking the second division frequency less than the second abnormal threshold as a second abnormal frequency; In practical application, the second total frequency is 100; the second average division frequency is calculated as 100÷10=10; the second abnormal threshold is calculated as 10×0.2=2; and the second abnormal threshold is 2. The second division frequency less than 2 is marked as a second abnormal frequency.

[0029] Step S709, if the rightmost second division frequency is a second abnormal frequency, deleting the rightmost second abnormal frequency, and continuously deleting the second abnormal frequency to the left until the rightmost second abnormal frequency is not a second abnormal frequency; after stopping, obtaining the maximum value of the second division range corresponding to the rightmost second abnormal frequency, and marking it as a detection length threshold; the detection length threshold is used to filter out a too large historical detection length; that is, deleting an abnormal point to make the maximum value of the obtained historical detection length more accurate. In practical application, for example, the detection length threshold is 0.62 cm.

[0030] Step S8, classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves; step S8 includes the following sub-steps: Step S801, if the real-time detection length greater than the detection length threshold appears, marking the real-time detection wave as a first kind of real-time wave; if the real-time detection length greater than the detection length threshold does not appear, marking the real-time detection wave as a second kind of real-time wave; if it is the first kind of real-time wave, eliminating the harmonic of the current output by the photovoltaic inverter before inputting it into the power grid; if it is the second kind of real-time wave, directly inputting the current output by the photovoltaic inverter into the power grid; if there is no harmonic, the real-time detection wave is similar to the reference periodic wave, and the real-time detection length is small; if there is a harmonic, the real-time detection wave is distorted, the real-time detection wave is different from the reference periodic wave, and the real-time detection length is large, and will be greater than the detection length threshold, so it is necessary to eliminate the harmonic before inputting it into the power grid. In practical application, there is more than one real-time detection length, for example, the real-time detection length 5 cm is greater than the detection length threshold 0.62 cm; the real-time detection wave is marked as the first kind of real-time wave, and the current output by the photovoltaic inverter is eliminated before being inputted into the power grid, which can use the existing harmonic elimination method.

[0031] In some embodiments, the electronic device can include a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory can communicate with each other through the communication bus. The memory can store computer-readable instructions. The processor can invoke the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in the method for photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization can be performed to achieve the following functions: obtaining a photovoltaic inverter output current wave, which is marked as a real-time detection wave; obtaining a first historical data point based on a normal current wave in the power grid; obtaining a screening coordinate point based on the first historical data point; obtaining a reference periodic wave based on the screening coordinate point; constructing a real-time detection length based on the real-time detection wave and the reference waveform; obtaining a historical detection length based on a normal wave without harmonics; obtaining a detection length threshold based on the historical detection length; and classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves.

[0032] In addition, the logical instructions in the memory described above can be implemented in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0033] In some embodiments, the electronic device can include a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory can communicate with each other through the communication bus. The memory can store computer-readable instructions. The processor can invoke the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in the method for photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization can be performed to achieve the following functions: obtaining a photovoltaic inverter output current wave, which is marked as a real-time detection wave; obtaining a first historical data point based on a normal current wave in the power grid; obtaining a screening coordinate point based on the first historical data point; obtaining a reference periodic wave based on the screening coordinate point; constructing a real-time detection length based on the real-time detection wave and the reference waveform; obtaining a historical detection length based on a normal wave without harmonics; obtaining a detection length threshold based on the historical detection length; and classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves.

[0034] Embodiment 4, the application also provides a computer readable storage medium, and the application provides a storage medium, which stores a computer program, and the computer program is executed by a processor to run the steps in the photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization method to realize the following functions: obtaining a photovoltaic inverter output current wave, marked as a real-time detection wave; obtaining a first historical data point based on a normal current wave in the power grid; obtaining a screening coordinate point based on the first historical data point; obtaining a reference periodic wave based on the screening coordinate point; constructing a real-time detection length based on the real-time detection wave and the reference wave; obtaining a historical detection length based on a normal wave without harmonics; obtaining a detection length threshold based on the historical detection length; classifying the real-time detection wave based on the real-time detection length and the detection length threshold, and performing different operations on different kinds of real-time detection waves.

[0035] Through the description of the above embodiments, the embodiments of the application can be provided as a method, a system or a computer program product. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the method described in each embodiment or some parts of the embodiment.

[0036] In the embodiments provided by the present application, it should be understood that the disclosed system or method can be implemented in other ways. The above described embodiments are only illustrative, for example, the division of the modules or units is only a logical function division, and there can be another division way in actual implementation, for example, a plurality of modules or units can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed each other can be through some communication interface, indirect coupling or communication connection between systems, modules and units can be electrical, mechanical or other forms.

[0037] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for photovoltaic inverter harmonic suppression and power grid power quality collaborative optimization, characterized in that, The method comprises the following steps: Obtain a photovoltaic inverter output current wave, marked as a real-time detection wave; Obtain a first historical data point based on a normal current wave in a power grid; Obtain a screening coordinate point based on the first historical data point; Obtain a reference periodic wave based on the screening coordinate point; Construct a real-time detection length based on the real-time detection wave and the reference wave; Obtain a historical detection length based on a normal wave without harmonics; Obtain a detection length threshold based on the historical detection length; Classify the real-time detection wave based on the real-time detection length and the detection length threshold, and perform different operations on different types of real-time detection waves.

2. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 1, wherein, Obtaining a first historical data point based on a normal current wave in a power grid comprises the following sub-steps: Obtain a first number of periodic waveforms in the normal current wave in the power grid, marked as historical periodic waves; Establish a plane rectangular coordinate system with the horizontal axis value as time and the vertical coordinate as the current value, marked as a historical current coordinate system; Make the starting points of the historical periodic waves coincide with the origin of the historical current coordinate system; Draw a second number of evenly spaced data points on each historical periodic wave, marked as first historical data points.

3. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 2, wherein, Obtaining a screening coordinate point based on the first historical data point comprises the following sub-steps: Obtain the vertical coordinates of the first historical data points with equal horizontal coordinates, marked as historical vertical coordinates; Obtain the range of the historical vertical coordinates, marked as a first overall range; Divide the first overall range into a third number of ranges, marked as first divided ranges; Obtain the frequency of the historical vertical coordinates in each first divided range, marked as first divided frequencies; Sort the first divided frequencies from left to right in ascending order according to the minimum values of the corresponding first divided ranges.

4. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 3, wherein, Obtaining a screening coordinate point based on the first historical data point further comprises the following sub-steps: Obtain the sum of the first frequencies, marked as a first sum frequency; Divide the first sum frequency by the third number to obtain a value, marked as a first evenly divided frequency; Set a first abnormal proportion; multiply the first evenly divided frequency by the first abnormal proportion to obtain a value, marked as a first abnormal threshold; Mark the first divided frequencies less than the first abnormal threshold as first abnormal frequencies; If the leftmost first divided frequency is a first abnormal frequency, delete the leftmost first abnormal frequency and continue to delete the first abnormal frequencies to the right until the leftmost is not a first abnormal frequency, then stop; after stopping, obtain the minimum value of the first divided range corresponding to the leftmost first abnormal frequency, marked as a first vertical coordinate value; If the rightmost first divided frequency is a first abnormal frequency, delete the rightmost first abnormal frequency and continue to delete the first abnormal frequencies to the left until the rightmost is not a first abnormal frequency, then stop; after stopping, obtain the maximum value of the first divided range corresponding to the rightmost first abnormal frequency, marked as a second vertical coordinate value; Obtain the first historical data points with vertical coordinates between the first vertical coordinate value and the second vertical coordinate value, marked as screening coordinate points.

5. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 4, wherein, Obtaining a reference periodic wave based on the screening coordinate point comprises the following sub-steps: Obtain the screening coordinate points with the same horizontal coordinates; Obtain a function by fitting all the screening coordinate points, marked as a reference periodic wave.

6. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 5, wherein, Constructing a real-time detection length based on the real-time detection wave and the reference wave comprises the following sub-steps: Obtaining each cycle waveform in the real-time detection wave, and marking as a real-time detection cycle wave; Aligning the starting point of the real-time detection cycle wave with the starting point of the reference cycle wave; Drawing sixth quantity of coordinate points with equal interval paths on the real-time detection cycle wave, and marking as first detection coordinate points; Marking sequence numbers of the first detection coordinate points according to the abscissas of the first detection coordinate points from small to large, and marking as first sequence numbers; the first sequence numbers are positive integers starting from 1; Drawing sixth quantity of coordinate points with equal interval paths on the reference cycle wave, and marking as second detection coordinate points; Marking sequence numbers of the second detection coordinate points according to the abscissas of the second detection coordinate points from small to large, and marking as second sequence numbers; the second sequence numbers are positive integers starting from 1; Connecting the first detection coordinate points and the second detection coordinate points with the same first sequence numbers and second sequence numbers to obtain line segments, and marking as interval line segments; Obtaining lengths between the interval line segments, and marking as real-time detection lengths. Obtaining a historical detection length based on the normal waves without harmonics includes the following sub-steps:

7. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 6, wherein, Obtaining cycle waves of fourth quantity of normal waves without harmonics, and marking as second historical cycle waves; Obtaining a real-time detection length based on the second historical cycle waves as the real-time detection cycle waves, and marking as a historical detection length. Obtaining a detection length threshold value based on the historical detection length includes the following sub-steps:

8. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 7, wherein, Obtaining a range of the historical detection lengths, and marking as a second overall range; Dividing the second overall range into fifth quantity of ranges, and marking as second divided ranges; Obtaining frequency numbers of the historical detection lengths in each second divided range, and marking as second divided frequency numbers; Sorting the second divided frequency numbers from left to right according to the minimum values of the corresponding second divided ranges from small to large. Obtaining a detection length threshold value based on the historical detection length further includes the following sub-steps:

9. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 8, wherein, Obtaining a sum of the second frequency numbers, and marking as a second sum frequency number; Dividing the second sum frequency number by the fifth quantity to obtain a value, and marking as a second average frequency number; Setting a second abnormal proportion; multiplying the second average frequency number and the second abnormal proportion to obtain a value, and marking as a second abnormal threshold value; Marking the second divided frequency numbers less than the second abnormal threshold value as second abnormal frequency numbers; If the rightmost second divided frequency number is the second abnormal frequency number, deleting the rightmost second abnormal frequency number, and continuously deleting the second abnormal frequency numbers to the left until the rightmost second abnormal frequency number is not the second abnormal frequency number, and then stopping; after stopping, obtaining the maximum value of the second divided range corresponding to the rightmost second abnormal frequency number, and marking as a detection length threshold value. Classifying the real-time detection waves based on the real-time detection lengths and the detection length threshold value, and performing different operations on different kinds of real-time detection waves includes the following sub-steps:

10. The photovoltaic inverter harmonic mitigation and grid power quality co-optimization method of claim 9, wherein, If the real-time detection length greater than the detection length threshold value appears, marking the real-time detection wave as a first kind of real-time wave; if the real-time detection length greater than the detection length threshold value does not appear, marking the real-time detection wave as a second kind of real-time wave; if it is the first kind of real-time wave, eliminating the harmonics of the current output by the photovoltaic inverter before inputting the current into the power grid; if it is the second kind of real-time wave, directly inputting the current output by the photovoltaic inverter into the power grid. ​

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