Photovoltaic grid-connected broadband oscillation suppression system based on network construction type energy storage

Abstract

The invention discloses a photovoltaic grid-connected broadband oscillation suppression system based on network construction type energy storage, and belongs to the technical field of photovoltaic grid connection. The invention aims to solve the problem of broadband oscillation in photovoltaic grid connection. Comprising the following steps: acquiring voltage and current of a public grid-connected point and energy storage voltage and current by adopting a data acquisition module, and preprocessing; a data processing module is adopted to carry out autoregressive empirical wavelet transform on voltage and current of a common grid-connected point to obtain an oscillation signal, and then interpolation discrete Fourier transform of a Hanning window is adopted to obtain modal information; filtering a fundamental component of the energy storage voltage based on the modal information by adopting an adaptive impedance remodeling module, and then filtering to obtain a filtered energy storage voltage harmonic component; self-adaptive impedance remodeling is carried out to obtain an energy storage voltage harmonic component after amplitude and phase adjustment; and inputting the harmonic component of the energy storage voltage after amplitude and phase adjustment as a voltage feedback signal to a PWM control link of the inverter, thereby realizing broadband oscillation suppression at the public grid-connected point. The method is used for photovoltaic grid-connected oscillation suppression.

Description

Technical Field

[0001] The present invention relates to a photovoltaic grid-connected broadband oscillation suppression system based on grid-type energy storage, and belongs to the technical field of photovoltaic grid-connected technology. Background Art

[0002] With the continued increase in renewable energy penetration and the large-scale application of power electronics, the mechanisms for safe and stable operation of power systems have undergone qualitative changes, leading to the frequent occurrence of broadband oscillations. Specifically, as the scale of photovoltaic grid integration continues to expand, its impact on system stability is also increasing. The integration of large numbers of photovoltaics into weak grids can lead to complex oscillation problems, affecting frequency bands including low-frequency, sub-synchronous / super-synchronous, and medium- and high-frequency.

[0003] In practical applications, energy storage grid-connected converters are often deployed with photovoltaic power generation to smooth output power fluctuations. Therefore, grid-connected energy storage converters can be used to enhance the stability of photovoltaic grid-connected power generation. However, simply integrating grid-connected energy storage into a photovoltaic system still carries the risk of broadband oscillation. Therefore, it is necessary to suppress broadband oscillations in photovoltaic grid-connected systems. Summary of the Invention

[0004] In response to the broadband oscillation problem existing in photovoltaic grid-connected systems, the present invention provides a photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage.

[0005] The present invention provides a photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage, comprising: A data acquisition module is used to collect the public grid connection point voltage and public grid connection point current of the photovoltaic grid, as well as the energy storage voltage and energy storage current; pre-process the collected data to obtain the pre-processed public grid connection point voltage and pre-processed public grid connection point current, as well as the pre-processed energy storage voltage and pre-processed energy storage current; The data processing module includes a spectrum analysis unit and an oscillation mode extraction unit: The spectrum analysis unit is used to perform spectrum analysis on the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current by using an autoregressive empirical wavelet transform method to obtain time domain signals of the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current in different frequency bands; identify the time domain signals to determine the oscillation signal; and the oscillation mode extraction unit is used to perform an interpolation discrete Fourier transform using a Hanning window on the oscillation signal and calculate and obtain the modal information of the oscillation signal; The adaptive impedance reshaping module includes a notch filter, adaptive bandpass filters for multiple frequency bands, and corresponding adaptive amplitude and phase adjustment units: The notch filter is used to filter out the fundamental frequency component of the pre-processed energy storage voltage to obtain the energy storage voltage harmonic component; the adaptive band-pass filter corresponding to the current pre-processed energy storage voltage frequency band adaptively adjusts its center frequency and quality factor according to the modal information, and then filters the received energy storage voltage harmonic component to obtain the filtered energy storage voltage harmonic component; the adaptive amplitude and phase adjustment unit is set in the form of a virtual impedance, adaptively reshapes the impedance according to the pre-processed energy storage voltage and the pre-processed energy storage current, and adaptively adjusts the amplitude and phase of the filtered energy storage voltage harmonic component to obtain the energy storage voltage harmonic component after amplitude and phase adjustment; The harmonic component of the energy storage voltage after the amplitude and phase adjustment is input as a voltage feedback signal to the PWM control link of the inverter to achieve broadband oscillation suppression at the public grid connection point.

[0006] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, the autoregressive empirical wavelet transform method includes an autoregressive algorithm: An autoregressive algorithm is used to obtain an adaptive model for the pre-processed common grid connection point voltage and the pre-processed common grid connection point current using a Burg algorithm, and a corresponding power spectrum is obtained according to the adaptive model; The power spectrum is then divided into frequency bands: the local maximum of each frequency band of the power spectrum is identified, and the midpoint between adjacent local maxima is taken as the power spectrum boundary of adjacent frequency bands.

[0007] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, the transfer function of the adaptive model is for: (1), In the formula is a complex variable, For the i The order model coefficients, is the model order; Power spectrum obtained from the adaptive model for: (2), In the formula is the center frequency, is the variance.

[0008] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, the autoregressive empirical wavelet transform method also includes an empirical wavelet transform method: The empirical wavelet transform method establishes a wavelet packet bandpass filter based on the power spectrum boundary and obtains the wavelet packet empirical mode; based on the wavelet packet empirical mode, the corresponding time domain signal is obtained from the power spectrum data of the corresponding frequency band; and then the Hilbert transform is used to obtain the oscillation signal from the time domain signals of different frequency bands.

[0009] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, the oscillation mode extraction unit uses a Hanning window to select the oscillation signal, and then performs an interpolation discrete Fourier transform on the currently selected oscillation signal; the modal information of the oscillation signal is obtained based on the spectral function of the Hanning window, including the oscillation frequency and oscillation amplitude.

[0010] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, the adaptive bandpass filter adjusts the center frequency according to the oscillation frequency and adjusts the quality factor according to the oscillation amplitude.

[0011] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-type energy storage of the present invention, an adaptive bandpass filter of the corresponding frequency band is selected according to the frequency band of the current preprocessed energy storage voltage to filter the received energy storage voltage harmonic components to obtain the filtered energy storage voltage harmonic components.

[0012] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-type energy storage of the present invention, the adaptive amplitude and phase adjustment unit adaptively adjusts the size of the virtual resistance and virtual inductance according to the impedance empirical formula and the amplitude and phase of the corresponding adaptive bandpass filter, thereby providing positive damping for the system impedance within the corresponding oscillation frequency range and reshaping the system impedance.

[0013] According to the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage of the present invention, preprocessing of collected data includes filtering, noise reduction and interference reduction of the collected data.

[0014] The beneficial effects of the present invention are as follows: the system of the present invention is based on the collection of current and voltage data at the public grid-connected point and accurately identifies oscillations in different frequency bands through autoregressive empirical wavelet transform, and obtains oscillation modal information by adopting the interpolation discrete Fourier transform of the Hanning window; then adaptive impedance reshaping is performed based on the oscillation modal information: the energy storage voltage is feedback-controlled through the notch filter, adaptive bandpass filter and adaptive amplitude and phase adjustment unit, and the system impedance is adaptively reshaped to achieve broadband oscillation suppression of photovoltaic grid-connected cells.

[0015] The system of the present invention uses an autoregressive empirical wavelet transform method to process the grid-connected voltage and current signals. Compared with the traditional spectrum method relying on Fourier transform, it is more accurate and reliable, will not misinterpret noise spikes and false peaks, resulting in incorrect or missed frequency boundary detection, has excellent noise resistance, and produces a smoother spectral shape and clearer peaks, which can more accurately identify oscillations of each frequency and provide more accurate data for subsequent oscillation mode extraction. The use of Hanning window interpolation discrete Fourier transform to extract oscillation modes can effectively suppress spectrum leakage, thereby improving extraction accuracy. The use of an adaptive impedance reshaping device to adaptively reshape the impedance of the system according to the modal data of the oscillation has a relatively independent processing process and is simple to operate. The use of an adaptive bandpass filter in the adaptive impedance reshaping module has a better effect in suppressing oscillations. Since oscillations usually have a certain range, the adaptive bandpass filter can suppress existing oscillations while also reducing the risk of oscillations within a certain frequency range. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the structure of the photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to the present invention; GFL in the figure indicates that the photovoltaic control is traditional grid-following control; Figure 2 It is the flow chart of the data processing module; Figure 3 is a schematic diagram of the adaptive impedance reshaping module; Figure 4 This is a schematic diagram of power spectrum segmentation. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0019] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0020] Combine Figures 1 to 4 As shown, the present invention provides a photovoltaic grid-connected broadband oscillation suppression system based on grid-type energy storage, comprising: A data acquisition module is used to collect the public grid connection point voltage and public grid connection point current of the photovoltaic grid, as well as the energy storage voltage and energy storage current; pre-process the collected data to obtain the pre-processed public grid connection point voltage and pre-processed public grid connection point current, as well as the pre-processed energy storage voltage and pre-processed energy storage current; The data processing module includes a spectrum analysis unit and an oscillation mode extraction unit: The spectrum analysis unit is used to perform spectrum analysis on the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current by using an autoregressive empirical wavelet transform method to obtain time domain signals of the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current in different frequency bands; identify the time domain signals to determine the oscillation signal; and the oscillation mode extraction unit is used to perform an interpolation discrete Fourier transform using a Hanning window on the oscillation signal and calculate and obtain the modal information of the oscillation signal; The adaptive impedance reshaping module includes a notch filter, adaptive bandpass filters for multiple frequency bands, and corresponding adaptive amplitude and phase adjustment units: The notch filter is used to filter out the fundamental frequency component of the pre-processed energy storage voltage to obtain the energy storage voltage harmonic component; the adaptive band-pass filter corresponding to the current pre-processed energy storage voltage frequency band adaptively adjusts its center frequency and quality factor according to the modal information, and then filters the received energy storage voltage harmonic component to obtain the filtered energy storage voltage harmonic component; the adaptive amplitude and phase adjustment unit is set in the form of a virtual impedance, adaptively reshapes the impedance according to the pre-processed energy storage voltage and the pre-processed energy storage current, and adaptively adjusts the amplitude and phase of the filtered energy storage voltage harmonic component to obtain the energy storage voltage harmonic component after amplitude and phase adjustment; The harmonic component of the energy storage voltage after the amplitude and phase adjustment is input as a voltage feedback signal to the PWM control link of the inverter to achieve broadband oscillation suppression at the public grid connection point.

[0021] The spectrum analysis unit is used to determine whether the signal oscillates and the oscillation frequency; the oscillation mode extraction unit transforms the oscillation data to obtain oscillation mode information; after identifying the oscillation, the adaptive impedance reshaping module adaptively reshapes the energy storage system impedance according to the oscillation mode information to suppress the photovoltaic grid-connected broadband oscillation.

[0022] The notch filter is used to filter out the fundamental frequency component of the energy storage voltage to prevent the impedance reshaping device from affecting the fundamental frequency impedance of the energy storage system, thereby affecting the static operating point of the system; the adaptive amplitude and phase adjustment unit is used to adaptively adjust the final phase and amplitude of the voltage feedback, so that the impedance of the photovoltaic and energy storage grid-connected system is reshaped at the corresponding oscillation frequency, thereby suppressing the occurrence of photovoltaic broadband oscillation.

[0023] Large-scale photovoltaic grid integration leads to frequent broadband oscillations, which adversely affect the normal operation of the power system, grid dispatch decisions, and safe and economical operation. This embodiment is used to effectively suppress the broadband oscillations caused by photovoltaic grid integration.

[0024] Combine Figure 1 As shown, a photovoltaic power station and grid-connected energy storage are connected at a public grid connection point (PCC) to form a photovoltaic-energy storage hybrid grid-connected system. The grid-connected energy storage system includes not only its grid-connected (GFM) inverter control but also an adaptive impedance reshaping device. In this implementation, the adaptive impedance reshaping device, based on grid-connected energy storage voltage feedback, suppresses oscillations, achieving excellent results, low cost, and ease of practical engineering implementation.

[0025] In this embodiment, the data acquisition module collects the voltage and current at the PCC point, and filters, reduces noise, and interference for subsequent spectrum analysis. It can also collect currents at the photovoltaic grid-connected point and the grid-connected energy storage point to verify the empirical impedance formula (the empirical impedance formula can be obtained by theoretical derivation by adding a broadband disturbance signal, measuring the change value of the voltage and current at each frequency, and taking the negative value of the ratio of the two as the impedance at the corresponding frequency) for the subsequent adaptive phase and amplitude adjustment link.

[0026] Combine Figure 2 As shown, the autoregressive empirical wavelet transform method includes an autoregressive algorithm: An autoregressive algorithm is used to obtain an adaptive model for the pre-processed common grid connection point voltage and the pre-processed common grid connection point current using a Burg algorithm, and a corresponding power spectrum is obtained according to the adaptive model; The power spectrum is then divided into frequency bands: the local maximum of each frequency band of the power spectrum is identified by locating points whose amplitude is greater than that of their adjacent points. After obtaining the local maximum, the midpoint between adjacent local maxima is taken as the power spectrum boundary of adjacent frequency bands.

[0027] In this embodiment, the autoregressive algorithm performs power spectrum division on the collected data, has excellent noise resistance, and can generate a smooth power spectrum.

[0028] Furthermore, the transfer function of the adaptive model for: (1), In the formula is a complex variable, For the i The order model coefficients, is the model order; Power spectrum estimation requires obtaining the autoregressive model parameters and white noise variance. The power spectrum obtained by the adaptive model for: (2), In the formula is the center frequency, is the white noise variance.

[0029] This embodiment uses the Burg algorithm to obtain autoregressive model parameters. The Burg algorithm is a modern spectral estimation method that does not rely on the signal's autocorrelation sequence but instead directly solves for the reflection coefficient from the observed data. This method is closely related to the prediction error lattice filter and determines the optimal reflection coefficient by minimizing the average power of the forward and backward prediction errors. The advantage of the Burg algorithm is that it avoids the use of the autocorrelation function, which can lead to inaccurate estimation in traditional methods.

[0030] Using the Burg algorithm, the forward and backward prediction errors are expressed as: , , The best criterion for selecting the reflection coefficient is to reduce the overall forward and backward prediction errors, resulting in a smoother and higher resolution autoregressive model. The prediction error is expressed as: , Finally, the coefficients of the AR model are determined using the Levinson recursive formula, which is expressed as: , in, For the k The first i The reflection coefficient, Denotes the new reflection coefficient, which is given by get, is the prediction error.

[0031] The autoregressive empirical wavelet transform method also includes an empirical wavelet transform method: The empirical wavelet transform method establishes a wavelet packet bandpass filter based on the power spectrum boundary and obtains the wavelet packet empirical mode; based on the wavelet packet empirical mode, the corresponding time domain signal is obtained from the power spectrum data of the corresponding frequency band; and then the Hilbert transform is used to obtain the oscillation signal from the time domain signals of different frequency bands.

[0032] The autoregressive empirical wavelet establishes a bandpass filter formed by the empirical wave packet according to the power spectrum obtained by the adaptive algorithm, and obtains the empirical mode, thereby identifying the oscillation signal and obtaining the oscillation data.

[0033] After obtaining the power spectrum and its boundaries through the Burg algorithm, the power spectrum is segmented. The segmentation method identifies the local maximum by locating the points whose amplitude is greater than that of its immediate neighbors. After obtaining the local maximum in the smoothed spectrum, the boundaries are determined by taking the midpoints between adjacent maxima and finally mapped to the Fourier spectrum [0,π]. The corresponding boundaries are mapped to the center frequency of each segment. : The method of splitting the power spectrum map to obtain the Fourier spectrum can be referred to Figure 4 As shown, in Figure 4 In the example, the local maximum is represented by points p1, p2, ..., p n , p n+1 , highlighted with a red circle. The boundary corner frequency is defined as the midpoint between adjacent local maxima 、 … 、 … , represented by the red dotted line, the bandpass filter between each pair of adjacent angular frequencies is the wavelet packet function. Figure 4 middle 、 … and represents the transition part corresponding to the boundary angular frequency, is the wavelet packet empirical mode scaling function corresponding to the boundary angular frequency, 、 and is the wavelet packet function corresponding to the boundary angular frequency.

[0034] The empirical wavelet transform is used to segment the power spectrum, establish a wavelet packet bandpass filter, obtain wavelet packet empirical modes, and identify wide-band oscillations. After segmenting the power spectrum, the empirical wavelet is used as a bandpass filter according to the wavelet packet function and the wavelet packet empirical modes are obtained according to the empirical mode scaling formula. The wavelet packet function and the empirical mode scaling function are: in, is the wavelet packet function, is the empirical mode scaling function, represents the conversion function, represents the coefficient, 2 is the transition part of each boundary angular frequency.

[0035] After obtaining the wavelet packet empirical pattern, the time domain information can be extracted: the detail coefficients are derived from the dot product of the signal (collected voltage and current) and the wavelet function. The approximate coefficients are obtained by calculating the dot product of the signal and the scaling function, as shown in the following formula: where · represents the dot product. The superscript represents the conjugate of the variable. The Fourier transform is given by F [·]express, F -1 [·] represents its inverse function.

[0036] The voltage and current time domain information corresponding to each approximation coefficient can be easily obtained: After obtaining the time domain information of different frequency bands, the Hilbert transform is used to identify whether oscillation occurs in each frequency band (each power spectrum represents a frequency band). If oscillation is identified, the data is sent to the oscillation mode extraction unit. The Hilbert transform identification process is as follows: , , , in, for The discretized real signal.

[0037] The amplitude and frequency of each mode are calculated as follows: , , When the amplitude exceeds the set value, it is determined that an oscillation of the corresponding frequency has occurred. After the oscillation is identified, all data are sent to the oscillation mode extraction unit to further extract the oscillation mode information more accurately.

[0038] The oscillation mode extraction unit uses a Hanning window to select the oscillation signal and then performs an interpolated discrete Fourier transform on the selected oscillation signal. Based on the spectral function of the Hanning window, the modal information of the oscillation signal, including the oscillation frequency and oscillation amplitude, is obtained. The discrete Fourier transform using the Hanning window effectively suppresses the mutual interference caused by spectral leakage of multiple oscillation modes, allowing for more accurate extraction of the modal information of each oscillation mode.

[0039] The notch filter is used to filter out the fundamental frequency component of the energy storage voltage to prevent the impedance reshaping device from affecting the fundamental frequency impedance of the energy storage system, thereby affecting the static operating point of the system. The formula is: , in, is the fundamental frequency, It reflects the bandwidth capability of the notch filter.

[0040] After the data enters the oscillation mode extraction unit, the oscillation mode information will be extracted using the difference Fourier transform algorithm based on the Hanning window. The algorithm process is as follows: S1: Apply a Hanning window to the broadband oscillating signal and then perform a DFT on the windowed signal. The spectral function is expressed as: in, , It is a Hanning window. The broadband oscillation signal is the oscillation signal identified by Hilbert transform. N Signal length.

[0041] S2: The positions of the maximum and second maximum in the spectrum function are defined as k m and k m+1 , and their values ​​are expressed as: S3: Set variable parameters a = k 0- k m -0.5, where k 0 is the theoretical frequency index, ranging from -0.5 to 0.5, and the formula for the ratio is: , in W is the spectral function of the Hanning window.

[0042] S4: The modal information of the final oscillation is as follows, and the formulas for the oscillation frequency and amplitude are: in, f s is the sampling frequency.

[0043] Furthermore, the adaptive bandpass filter adjusts the center frequency according to the oscillation frequency and adjusts the quality factor according to the oscillation amplitude. The adaptive bandpass filter adaptively changes its cutoff frequency and quality factor based on the oscillation mode information to more accurately and effectively suppress oscillations in each frequency band and reduce the risk of oscillations in nearby frequencies. The formula is: , in, is the center frequency, is the quality factor.

[0044] According to the frequency band of the current pre-processed energy storage voltage, an adaptive band-pass filter of a corresponding frequency band is selected to filter the received energy storage voltage harmonic components to obtain filtered energy storage voltage harmonic components.

[0045] The adaptive amplitude and phase adjustment unit adaptively adjusts the size of the virtual resistance and virtual inductance according to the impedance empirical formula and the amplitude and phase of the corresponding adaptive bandpass filter, providing positive damping for the system impedance within the corresponding oscillation frequency range and reshaping the system impedance.

[0046] The adaptive amplitude and phase adjustment unit adjusts the phase and amplitude of the final voltage feedback by adjusting the value of the virtual impedance, completing the adaptive impedance reshaping and suppressing the broadband oscillation of the photovoltaic grid. The formula is: , in, is the virtual inductor, is a virtual resistor.

[0047] After obtaining the oscillation mode information, it is sent to the adaptive impedance reshaping module for adaptive adjustment. The structure of the adaptive impedance reshaping module is referenced Figure 3 The collected energy storage voltage first passes through a notch filter, then through multiple adaptive bandpass filters in parallel and the corresponding amplitude and phase adjustment links, and finally the feedback signal is involved in the modulation wave calculation of the energy storage inverter.

[0048] The oscillation modal information is first filtered out by a notch filter to remove the fundamental frequency to prevent it from affecting the static stability operating point of the system.

[0049] The center frequency of the adaptive bandpass filter is adjusted according to the frequency of the oscillation modal information, and the quality factor of the adaptive bandpass filter is adjusted according to the frequency range of the oscillation to reduce the risk of oscillation at frequencies near the oscillation; oscillations in different frequency bands (achieved by power spectrum segmentation) are distributed to multiple adaptive bandpass filters, which work together to process the oscillations in the corresponding frequency bands respectively, achieving wide frequency band coverage.

[0050] The amplitude and phase adjustment link adaptively adjusts the size of the virtual resistance and virtual inductance according to the impedance empirical formula and the amplitude and phase of the corresponding adaptive bandpass filter, providing positive damping for the system impedance at the frequency of oscillation and within a certain range, reshaping the system impedance and thus suppressing the oscillation.

[0051] Preprocessing of collected data includes filtering, noise reduction and interference reduction to avoid the impact of noise and interference on data results.

[0052] In summary, the present invention collects and filters the voltage and current at the common connection point (PCC) where the photovoltaic and grid-connected energy storage systems are connected to the grid, and performs spectrum analysis to identify and determine whether oscillation occurs. If oscillation occurs, the oscillation mode is extracted by an oscillation mode extraction unit, and an adaptive impedance reshaping device is used to adaptively reshape the impedance of the photovoltaic and grid-connected energy storage systems based on the oscillation mode information, thereby achieving broadband oscillation suppression for photovoltaic grid connection.

[0053] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be employed in conjunction with other described embodiments.

Claims

1. A photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage, characterized in that: include: A data acquisition module is used to collect the voltage and current of the public grid connection point of the photovoltaic grid, as well as the energy storage voltage and energy storage current; Preprocessing the collected data to obtain a preprocessed common grid connection point voltage and a preprocessed common grid connection point current, as well as a preprocessed energy storage voltage and a preprocessed energy storage current; The data processing module includes a spectrum analysis unit and an oscillation mode extraction unit: The spectrum analysis unit is used to perform spectrum analysis on the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current by using an autoregressive empirical wavelet transform method to obtain time domain signals of the pre-processed common grid-connected point voltage and the pre-processed common grid-connected point current in different frequency bands; identify the time domain signals to determine the oscillation signal; and the oscillation mode extraction unit is used to perform an interpolation discrete Fourier transform using a Hanning window on the oscillation signal and calculate and obtain the modal information of the oscillation signal; The adaptive impedance reshaping module includes a notch filter, adaptive bandpass filters for multiple frequency bands, and corresponding adaptive amplitude and phase adjustment units: The notch filter is used to filter out the fundamental frequency component of the pre-processed energy storage voltage to obtain the energy storage voltage harmonic component; the adaptive bandpass filter corresponding to the current pre-processed energy storage voltage frequency band adaptively adjusts its center frequency and quality factor according to the modal information, and then filters the received energy storage voltage harmonic component to obtain the filtered energy storage voltage harmonic component; The adaptive amplitude and phase adjustment unit is set in the form of a virtual impedance, adaptively reshapes the impedance according to the pre-processed energy storage voltage and the pre-processed energy storage current, and adaptively adjusts the amplitude and phase of the filtered energy storage voltage harmonic component to obtain the energy storage voltage harmonic component after amplitude and phase adjustment; The harmonic component of the energy storage voltage after the amplitude and phase adjustment is input as a voltage feedback signal to the PWM control link of the inverter to achieve broadband oscillation suppression at the public grid connection point.

2. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 1 is characterized in that: The autoregressive empirical wavelet transform method includes an autoregressive algorithm: An autoregressive algorithm is used to obtain an adaptive model for the pre-processed common grid connection point voltage and the pre-processed common grid connection point current using a Burg algorithm, and a corresponding power spectrum is obtained according to the adaptive model; The power spectrum is then divided into frequency bands: the local maximum of each frequency band of the power spectrum is identified, and the midpoint between adjacent local maxima is taken as the power spectrum boundary of adjacent frequency bands.

3. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 2 is characterized in that: The transfer function of the adaptive model for: （1）， In the formula is a complex variable, For the i The order model coefficients, is the model order; Power spectrum obtained according to the adaptive model for: （2）， In the formula is the center frequency, is the variance.

4. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 3 is characterized in that: The autoregressive empirical wavelet transform method also includes an empirical wavelet transform method: The empirical wavelet transform method establishes a wavelet packet bandpass filter based on the power spectrum boundary and obtains the wavelet packet empirical mode; based on the wavelet packet empirical mode, the corresponding time domain signal is obtained from the power spectrum data of the corresponding frequency band; and then the Hilbert transform is used to obtain the oscillation signal from the time domain signals of different frequency bands.

5. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 4 is characterized in that: The oscillation mode extraction unit selects the oscillation signal using a Hanning window, and then performs an interpolation discrete Fourier transform on the currently selected oscillation signal; based on the spectral function of the Hanning window, the modal information of the oscillation signal, including the oscillation frequency and oscillation amplitude, is obtained.

6. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 5, characterized in that: The adaptive bandpass filter adjusts the center frequency according to the oscillation frequency and adjusts the quality factor according to the oscillation amplitude.

7. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 6, characterized in that: According to the frequency band of the current pre-processed energy storage voltage, an adaptive band-pass filter of a corresponding frequency band is selected to filter the received energy storage voltage harmonic components to obtain filtered energy storage voltage harmonic components.

8. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 7, characterized in that: The adaptive amplitude and phase adjustment unit adaptively adjusts the size of the virtual resistance and virtual inductance according to the impedance empirical formula and the amplitude and phase of the corresponding adaptive bandpass filter, providing positive damping for the system impedance within the corresponding oscillation frequency range and reshaping the system impedance.

9. The photovoltaic grid-connected broadband oscillation suppression system based on grid-connected energy storage according to claim 1, characterized in that: Preprocessing the collected data includes filtering, noise reduction and interference reduction.

Images