CN116885718A - Remote control method and system for impurity current of power grid - Google Patents
Remote control method and system for impurity current of power grid Download PDFInfo
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Abstract
The disclosure provides a method and a system for remotely controlling impurity current of a power grid, comprising the following steps: analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm, and converting the time domain waveform into a frequency domain representation; determining the signal energy of each frame fundamental frequency in the frequency domain representation according to the frequency domain amplitude value of the frequency domain representation and a preset sampling window through a frequency spectrum analysis algorithm; determining a fundamental frequency entropy value and harmonic information of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency; and according to the current and voltage waveform data, combining the fundamental frequency entropy value of the fundamental frequency of each frame and harmonic information, and positioning the source of the clutter current.
Description
Technical Field
The disclosure relates to power grid technology, in particular to a method and a system for remotely controlling impurity current of a power grid.
Background
Grid impurity currents generally refer to nonlinear currents or harmonic currents present in an electrical power system that may be caused by various factors, including faults of electrical equipment, nonlinear loads of electronic equipment, and other sources of interference in the electrical power system. To ensure stable operation of the power system, control and management of grid impurity currents is important, which currents may cause overload, damage or other problems to the power equipment, while also adversely affecting the power quality, such as voltage distortion and harmonic increase.
CN108879782a, a grid-connected inverter optimization control method based on double filtering grid voltage feedforward, discloses collecting voltage and current at PCC points and capacitance current of an LCL filter; extracting the phase of the voltage at the PCC point and multiplying the phase with a given network access current value to obtain a given reference signal of the network access current; the voltage at the PCC point is output by a power grid voltage feedforward link corrected by a double filtering link; comparing the given reference signal with the current at the PCC point to obtain an error signal, and regulating the error signal through a current regulator to obtain a command signal; comparing the command signal with the acquired capacitance current signal and the feedforward signal to generate a modulation signal, and comparing the modulation signal with a triangular carrier wave to generate a PWM wave; and controlling the operation of the grid-connected inverter by using the PWM signal.
The patent does not mention how to specifically design and select parameters for the dual filtering stage. Lack of detailed filter design methods and optimization strategies may lead to unstable system response or undesirable filtering effects; the method lacks of adaptability analysis on actual power grid disturbance conditions and robustness consideration on voltage feedforward links.
CN115241881a, adapted to the LCL active power filter improved current control method in the power grid frequency fluctuation scene, discloses collecting pulse signals, and injecting harmonic compensation currents with equal size and opposite phases into the power grid through a three-phase inverter; the control system is used for detecting harmonic current generated by a load, obtaining harmonic current signals to be compensated for the APF according to the detected load current, obtaining fundamental wave command current according to the detected DC bus capacitor voltage, obtaining command current to be compensated for the harmonic command current plus the fundamental wave command current, performing current closed-loop control by combining the command current with the actual output current of the inverter, and finally modulating by a driving circuit to obtain a modulating wave by adopting fuzzy proportion control and rapid repetition control.
The patent does not describe in detail the harmonic compensation strategy of the power filter, and the specific method and strategy of how to achieve injection and compensation of the harmonic current is not given.
Disclosure of Invention
The embodiment of the disclosure provides a method and a system for remotely controlling impurity current of a power grid, which can at least solve part of problems in the prior art, namely lack of adaptability analysis on actual power grid disturbance conditions and robustness consideration on a voltage feedforward link.
In a first aspect of embodiments of the present disclosure,
the utility model provides a remote control method for the impurity current of a power grid, which comprises the following steps:
analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm, and converting the time domain waveform into a frequency domain representation;
determining the signal energy of each frame fundamental frequency in the frequency domain representation according to the frequency domain amplitude value of the frequency domain representation and a preset sampling window through a frequency spectrum analysis algorithm; determining a fundamental frequency entropy value and harmonic information of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency;
and according to the current and voltage waveform data, combining the fundamental frequency entropy value of the fundamental frequency of each frame and harmonic information, and positioning the source of the clutter current.
In an alternative embodiment of the present application,
the signal energy of each frame fundamental frequency in the frequency domain representation is determined according to the frequency spectrum amplitude value of the frequency domain representation and a preset sampling window through a frequency spectrum analysis algorithm; the determining the fundamental frequency entropy value and the harmonic information of each frame fundamental frequency in the frequency domain representation according to the preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency comprises:
the signal energy of each frame base frequency in the candidate base frequencies is determined as follows:
wherein ,Erepresenting the signal energy of each frame fundamental frequency in the candidate fundamental frequencies,Mrepresenting the number of samples to be taken,krepresenting the frequency domain points,rthe phase shift angle is indicated as such,Nthe number of frames representing the candidate fundamental frequency,representing the frequency response of the preset sampling window,w j represent the firstjThe sampling scale of the individual sampling points is such that,uthe size of the sampling window is indicated,erepresenting the sampling frequency of the sample,G(n)represent the firstnSpectrum signal atoms;
the energy per subband is determined as follows:
wherein ,Ezwhich is indicative of the energy of the sub-band,P(.)representing the function of the spectral probability density,erepresenting the sampling frequency of the sample,hrepresenting the sampled smoothed values of the samples,H(i)representing the first of the candidate fundamental frequenciesi frameIs provided with a time-domain waveform of (a),a i represent the firstiThe number of sub-band orders of the frame,Nrepresenting the number of frames of the candidate fundamental frequency.
In an alternative embodiment of the present application,
the positioning the source of the clutter current according to the current and voltage waveform data and combining the fundamental frequency entropy value and the harmonic information of each frame fundamental frequency comprises:
screening out frames with the front value of the entropy value in the fundamental frequency entropy value according to the fundamental frequency entropy value of each frame fundamental frequency;
and in the selected frame, synthesizing the fundamental frequency entropy value and harmonic information corresponding to the selected frame, and combining the power grid topology and the measuring point position to perform source positioning of clutter current.
In an alternative embodiment of the present application,
after locating the source of the clutter current, the method further comprises:
the phase angle margin of the output impedance of the grid-connected inverter is improved by adding a phase compensation link in the current controller;
based on a transfer function of the proportional feedforward, a first-order low-pass filter is added in a power grid voltage feedforward link, the output impedance amplitude of the grid-connected inverter is increased, and high-frequency harmonic components are filtered;
and a plurality of multi-resonance controllers are connected in parallel in the current controller, the amplitude-frequency gain of the output impedance of the inverter is increased through the multi-resonance controllers, and the interference of the harmonic voltage of the corresponding frequency on the power grid side to the grid-connected current is restrained.
In an alternative embodiment of the present application,
the phase angle margin for improving the output impedance of the grid-connected inverter by adding a phase compensation link in the current controller is shown in the following formula:
wherein ,
wherein ,representing a first intermediate value,/->A second intermediate value is indicated and is used to represent,brepresenting correction factors->Representing the compensation coefficient of the compensation coefficient,representing the maximum compensation phase angle +.>Representing the frequency of the maximum compensation angle.
In an alternative embodiment of the present application,
a plurality of multi-resonance controllers are connected in parallel in the current controller, and the amplitude-frequency gain of the output impedance of the inverter is increased through the multi-resonance controllers as shown in the following formula:
wherein ,nrepresenting the number of times a harmonic controller is added,representing the proportionality coefficient>Representing the resonance coefficient +.>Represents the cut-off angular frequency, +.>Representing the fundamental angular frequency.
In a second aspect of the embodiments of the present disclosure,
provided is a remote control system for impurity current of a power grid, comprising:
the first unit is used for analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm and converting the time domain waveform into a frequency domain representation;
a second unit, configured to determine, according to a spectrum amplitude value of the frequency domain representation and a preset sampling window, signal energy of each frame fundamental frequency in the frequency domain representation by using a spectrum analysis algorithm; determining a fundamental frequency entropy value and harmonic information of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency;
and the third unit is used for positioning the source of the clutter current according to the current and voltage waveform data and combining the fundamental frequency entropy value of each frame fundamental frequency and harmonic information.
In a third aspect of the embodiments of the present disclosure,
there is provided an electronic device including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the instructions stored in the memory to perform the method described previously.
In a fourth aspect of embodiments of the present disclosure,
there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method as described above.
The beneficial effects of the embodiments of the present disclosure may refer to the beneficial effects corresponding to technical features in the specific embodiments, and are not described herein.
Drawings
FIG. 1 is a schematic flow chart of a method for remote harnessing of grid impurity currents in an embodiment of the disclosure;
fig. 2 is a schematic structural diagram of a remote control system for impurity current of a power grid according to an embodiment of the disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. Based on the embodiments in this disclosure, all other embodiments that a person of ordinary skill in the art would obtain without making any inventive effort are within the scope of protection of this disclosure.
The technical scheme of the present disclosure is described in detail below with specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
Fig. 1 is a schematic flow chart of a method for remotely controlling an impurity current of a power grid according to an embodiment of the disclosure, as shown in fig. 1, the method includes:
s101, analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm, and converting a time domain waveform into a frequency domain representation;
for example, current and voltage waveform data in the power grid may be collected using current and voltage sensors. Assuming that the current waveform data collected by us is I (t), and the voltage waveform data is V (t); harmonic analysis is carried out on the acquired current and voltage waveform data, a time domain waveform is converted into a frequency domain representation, and frequency spectrum analysis can be carried out by using algorithms such as Fourier transform or Fast Fourier Transform (FFT); the frequency and phase information of the harmonic components in the frequency domain representation is determined by a spectral analysis algorithm, which may be done by finding peaks in the frequency spectrum or using a harmonic extraction algorithm. And according to the current and voltage waveform data, combining the frequency and phase information of the harmonic component, and positioning the source of the clutter current.
S102, determining the signal energy of each frame fundamental frequency in the frequency domain representation according to the frequency domain amplitude value of the frequency domain representation and a preset sampling window through a frequency spectrum analysis algorithm; determining a fundamental frequency entropy value of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency;
illustratively, the spectral probability density function is constructed from a sampled smoothed value and a frequency magnitude fitting function. The spectrum analysis algorithm of the embodiment of the application can comprise a method for converting a time domain signal into a frequency domain signal, wherein a Fast Fourier Transform (FFT) is one of the most commonly used spectrum analysis algorithms, and can convert the time domain signal into a frequency domain representation to obtain a corresponding relationship between frequency and amplitude. The frequency domain representation refers to converting the signal from a time domain representation to a frequency domain representation. In a frequency domain representation, the information of the signal is presented in the form of frequency and amplitude, rather than a time domain waveform, the frequency domain representation provides more information about the frequency content of the signal.
The spectral amplitude values represent the amplitude magnitudes of the different frequency components in the frequency domain, reflecting the energy distribution of the signal at the different frequencies. The fundamental frequency is the main frequency component in the frequency spectrum, generally corresponding to the main frequency of the signal. The signal energy represents the total energy of the signal over a particular period of time, which in the frequency domain representation can be calculated by summing or integrating the spectral amplitude values. The spectral probability density function is a function modeling the probability distribution of signal spectral amplitude values, which can be used to describe the probability distribution of different frequency components in the signal spectrum.
The fundamental frequency entropy value is an uncertainty measure of the energy of the fundamental frequency signal, which is obtained by calculating the energy of the fundamental frequency signal and a preset frequency spectrum probability density function, and the higher the fundamental frequency entropy value is, the larger the uncertainty of the fundamental frequency signal is, which may correspond to clutter current in a current waveform.
Assuming that the frequency spectrum data of a current signal is set, obtaining a frequency spectrum amplitude value through a frequency spectrum analysis algorithm, setting the size of a sampling window to be 100 frequency points, calculating a fundamental frequency amplitude value in a frequency spectrum as signal energy for each sampling window frame, and calculating a fundamental frequency entropy value according to a preset frequency spectrum probability density function.
Assuming that the fundamental frequency amplitude in the spectrum of the first sampling window frame is 10, the fundamental frequency amplitude of the second sampling window frame is 15, and the fundamental frequency amplitude of the third sampling window frame is 5. According to the set frequency spectrum probability density function, we can calculate the fundamental frequency entropy value of each sampling window frame to be 2.3, 2.7 and 1.8 respectively.
The signal energy and the fundamental frequency entropy value of the fundamental frequency of each frame in the frequency domain representation can be obtained by calculating the fundamental frequency amplitude and the fundamental frequency entropy value of each sampling window frame, and then the source location of the clutter current can be carried out by combining the information of the power grid topology, the measuring point position and the like.
In an alternative embodiment of the present application,
the determining, by the spectrum analysis algorithm, the signal energy of each frame of fundamental frequency in the frequency domain representation according to the spectrum amplitude value of the frequency domain representation and a preset sampling window includes:
determining a phase offset angle of a frequency domain point in the frequency domain representation and the number of frames of candidate fundamental frequencies through a frequency spectrum analysis algorithm, and determining a frequency spectrum amplitude value of the frequency domain representation;
determining the frequency response corresponding to the preset sampling window according to the frequency response of the preset sampling window, the sampling scale of the sampling point and the size of the sampling window;
the signal energy for determining the fundamental frequency of each frame in the frequency domain representation is represented by the formula:
；
wherein ,Erepresenting the signal energy at the fundamental frequency of each frame in the frequency domain representation,Mrepresenting the number of samples to be taken,krepresenting the frequency domain points,rthe phase shift angle is indicated as such,Nthe number of frames representing the frequency domain representation,representing the frequency response of the preset sampling window,w j represent the firstjThe sampling scale of the individual sampling points is such that,uthe size of the sampling window is indicated,erepresenting the sampling frequency of the sample,G(n)represent the firstnAnd spectrum signal atoms.
Illustratively, the phase offset angle represents a phase difference of each frequency component in the frequency spectrum relative to a reference frequency. The frequency response refers to the response characteristics of the sampling window to signals of different frequencies. The sampling scale of the sampling points represents the number of sample points contained in the sampling window in the spectral analysis, the larger the sampling scale, the higher the frequency resolution of the spectral analysis.
In the spectrum analysis, the spectrum amplitude value can only reflect the amplitude information of the signal, but the phase information cannot be directly obtained. And through the acquired current and voltage waveform data, phase demodulation can be performed to obtain the phase offset angle of the frequency domain point. The number of frames of the candidate fundamental frequency refers to the number of frames containing all harmonics of the fundamental frequency in the sampling window. The signal energy of each frame fundamental frequency in the frequency domain representation is determined, so that the intensity change of fundamental frequency signals in different time periods is obtained, meanwhile, the phase information of harmonic waves can be further obtained through phase demodulation and the number of frames of candidate fundamental frequencies, and the phase relation of current and voltage waveforms is analyzed.
In an alternative embodiment of the present application,
the determining the fundamental frequency entropy value of each frame fundamental frequency in the frequency domain representation according to the preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency comprises:
based on the preset frequency spectrum probability density function, combining the frequency domain representation, dividing each frame fundamental frequency in the frequency domain representation into a plurality of sub-bands, and determining sub-band energy of each sub-band;
respectively determining the energy probability and the information entropy corresponding to the sub-band energy of each sub-band, and determining the fundamental frequency entropy value of the fundamental frequency of each frame in the frequency domain representation according to the method shown in the following formula by combining the sub-band energy of each sub-band:
；
wherein ,Qirepresents the fundamental frequency entropy value of the fundamental frequency of each frame in the frequency domain representation,V(i)represent the firstiThe probability of the energy of the frame,L(i)represent the firstiThe entropy of the information of the frame,Ez(i)represent the firstiFrame and thi+1The sub-band energy of the frame is,Nrepresenting the number of frames.
In an alternative embodiment of the present application,
the determination of the subband energy for each subband is shown in the following equation:
；
wherein ,Ezwhich is indicative of the energy of the sub-band,P(.)representing the function of the spectral probability density,erepresenting the sampling frequency of the sample,hrepresenting the sampled smoothed values of the samples,H(i)representing the first of the candidate fundamental frequenciesi frameIs provided with a time-domain waveform of (a),a i represent the firstiThe number of sub-band orders of the frame,Na number of frames representing candidate fundamental frequencies;
the sampling smoothing value refers to a parameter that samples and smoothes a continuous signal during sampling. The sample smoothing value is used to reduce noise and fluctuations in the sampled data to obtain a more stable and reliable signal representation. The frequency domain representation is a conversion of the signal from a time domain representation to a frequency domain representation, wherein the frequency range refers to a frequency range of interest in the frequency domain. In power systems, harmonic analysis is typically performed on current and voltage, and the frequency of the harmonics is an integer multiple of the fundamental frequency. Thus, the frequency range of the frequency domain representation typically selects a range of fundamental frequencies and their harmonic frequencies.
In the frequency domain representation, the fundamental frequency signal of each frame may be further divided into a plurality of sub-bands for better analysis of the harmonic characteristics of the signal. The subband order refers to the number of subbands into which the fundamental frequency spectrum is divided, and is typically a positive integer that determines the fine granularity of the fundamental frequency signal per frame in the frequency domain representation. The larger the subband order is, the more the fundamental frequency signal is further subdivided, and the more detailed analysis is performed on the harmonic components of the signal; and the smaller the sub-band order is, the coarser the fundamental frequency signal is divided, and the harmonic component of the signal is analyzed as a whole.
And determining the energy probability and the information entropy corresponding to the sub-band energy of each sub-band as shown in the following formula:
；
；
wherein ,V(i)represent the firstiThe probability of the energy of the frame,L(i)represent the firstiThe entropy of the information of the frame,Ez(i)represent the firstiSub-band energy of the frame.
Illustratively, the spectral probability density function is a function modeling a probability distribution of spectral amplitude values of the signal, describing probability distribution of different frequency components in the frequency domain representation, i.e. occurrence probabilities of the different frequency components. The fundamental frequency entropy value is an uncertainty measure of the energy of the fundamental frequency signal, and is obtained by calculating the energy of the fundamental frequency signal and a preset frequency spectrum probability density function. The higher the fundamental entropy value, the greater the uncertainty representing the fundamental signal, which may correspond to the clutter current in the current waveform.
Dividing each frame fundamental frequency in the frequency domain representation into a plurality of sub-bands, wherein the sub-bands can be divided according to a preset frequency range and a frequency spectrum probability density function, ensuring that the frequency range of each sub-band has enough frequency resolution, and calculating the energy of each sub-band. The subband energy reflects the magnitude of the different subbands in the spectrum. The energy probability refers to an occurrence probability corresponding to energy of each subband. The information entropy is an uncertainty measure of the sub-band energy and is used for representing the confusion degree of the sub-band energy, and the higher the information entropy is, the more scattered and uncertain the sub-band energy distribution is.
Wherein the energy probabilities reflect the importance and extent of contribution of the different sub-band energies in the frequency domain representation. The high energy probability subband represents that the subband energy occupies a larger proportion in the whole frequency domain representation, indicating that the harmonic components in the frequency range are stronger; information entropy is used to balance the uncertainty of sub-band energy. The higher the information entropy is, the more scattered the sub-band energy distribution is, the energy of the harmonic signal is not obviously concentrated in the frequency domain, and the complexity of the signal and the existence of clutter current are reflected. Through analysis of subband energy, energy probability and information entropy, deep knowledge of harmonic components of fundamental frequency signals can be obtained, including energy distribution conditions and uncertainty degree of harmonic signals, and further sources of clutter currents can be positioned and judged more accurately.
S103, locating the source of clutter current according to the current and voltage waveform data and combining the fundamental frequency entropy value of each frame fundamental frequency.
In an alternative embodiment, the locating the source of the clutter current according to the current and voltage waveform data in combination with the fundamental frequency entropy value of each frame fundamental frequency includes:
screening out frames with the front value of the entropy value in the fundamental frequency entropy value according to the fundamental frequency entropy value of each frame fundamental frequency; and in the selected frame, synthesizing the fundamental frequency entropy value and harmonic information corresponding to the selected frame, and combining the power grid topology and the measuring point position, and carrying out source positioning of clutter current through a phase comparison algorithm.
For example, the current waveform data may be frame-segmented, each frame containing one complete cycle; and extracting the fundamental frequency of each frame, and obtaining fundamental frequency information by using an autocorrelation method or a maximum peak search method. The method comprises the steps of carrying out a first treatment on the surface of the
According to the fundamental frequency entropy value, screening out frames with higher entropy values as frames possibly containing clutter current; extracting harmonic information in the selected frame through a harmonic analysis algorithm, wherein the harmonic information comprises harmonic frequency, phase and the like; and (3) synthesizing fundamental frequency entropy and harmonic information, and combining the power grid topology and the position of a measuring point to perform source positioning of clutter current.
The clutter current positioning may be one of the following methods:
phase comparison method: comparing the phase difference of the harmonic currents of different measuring points, and determining the propagation path and source of the clutter current according to the phase difference;
time difference method: determining the propagation path and source of clutter current by measuring time delays of different positions according to the propagation speed of harmonic current in a power grid;
multipoint measurement method: and selecting a plurality of measuring points in the power grid, and determining the propagation path and source of the clutter current through comprehensive analysis of the characteristics of the harmonic current such as frequency, phase and amplitude.
Assuming we have two measurement points a and B, the 3 rd harmonic current waveform data measured in the grid is as follows:
current waveform data of measurement point a: IA (t) =10sin (2pi×50t) +5sin (2pi×150t) +2sin (2pi×300t);
current waveform data of measurement point B: IB (t) =8sin (2pi×50t+pi/2) +4sin (2pi×150t+pi/3) +3sin (2pi×300t+pi/4);
the current waveform data is subjected to harmonic analysis and converted into frequency domain representation, and frequency and phase information of the 3 rd harmonic is extracted, so that the following result is obtained: frequency analysis results:
frequency of the 3 rd harmonic: f3 =150 Hz;
phase analysis results:
measuring the phase of the 3 rd harmonic of point a: Φa3=0;
measuring the phase of the 3 rd harmonic of point B: Φb3=pi/3;
from the phase difference ΔΦ=Φa3- Φb3=0-pi/3= -pi/3, we can determine the propagation path and source of the clutter current; from this phase difference result, it can be inferred that the clutter currents may come from the grid section between measurement points a and B and that there may be some phase difference in their propagation paths.
In an alternative embodiment of the present application,
after locating the source of the clutter current, the method further comprises:
the phase angle margin of the output impedance of the grid-connected inverter is improved by adding a phase compensation link in the current controller;
based on a transfer function of the proportional feedforward, a first-order low-pass filter is added in a power grid voltage feedforward link, the output impedance amplitude of the grid-connected inverter is increased, and high-frequency harmonic components are filtered;
and a plurality of multi-resonance controllers are connected in parallel in the current controller, the amplitude-frequency gain of the output impedance of the inverter is increased through the multi-resonance controllers, and the interference of the harmonic voltage of the corresponding frequency on the power grid side to the grid-connected current is restrained.
The current controller is an apparatus or module for controlling current, is widely used in power electronic equipment such as an inverter, and can adjust output current according to grid conditions and inverter output requirements to ensure stable operation of a power system. The phase compensation link is a control strategy for adjusting the phase relation between the output current and the voltage, and by adding the phase compensation link into the current controller, the phase angle margin of the output impedance of the grid-connected inverter can be improved, namely the phase difference between the output current and the voltage of the inverter is enhanced, and the stability of the system is improved.
Proportional feedforward is a control strategy for adjusting the response speed and stability of a system, and transfer functions are mathematical expressions describing the relationship between the system inputs and outputs. In the embodiment of the application, the transfer function of the proportional feedforward is used for adjusting the control parameter of the feedforward link of the power grid voltage so as to realize the adjustment of the amplitude of the output impedance and the high-frequency harmonic component.
A low pass filter is a filter that allows only signal components above a certain cut-off frequency to be filtered out by signal components below the cut-off frequency. The first-order low-pass filter is used for increasing the amplitude of the output impedance of the grid-connected inverter and filtering out high-frequency harmonic components, so that the quality of a current waveform is improved.
The multi-resonance controller is a controller which can simultaneously inhibit interference of a plurality of harmonic frequencies, and the current controller is connected with the multi-resonance controller in parallel, so that interference of harmonic voltage of corresponding frequency on the power grid side to grid-connected current can be inhibited by increasing amplitude-frequency gain of output impedance of the inverter.
In an alternative embodiment of the present application,
the phase angle margin for improving the output impedance of the grid-connected inverter by adding a phase compensation link in the current controller is shown in the following formula:
；
wherein ,
；
；
wherein ,representing a first intermediate value,/->A second intermediate value is indicated and is used to represent,brepresenting correction factors->Representing the compensation coefficient of the compensation coefficient,representing the maximum compensation phase angle +.>Representing the frequency of the maximum compensation angle.
In an alternative embodiment of the present application,
a plurality of multi-resonance controllers are connected in parallel in the current controller, and the amplitude-frequency gain of the output impedance of the inverter is increased through the multi-resonance controllers as shown in the following formula:
；
wherein ,nrepresenting the number of times a harmonic controller is added,representing the proportionality coefficient>Representing the resonance coefficient +.>Represents the cut-off angular frequency, +.>Representing the fundamental angular frequency.
When the power grid impedance is purely inductive, the phase angle difference between the phase angle margin of the output impedance of the inverter and the interaction point of the inductive power grid impedance can be made smaller than 180 degrees by improving the phase angle margin of the output impedance of the inverter, so that harmonic components in the current are prevented from being excited by resonance phenomenon. When the problem of multi-resonance generated by the interaction of the output impedance of the inverter and the transmission line of the RLC structure is restrained, the amplitude of the output impedance of the inverter is increased to avoid the generation of an interaction resonance point of the impedance of the inverter and the transmission line due to the complexity of the interaction condition. Since the power grid background harmonic component is an important reason for exciting the harmonic oscillation amplification of the interaction resonance point, the harmonic oscillation amplification is also suppressed to a certain extent.
Disturbance components in the grid voltage can be collected by adopting a grid voltage feedforward control strategy and fed back to the output end of the current controller, so that compensation of generated modulation waves is realized, and the influence of background harmonic voltage on a system can be eliminated from the source. Meanwhile, after feedforward control is added, the current regulator only needs to control the voltage at two ends of the filter, so that the strategy has the advantage of accelerating response speed.
When the feedforward coefficient of the power grid voltage is changed to enable the amplitude of the output impedance of the inverter to be infinite, the generation of interaction points between the output impedance of the inverter and the impedance of the transmission line can be avoided, and the background harmonic wave of the grid side can be restrained. A step of
In order to avoid the occurrence of multiple resonance points and improve the anti-interference capability of the inverter to background harmonic disturbance, a low-pass filter is added in a feedforward link, so that the output impedance of the inverter cannot be improved infinitely, a plurality of controllers with specific frequencies can be considered to be connected in parallel in a current controller, the controllers are called as multiple resonance controllers, the amplitude-frequency gain of the output impedance of the inverter at the specific harmonic frequency is improved by utilizing the multiple resonance controllers, and the attenuation of the harmonic wave is realized.
The grid-connected inverter is equivalent to a parallel connection of a current source and an output impedance, while the power grid is regarded as a series connection of a voltage source and a power grid impedance, and is regarded as a hybrid system consisting of the voltage source and the current source as a whole,
the inverter output current is shown by the following formula:
；
wherein ,representing inverter output current,/->Representing a current source +.>Representing the output impedance +.>Represents a voltage source, < >>Representing the grid impedance;
in order to avoid the occurrence of multiple resonance points and improve the anti-interference capability of the inverter to background harmonic disturbance, the core idea of the proposal is to improve the output impedance of the inverter. The low-pass filter is added in the feedforward link, so that the output impedance of the inverter cannot be infinitely increased, a plurality of multi-resonance controllers with specific frequencies can be connected in parallel in the current controller, the multi-resonance controllers are utilized to increase the amplitude-frequency gain of the output impedance of the inverter at the specific harmonic frequency, and the attenuation of the harmonic wave is realized.
Because the background harmonic component of the power grid is an important reason for exciting the harmonic oscillation amplification of the interaction resonance point, the background harmonic component of the power grid is also suppressed to a certain extent, the disturbance component in the power grid voltage can be collected by adopting a power grid voltage feedforward control strategy and fed back to the output end of the current controller, and compensation of generated modulation waves is realized, so that the influence of the background harmonic voltage on a system can be eliminated from the source. Meanwhile, after feedforward control is added, the current regulator only needs to control the voltage at two ends of the filter, so that the strategy has the advantage of accelerating response speed.
The phase compensation link is added to improve the phase margin of the output impedance of the inverter to avoid single resonance points, and the amplitude of the output impedance of the inverter is greatly improved to inhibit multi-resonance problems by improving the power grid voltage feedforward strategy, so that the system stability is improved.
In a second aspect of the embodiments of the present disclosure,
provided is a remote control system for impurity current of a power grid, fig. 2 is a schematic structural diagram of the remote control system for impurity current of a power grid according to an embodiment of the disclosure, including:
the first unit is used for analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm and converting the time domain waveform into a frequency domain representation;
a second unit, configured to determine, according to a spectrum amplitude value of the frequency domain representation and a preset sampling window, signal energy of each frame fundamental frequency in the frequency domain representation by using a spectrum analysis algorithm; determining a fundamental frequency entropy value of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency, wherein the frequency spectrum probability density function is constructed according to a sampling smooth value and a frequency amplitude fitting function;
and a third unit for locating the source of the clutter current according to the current and voltage waveform data and combining the fundamental frequency entropy value of each frame fundamental frequency.
In a third aspect of the embodiments of the present disclosure,
there is provided an electronic device including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the instructions stored in the memory to perform the method described previously.
In a fourth aspect of embodiments of the present disclosure,
there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method as described above.
The present application may be a method, apparatus, system, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for performing various aspects of the present application.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present disclosure, and not for limiting the same; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present disclosure.
Claims (10)
1. The utility model provides a remote control method of the impurity current of a power grid, which is characterized by comprising the following steps:
analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm, and converting the time domain waveform into a frequency domain representation;
determining the signal energy of each frame fundamental frequency in the frequency domain representation according to the frequency domain amplitude value of the frequency domain representation and a preset sampling window through a frequency spectrum analysis algorithm; determining a fundamental frequency entropy value of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency, wherein the frequency spectrum probability density function is constructed according to a sampling smooth value and a frequency amplitude fitting function;
and according to the current and voltage waveform data, combining the fundamental frequency entropy value of the fundamental frequency of each frame to position the source of clutter current.
2. The method of claim 1, wherein determining, by a spectral analysis algorithm, signal energy for each frame fundamental frequency in the frequency domain representation from the spectral amplitude values of the frequency domain representation and a preset sampling window comprises:
determining a phase offset angle of a frequency domain point in the frequency domain representation and the number of frames of candidate fundamental frequencies through a frequency spectrum analysis algorithm, and determining a frequency spectrum amplitude value of the frequency domain representation;
determining the frequency response corresponding to the preset sampling window according to the frequency response of the preset sampling window, the sampling scale of the sampling point and the size of the sampling window;
the signal energy for determining the fundamental frequency of each frame in the frequency domain representation is represented by the formula:
；
wherein ,Erepresenting the signal energy at the fundamental frequency of each frame in the frequency domain representation,Mrepresenting the number of samples to be taken,krepresenting the frequency domain points,rthe phase shift angle is indicated as such,Nthe number of frames representing the frequency domain representation,representing the frequency response of the preset sampling window,w j represent the firstjThe sampling scale of the individual sampling points is such that,uthe size of the sampling window is indicated,erepresenting the sampling frequency of the sample,G(n)represent the firstnAnd spectrum signal atoms.
3. The method of claim 1, wherein said determining the base frequency entropy value of each base frequency in the frequency domain representation from the predetermined spectral probability density function and the signal energy of each base frequency comprises:
based on the preset frequency spectrum probability density function, combining the frequency domain representation, dividing each frame fundamental frequency in the frequency domain representation into a plurality of sub-bands, and determining sub-band energy of each sub-band;
respectively determining the energy probability and the information entropy corresponding to the sub-band energy of each sub-band, and determining the fundamental frequency entropy value of the fundamental frequency of each frame in the frequency domain representation according to the method shown in the following formula by combining the sub-band energy of each sub-band:
；
wherein ,Qirepresents the fundamental frequency entropy value of the fundamental frequency of each frame in the frequency domain representation,V(i)represent the firstiThe probability of the energy of the frame,L (i)represent the firstiThe entropy of the information of the frame,Ez(i)represent the firstiFrame and thi+1The sub-band energy of the frame is,Nthe number of frames representing the frequency domain representation.
4. A method according to claim 3, wherein the determining the subband energy for each subband is represented by the formula:
；
wherein ,E z which is indicative of the energy of the sub-band,P(.)representing the function of the spectral probability density,erepresenting the sampling frequency of the sample,hrepresenting the sampled smoothed values of the samples,H(i)represent the firstiThe frequency range of the frame frequency domain representation,a i represent the firstiThe subband order of the frame;
and determining the energy probability and the information entropy corresponding to the sub-band energy of each sub-band as shown in the following formula:
；
；
wherein ,V(i)represent the firstiThe probability of the energy of the frame,L(i)represent the firstiThe entropy of the information of the frame,Ez(i)represent the firstiSub-band energy of the frame.
5. The method of claim 1, wherein locating the source of clutter current in conjunction with the fundamental frequency entropy value of each frame fundamental frequency based on the current and voltage waveform data comprises:
screening out frames with the front value of the entropy value in the fundamental frequency entropy value according to the fundamental frequency entropy value of each frame fundamental frequency; and in the selected frame, synthesizing the fundamental frequency entropy value and harmonic information corresponding to the selected frame, and combining the power grid topology and the measuring point position, and carrying out source positioning of clutter current through a phase comparison algorithm.
6. The method of claim 1, wherein after locating the source of the clutter current, the method further comprises:
the phase angle margin of the output impedance of the grid-connected inverter is improved by adding a phase compensation link in the current controller;
based on a transfer function of the proportional feedforward, a first-order low-pass filter is added in a power grid voltage feedforward link, the output impedance amplitude of the grid-connected inverter is increased, and high-frequency harmonic components are filtered;
and a plurality of multi-resonance controllers are connected in parallel in the current controller, the amplitude-frequency gain of the output impedance of the inverter is increased through the multi-resonance controllers, and the interference of the harmonic voltage of the corresponding frequency on the power grid side to the grid-connected current is restrained.
7. The method of claim 6, wherein the phase angle margin for increasing the output impedance of the grid-connected inverter by adding a phase compensation link to the current controller is represented by the formula:
；
wherein ,
；
；
wherein ,representing a first intermediate value,/->A second intermediate value is indicated and is used to represent,brepresenting correction factors->Representing compensation coefficient->Representing the maximum compensation phase angle +.>Representing the frequency of the maximum compensation angle.
8. The method of claim 7, wherein a plurality of multi-resonant controllers are connected in parallel in the current controller and the amplitude-frequency gain for increasing the output impedance of the inverter by the multi-resonant controllers is represented by the formula:
；
wherein ,nrepresenting the number of times a harmonic controller is added,representing the proportionality coefficient>Representing the resonance coefficient +.>Represents the cut-off angular frequency, +.>Representing the fundamental angular frequency.
9. A remote control system for impurity current of a power grid, comprising:
the first unit is used for analyzing the acquired current and voltage waveform data by using a harmonic analysis algorithm and converting the time domain waveform into a frequency domain representation;
a second unit, configured to determine, according to a spectrum amplitude value of the frequency domain representation and a preset sampling window, signal energy of each frame fundamental frequency in the frequency domain representation by using a spectrum analysis algorithm; determining a fundamental frequency entropy value and harmonic information of each frame fundamental frequency in the frequency domain representation according to a preset frequency spectrum probability density function and the signal energy of each frame fundamental frequency;
and the third unit is used for positioning the source of the clutter current according to the current and voltage waveform data and combining the fundamental frequency entropy value of each frame fundamental frequency and harmonic information.
10. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 8.
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