Three-phase inverter direct current side electric leakage fault type discrimination method and electronic equipment

Abstract

The invention provides a three-phase inverter direct current side electric leakage fault type discrimination method and electronic equipment, and the method comprises the steps: carrying out the frequency spectrum time sequence characteristic analysis of the residual current of the alternating current side of a three-phase inverter, and analyzing the change of the amplitude of the residual current along with the time under different frequencies; the fault type of the direct current side electric leakage of the inverter can be known; by performing continuous energy monitoring on the residual current signal of the inverter, real-time current monitoring on the inverter is realized, and sudden change of the fault type of electric leakage or instantaneous electric leakage can be well monitored and distinguished. Aiming at the specific characteristics of the harmonic component of the leakage current of the inverter, different frequency spectrum characteristics of the leakage current under different fault types are determined, the electric leakage fault type discrimination method based on harmonic time-frequency characteristic extraction is provided on the basis, the specific fault type of the inverter can be discriminated under various working conditions, the position of the electric leakage fault is further positioned, and the reliability of the inverter is improved. The problem of inaccurate electric leakage fault type judgment and positioning in the current engineering application is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of leakage detection, and in particular relates to a method for distinguishing the type of leakage fault on the DC side of a three-phase inverter and electronic equipment. Background Art

[0002] The three-phase grid-connected inverter is a key device that converts the DC power generated by the power generation system into AC power. In the power generation system, DC side leakage is a common fault condition. Leakage not only causes direct energy loss and reduces the working efficiency of the inverter, but also may cause overheating, short circuit and even fire inside the equipment, posing a serious threat to personnel and property. In addition, the diversity of DC side leakage fault types, including high-resistance leakage, resistance-capacitance series leakage, resistance-capacitance parallel leakage and resonant leakage, each type has its own unique electrical characteristics, which makes the diagnosis and location of faults extremely complicated. This complexity requires the use of more sophisticated and intelligent detection technology to ensure the safe operation of the system.

[0003] Traditional methods for identifying leakage often rely on regular manual inspections or simple threshold alarm mechanisms, which are difficult to be effective when faced with the complexity and concealment of leakage. First, manual inspections are time-consuming and labor-intensive, and real-time monitoring is not possible. For intermittent or instantaneous leakage, the moment of the fault may be missed. Secondly, although the alarm system based on fixed thresholds can detect obvious leakage events, it lacks sensitivity for low-level leakage or changing leakage patterns, and is prone to false alarms or missed alarms. In addition, traditional methods also have shortcomings in fault location. Once an alarm is triggered, maintenance personnel often need to spend a lot of time to investigate the specific location of the leakage fault, which not only increases maintenance costs, but may also lead to an expansion of the scope of the fault.

[0004] Patent CN107179492B discloses a leakage detection method for distribution lines. This method simultaneously obtains the residual current signal and voltage signal of the distribution line, and performs resistive component separation calculation on the residual current according to the relationship between the amplitude and phase of the residual current and voltage at each frequency, obtains the resistive leakage current in the residual current, and compares the resistive leakage current with a predefined threshold to determine the leakage condition of the distribution line. Although it can detect leakage events, it lacks sensitivity for low-level leakage or changing leakage modes, is prone to false alarms or missed alarms, and cannot identify the type and location of the fault. Summary of the invention

[0005] The purpose of the present invention is to address the deficiencies in the prior art and provide a method for distinguishing the type of leakage fault on the DC side of a three-phase inverter and an electronic device, which can identify the type of leakage fault and improve the accuracy of leakage fault locating.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for distinguishing the type of leakage fault on the DC side of a three-phase inverter includes the following implementation process:

[0008] S1: Collect the grid-connected current signal on the AC side of the grid-connected inverter, and add the grid-connected current signals of the three phases to obtain the residual current signal;

[0009] S2: performing wavelet packet decomposition and reconstruction on the residual current signal to obtain a time variation curve and energy spectrum of the residual current amplitude at different frequencies;

[0010] S3: Determine the type of leakage fault according to the amplitude variation curve of the residual current at different frequencies over time; identify the energy change of the residual current according to the energy spectrum of the residual current at different frequencies, and when the energy change is greater than or equal to the first threshold, determine that the type of leakage fault has changed or instantaneous leakage has occurred.

[0011] The present invention analyzes the spectrum time series characteristics of the residual current on the AC side of the three-phase inverter, and then analyzes the change of the residual current amplitude with time at different frequencies, so as to understand the fault type of leakage on the DC side of the inverter; by continuously monitoring the energy of the residual current signal of the inverter, real-time current monitoring of the inverter is achieved, and the sudden change or instantaneous leakage of the leakage fault type can also be well monitored and distinguished; the present invention can identify the leakage fault type and improve the accuracy of leakage fault location.

[0012] The present invention aims at the specific characteristics of the harmonic components of the inverter leakage current and clarifies that the frequency spectrum characteristics of the leakage current under different fault types are different. On this basis, a leakage fault type discrimination method based on harmonic time-frequency feature extraction is proposed. The specific fault type of the inverter can be discriminated under various working conditions, and then the leakage fault position can be located, which solves the problem of inaccurate leakage fault type discrimination and positioning in current engineering applications.

[0013] Furthermore, according to the curve of the amplitude variation with time of the residual current at different frequencies, the implementation process of judging the type of leakage fault includes:

[0014] There are DC components and harmonic components of odd-numbered switching frequencies in the residual current after wavelet packet decomposition and reconstruction. When the amplitude of the DC component and the amplitude of the harmonic component of odd-numbered switching frequencies are respectively greater than or equal to the second threshold and less than or equal to the third threshold, it is determined that the fault type of the leakage is parasitic resistance fault leakage;

[0015] When the amplitude of the DC component and the amplitude of the harmonic component of the odd multiple switching frequency are respectively greater than or equal to the fourth threshold and less than or equal to the fifth threshold, it is determined that the fault type of the leakage is a parallel fault leakage of parasitic resistance and parasitic capacitance;

[0016] After wavelet packet decomposition and reconstruction, the residual current contains only harmonic components of odd multiples of the switching frequency. When the amplitude is greater than or equal to the second threshold and less than or equal to the third threshold, the fault type of the leakage is determined to be a series fault of parasitic resistance and parasitic capacitance.

[0017] When the amplitude is greater than or equal to the fourth threshold value and less than or equal to the fifth threshold value, it is determined that the fault type of the leakage is a parasitic capacitance fault leakage.

[0018] Furthermore, the fourth threshold is less than or equal to 5 times the second threshold, and the fifth threshold is less than or equal to 5 times the third threshold.

[0019] Based on the same inventive concept, the present invention also provides an electronic device, including:

[0020] one or more processors;

[0021] A memory having one or more programs stored thereon, which, when executed by the one or more processors, enables the one or more processors to implement the steps of a method for distinguishing the type of leakage fault on the DC side of a three-phase inverter.

[0022] Based on the same inventive concept, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a method for distinguishing the type of leakage fault on the DC side of a three-phase inverter.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention analyzes the spectrum time series characteristics of the residual current on the AC side of the three-phase inverter, and then analyzes the change of the residual current amplitude with time at different frequencies, so as to understand the fault type of leakage on the DC side of the inverter; by continuously monitoring the energy of the residual current signal of the inverter, real-time current monitoring of the inverter is achieved, and the sudden change or instantaneous leakage of the leakage fault type can also be well monitored and distinguished; the present invention can identify the leakage fault type and the leakage fault location, and improve the accuracy of leakage fault location.

[0025] The present invention aims at the specific characteristics of the harmonic components of the inverter leakage current and clarifies that the frequency spectrum characteristics of the leakage current under different fault types are different. On this basis, a leakage fault type discrimination method based on harmonic time-frequency feature extraction is proposed. The specific fault type of the inverter can be discriminated under various working conditions, and then the leakage fault position can be located, which solves the problem of inaccurate leakage fault type discrimination and positioning in current engineering applications.

[0026] The present invention can not only monitor the residual current changes of the inverter in real time and discover potential leakage problems in time, but also use the timing characteristics of the residual current to determine the fault type and location of the current time period, and take corresponding repair measures for different fault types in time. Even intermittent or instantaneous leakage can be captured. Accurate fault identification helps to reduce unnecessary maintenance work, ensure that maintenance actions are highly targeted, and improve the overall reliability and availability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of a module for distinguishing the type of leakage fault on the DC side of a three-phase inverter according to the present invention;

[0028] Figure 2 It is a flow chart of a module for distinguishing the type of leakage fault on the DC side of a three-phase inverter according to the present invention;

[0029] Figure 3 It is a flow chart of residual current amplitude and energy spectrum feature extraction of the present invention;

[0030] Figure 4 It is a structural schematic diagram of a non-isolated photovoltaic three-phase grid-connected inverter under different fault types;

[0031] Figure 5 Reconstruct node coefficient graphs for residual current at different frequencies;

[0032] Figure 6 It is the residual current energy spectrum of different nodes;

[0033] Figure 7 This is a flowchart of the leakage fault type identification unit of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be described in detail below in conjunction with the embodiments. It should be noted that the embodiments and features of the embodiments of the present invention can be combined with each other without conflict. For the convenience of description, if the words "upper", "lower", "left" and "right" appear in the following, they only indicate that the upper, lower, left and right directions are consistent with the drawings themselves, and do not limit the structure.

[0035] Example

[0036] like Figure 1 , Figure 2The present embodiment provides a three-phase inverter DC side leakage fault type identification system, including a data acquisition unit, a timing analysis unit, a fault identification unit and an instantaneous leakage identification unit. Since the leakage current is generated in the loop formed by the power grid and the parasitic impedance and the earth, the data acquisition unit first uses the current sensor on the AC side to collect the amplitude, frequency and other information of the AC side grid-connected current. Since the residual current is the sum of the currents of the three phases A, B and C, the amplitude, frequency and other information of the residual current can be obtained by adding the grid-connected currents of the three phases. The residual current data is transmitted to the timing analysis unit, and then the collected residual current signal is decomposed by wavelet packets using the wavelet packet transform (Wavelet Analyzer) technology of the timing analysis unit to obtain a wavelet packet tree of the residual current data, and each node is reconstructed to obtain the amplitude-time curve variation diagram of the residual current at different frequencies and the time energy spectrum of each node at each frequency. The amplitude-time curve variation diagram of the residual current at different frequencies is then handed over to the fault discrimination unit for fault discrimination and classification. Finally, the instantaneous leakage identification unit monitors the residual current energy of each frequency per unit time in real time. When a sudden change or abnormality in the energy is found, it is judged that a sudden change in the leakage fault has occurred, resulting in intermittent or instantaneous leakage.

[0037] Figure 3 It is the residual current timing fault feature extraction flow chart. The mechanism of fault feature extraction is explained as follows:

[0038] Due to the modulation effect of the three-phase inverter, the voltage component of the switching subharmonic will be generated, and then the high-frequency zero-sequence leakage current of integer odd multiples of the switching frequency will be generated. Generally, the high-frequency zero-sequence leakage current component of one switching frequency is the most obvious. Now, the timing characteristics of the residual current generated on the AC side of the three-phase inverter are extracted and analyzed. First, the wavelet packet decomposition is used to process the residual current signal data. Wavelet packet decomposition is widely used in the field of signal processing. It can decompose both the low-frequency part of the signal and the high-frequency part. Moreover, this decomposition has neither redundancy nor omission, so it can perform better time-frequency localization analysis on signals containing a large amount of medium and high-frequency information. The principles of wavelet packet decomposition and reconstruction are as follows:

[0039] Let x(t) be a time signal, Represents the i-th wavelet packet on the j-th layer,

[0040]

[0041] Wavelet packet decomposition is expressed as:

[0042]

[0043] Wavelet packet reconstruction is expressed as:

[0044]

[0045] Among them, h(·) is a low-pass filter, g(·) is a high-pass filter, l and k are the number of decomposition levels, h and g are filter coefficients, h is related to the scale function, and g is related to the wavelet function.

[0046] The original signal containing harmonics is decomposed into signals of different frequency bands. The result in the low frequency band is regarded as the fundamental component, and the high frequency band is each harmonic. The residual current signal is decomposed into each node by wavelet packet decomposition, and each bottom node corresponds to a different frequency band. Observe each node coefficient graph, that is, the decomposition result of the original signal in each frequency band. When the residual current data is decomposed by wavelet packet, each node coefficient graph is the amplitude time curve graph of the current decomposition in each frequency band. However, as the number of decomposition layers increases, the higher-level wavelet packet decomposition allows the signal to be analyzed within a higher frequency range. Therefore, the frequency range corresponding to each node coefficient will become narrower, that is, the higher frequency components are decomposed and described more carefully, and the time resolution will decrease accordingly as the frequency resolution increases. Therefore, as the number of layers increases, the time range representation of the node coefficient is no longer like the original signal can represent all time domains. Therefore, it is necessary to reconstruct each node of the bottom decomposition to obtain the reconstructed node coefficient graph, that is, to obtain the coefficient distribution graph used to reconstruct the original signal according to the node coefficient. At this time, the amplitude time curve graph of the residual current at different frequencies can be obtained through the reconstructed coefficient distribution graph.

[0047] Wavelet packet decomposition can extract energy features from signals. The residual current signal is decomposed into 4 layers of wavelet packets, and each wavelet packet coefficient at the bottom layer is reconstructed to obtain the reconstructed signal X a,b , a∈(1,4), b∈(1,2 a )), where the subscript a represents the decomposition layer number of the wavelet packet coefficients used for reconstruction, and b represents the sorting position of the wavelet packet coefficients used for reconstruction in the a-layer coefficients.

[0048] Get the reconstructed signal X a,b Then, calculate the energy E a,b :

[0049]

[0050] Among them, n represents the sequence length, and the energy is arranged in the original order to obtain the energy sequence Y of the corresponding layer reconstruction signal a . For example, the energy sequence of the third layer is:

[0051] Y3=(E 3,1 ,E 3,2 ,E 3,3 ,E 3,4 ,E 3,5 ,E 3,6 ,E 3,7,E 3,8 )

[0052] Figure 4 This is the structure diagram of a non-isolated photovoltaic three-phase grid-connected inverter under different fault types. Figure 4 The inverter model shown is used to collect different components of leakage current, and the simulation parameters used are shown in Table 1.

[0053] Table 1 Simulation model parameters for collecting leakage current of each component under different fault types

[0054] parameter Numeric <![CDATA[Photovoltaic equivalent DC voltage U dc / V]]> 1000 Parasitic resistance to ground R / Ω 500 <![CDATA[Parasitic capacitance C to the ground PV / μF]]> 1 Filter inductance L / / mH 5 <![CDATA[Filter capacitor C f / μF]]> 10 <![CDATA[Grid-side filtering inductor L g / μH]]> 100 <![CDATA[Switching frequency f s / Hz]]> 10000 Fundamental frequency f / Hz 50 <![CDATA[Dead zone delay time t d / μs]]> 5

[0055] The leakage current size under different fault types is obtained through simulation wavelet packet decomposition analysis as shown in Table 2.

[0056] Table 2 Leakage current components under different fault types

[0057]

[0058] According to Table 2, it can be concluded that the DC component in the leakage current and the zero-sequence high-frequency component under the switching sub-frequency harmonics are large, which is the main reason, while the low-frequency dead zone component is small and can be ignored. Therefore, wavelet packet decomposition is used to extract the time series change characteristics of the DC component of the current signal and the high-frequency component of the integer multiple of the switching sub-frequency. The original signal containing each harmonic is decomposed into signals in different frequency bands, and the results in the low-frequency band are regarded as the fundamental component, and the high-frequency band is each harmonic. The current signal is decomposed into each node using wavelet packet decomposition. Each bottom-level node corresponds to a different frequency band. Observe the coefficient diagram of each node, that is, the decomposition result of the original signal in each frequency band.

[0059] Figure 5 It is the coefficient diagram of the node reconstruction of the residual current at different frequencies. The original signal is decomposed by 3 layers of wavelet packets, the sampling frequency is 100000Hz, and the simulation time is 0.8s. The simulation time is divided into four time periods corresponding to different leakage fault types: 0~0.2s is a parasitic resistance fault; 0.2~0.4s is a parasitic resistance and parasitic capacitance series fault; 0.4~0.6s is a parasitic resistance and parasitic capacitance parallel fault; 0.6~0.8s is a parasitic capacitance fault, as shown in Table 3.

[0060] Table 3 Fault type timetable

[0061] Fault type Time / s Parasitic resistance fault 0～0.2 Parasitic capacitance failure 0.2～0.4 Parasitic resistance and parasitic capacitance series fault 0.4～0.6 Parasitic resistance and capacitance in parallel 0.6～0.8

[0062] The residual current data is decomposed through three layers, and the frequency band is divided into eight regions. The width of each sub-frequency band is 50000 / 8=6260 Hz. Considering the disorder of the frequency band order of wavelet packet decomposition, the wavelet packet decomposition nodes are (3, 0) to (3, 7), as shown in Table 4.

[0063] Table 4 Frequency band division of wavelet packet decomposition

[0064] Decomposition Node Frequency band / Hz Harmonic Components (3，0) 0～6250 DC component (3，1) 6250～12500 fs frequency harmonic component (3，2) 12500～18750 / (3，3) 18750～25000 2fs frequency sideband harmonic components (3，4) 25000～31250 3fs frequency harmonic component (3，5) 31250～37500 / (3，6) 37500～43750 4fs frequency sideband harmonic components (3，7) 43750～50000 /

[0065] The frequency band of node 7 (3, 0) is 0-6250Hz, including DC components, and the frequency band of node 8 (3, 1) is 6250-12500Hz, including switching frequency harmonic components. The harmonic components of node (3, 0) are mainly dominated by DC components. It can be found that since there is no parasitic capacitance directly connected in series in the common mode loop, a more obvious DC component will be generated when leakage occurs due to parasitic resistance faults and faults in parallel between parasitic resistance and parasitic capacitance. Node (3, 1) is mainly the harmonic component of the switching frequency. It can be found that the high-frequency leakage current generated by parasitic capacitance faults and faults in parallel between parasitic resistance and parasitic capacitance is large in value, which is the main reason for the generation of leakage current components.

[0066] Figure 6 The residual current energy spectrum of different nodes is obtained by wavelet packet decomposition to obtain the image of the residual current signal energy sequence. It can be clearly seen that the distribution of the reconstructed signal energy at different nodes, that is, at different frequency bands, is significantly different. The frequency band range of (3,0) node 7 is 0-6250Hz, including the DC component, and the frequency band range of (3,1) node 8 is 6250-12500Hz, including the switching frequency harmonic component. In the fixed frequency band interval, the energy of the current at each frequency is also distinguished. Due to the switching effect of the inverter, the energy is mainly distributed on the DC side and in the high-frequency harmonics of the integer odd multiple switching frequency, that is, nodes 7 and 8. And due to different fault types, the energy spectrum color and energy size are also different. When the energy spectrum color changes deeply or the energy size changes too much, it can be judged that the fault type has changed.

[0067] Figure 7 This is a flow chart of the leakage fault type discrimination unit. The mechanism of the leakage fault type discrimination mechanism is explained as follows:

[0068] Due to the modulation effect of the three-phase inverter, the voltage component of the switching subharmonic will be generated. The Fourier series expression of the A-phase voltage waveform of the three-phase inverter is as follows:

[0069]

[0070] In the formula, ω=2πf, f is the fundamental frequency, E d is the DC power supply voltage, M is the modulation index, N is the carrier ratio, m is the harmonic number relative to the carrier, n is the harmonic number relative to the modulating wave, is the initial phase of the modulation wave, J0, J n is a Bessel function of the first kind.

[0071] The phase voltage waveforms of the three-phase inverter are 120° out of phase with each other. The Fourier series expression of the B-phase voltage waveform of the three-phase inverter is as follows:

[0072]

[0073] The Fourier series expression of the C-phase voltage waveform of the three-phase inverter is as follows:

[0074]

[0075] The first term in the above three expressions is the voltage fundamental wave, the second term is the mth harmonic of the carrier, and the third term is the upper and lower sideband harmonics of the mth harmonic of the carrier.

[0076] Note the mth harmonic of the carrier in the second item. Since the voltage components of the integer harmonics of the carrier generated by the three phases A, B, and C in this item are in the same phase, a certain amount of zero-sequence voltage will be generated, and zero-sequence current will also be generated. The harmonic order of this current should be an integer multiple of the carrier, that is, an integer odd multiple of the switching harmonic. The switching frequency is generally a high frequency of kilohertz, so leakage current may be generated, which is manifested in the form of high-frequency zero-sequence leakage current of integer odd multiples of the switching frequency.

[0077] There is parasitic impedance between the metal frame of the inverter and the ground, and its size is affected by the size of the equipment, installation conditions and environment. Generally, the possible parasitic impedance may be in the form of parasitic resistance and parasitic capacitance, and the leakage current caused by the fault conditions is also different. After wavelet packet reconstruction and analysis of the waveform results, it can be concluded that if the fault type is parasitic resistance leakage, then the DC leakage component and the leakage component at odd integer multiples of the inverter switching frequency will be detected, but the amplitude is small, the amplitude is greater than or equal to the second threshold, and less than or equal to the third threshold; if the fault type is parasitic resistance and parasitic capacitance leakage in parallel, then the DC leakage component and the leakage component at odd integer multiples of the inverter switching frequency will be detected and the amplitude is large, the amplitude is greater than or equal to the fourth threshold, and less than or equal to the fifth threshold. If the fault type is leakage of parasitic resistance and parasitic capacitance in series, only leakage components at odd integer multiples of the inverter switching frequency will be detected, but the amplitude is small, the amplitude is greater than or equal to the second threshold, and less than or equal to the third threshold; if the fault type is leakage of parasitic capacitance, only leakage components at odd integer multiples of the inverter switching frequency will be detected and the amplitude is large, the amplitude is greater than or equal to the fourth threshold, and less than or equal to the fifth threshold. The fourth threshold is less than or equal to 5 times the second threshold, and the fifth threshold is less than or equal to 5 times the third threshold. Based on this, it can be concluded that under different fault conditions, according to the frequency at which the leakage current is generated and the amplitude generated, it can be inferred what type of fault causes the leakage, and a leakage fault type discrimination unit is established to make a judgment on the fault type of the inverter.

[0078] Preferably, the second threshold is 0A, the third threshold is 3A, the fourth threshold is 4A, and the fifth threshold is 10A.

[0079] The method for distinguishing the type of leakage fault on the DC side of the inverter has always been one of the keys to the safe and reliable operation of the inverter system. Traditional fault identification methods are often limited by the high cost of manual detection, long identification time, and difficulty in online monitoring. However, by performing spectrum time series analysis on the leakage current on the AC side of the inverter, the specific situation of the leakage fault type on the DC side can be clearly understood in a more economical and efficient way, and real-time monitoring can be achieved at the same time. The time series characteristics of the current, such as waveform, amplitude, and energy, can be used to quickly respond to changes in the fault type, so as to timely and efficiently detect intermittent or instantaneous leakage caused by changes in the fault type. According to the specific characteristics of the harmonic components of the inverter leakage current, it is clear that the spectrum characteristics of the leakage current under different fault types are different. On this basis, a method for distinguishing the type of leakage fault based on the extraction of harmonic time-frequency features is proposed, which can distinguish the specific fault type and location of the inverter under various working conditions, solving the problem of inaccurate judgment and positioning of leakage fault types in current engineering applications.

[0080] This method effectively overcomes the limitations of traditional technologies in inverter leakage current fault identification, such as long identification time, inaccurate fault type and location, etc. This method is easy to operate and can improve detection accuracy. It can not only monitor the residual current changes of the inverter in real time and find potential leakage problems in time, but also use the timing characteristics of the residual current to determine the fault type and location in the current time period, and take corresponding repair measures for different fault types in time. Even intermittent or instantaneous leakage can be captured. Accurate fault identification helps reduce unnecessary maintenance work, ensures that maintenance actions are highly targeted, and improves the overall reliability and availability of the system.

[0081] Another embodiment of the present invention provides an electronic device, including:

[0082] one or more processors;

[0083] A memory stores one or more programs, and when the one or more programs are executed by one or more processors, the one or more processors implement the steps of a method for distinguishing the type of leakage fault on the DC side of a three-phase inverter.

[0084] In some implementations, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0085] In some other implementations, the processor may be a central processing unit (CPU), a digital signal processor (DSP), or other general-purpose processors of various types, which are not limited herein.

[0086] Another embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the steps of a method for distinguishing a type of leakage fault on a DC side of a three-phase inverter when the computer program is executed by a processor.

[0087] The contents explained in the above embodiments should be understood as these embodiments are only used to more clearly illustrate the present invention, and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

Claims

1. A method for distinguishing the type of leakage fault on the DC side of a three-phase inverter, characterized in that: The implementation process includes the following: S1: Collect the grid-connected current signal on the AC side of the grid-connected inverter, and add the grid-connected current signals of the three phases to obtain the residual current signal; S2: performing wavelet packet decomposition and reconstruction on the residual current signal to obtain a time variation curve and energy spectrum of the residual current amplitude at different frequencies; S3: Determine the type of leakage fault according to the amplitude variation curve of the residual current at different frequencies over time; identify the energy change of the residual current according to the energy spectrum of the residual current at different frequencies, and when the energy change is greater than or equal to the first threshold, determine that the type of leakage fault has changed or instantaneous leakage has occurred.

2. The method for distinguishing the type of leakage fault on the DC side of a three-phase inverter according to claim 1, characterized in that: The implementation process of judging the type of leakage fault according to the curve of the amplitude variation with time at different frequencies of the residual current includes: There are DC components and harmonic components of odd-numbered switching frequencies in the residual current after wavelet packet decomposition and reconstruction. When the amplitude of the DC component and the amplitude of the harmonic component of odd-numbered switching frequencies are respectively greater than or equal to the second threshold and less than or equal to the third threshold, it is determined that the fault type of the leakage is parasitic resistance fault leakage; When the amplitude of the DC component and the amplitude of the harmonic component of the odd multiple switching frequency are respectively greater than or equal to the fourth threshold and less than or equal to the fifth threshold, it is determined that the fault type of the leakage is a parallel fault leakage of parasitic resistance and parasitic capacitance; After wavelet packet decomposition and reconstruction, the residual current contains only harmonic components of odd multiples of the switching frequency. When the amplitude is greater than or equal to the second threshold and less than or equal to the third threshold, the fault type of the leakage is determined to be a series fault of parasitic resistance and parasitic capacitance. When the amplitude is greater than or equal to the fourth threshold value and less than or equal to the fifth threshold value, it is determined that the fault type of the leakage is a parasitic capacitance fault leakage.

3. The method for distinguishing the type of leakage fault on the DC side of a three-phase inverter according to claim 2, characterized in that: The fourth threshold is less than or equal to 5 times the second threshold, and the fifth threshold is less than or equal to 5 times the third threshold.

4. An electronic device, characterized in that: include: one or more processors; A memory having one or more programs stored thereon, which, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the steps of the method according to any one of claims 1 to 3.

5. A computer-readable storage medium, characterized in that: The computer program is stored therein, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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