Power supply early warning method, device and equipment of inverter based on high-frequency resonance

Abstract

The invention provides a power supply early warning method, device and equipment for an inverter based on high-frequency resonance. The method comprises the following steps: injecting a plurality of micro-amplitude high-frequency excitation signals into the output end of the inverter; obtaining a high-frequency equivalent impedance drift coefficient of the output side of the inverter based on the obtained response data; determining whether the output side of the inverter is in a high-frequency impedance abrupt change state or not according to the high-frequency equivalent impedance drift coefficient; when the output side of the inverter is in a high-frequency impedance abrupt change state, obtaining a resonance characteristic fuzzy degradation coefficient of the output side of the inverter based on the response data; determining a frequency protection tripping trigger evaluation index of the inverter according to the high-frequency equivalent impedance drift coefficient and the resonance characteristic fuzzy degradation degree; and pushing a protection tripping early warning signal according to the frequency protection tripping triggering evaluation index. The method is used for carrying out risk early warning on the condition of inverter tripping caused by frequency protection mechanism mistaken touch, so that the power supply stability of the inverter is improved, and then the normal operation effect of a load is guaranteed.

Description

Technical Field

[0001] This application relates to the field of power grids, and in particular to a power supply early warning method, device and equipment based on a high-frequency resonant inverter. Background Technology

[0002] In microgrid islanded operation scenarios, traditional inverter control typically relies on sampling physical quantities such as voltage and current to achieve power supply control. However, under extreme conditions such as severe grid fluctuations or sensor failures, this type of control strategy based on physical quantity sampling faces significant reliability challenges.

[0003] In related technologies, sensorless inverter control technology based on high-frequency resonance characteristic identification has emerged to improve the reliability of inverter power supply control systems. This technology actively injects excitation signals into the inverter output side to stimulate the system's resonant frequency band response, thereby extracting its intrinsic frequency characteristics to achieve the construction of the output synchronization angle and dynamic power supply control. It has outstanding advantages such as not relying on physical sensors and rapid dynamic response.

[0004] However, the sensorless inverter control based on high-frequency resonance characteristic identification is subject to interference from high-frequency impedance abrupt changes and resonance characteristic ambiguity degradation within the system. This can cause the frequency protection mechanism to be triggered falsely, leading to inverter tripping, power supply interruption, and affecting the normal operation of the load. Summary of the Invention

[0005] This application provides a power supply early warning method, device, and equipment for inverters based on high-frequency resonance, which can provide risk warning for inverter tripping caused by false triggering of the frequency protection mechanism, thereby improving the power supply stability of the inverter and ensuring the normal operation of the load.

[0006] In a first aspect, embodiments of this application provide a power supply early warning method for an inverter based on high-frequency resonance, comprising:

[0007] Inject multiple micro-amplitude high-frequency excitation signals of different frequencies into the output terminal of the inverter;

[0008] The response data of the plurality of micro-amplitude high-frequency excitation signals are obtained, and based on the response data, the high-frequency equivalent impedance drift coefficient of the inverter output side is obtained. The high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance of the inverter output side.

[0009] Based on the high-frequency equivalent impedance drift coefficient, determine whether the inverter output side is in a high-frequency impedance change state;

[0010] When the inverter output side is in a high-frequency impedance change state, the resonant characteristic fuzziness degradation coefficient of the inverter output side is obtained based on the response data. The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of resonant characteristic fuzziness degradation of the inverter output side.

[0011] Based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonant characteristics, the frequency protection tripping trigger evaluation index of the inverter is determined. The frequency protection tripping trigger evaluation index is used to quantify the risk level of the inverter tripping due to the frequency protection mechanism.

[0012] Based on the frequency protection trip trigger evaluation index, a protection trip warning signal is pushed.

[0013] In one possible implementation, the response data includes: voltage response data and current response data at the output of the inverter;

[0014] The step of obtaining the high-frequency equivalent impedance drift coefficient on the inverter output side based on the response data includes:

[0015] Based on the voltage response data and the current response data, obtain the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment;

[0016] For each frequency, the residual impedance coefficient of the inverter output side at the current moment is calculated based on the instantaneous frequency impedance spectrum corresponding to the frequency.

[0017] Based on the residual impedance coefficient corresponding to each frequency at the current moment, the time-frequency offset coefficient of the inverter output side at the current moment is calculated.

[0018] The high-frequency equivalent impedance drift coefficient of the inverter output side is determined based on the time-frequency offset coefficient and the mean residual impedance. The mean residual impedance is obtained by averaging the residual impedance coefficients corresponding to each frequency.

[0019] In one possible implementation, obtaining the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment based on the voltage response data and the current response data includes:

[0020] A bandpass filter is used to extract the high-frequency component of the output voltage corresponding to each frequency from the voltage response data, and the high-frequency component of the output current corresponding to each frequency is extracted from the current response data.

[0021] For each frequency, the high-frequency part of the output voltage corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the voltage response intensity of the output voltage to the frequency at the current moment. The high-frequency part of the output current corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the current response intensity of the output current to the frequency at the current moment.

[0022] Based on the voltage response intensity and current response intensity corresponding to the frequency, the instantaneous frequency impedance spectrum of the inverter output side at the current moment corresponding to the frequency is obtained.

[0023] In one possible implementation, determining whether the inverter output side is in a high-frequency impedance abrupt change state based on the high-frequency equivalent impedance drift coefficient includes:

[0024] If the high-frequency equivalent impedance drift coefficient is greater than the preset drift threshold, then the inverter output side is determined to be in a high-frequency impedance abrupt change state.

[0025] If the high-frequency equivalent impedance drift coefficient is less than or equal to the preset drift threshold, then it is determined that the inverter output side is not in a high-frequency impedance abrupt change state.

[0026] In one possible implementation, when the inverter output side is in a high-frequency impedance abrupt change state, obtaining the resonant characteristic fuzziness degradation coefficient of the inverter output side based on the response data includes:

[0027] If the inverter output side is in a high-frequency impedance change state, the spectrum peak extraction algorithm is used to identify the main resonant frequency of the response data and record the resonant response delay corresponding to each excitation signal application time.

[0028] Calculate the frequency transition rate corresponding to each sampling interval based on the main resonant frequency;

[0029] The mean and variance of the resonant response delay corresponding to the application time of multiple excitation signals within a preset time window are calculated respectively to obtain the first mean and the first variance. Based on the first mean and the first variance, the delay ambiguity factor of the inverter output side is calculated.

[0030] The mean and variance of the frequency transition rates corresponding to multiple sampling intervals within a preset time window are calculated respectively to obtain the second mean and the second variance. Based on the second mean and the second variance, the frequency ambiguity factor of the inverter output side is calculated.

[0031] The fuzzy degradation coefficient of the resonant characteristics on the output side of the inverter is calculated based on the delay fuzziness factor and the frequency fuzziness factor.

[0032] In one possible implementation, determining the frequency protection tripping trigger evaluation index of the inverter based on the high-frequency equivalent impedance drift coefficient and the degree of resonant characteristic fuzziness degradation includes:

[0033] The frequency protection tripping trigger evaluation index of the inverter is obtained by weighted summation based on the high-frequency equivalent impedance drift coefficient, the first preset weight, the degree of fuzzy degradation of the resonance characteristics, and the second preset weight.

[0034] In one possible implementation, the step of pushing a protection trip warning signal based on the frequency protection trip trigger evaluation index includes:

[0035] If a frequency protection trip trigger evaluation index exceeds the preset trigger evaluation index threshold, then multiple frequency protection trip trigger evaluation indices within the subsequent preset time period are obtained.

[0036] The standard deviation of the multiple trigger evaluation indices is calculated, and when the standard deviation is greater than a preset standard deviation threshold, the protection trip warning signal is pushed.

[0037] In one possible implementation, calculating the residual impedance coefficient of the inverter output side at the current moment based on the instantaneous frequency impedance spectrum corresponding to the frequency includes:

[0038] Based on the instantaneous frequency impedance spectrum corresponding to the stated frequency, the following formula is used:

[0039] The residual impedance coefficient of the inverter output side at the current time corresponding to the frequency is calculated.

[0040] Accordingly, the step of calculating the time-frequency offset coefficient of the inverter output side at the current moment based on the residual impedance coefficient corresponding to each frequency at the current moment includes:

[0041] Based on the residual impedance coefficient corresponding to each frequency at the current moment, the formula is used:

[0042] Hz=∑ f Rz(f,t)*log(Rz(f,t)) calculates the time-frequency offset coefficient of the inverter output side at the current moment;

[0043] Where Rz(f,t) represents the residual impedance coefficient corresponding to frequency f at time t, Zk(f,t) represents the instantaneous frequency impedance spectrum corresponding to frequency f at time t, Zre(f,t) represents the historical reference impedance spectrum corresponding to frequency f at time t, and Hz represents the time-frequency offset coefficient of the inverter output side at the current time.

[0044] Secondly, embodiments of this application provide a power supply early warning device for an inverter based on high-frequency resonance, comprising:

[0045] An excitation injection module is used to inject multiple micro-amplitude high-frequency excitation signals with different frequencies into the output terminal of the inverter.

[0046] The first acquisition module is used to acquire response data of the plurality of micro-amplitude high-frequency excitation signals, and based on the response data, acquire the high-frequency equivalent impedance drift coefficient of the inverter output side. The high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance of the inverter output side.

[0047] The first determining module is used to determine whether the inverter output side is in a high-frequency impedance change state based on the high-frequency equivalent impedance drift coefficient.

[0048] The second acquisition module is used to acquire the resonant characteristic fuzziness degradation coefficient of the inverter output side based on the response data when the inverter output side is in a high-frequency impedance change state. The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of resonant characteristic fuzziness degradation of the inverter output side.

[0049] The second determining module is used to determine the frequency protection tripping trigger evaluation index of the inverter based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonant characteristics. The frequency protection tripping trigger evaluation index is used to quantify the risk level of the inverter tripping due to the frequency protection mechanism.

[0050] The push module is used to push a protection trip warning signal based on the frequency protection trip trigger evaluation index.

[0051] In one possible implementation, the first acquisition module includes:

[0052] The acquisition unit is used to acquire the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment based on the voltage response data and the current response data.

[0053] The first calculation unit is used to calculate the residual impedance coefficient of the inverter output side at the current time based on the instantaneous frequency impedance spectrum corresponding to the frequency for each frequency.

[0054] The second calculation unit is used to calculate the time-frequency offset coefficient of the inverter output side at the current moment based on the residual impedance coefficient corresponding to each frequency at the current moment.

[0055] The third calculation unit is used to determine the high-frequency equivalent impedance drift coefficient on the output side of the inverter based on the time-frequency offset coefficient and the mean residual impedance. The mean residual impedance is obtained by averaging the residual impedance coefficients corresponding to each frequency.

[0056] In one possible implementation, the acquiring unit is specifically used for:

[0057] A bandpass filter is used to extract the high-frequency component of the output voltage corresponding to each frequency from the voltage response data, and the high-frequency component of the output current corresponding to each frequency is extracted from the current response data.

[0058] For each frequency, the high-frequency part of the output voltage corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the voltage response intensity of the output voltage to the frequency at the current moment. The high-frequency part of the output current corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the current response intensity of the output current to the frequency at the current moment.

[0059] Based on the voltage response intensity and current response intensity corresponding to the frequency, the instantaneous frequency impedance spectrum of the inverter output side at the current moment corresponding to the frequency is obtained.

[0060] In one possible implementation, the first determining module is specifically used for:

[0061] If the high-frequency equivalent impedance drift coefficient is greater than the preset drift threshold, then the inverter output side is determined to be in a high-frequency impedance abrupt change state.

[0062] If the high-frequency equivalent impedance drift coefficient is less than or equal to the preset drift threshold, then it is determined that the inverter output side is not in a high-frequency impedance abrupt change state.

[0063] In one possible implementation, the second acquisition module is specifically used for:

[0064] If the inverter output side is in a high-frequency impedance change state, the spectrum peak extraction algorithm is used to identify the main resonant frequency of the response data and record the resonant response delay corresponding to each excitation signal application time.

[0065] Calculate the frequency transition rate corresponding to each sampling interval based on the main resonant frequency;

[0066] The mean and variance of the resonant response delay corresponding to the application time of multiple excitation signals within a preset time window are calculated respectively to obtain the first mean and the first variance. Based on the first mean and the first variance, the delay ambiguity factor of the inverter output side is calculated.

[0067] The mean and variance of the frequency transition rates corresponding to multiple sampling intervals within a preset time window are calculated respectively to obtain the second mean and the second variance. Based on the second mean and the second variance, the frequency ambiguity factor of the inverter output side is calculated.

[0068] The fuzzy degradation coefficient of the resonant characteristics on the output side of the inverter is calculated based on the delay fuzziness factor and the frequency fuzziness factor.

[0069] In one possible implementation, the second determining module is specifically used for:

[0070] The frequency protection tripping trigger evaluation index of the inverter is obtained by weighted summation based on the high-frequency equivalent impedance drift coefficient, the first preset weight, the degree of fuzzy degradation of the resonance characteristics, and the second preset weight.

[0071] In one possible implementation, the push module is specifically used for:

[0072] If a frequency protection trip trigger evaluation index exceeds the preset trigger evaluation index threshold, then multiple frequency protection trip trigger evaluation indices within the subsequent preset time period are obtained.

[0073] The standard deviation of the multiple trigger evaluation indices is calculated, and when the standard deviation is greater than a preset standard deviation threshold, the protection trip warning signal is pushed.

[0074] In one possible implementation, the first computing unit is specifically used for:

[0075] Based on the instantaneous frequency impedance spectrum corresponding to the stated frequency, the following formula is used:

[0076] The residual impedance coefficient of the inverter output side at the current time corresponding to the frequency is calculated.

[0077] The second calculation unit is specifically used for:

[0078] Based on the residual impedance coefficient corresponding to each frequency at the current moment, the formula is used:

[0079] Hz=∑ f Rz(f,t)*log(Rz(f,t)) calculates the time-frequency offset coefficient of the inverter output side at the current moment;

[0080] Where Rz(f,t) represents the residual impedance coefficient corresponding to frequency f at time t, Zk(f,t) represents the instantaneous frequency impedance spectrum corresponding to frequency f at time t, Zre(f,t) represents the historical reference impedance spectrum corresponding to frequency f at time t, and Hz represents the time-frequency offset coefficient of the inverter output side at the current time.

[0081] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0082] The memory stores computer-executed instructions;

[0083] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0084] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0085] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0086] The power supply early warning method, device, and equipment for inverters based on high-frequency resonance provided in this application significantly improve the overall stability, reliability, and intelligence level of the power supply control system for sensorless inverters in microgrid islanded operation scenarios by introducing a dual online dynamic evaluation mechanism of high-frequency equivalent impedance drift coefficient and resonance characteristic fuzzy degradation coefficient into the traditional sensorless inverter control method. First, by using a low-amplitude high-frequency excitation signal to obtain the high-frequency equivalent impedance drift coefficient on the inverter output side, non-invasive, real-time detection of internal structural changes such as aging, saturation, and dielectric loss in key components like LCL filters, inductors, and capacitors on the inverter output side can be performed. The degree of impedance drift can accurately determine whether a high-frequency impedance abrupt change has occurred. Second, upon detecting an impedance abrupt change, the resonance characteristic fuzziness degradation coefficient is further obtained to quantitatively assess the reliability of intrinsic frequency extraction and the degree of degradation in resonance response clarity, avoiding misjudgments caused by a single indicator. Then, by inputting the above two coefficients into the constructed frequency protection trip trigger evaluation model, a quantitative frequency protection trip trigger evaluation index is output. This index reflects the potential risk of frequency protection tripping in islanded mode in real time, generating a protection trip warning signal when there is high risk accompanied by severe fluctuations, achieving early warning of frequency anomalies and a smooth transition between protection actions. Therefore, it can be seen that in engineering applications, this invention can provide risk warning for inverter tripping caused by false activation of the frequency protection mechanism, which can significantly reduce the probability of false overvoltage / undervoltage alarms and grid disconnection of the entire unit, thereby improving the power supply stability of the inverter and ensuring the normal operation of the load. Attached Figure Description

[0087] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0088] Figure 1 A schematic flowchart of the power supply early warning method for inverters based on high-frequency resonance provided in Embodiment 1 of this application;

[0089] Figure 2 This is a schematic diagram of the power supply early warning device for an inverter based on high-frequency resonance, provided in Embodiment 3 of this application.

[0090] Figure 3 A schematic diagram of the structure of the electronic device provided in this application.

[0091] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0092] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0093] To facilitate understanding of the technical content of this solution, the background technology is described in detail below:

[0094] In microgrid islanded operation scenarios, the inverter control system includes the inverter and the inverter output side. The inverter output side refers to the load network connected to the inverter output, which includes at least an inductor-capacitor-inductor (LCL) filter and the grid load. While researching control methods based on high-frequency resonance characteristic identification, the inventors discovered that during actual operation, a series of interference factors may still occur within the inverter control system, severely affecting the stability and effectiveness of such methods.

[0095] Among the most significant challenges are the high-frequency impedance abrupt changes and the ambiguity and degradation of resonant characteristics on the inverter output side of the system. The former typically manifests as unexpected shifts in the system's resonant frequency and quality factor (Q) caused by factors such as aging of LCL filter devices, inductor nonlinearity saturation, and capacitor dielectric losses on the inverter output side. This directly leads to distortion of the resonant response characteristics on the inverter output side, making it difficult for the system to stably extract the locking angle, ultimately resulting in output voltage frequency shift, phase distortion, and power imbalance. The latter manifests as a decrease in the signal-to-noise ratio of the intrinsic frequency extraction on the inverter output side and aliasing and ambiguity of the response characteristics under conditions of load nonlinearity, grid disturbances, or harmonic superposition, causing synchronization angle locking errors or modulation angle drift. In islanded mode, such mismatches can easily trigger frequency protection, false overvoltage / undervoltage alarms, or even complete grid disconnection. Therefore, it is urgent to establish dynamic modeling and compensation mechanisms for internal structural disturbances and intrinsic frequency drift in high-frequency resonant control methods to improve their control stability and applicability in complex scenarios.

[0096] Based on this, the inventors considered introducing a dual online dynamic evaluation mechanism of high-frequency equivalent impedance drift coefficient and resonant characteristic fuzzy degradation coefficient into the traditional sensorless inverter control method during system operation. This mechanism is used to judge the potential risk of system triggering frequency protection tripping in real time under islanded mode, thereby achieving early warning of inverter tripping and enabling staff to take defensive measures as early as possible. This significantly reduces the probability of false overvoltage / undervoltage alarms and system disconnection, thereby improving the power supply stability of the inverter and ensuring the normal operation of the load.

[0097] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0098] Figure 1 This is a flowchart illustrating the power supply early warning method for inverters based on high-frequency resonance provided in Embodiment 1 of this application, as shown below. Figure 1 As shown, the power supply warning for the inverter based on high-frequency resonance provided in this embodiment includes:

[0099] S101. Inject multiple micro-amplitude high-frequency excitation signals with different frequencies into the output terminal of the inverter.

[0100] The frequency of each micro-amplitude high-frequency excitation signal is predefined.

[0101] This solution is applicable to inverter control systems, and is especially suitable for sensorless power supply control systems with LCL filter structures.

[0102] As a specific example, a typical high-frequency resonant range (e.g., 1–10 kHz) of the system's LCL filter can be selected, divided into multiple excitation frequency bands, and multiple frequencies fp can be determined based on these excitation frequency bands. i Each frequency fp i This allows for the construction of a corresponding micro-amplitude high-frequency excitation signal Uinj. i (t), specifically represented as Uinj i (t)=Az i *sin(2*π*fp i *t), where Az i This is a small disturbance amplitude, typically taken as 0.5% to 1% of the inverter's rated output voltage.

[0103] In practical applications, after acquiring multiple micro-amplitude high-frequency excitation signals, the micro-amplitude high-frequency excitation signals are usually superimposed on the PWM output voltage modulation reference waveform to achieve active injection of high-frequency micro-amplitude disturbances.

[0104] S102. Obtain response data of multiple micro-amplitude high-frequency excitation signals, and based on the response data, obtain the high-frequency equivalent impedance drift coefficient of the inverter output side.

[0105] Among them, the high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance on the inverter output side.

[0106] In this step, the response data of the multiple micro-amplitude high-frequency excitation signals are collected to quantify the dynamic offset of the high-frequency impedance on the inverter output side of the system, and the high-frequency equivalent impedance drift coefficient is obtained.

[0107] For example, the actual high-frequency impedance of the inverter output side can be calculated based on the response data, and the actual high-frequency impedance can be compared with the reference high-frequency impedance during the system calibration stage. Based on the comparison results, the dynamic offset of the high-frequency impedance of the inverter output side can be quantitatively calculated.

[0108] It should be understood that the high-frequency equivalent impedance drift coefficient can truly reflect the structural parameter shifts caused by hardware changes such as filter device aging, inductor saturation, and capacitor loss. It is a non-intrusive, real-time evaluation method for the internal state of the system.

[0109] It should be noted that the dynamic offset of the high-frequency impedance on the inverter output side is an important factor that causes the inverter to trip due to the influence of the system's frequency protection mechanism. This solution quantifies this characteristic, which can provide a guarantee for the effective prevention of inverter tripping.

[0110] S103. Determine whether the inverter output side is in a high-frequency impedance change state based on the high-frequency equivalent impedance drift coefficient.

[0111] In this step, the magnitude of the high-frequency equivalent impedance drift coefficient will be used to determine whether the inverter output side is in a high-frequency impedance abrupt change state.

[0112] S104. When the inverter output side is in a high-frequency impedance change state, obtain the fuzzy degradation coefficient of the resonant characteristics of the inverter output side based on the response data.

[0113] The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of fuzziness degradation of the resonant characteristics on the inverter output side. Specifically, it is an important indicator for measuring the clarity, identifiability, and stability degradation of the resonant response characteristics that can be obtained during high-frequency resonant control of the inverter. This coefficient constructs a comprehensive evaluation quantity that reflects the dynamic trend of resonant characteristic degradation. The larger the value, the more fuzzy and severe the degradation of the system's resonant response characteristics; the smaller the value, the more stable and clear the intrinsic frequency response output of the current system can still be maintained under high-frequency excitation, possessing good resonant identifiability and modulation support capabilities.

[0114] In this step, assuming that the inverter output side is in a high-frequency impedance abrupt change state, the response data will continue to be analyzed. Based on the resonance characteristics of the response data, the degree of fuzzy degradation of the resonance characteristics of the inverter output side will be quantified, and the fuzzy degradation coefficient of the resonance characteristics will be calculated.

[0115] It should be noted that factors affecting the degree of fuzziness degradation of the resonant characteristics on the inverter output side include: first, harmonic energy injection, nonlinear load disturbances, or changes in system filter parameters leading to fuzziness of the resonant point, resulting in distortion or even disappearance of the intrinsic peak value in the spectral response; second, the expansion of the intrinsic frequency bandwidth and the reduction of the Q value, causing the modulator to be unable to accurately lock the synchronization angle; and third, interference sources such as spectral aliasing and fundamental frequency interference mask the resonant characteristic signal, affecting the demodulation results of the modulation algorithm on the response signal. Since these degradation phenomena directly weaken the accuracy and stability of the system's sensorless synchronization control, especially in islanded mode, the inability to accurately obtain the resonant frequency lock angle may cause the output voltage frequency to deviate from the set reference, triggering false frequency anomaly identification or misjudging it as system instability, thus prematurely triggering frequency protection tripping. Therefore, this scheme further quantifies the fuzziness degradation coefficient of the resonant characteristics on the inverter output side. This coefficient serves as an important basis for judging whether there is a potential for degradation in the resonant control accuracy or failure of the modulation strategy on the inverter output side. It can significantly enhance the sensitivity and response capability of the early warning method of this scheme to complex internal state coupling faults, and can provide further assurance for the effective prevention of inverter false tripping.

[0116] S105. Based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonance characteristics, determine the frequency protection tripping trigger evaluation index of the inverter.

[0117] Among them, the frequency protection tripping trigger assessment index is used to quantify the risk level of inverter tripping due to frequency protection mechanism.

[0118] In this step, the risk level of inverter tripping due to frequency protection mechanism is assessed by using the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of resonance characteristics. This enables the reliability of the assessment results from both "structural disturbance" and "control accuracy" perspectives, so that the frequency protection tripping trigger assessment index can reflect the actual operating risk of the system. This effectively prevents false tripping or leakage protection, and improves the safety, fault tolerance and intelligent discrimination level of the inverter under islanded operation.

[0119] S106. Based on the frequency protection trip trigger evaluation index, push the protection trip early warning signal.

[0120] In this step, the risk level of the current frequency protection tripping trigger will be determined based on the established frequency protection tripping trigger evaluation index, and a protection tripping warning signal will be pushed when the risk level is high.

[0121] The power supply early warning method, device, and equipment for inverters based on high-frequency resonance provided in this application significantly improve the overall stability, reliability, and intelligence level of the power supply control system for sensorless inverters in microgrid islanded operation scenarios by introducing a dual online dynamic evaluation mechanism of high-frequency equivalent impedance drift coefficient and resonance characteristic fuzzy degradation coefficient into the traditional sensorless inverter control method. First, by using a micro-amplitude high-frequency excitation signal to obtain the high-frequency equivalent impedance drift coefficient on the inverter output side, non-invasive, real-time detection of internal structural changes such as aging, saturation, and dielectric loss in key components like LCL filters, inductors, and capacitors on the inverter output side can be performed. The degree of impedance drift can accurately determine whether a high-frequency impedance abrupt change has occurred. Second, upon detecting an impedance abrupt change, the resonance characteristic fuzziness degradation coefficient is further obtained to quantitatively assess the reliability of intrinsic frequency extraction and the degree of degradation in resonance response clarity, avoiding misjudgments caused by a single indicator. Then, by inputting the above two coefficients into the constructed frequency protection trip trigger evaluation model, a quantitative frequency protection trip trigger evaluation index is output. This index reflects the potential risk of frequency protection tripping in islanded mode, identifies potential control instability trends in advance, and generates protection trip warning signals when there is high risk accompanied by severe fluctuations, thereby achieving early warning of frequency anomalies and a smooth transition between protection actions. Therefore, it can be seen that in engineering applications, this invention can provide risk warning for inverter tripping caused by false activation of the frequency protection mechanism, which can significantly reduce the probability of false overvoltage / undervoltage alarms and grid disconnection of the entire unit, thereby improving the power supply stability of the inverter and ensuring the normal operation of the load.

[0122] Furthermore, Embodiment 2 of this application provides a specific power supply early warning method for inverters based on high-frequency resonance. Based on the above embodiments, this embodiment provides a detailed description of the specific implementation of steps S101-106, as follows:

[0123] S101. Inject multiple micro-amplitude high-frequency excitation signals with different frequencies into the output terminal of the inverter.

[0124] S102. Obtain response data of multiple micro-amplitude high-frequency excitation signals, and based on the response data, obtain the high-frequency equivalent impedance drift coefficient of the inverter output side.

[0125] The response data includes voltage response data and current response data collected at the output of the inverter.

[0126] Specifically, step S102 includes the following steps 2.1 to 2.4:

[0127] Step 2.1: Based on the voltage response data and current response data, obtain the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment.

[0128] Here, "each frequency" corresponds to the frequency of each of the aforementioned micro-amplitude high-frequency excitation signals. The instantaneous frequency impedance spectrum refers to the impedance value of the inverter output side at a specific frequency.

[0129] In one possible implementation, step 2.1 can be implemented as follows: steps 2.1.1 to 2.1.2:

[0130] Step 2.1.1: Use a bandpass filter to extract the high-frequency part of the output voltage corresponding to each frequency from the voltage response data, and extract the high-frequency part of the output current corresponding to each frequency from the current response data.

[0131] For example, for each frequency, the high-frequency components corresponding to that frequency are extracted from the voltage response data and current response data using a bandpass filter to obtain the high-frequency response data sequence {Vhf(t), Ihf(t)}, which can be expressed by the following formula:

[0132]

[0133] Where Vhf(t) is the high-frequency part of the output voltage Vout(t), and Ihf(t) is the high-frequency part of the output current Iout(t).

[0134] It should be noted that Βf[·] is a bandpass filter operator used to perform bandpass filtering on the output voltage Vout(t) and output current Iout(t) to extract their components within a specific high-frequency band, thereby obtaining the high-frequency part of the output voltage Vhf(t) and the high-frequency part of the output current Ihf(t) at the corresponding frequency of that high-frequency band.

[0135] Step 2.1.2: For each frequency, use the continuous wavelet transform method to extract the high-frequency part of the output voltage corresponding to that frequency to obtain the voltage response intensity of the output voltage at the current moment at that frequency. Then, use the continuous wavelet transform method to extract the high-frequency part of the output current corresponding to that frequency to obtain the current response intensity of the output current at the current moment at that frequency.

[0136] For example, the extraction of instantaneous frequency response using wavelet transform can be represented by the following formula:

[0137]

[0138] Where CWT[·] represents continuous wavelet transform, V(f,t) represents the response intensity of the output voltage at time t to frequency f, and I(f,t) represents the response intensity of the output current at time t to frequency f.

[0139] It should be noted that CWT is a time-frequency analysis method for continuous scale (frequency) changes, and it has good ability to extract local transient features.

[0140] Step 2.1.3: Based on the voltage response intensity and current response intensity corresponding to the frequency, obtain the instantaneous frequency impedance spectrum of the inverter output side at the current moment corresponding to that frequency.

[0141] For example, the instantaneous frequency impedance spectrum Zk(f,t) corresponding to frequency f at time t can be calculated using the following formula:

[0142] Step 2.2: For each frequency, calculate the residual impedance coefficient of the inverter output side at the current time based on the instantaneous frequency impedance spectrum corresponding to that frequency.

[0143] The residual impedance coefficient is a coefficient used to quantify the degree of deviation between the impedance value at a specific frequency at the current moment and the reference impedance value at that frequency. It is a key indicator for measuring the dynamic offset of the system impedance.

[0144] As a specific example, the residual impedance coefficient Rz(f,t) at frequency f at time t can be calculated using the following formula:

[0145]

[0146] Where Zre(f,t) represents the historical reference impedance spectrum corresponding to frequency f at time t, which is a reference value determined during the system calibration phase.

[0147] Step 2.3: Calculate the time-frequency offset coefficient of the inverter output side at the current moment based on the residual impedance coefficient corresponding to each frequency at the current moment.

[0148] Among them, the time-frequency offset coefficient is used to comprehensively quantify the overall offset trend of the residual impedance coefficients at all the frequencies of interest on the inverter output side at the current moment.

[0149] As a specific example, the time-frequency offset coefficient (Hz) at the current moment can be calculated using the following formula:

[0150]

[0151] Step 2.4: Determine the high-frequency equivalent impedance drift coefficient on the inverter output side based on the time-frequency offset coefficient and the mean residual impedance.

[0152] The mean residual impedance is obtained by averaging the residual impedance coefficients corresponding to each frequency. It is used to reflect the average level of the offset of the residual impedance coefficients at all the frequencies of interest on the inverter output side at the current moment.

[0153] Specifically, the mean residual impedance Cjz can be expressed as: Where fn represents the total number of frequency points.

[0154] It should be understood that both the time-frequency offset coefficient and the mean residual impedance can reflect the current dynamic offset of the high-frequency impedance at the inverter output. Therefore, this scheme determines the high-frequency equivalent impedance drift coefficient by combining the time-frequency offset coefficient and the mean residual impedance.

[0155] As a specific example, the high-frequency equivalent impedance drift coefficient Dpzk can be calculated using the following formula:

[0156] Dpzk=a1*Cjz+a2*Hz

[0157] Where a1 represents the preset proportional coefficient of the residual impedance mean, and a2 represents the preset proportional coefficient of the time-frequency offset coefficient.

[0158] Specifically, a1 and a2 are set according to the actual situation. For example, the expert empowerment method is adopted, that is, experts in relevant fields are invited to determine the preset ratio coefficients of each indicator through professional opinion surveys and comprehensive evaluations. For example, a1 and a2 can be 0.5 and 0.5 respectively.

[0159] It should be noted that in practical applications, the formulas in this scheme are all calculated by removing dimensions and taking their numerical values. Commonly used methods for removing dimensions include Min-Max normalization, Z-score standardization, etc., which will not be elaborated here.

[0160] S103. Determine whether the inverter output side is in a high-frequency impedance change state based on the high-frequency equivalent impedance drift coefficient.

[0161] In one possible implementation, if the high-frequency equivalent impedance drift coefficient is greater than a preset drift threshold, the inverter output side is determined to be in a high-frequency impedance abrupt change state; if the high-frequency equivalent impedance drift coefficient is less than or equal to the preset drift threshold, the inverter output side is determined not to be in a high-frequency impedance abrupt change state.

[0162] The preset drift threshold is set based on historical experience or expert advice, and this application does not limit the specific value used.

[0163] It should be understood that if the high-frequency equivalent impedance drift coefficient is greater than the preset drift threshold, it indicates that the high-frequency equivalent impedance parameter of the current system has shifted significantly, indicating that there are structural changes in the filter device, power device or transmission path (such as inductor saturation, LCL parameter aging, and increased capacitor dielectric loss), which causes nonlinear drift in the system resonant frequency and quality factor, which may affect the high-frequency phase-locked loop accuracy and modulation angle tracking stability. In this case, the impedance state of the current system can be determined as a high-frequency impedance abrupt change state.

[0164] If the high-frequency equivalent impedance drift coefficient is less than or equal to the high-frequency equivalent impedance drift coefficient threshold, it indicates that the high-frequency impedance parameters of the current system are still within the fluctuation range allowed by the calibration model, and no obvious structural degradation has occurred. The resonant frequency, Q value, and equivalent impedance spectrum characteristics are highly consistent with the initial operating conditions. This can be considered as the effective identification characteristics of the control system, the stable synchronization modulation angle, and the power supply control being able to continue to be maintained within the non-inductive control tolerance. Thus, the impedance state of the current system can be determined as an impedance stable state (i.e., not in a high-frequency impedance abrupt change state).

[0165] S104. When the inverter output side is in a high-frequency impedance change state, obtain the fuzzy degradation coefficient of the resonant characteristics of the inverter output side based on the response data.

[0166] It should be noted that when the inverter output side is determined to be in a high-frequency impedance abrupt change state, it indicates that the current sensorless synchronization control method based on this characteristic will have difficulty accurately locking the system synchronization angle, resulting in frequency drift and phase distortion of the output voltage, and even control loop oscillation, which can easily lead to transformer malfunction. Therefore, only when the inverter output side is in a high-frequency impedance abrupt change state should the fuzzy degradation coefficient of the resonant characteristic of the inverter output side be obtained to further determine whether an early warning is needed.

[0167] In one possible implementation, steps 4.1 to 4.5 can be used:

[0168] Step 4.1: If the inverter output side is in a high-frequency impedance change state, the spectrum peak extraction algorithm is used to identify the main resonant frequency of the response data and record the resonant response delay corresponding to each excitation signal application time.

[0169] In this step, the main resonant frequency will be extracted from the response data, and the resonant response delay corresponding to the excitation signal will be recorded each time an excitation signal is applied.

[0170] The main resonant frequency refers to the resonant frequency component with the highest amplitude extracted from the response data; the resonant response delay refers to the difference between the time when the main resonant frequency first appears after each application of a micro-amplitude high-frequency excitation signal and the time when the micro-amplitude high-frequency excitation signal is applied.

[0171] It should be noted that the spectrum peak extraction algorithm used to identify the main resonant frequency includes, but is not limited to, Fast Fourier Transform (FFT) peak detection algorithms, LocalMaxima Clustering for Spectral Peaks, high-resolution frequency estimation methods (such as Multiple Signal Classification Algorithm (MUSIC)), Estimation of Signal Parameters via Rotational Invariance Techniques Algorithm (ESPRIT), and Weighted Spectral Envelope Filtering (WSEFA). In its specific implementation, this invention can flexibly select appropriate frequency extraction methods based on factors such as the noise environment, frequency distribution density, and computational resources of the resonant response signal to ensure the accuracy and real-time performance of frequency extraction. The aforementioned spectrum analysis and main frequency identification methods already have mature mathematical modeling and engineering implementation methods, and the relevant basic principles and implementation processes have been disclosed in detail in the existing spectrum analysis technology field, and will not be repeated here.

[0172] For example, the resonant response delay τr(t) corresponding to each excitation signal application time is expressed as: τr(t) = tres(t) - texc(t), where texc(t) is the application time of the micro-amplitude high-frequency excitation signal, and tres(t) is the time when the main resonant frequency first appears after the application time texc(t).

[0173] Step 4.2: Calculate the frequency transition rate corresponding to each sampling interval based on the main resonant frequency.

[0174] In this step, based on the main resonant frequencies extracted at multiple times, the frequency transition rate is calculated over a continuous sampling interval Δt: Δf(t)=|fr(t)-fr(t-Δt)|, where Δf(t) is the frequency transition rate, fr(t) is the main resonant frequency extracted at time t, and fr(t-Δt) is the main resonant frequency extracted at time (t-Δt).

[0175] Step 4.3: Calculate the mean and variance of the resonant response delay corresponding to the application time of multiple excitation signals within the preset time window, obtain the first mean and the first variance, and calculate the delay ambiguity factor on the inverter output side based on the first mean and the first variance.

[0176] The value of the preset time window can be determined according to the actual application situation, and this application does not impose any restrictions on it.

[0177] For example, the mean and variance of the resonant response delay are first calculated within a fixed time window T: Where μτr is the first mean value corresponding to the resonant response delay, and στr is the first variance corresponding to the resonant response delay;

[0178] Then, use the formula Calculate the delay ambiguity factor θτ, where ∈ is a minimal constant to prevent division by zero (generally taken as ∈ = 10). -6 ).

[0179] Step 4.4: Calculate the mean and variance of the frequency transition rates corresponding to multiple sampling intervals within the preset time window to obtain the second mean and the second variance, and calculate the frequency ambiguity factor on the inverter output side based on the second mean and the second variance.

[0180] For example, first, the mean and variance of the frequency transition rate are calculated within a fixed time window T: Where μf is the second mean value corresponding to the frequency transition rate, and σf is the second variance corresponding to the frequency transition rate;

[0181] Then, use the formula Calculate the frequency ambiguity factor θf, where ∈ is a minimal constant to prevent division by zero (generally taken as ∈ = 10).-6 ).

[0182] Step 4.5: Calculate the fuzzy degradation coefficient of the resonant characteristic on the inverter output side based on the delay fuzziness factor and the frequency fuzziness factor.

[0183] In this step, since the delay ambiguity factor and the frequency ambiguity factor are both factors affecting the degree of ambiguity degradation of the resonant characteristics, this scheme will determine the ambiguity degradation coefficient of the resonant characteristics on the inverter output side based on the two factors together.

[0184] For example, the resonance characteristic fuzziness degradation coefficient Xzth can be calculated using the following formula:

[0185] Xzth=b1*θf+b2*θτ

[0186] Where Xzth is the resonant characteristic fuzziness degradation coefficient, b1 and b2 represent the preset proportional coefficients of the frequency fuzziness factor and the delay fuzziness factor, respectively, and both b1 and b2 are greater than 0.

[0187] Among them, b1 and b2 are set according to the actual situation. For example, the expert empowerment method is adopted, that is, experts in relevant fields are invited to determine the preset ratio coefficients of each indicator through professional opinion surveys and comprehensive evaluations. For example, b1 and b2 can be 0.5 and 0.5 respectively.

[0188] S105. Based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonance characteristics, determine the frequency protection tripping trigger evaluation index of the inverter.

[0189] In one possible implementation, the frequency protection tripping trigger evaluation index of the inverter is obtained by weighted summation based on the high-frequency equivalent impedance drift coefficient, the first preset weight, the degree of fuzzy degradation of the resonance characteristics, and the second preset weight.

[0190] The values ​​of the first preset weight and the second preset weight are not specifically limited in this application and can be set according to the actual situation. For example, the expert weighting method can be adopted, that is, experts in relevant fields are invited to determine the values ​​through professional opinion surveys and comprehensive evaluations. For example, the first preset weight and the second preset weight can be 0.5 and 0.5 respectively.

[0191] For example, the frequency protection trip trigger evaluation index ogk is calculated using the following formula:

[0192] ogk = w1 * Dpzk + w2 * Xzth

[0193] Where w1 is the first preset weight and w2 is the second preset weight.

[0194] S106. Based on the frequency protection trip trigger evaluation index, push the protection trip early warning signal.

[0195] It should be understood that, based on the calculation method of the frequency protection trip trigger evaluation index, the larger the high-frequency equivalent impedance drift coefficient and the larger the resonance characteristic fuzziness degradation coefficient, the larger the frequency protection trip trigger evaluation index. This indicates that the high-frequency equivalent impedance drift of the current system is more significant, and the resonance characteristic exhibits obvious fuzziness degradation characteristics. This reflects potential hidden dangers such as weakened stability support capability for disturbances, decreased electrical inertia, weakened control feedback efficiency, and enhanced resonance coupling. As a result, the risk of triggering frequency protection tripping under islanded operation mode increases significantly. Conversely, the smaller the high-frequency equivalent impedance drift coefficient and the smaller the resonance characteristic fuzziness degradation coefficient, the smaller the frequency protection trip trigger evaluation index. This indicates that the system parameters are stable, the resonance response is predictable, the system is in a high-safety operation state, and the risk of frequency protection tripping is relatively low.

[0196] In one specific implementation, the frequency protection tripping trigger evaluation index is compared with a preset trigger evaluation index threshold. The moment when the frequency protection tripping trigger evaluation index is greater than the preset trigger evaluation index threshold is determined as a high-risk moment. When the current moment is determined to be a high-risk moment, a protection tripping warning signal is pushed so that corresponding maintenance measures can be taken, such as driving the system into a transitional working mode or triggering a flexible protection mechanism.

[0197] In detail, if the frequency protection tripping trigger assessment index is greater than the trigger assessment index threshold, it indicates that the high-frequency equivalent impedance fluctuation in the current microgrid system is severe and the resonance characteristics are significantly blurred and degraded. This indicates that the system stability margin is reduced and the absorption capacity of frequency disturbances is weakened. The probability of frequency over-limit or sudden change in islanded operation mode is significantly increased, which is very likely to trigger the protection action tripping. The risk level of frequency protection tripping triggering in islanded mode is marked as high risk level, and the corresponding time is determined as high risk time.

[0198] If the frequency protection tripping trigger evaluation index is less than or equal to the triggering evaluation index threshold, it indicates that the high-frequency equivalent impedance change of the current system is within an acceptable range, the resonance characteristic stability is good, the main frequency response is clear and the delay is stable, the system has a strong disturbance mitigation and frequency maintenance capability under islanded operation, the probability of triggering frequency protection tripping is low, the system is still in a safe and stable operating range, the risk level of frequency protection tripping triggering under islanded mode is marked as low risk level, and the corresponding time is determined as low risk time.

[0199] In one possible implementation, if a frequency protection trip trigger evaluation index exceeds a preset trigger evaluation index threshold, then multiple frequency protection trip trigger evaluation indices within a subsequent preset time period are obtained, the standard deviation of these multiple trigger evaluation indices is calculated, and a protection trip warning signal is pushed when the standard deviation exceeds a preset standard deviation threshold.

[0200] The preset standard deviation is determined according to the actual situation, such as based on historical experience or expert advice. This application does not impose specific restrictions on its value.

[0201] As a specific example, if a frequency protection tripping trigger evaluation index exceeds a preset trigger evaluation index threshold, then multiple frequency protection tripping trigger evaluation indices within a subsequent preset time period are obtained to obtain a frequency protection tripping trigger evaluation index sequence {ogk}. h}={ogk1,ogk2,...,ogk H}, where ogk h Let h be the frequency protection trip trigger evaluation index at time h, where h∈{1,2,...,H} and H is the total number of frequency protection trip trigger evaluation indices;

[0202] The standard deviation of the frequency protection tripping trigger evaluation index sequence, Bogh, is calculated using the following formula:

[0203]

[0204] in, The mean of the evaluation index sequence for frequency protection trip triggering.

[0205] The standard deviation is compared with a preset standard deviation threshold, and a protection trip warning signal is pushed when the standard deviation is greater than the preset standard deviation.

[0206] It should be understood that if the standard deviation of the frequency protection trip trigger assessment index time series is greater than the standard deviation threshold, it indicates that the current frequency protection trip trigger assessment index is fluctuating drastically, reflecting a trend of rapid change in the dynamic behavior of the system frequency, implying a high probability of rapid frequency shift or sudden change, further deteriorating the system frequency stability, and immediately generating a protection trip warning signal.

[0207] If the standard deviation of the frequency protection trip trigger assessment index time series is less than or equal to the standard deviation threshold, it indicates that although the system is currently at a high risk level, the fluctuation range of the frequency protection trip trigger assessment index is small, the system frequency disturbance is still controllable and has the ability to mitigate, and the short-term trip risk is low. At this time, it is considered that the system has not yet entered the critical state of frequency protection triggering, and there is no need to generate a protection trip warning signal.

[0208] This implementation method determines whether to push an early warning signal based on standard deviation verification, effectively avoiding false early warnings triggered by abnormal data at a single moment (such as sudden noise interference causing the assessment index to exceed the standard instantaneously). Furthermore, by judging the volatility of risk through standard deviation, it ensures that the pushed early warning signal corresponds to the real and trending risk of deregulation in the system, thereby improving the reliability of the early warning.

[0209] Based on the above embodiments, this embodiment provides a specific implementation method for the high-frequency equivalent impedance drift coefficient and the resonance characteristic fuzzy degradation coefficient. Specifically, the high-frequency equivalent impedance drift coefficient integrates the time-frequency offset coefficient and the residual impedance mean to achieve a comprehensive quantification of the overall drift trend of the high-frequency impedance on the inverter output side. It can intuitively reflect the degree of impedance characteristics deviating from the reference state due to factors such as device aging and load changes. The resonance characteristic fuzzy degradation coefficient is based on the frequency fuzziness factor and delay fuzziness factor determined by the response data. It accurately quantifies the degree of fuzzy degradation of the resonance characteristics on the inverter output side through a dual-factor determination method, providing a guarantee for the reliable operation of this solution.

[0210] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0211] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0212] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0213] In the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0214] Figure 2 This is a schematic diagram of the power supply early warning device for an inverter based on high-frequency resonance, as provided in Embodiment 3 of this application. Figure 2 As shown, the power supply early warning device 20 based on a high-frequency resonant inverter provided in this embodiment includes:

[0215] The excitation injection module 201 is used to inject multiple micro-amplitude high-frequency excitation signals with different frequencies into the output terminal of the inverter.

[0216] The first acquisition module 202 is used to acquire response data of the plurality of micro-amplitude high-frequency excitation signals, and based on the response data, acquire the high-frequency equivalent impedance drift coefficient of the inverter output side. The high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance of the inverter output side.

[0217] The first determining module 203 is used to determine whether the inverter output side is in a high-frequency impedance change state based on the high-frequency equivalent impedance drift coefficient.

[0218] The second acquisition module 204 is used to acquire the resonant characteristic fuzziness degradation coefficient of the inverter output side based on the response data when the inverter output side is in a high-frequency impedance change state. The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of resonant characteristic fuzziness degradation of the inverter output side.

[0219] The second determining module 205 is used to determine the frequency protection tripping trigger evaluation index of the inverter based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonance characteristics. The frequency protection tripping trigger evaluation index is used to quantify the risk level of the inverter tripping due to the frequency protection mechanism.

[0220] The push module 206 is used to push a protection trip warning signal based on the frequency protection trip trigger evaluation index.

[0221] In one possible implementation, the first acquisition module 202 includes:

[0222] The acquisition unit is used to acquire the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment based on the voltage response data and the current response data.

[0223] The first calculation unit is used to calculate the residual impedance coefficient of the inverter output side at the current time based on the instantaneous frequency impedance spectrum corresponding to the frequency for each frequency.

[0224] The second calculation unit is used to calculate the time-frequency offset coefficient of the inverter output side at the current moment based on the residual impedance coefficient corresponding to each frequency at the current moment.

[0225] The third calculation unit is used to determine the high-frequency equivalent impedance drift coefficient on the output side of the inverter based on the time-frequency offset coefficient and the mean residual impedance. The mean residual impedance is obtained by averaging the residual impedance coefficients corresponding to each frequency.

[0226] In one possible implementation, the acquiring unit is specifically used for:

[0227] A bandpass filter is used to extract the high-frequency component of the output voltage corresponding to each frequency from the voltage response data, and the high-frequency component of the output current corresponding to each frequency is extracted from the current response data.

[0228] For each frequency, the high-frequency part of the output voltage corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the voltage response intensity of the output voltage to the frequency at the current moment. The high-frequency part of the output current corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the current response intensity of the output current to the frequency at the current moment.

[0229] Based on the voltage response intensity and current response intensity corresponding to the frequency, the instantaneous frequency impedance spectrum of the inverter output side at the current moment corresponding to the frequency is obtained.

[0230] In one possible implementation, the first determining module 203 is specifically used for:

[0231] If the high-frequency equivalent impedance drift coefficient is greater than the preset drift threshold, then the inverter output side is determined to be in a high-frequency impedance abrupt change state.

[0232] If the high-frequency equivalent impedance drift coefficient is less than or equal to the preset drift threshold, then it is determined that the inverter output side is not in a high-frequency impedance abrupt change state.

[0233] In one possible implementation, the second acquisition module 204 is specifically used for:

[0234] If the inverter output side is in a high-frequency impedance change state, the spectrum peak extraction algorithm is used to identify the main resonant frequency of the response data and record the resonant response delay corresponding to each excitation signal application time.

[0235] Calculate the frequency transition rate corresponding to each sampling interval based on the main resonant frequency;

[0236] The mean and variance of the resonant response delay corresponding to the application time of multiple excitation signals within a preset time window are calculated respectively to obtain the first mean and the first variance. Based on the first mean and the first variance, the delay ambiguity factor of the inverter output side is calculated.

[0237] The mean and variance of the frequency transition rates corresponding to multiple sampling intervals within a preset time window are calculated respectively to obtain the second mean and the second variance. Based on the second mean and the second variance, the frequency ambiguity factor of the inverter output side is calculated.

[0238] The fuzzy degradation coefficient of the resonant characteristics on the output side of the inverter is calculated based on the delay fuzziness factor and the frequency fuzziness factor.

[0239] In one possible implementation, the second determining module 205 is specifically used for:

[0240] The frequency protection tripping trigger evaluation index of the inverter is obtained by weighted summation based on the high-frequency equivalent impedance drift coefficient, the first preset weight, the degree of fuzzy degradation of the resonance characteristics, and the second preset weight.

[0241] In one possible implementation, the push module 206 is specifically used for:

[0242] If a frequency protection trip trigger evaluation index exceeds the preset trigger evaluation index threshold, then multiple frequency protection trip trigger evaluation indices within the subsequent preset time period are obtained.

[0243] The standard deviation of the multiple trigger evaluation indices is calculated, and when the standard deviation is greater than a preset standard deviation threshold, the protection trip warning signal is pushed.

[0244] In one possible implementation, the first computing unit is specifically used for:

[0245] Based on the instantaneous frequency impedance spectrum corresponding to the stated frequency, the following formula is used:

[0246] The residual impedance coefficient of the inverter output side at the current time corresponding to the frequency is calculated.

[0247] The second calculation unit is specifically used for:

[0248] Based on the residual impedance coefficient corresponding to each frequency at the current moment, the formula is used:

[0249] Hz=∑ f Rz(f,t)*log(Rz(f,t)) calculates the time-frequency offset coefficient of the inverter output side at the current moment;

[0250] Where Rz(f,t) represents the residual impedance coefficient corresponding to frequency f at time t, Zk(f,t) represents the instantaneous frequency impedance spectrum corresponding to frequency f at time t, Zre(f,t) represents the historical reference impedance spectrum corresponding to frequency f at time t, and Hz represents the time-frequency offset coefficient of the inverter output side at the current time.

[0251] The power supply early warning device 20 based on a high-frequency resonant inverter provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0252] Figure 3 A schematic diagram of the structure of the electronic device provided in this application. Figure 3 As shown, the electronic device 30 provided in this embodiment includes at least one processor 301 and a memory 302. Optionally, the device 30 further includes a communication component 303. The processor 301, memory 302, and communication component 303 are connected via a bus 304.

[0253] In a specific implementation, at least one processor 301 executes computer execution instructions stored in memory 302, causing at least one processor 301 to perform the above-described method.

[0254] The specific implementation process of processor 301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0255] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0256] The memory may include read-only memory and random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0257] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0258] This application also provides a computer program product, including a computer program that, when executed, implements the above-described method.

[0259] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, implement the above-described method.

[0260] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as SRAM, EEPROM, EPROM, PROM, ROM, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0261] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside within an ASIC. Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0262] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0263] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0264] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0265] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0266] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0267] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

[0268] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A power supply early warning method for an inverter based on high-frequency resonance, characterized in that, include: Inject multiple micro-amplitude high-frequency excitation signals of different frequencies into the output terminal of the inverter; The response data of the plurality of micro-amplitude high-frequency excitation signals are obtained, and based on the response data, the high-frequency equivalent impedance drift coefficient of the inverter output side is obtained. The high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance of the inverter output side. Based on the high-frequency equivalent impedance drift coefficient, determine whether the inverter output side is in a high-frequency impedance change state; When the inverter output side is in a high-frequency impedance change state, the resonant characteristic fuzziness degradation coefficient of the inverter output side is obtained based on the response data. The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of resonant characteristic fuzziness degradation of the inverter output side. Based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonant characteristics, the frequency protection tripping trigger evaluation index of the inverter is determined. The frequency protection tripping trigger evaluation index is used to quantify the risk level of the inverter tripping due to the frequency protection mechanism. Based on the frequency protection trip trigger evaluation index, a protection trip warning signal is pushed.

2. The method according to claim 1, characterized in that, The response data includes: voltage response data and current response data at the output terminal of the inverter; The step of obtaining the high-frequency equivalent impedance drift coefficient of the inverter output side based on the response data includes: Based on the voltage response data and the current response data, obtain the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment; For each frequency, the residual impedance coefficient of the inverter output side at the current moment is calculated based on the instantaneous frequency impedance spectrum corresponding to the frequency. Based on the residual impedance coefficient corresponding to each frequency at the current moment, the time-frequency offset coefficient of the inverter output side at the current moment is calculated. The high-frequency equivalent impedance drift coefficient of the inverter output side is determined based on the time-frequency offset coefficient and the mean residual impedance. The mean residual impedance is obtained by averaging the residual impedance coefficients corresponding to each frequency.

3. The method according to claim 2, characterized in that, The step of obtaining the instantaneous frequency impedance spectrum of the inverter output side at each frequency at the current moment based on the voltage response data and the current response data includes: A bandpass filter is used to extract the high-frequency component of the output voltage corresponding to each frequency from the voltage response data, and the high-frequency component of the output current corresponding to each frequency is extracted from the current response data. For each frequency, the high-frequency part of the output voltage corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the voltage response intensity of the output voltage to the frequency at the current moment. The high-frequency part of the output current corresponding to the frequency is extracted using the continuous wavelet transform method to obtain the current response intensity of the output current to the frequency at the current moment. Based on the voltage response intensity and current response intensity corresponding to the frequency, the instantaneous frequency impedance spectrum of the inverter output side at the current moment corresponding to the frequency is obtained.

4. The method according to any one of claims 1 to 3, characterized in that, The step of determining whether the inverter output side is in a high-frequency impedance abrupt change state based on the high-frequency equivalent impedance drift coefficient includes: If the high-frequency equivalent impedance drift coefficient is greater than the preset drift threshold, then the inverter output side is determined to be in a high-frequency impedance abrupt change state. If the high-frequency equivalent impedance drift coefficient is less than or equal to the preset drift threshold, then it is determined that the inverter output side is not in a high-frequency impedance abrupt change state.

5. The method according to any one of claims 1 to 3, characterized in that, When the inverter output side is in a high-frequency impedance abrupt change state, based on the response data, the resonant characteristic fuzziness degradation coefficient of the inverter output side is obtained, including: If the inverter output side is in a high-frequency impedance change state, the spectrum peak extraction algorithm is used to identify the main resonant frequency of the response data and record the resonant response delay corresponding to each excitation signal application time. Calculate the frequency transition rate corresponding to each sampling interval based on the main resonant frequency; The mean and variance of the resonant response delay corresponding to the application time of multiple excitation signals within a preset time window are calculated respectively to obtain the first mean and the first variance. Based on the first mean and the first variance, the delay ambiguity factor of the inverter output side is calculated. The mean and variance of the frequency transition rates corresponding to multiple sampling intervals within a preset time window are calculated respectively to obtain the second mean and the second variance. Based on the second mean and the second variance, the frequency ambiguity factor of the inverter output side is calculated. The fuzzy degradation coefficient of the resonant characteristics on the output side of the inverter is calculated based on the delay fuzziness factor and the frequency fuzziness factor.

6. The method according to any one of claims 1 to 3, characterized in that, The step of determining the frequency protection tripping trigger evaluation index of the inverter based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonant characteristics includes: The frequency protection tripping trigger evaluation index of the inverter is obtained by weighted summation based on the high-frequency equivalent impedance drift coefficient, the first preset weight, the degree of fuzzy degradation of the resonance characteristics, and the second preset weight.

7. The method according to any one of claims 1 to 3, characterized in that, The step of pushing a protection trip warning signal based on the frequency protection trip trigger evaluation index includes: If a frequency protection trip trigger evaluation index exceeds the preset trigger evaluation index threshold, then multiple frequency protection trip trigger evaluation indices within the subsequent preset time period are obtained. The standard deviation of the multiple trigger evaluation indices is calculated, and when the standard deviation is greater than a preset standard deviation threshold, the protection trip warning signal is pushed.

8. The method according to claim 2 or 3, characterized in that, The step of calculating the residual impedance coefficient of the inverter output side at the current moment based on the instantaneous frequency impedance spectrum corresponding to the frequency includes: Based on the instantaneous frequency impedance spectrum corresponding to the stated frequency, the following formula is used: The residual impedance coefficient of the inverter output side at the current time corresponding to the frequency is calculated. Accordingly, the step of calculating the time-frequency offset coefficient of the inverter output side at the current moment based on the residual impedance coefficient corresponding to each frequency at the current moment includes: Based on the residual impedance coefficient corresponding to each frequency at the current moment, the formula is used: Hz=∑ f Rz(f,t)*log(Rz(f,t)) calculates the time-frequency offset coefficient of the inverter output side at the current moment; Where Rz(f,t) represents the residual impedance coefficient corresponding to frequency f at time t, Zk(f,t) represents the instantaneous frequency impedance spectrum corresponding to frequency f at time t, Zre(f,t) represents the historical reference impedance spectrum corresponding to frequency f at time t, and Hz represents the time-frequency offset coefficient of the inverter output side at the current time.

9. A power supply early warning device based on a high-frequency resonant inverter, characterized in that, include: An excitation injection module is used to inject multiple micro-amplitude high-frequency excitation signals with different frequencies into the output terminal of the inverter. The first acquisition module is used to acquire response data of the plurality of micro-amplitude high-frequency excitation signals, and based on the response data, acquire the high-frequency equivalent impedance drift coefficient of the inverter output side. The high-frequency equivalent impedance drift coefficient is used to quantify the degree of dynamic offset of the high-frequency impedance of the inverter output side. The first determining module is used to determine whether the inverter output side is in a high-frequency impedance change state based on the high-frequency equivalent impedance drift coefficient. The second acquisition module is used to acquire the resonant characteristic fuzziness degradation coefficient of the inverter output side based on the response data when the inverter output side is in a high-frequency impedance change state. The resonant characteristic fuzziness degradation coefficient is used to quantify the degree of resonant characteristic fuzziness degradation of the inverter output side. The second determining module is used to determine the frequency protection tripping trigger evaluation index of the inverter based on the high-frequency equivalent impedance drift coefficient and the degree of fuzzy degradation of the resonant characteristics. The frequency protection tripping trigger evaluation index is used to quantify the risk level of the inverter tripping due to the frequency protection mechanism. The push module is used to push a protection trip warning signal based on the frequency protection trip trigger evaluation index.

10. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

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