A method, system, device and medium for optimizing power quality of M3C output

Abstract

The present application belongs to the technical field of power quality optimization, and discloses an M3C output power quality optimization method, system, device and medium, which comprises the following steps: acquiring an M3C output side electric signal in real time and converting it into a sampling sequence, extracting a harmonic error signal from the sampling sequence by using an adaptive filtering algorithm, and dynamically adjusting the step factor of the adaptive filtering algorithm according to the error signal; based on the harmonic error signal, generating a harmonic compensation signal for each bridge arm by using a bridge arm phase coordination strategy and superimposing the harmonic compensation signal on the basic modulation wave of the corresponding bridge arm; converting the modulation wave of each bridge arm after compensation and superposition into a switching driving signal, and realizing harmonic cancellation at the M3C output end by using the spatial phase redundancy between the bridge arms; and using passive filtering technology to assist in filtering the residual high-frequency harmonics in the M3C output waveform after harmonic compensation, so as to realize the optimization of the M3C output power quality. The adaptive harmonic extraction and bridge arm phase coordination compensation mechanism are introduced to realize the optimization of the output power quality.

Description

Technical Field

[0001] This invention belongs to the field of power quality optimization technology, specifically relating to a method, system, device and medium for optimizing the output power quality of an M3C. Background Technology

[0002] The Modular Multilevel Matrix Converter (M3C) is a core power electronic device for implementing Fractional Frequency Transmission Systems (FFTS). The M3C employs a nine-bridge topology, consisting of multiple cascaded full-bridge submodules, enabling direct AC-AC power conversion between a power frequency AC system (50 Hz) and a low-frequency AC system (20 Hz) without an intermediate DC link. Because the M3C lacks a DC bus to decouple the AC systems on both sides, the electrical quantities on the power frequency and low-frequency sides are directly coupled within the converter, resulting in complex ripple components in the submodule capacitor voltages. These ripple voltages, after being modulated by the switching function, generate abundant harmonic components on the output side, including low-order harmonics (such as the 3rd, 5th, and 7th harmonics) and sideband harmonics near the switching frequency. This severely affects the output power quality and may even cause abnormal operation or malfunction of protection systems in offshore wind farms.

[0003] Currently, technical solutions for harmonic suppression in M3C mainly employ indirect harmonic mitigation strategies based on circulating current suppression, harmonic mitigation strategies based on carrier phase-shift modulation, and passive filtering strategies based on fixed-parameter filters. However, common methods suffer from the following drawbacks: 1. The harmonic extraction process suffers from slow dynamic response and limited accuracy. Traditional FFT methods exhibit significant detection errors under system frequency shifts or dynamic operating conditions, making it difficult to meet real-time control requirements.

[0004] 2. Harmonic suppression strategies lack adaptability. Existing solutions are mostly based on fixed parameters or fixed frequencies. When changes in the operating conditions of the M3C (such as changes in transmission power, frequency shifts on both sides, and submodule parameter drift) cause changes in harmonic distribution characteristics, the suppression effect decreases significantly.

[0005] 3. The control system is complex and computationally burdensome. Schemes involving multiple PR (proportional resonant) controllers in parallel and complex coordinate transformations increase the complexity of the control system and place high demands on the controller hardware performance.

[0006] 4. Harmonic suppression is tightly coupled with the main control circuit. In existing active compensation schemes, the harmonic suppression circuit and the fundamental power control circuit often share the modulation channel, making parameter tuning difficult and posing a significant risk of mutual interference. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a method, system, device, and medium for optimizing the output power quality of an M3C. By introducing an adaptive harmonic extraction and bridge arm phase collaborative compensation mechanism, the output power quality of the M3C is optimized.

[0008] This invention provides the following technical solution: The primary objective of this invention is to provide a method for optimizing the power quality of M3C output, comprising: The output electrical signal of the M3C is acquired in real time and converted into a sampling sequence. The harmonic error signal is extracted from the sampling sequence using an adaptive filtering algorithm. The step size factor of the adaptive filtering algorithm is dynamically adjusted according to the error signal. Based on the harmonic error signal, the harmonic compensation signal of each bridge arm is generated by the bridge arm phase coordination strategy, and the harmonic compensation signal of each bridge arm is superimposed on the basic modulation wave of the corresponding bridge arm. The modulated waves of each bridge arm after compensation superposition are converted into switching drive signals, and harmonic cancellation is achieved at the output of M3C by utilizing the spatial phase redundancy between the bridge arms. Passive filtering technology is used to assist in filtering out residual high-frequency harmonics in the output waveform of M3C after harmonic compensation, thereby optimizing the power quality of M3C output.

[0009] An adaptive filtering algorithm that dynamically adjusts the step size factor based on the error signal enables rapid and accurate extraction of the total harmonic error signal, overcoming the contradiction between the convergence speed and steady-state accuracy of the traditional fixed step size algorithm. At the same time, a bridge arm phase coordination strategy is used to generate a compensation signal to achieve harmonic spatial cancellation, achieving a significant harmonic suppression effect with a small amount of compensation injection.

[0010] Preferably, the step of extracting harmonic error signals from the sampled sequence using an adaptive filtering algorithm includes: At each sampling moment, a unit sine reference signal and a unit cosine reference signal synchronized with the fundamental frequency of the M3C output side are generated to form the reference signal vector at the current sampling moment; Based on the weight vector updated at the previous time step and the reference signal vector at the current sampling time, calculate the fundamental component at the current time step; The harmonic error signal at the current moment is obtained by subtracting the fundamental component at the current moment from the sampled value at the current moment. The step size factor at the current sampling time is calculated based on the nonlinear function of the harmonic error signal. The weight vector at the next sampling time is updated based on the reference signal vector, harmonic error signal, step size factor, and weight vector at the current time, so as to realize the real-time calculation of fundamental component and the real-time extraction of harmonic error signal.

[0011] The complex problem of full-band harmonic extraction is simplified to real-time estimation and differential stripping of the fundamental component, reducing the computational cost of the algorithm and avoiding the delay of whole-cycle sampling in the traditional FFT algorithm, thus realizing instantaneous and high dynamic response extraction of harmonic error signals.

[0012] Preferably, the formula for calculating the step size factor is:

[0013] in, For the first n The step size factor at each sampling time. For the first n Harmonic error signal at each sampling time, The shape parameter controls the steepness of the Sigmoid function. This is the step size scaling factor.

[0014] By introducing a Sigmoid nonlinear adaptive variable step size mechanism, a large step size can be used for fast tracking during initial convergence or sudden changes in operating conditions (such as sudden changes in wind power output), while the step size is automatically reduced in the steady state stage to improve detection accuracy. This allows the step size factor to be continuously and smoothly adjusted with the error signal, effectively improving the steady-state accuracy of harmonic extraction.

[0015] Preferably, the step of generating harmonic compensation signals for each bridge arm based on the harmonic error signal and according to the bridge arm phase coordination strategy includes: Based on the spatial symmetry of the M3C bridge arm topology, the phase distribution rules of the harmonic compensation signals of each bridge arm are determined. Based on the harmonic error signal and phase distribution rules, harmonic compensation signals for each bridge arm are generated.

[0016] Preferably, the phase distribution rule is used to determine the phase angle of the harmonic compensation signal of each bridge arm, wherein the phase angle of the harmonic compensation signal of each bridge arm is determined by superimposing the output phase reference phase and the input phase phase offset of the corresponding bridge arm, so that the harmonic compensation signal superimposed by each bridge arm forms a spatial cancellation effect on the output side.

[0017] By fully utilizing the spatial symmetry and phase redundancy of the M3C nine-arm topology and through specific phase allocation rules, the harmonic compensation components injected by each arm can cancel each other out when synthesized on the output side, thus achieving efficient harmonic suppression without increasing additional hardware costs.

[0018] As a preferred option, when generating the harmonic compensation signals for each bridge arm, a compensation gain coefficient is introduced to adjust the harmonic compensation signals.

[0019] Preferably, the compensation gain coefficient is dynamically adjusted based on the changing trend of the effective value of the harmonic error signal and the difference between the effective value of the harmonic error signal and the preset target threshold.

[0020] By constructing a closed-loop regulation mechanism based on the effective value of harmonic error signals, the compensation intensity can be dynamically adjusted according to the actual effect of harmonic suppression, avoiding overcompensation or undercompensation, and enhancing the robustness of the power system under different operating conditions.

[0021] The second objective of this invention is to provide an M3C output power quality optimization system for implementing the above-mentioned method, comprising: The adaptive harmonic extraction module is located on the low-frequency output side of the M3C and is configured to acquire the electrical signal on the output side of the M3C in real time and convert it into a sampling sequence, and use an adaptive filtering algorithm to extract the harmonic error signal from the sampling sequence. The bridge arm harmonic compensation control module, connected to the adaptive harmonic extraction module, is configured to generate harmonic compensation signals for each bridge arm using a bridge arm phase coordination strategy, and to superimpose the harmonic compensation signals of each bridge arm onto the basic modulation wave of the corresponding bridge arm. The output drive module is configured to convert the modulated waves of each bridge arm after compensation superposition into switching drive signals, and to achieve harmonic cancellation at the M3C output terminal by utilizing the spatial phase redundancy between the bridge arms. The passive filter module is connected in parallel to the AC bus on the low-frequency output side of the M3C to assist in filtering out residual high-frequency harmonics in the output waveform of the M3C after harmonic compensation, thereby optimizing the power quality of the M3C output.

[0022] A third objective of this invention is to provide an electronic device comprising at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the aforementioned method.

[0023] A fourth objective of this invention is to provide a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the above-described method.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows: An adaptive filtering algorithm that dynamically adjusts the step size factor based on the error signal enables rapid and accurate extraction of the total harmonic error signal, overcoming the contradiction between the convergence speed and steady-state accuracy of the traditional fixed step size algorithm. At the same time, a bridge arm phase coordination strategy is used to generate a compensation signal to achieve harmonic spatial cancellation, achieving a significant harmonic suppression effect with a small amount of compensation injection.

[0025] An adaptive filter based on a dynamically variable step size LMS algorithm using the sigmoid function is employed for harmonic extraction. The step size factor is adjusted in real time according to the error signal. A large step size is used in the initial convergence phase to accelerate convergence, while the step size is automatically reduced in the steady-state phase to improve accuracy. Compared with the traditional fixed step size LMS algorithm, the convergence speed is improved and the steady-state error is reduced. Compared with the FFT method, it does not require integer-cycle sampling and is insensitive to system frequency shifts.

[0026] Through a closed-loop adaptive adjustment mechanism for the compensation gain coefficient, the system can automatically adjust the compensation intensity according to the current harmonic distortion level. When the operating conditions of the M3C change (such as changes in transmission power leading to changes in harmonic characteristics), it can automatically adjust to the optimal compensation state without manual intervention.

[0027] Using the total harmonic error signal as the control target, it suppresses all harmonic components (including integer harmonics, interharmonics, subharmonics, etc.) in the output waveform as a whole, overcoming the limitation of traditional schemes that are designed only for specific harmonics and thus cannot suppress harmonics in other frequency bands, and has strong versatility.

[0028] By injecting harmonic compensation signals with specific phase relationships into each bridge arm, and utilizing the spatial cancellation effect of the M3C nine-bridge parallel topology, harmonic current / voltage can be mutually canceled at the output port, achieving significant harmonic suppression effect with a small amount of compensation injection. Attached Figure Description

[0029] Figure 1 A flowchart of an M3C output power quality optimization method provided by the present invention; Figure 2 A schematic diagram of the overall structure of an M3C output power quality optimization system provided by the present invention; Figure 3 This is a schematic diagram of the variable step size factor curve based on the Sigmoid function in this invention; Figure 4 This is a functional structure diagram of the bridge arm harmonic compensation control module in this invention; Figure 5 This is a flowchart illustrating the adaptive harmonic extraction algorithm in this invention. Figure 6 The current waveform spectrum obtained from the simulation experiment using the traditional method in Example 5; Figure 7 The current waveform spectrum obtained by simulation experiment using the method of the present invention in Example 5; Figure 8 The image shows a simulation diagram of the current waveform of the present invention and the conventional solution in Example 5. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] The present invention will now be described in further detail with reference to the accompanying drawings: Example 1: like Figure 1 As shown, this embodiment provides a method for optimizing the power quality of M3C output, including: The output electrical signal of the M3C is acquired in real time and converted into a sampling sequence. The harmonic error signal is extracted from the sampling sequence using an adaptive filtering algorithm. The step size factor of the adaptive filtering algorithm is dynamically adjusted according to the error signal. Based on the harmonic error signal, the harmonic compensation signal of each bridge arm is generated by the bridge arm phase coordination strategy, and the harmonic compensation signal of each bridge arm is superimposed on the basic modulation wave of the corresponding bridge arm. The modulated waves of each bridge arm after compensation superposition are converted into switching drive signals, and harmonic cancellation is achieved at the output of M3C by utilizing the spatial phase redundancy between the bridge arms. Passive filtering technology is used to assist in filtering out residual high-frequency harmonics in the output waveform of M3C after harmonic compensation, thereby optimizing the power quality of M3C output.

[0032] Specifically, the adaptive filtering algorithm is a dynamically variable step-size LMS algorithm based on the Sigmoid function; the process of extracting harmonic error signals using the adaptive filtering algorithm is as follows: Figure 5 As shown, it includes the following steps: In the n At each sampling time, the fundamental frequency of the M3C output side is generated. Synchronized unit sine reference signal and unit cosine reference signal , constitute the first n Reference signal vector at each sampling time ;in The sampling period; Calculate the first n The fundamental component at each sampling time , ;in For weight vectors, , These are the unit sine reference signals. and unit cosine reference signal The weights; Calculate the first n Harmonic error signal at each sampling time ; Calculate the first harmonic error signal using a nonlinear function (Sigmoid function). n Step size factor at each sampling time point ;in The shape parameter, which controls the steepness of the Sigmoid function, ranges from 0.1 to 2.0. The step size scaling factor ranges from 0.01 to 0.5; the variable step size factor curve based on the Sigmoid function is shown below. Figure 3 As shown; Update the weight vector at the next sampling time n+1 ; Repeat the above steps at each sampling time to achieve continuous real-time estimation of the fundamental component and extraction of harmonic errors.

[0033] Real-time fundamental component estimation can be achieved with only two weighting coefficients, requiring minimal computation and making it suitable for real-time operation in embedded controllers such as DSPs or FPGAs.

[0034] The generation of harmonic compensation signals includes: Based on the spatial symmetry of the M3C nine-arm topology, the phase distribution rules of the harmonic compensation signals of each arm are determined. Based on the harmonic error signal and phase distribution rules, harmonic compensation signals for each bridge arm are generated.

[0035] Specifically, the M3C nine-arm topology and compensation phase allocation relationship are as follows: Assuming the reference compensation phase of the corresponding arm on the low-frequency output side A of the M3C is 0°, the nine arms are divided into three groups according to the three phases on the output side (A, B, C). Within each group, three arms correspond to the three phases on the input side (U, V, W). j Phase angle of harmonic compensation signal Determine using the following formula:

[0036] in, For bridge arm j The reference phases corresponding to the output phases (phase A 0°, phase B -120°, phase C +120°). For bridge arm j The phase offset corresponds to the input phase (U phase 0°, V phase -120°, W phase +120°). This phase allocation rule enables the harmonic compensation components injected by each bridge arm to form a spatial cancellation effect when synthesized on the low-frequency output side, maximizing the harmonic suppression effect.

[0037] The formula for generating the harmonic compensation signal is:

[0038] in, For the first j Instantaneous values ​​of harmonic compensation voltage for each bridge arm; This represents the continuous-time form of the harmonic error signal; k This is the compensation gain coefficient; For the first j The compensation phase angle of each bridge arm is determined by the phase allocation rule mentioned above.

[0039] The generated harmonic compensation signals for each bridge arm are then superimposed in parallel onto the fundamental modulation wave of each bridge arm. By injecting harmonic compensation signals with specific phase relationships into each bridge arm, and utilizing the spatial cancellation effect of the M3C nine-bridge-arm parallel topology, harmonic current / voltage mutual cancellation is achieved at the output port, resulting in significant harmonic suppression with a relatively small compensation injection amount. The bridge arm compensation circuit and the main control circuit adopt a parallel superposition structure, minimizing the impact on the main control circuit and facilitating functional expansion within the existing M3C control system.

[0040] Compensation gain coefficient k The following rules will be dynamically adjusted:

[0041] in, For the current period (i.e., the th) n The effective value of the harmonic error signal at each sampling time; The preset target harmonic error effective value threshold; for and (The previous cycle is the first) n The difference between the effective values ​​of the harmonic error signal at -1 sampling time; The gain adjustment step size ranges from 0.001 to 0.01. This adjustment rule can adaptively adjust the compensation intensity according to the real-time changing trend of the harmonic suppression effect, avoiding overcompensation or undercompensation.

[0042] Furthermore, the method also includes frequency and phase synchronization steps, specifically including: In application scenarios where the low-frequency side of the M3C may experience frequency shift, a phase-locked loop (PLL) is used to track the fundamental frequency and phase of the low-frequency side in real time. The frequency output of the PLL is used to calculate the unit reference signal, and the phase output of the PLL is used to calculate the harmonic compensation signal, ensuring the accuracy of harmonic extraction and compensation when the frequency fluctuates.

[0043] Example 2: like Figure 2 As shown, this embodiment provides an M3C output power quality optimization system for implementing the method provided in Embodiment 1, including: The adaptive harmonic extraction module is located on the low-frequency output side of the M3C and is configured to acquire the electrical signal on the output side of the M3C in real time and convert it into a sampling sequence, and use an adaptive filtering algorithm to extract the harmonic error signal from the sampling sequence. The bridge arm harmonic compensation control module, connected to the adaptive harmonic extraction module, is configured to generate harmonic compensation signals for each bridge arm using a bridge arm phase coordination strategy, and to superimpose the harmonic compensation signals of each bridge arm onto the corresponding bridge arm's fundamental modulation wave; the functional structure of the bridge arm harmonic compensation control module is as follows: Figure 4 As shown; The adaptive adjustment module for compensation gain is connected to the adaptive harmonic extraction module and the bridge arm harmonic compensation control module. It is used to dynamically adjust the harmonic compensation gain coefficient according to the changing trend of the harmonic error signal to achieve closed-loop adaptive optimization. The output drive module is configured to convert the modulated waves of each bridge arm after compensation superposition into switching drive signals, and to achieve harmonic cancellation at the M3C output terminal by utilizing the spatial phase redundancy between the bridge arms. The passive filter module is connected in parallel to the AC bus on the low-frequency output side of the M3C to assist in filtering out residual high-frequency harmonics in the output waveform of the M3C after harmonic compensation, thereby optimizing the power quality of the M3C output.

[0044] Example 3: This embodiment provides an electronic device, including at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the program is executed by the processing unit, the processing unit performs the method provided in Embodiment 1.

[0045] Example 4: This embodiment provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the method provided in Embodiment 1.

[0046] Example 5: Simulation verification was conducted based on a 220kV, 400MW M3C. A single-phase short-circuit ground fault occurred on the M3C's power frequency grid side at 0.3s. From 0.4s to 0.8s, the conventional M3C control strategy was used; from 0.8s to 1.2s, the power quality optimization method proposed in this invention was employed. The simulated current waveform is shown below. Figure 8 As shown, the current waveform spectra of the conventional scheme and the method of the present invention are respectively as follows: Figure 6 , Figure 7 As shown in the figure, it can be seen that by adopting the power quality optimization method proposed in this invention, harmonic components in the current can be effectively suppressed.

[0047] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the power quality of M3C output, characterized in that, include: The output electrical signal of the M3C is acquired in real time and converted into a sampling sequence. The harmonic error signal is extracted from the sampling sequence using an adaptive filtering algorithm. The step size factor of the adaptive filtering algorithm is dynamically adjusted according to the error signal. Based on the harmonic error signal, the harmonic compensation signal of each bridge arm is generated by the bridge arm phase coordination strategy, and the harmonic compensation signal of each bridge arm is superimposed on the basic modulation wave of the corresponding bridge arm. The modulated waves of each bridge arm after compensation superposition are converted into switching drive signals, and harmonic cancellation is achieved at the output of M3C by utilizing the spatial phase redundancy between the bridge arms. Passive filtering technology is used to assist in filtering out residual high-frequency harmonics in the output waveform of M3C after harmonic compensation, thereby optimizing the power quality of M3C output.

2. The method according to claim 1, characterized in that, The method of extracting harmonic error signals from the sampled sequence using an adaptive filtering algorithm includes: At each sampling moment, a unit sine reference signal and a unit cosine reference signal synchronized with the fundamental frequency of the M3C output side are generated to form the reference signal vector at the current sampling moment; Based on the weight vector updated at the previous time step and the reference signal vector at the current sampling time, calculate the fundamental component at the current time step; The harmonic error signal at the current moment is obtained by subtracting the fundamental component at the current moment from the sampled value at the current moment. The step size factor at the current sampling time is calculated based on the nonlinear function of the harmonic error signal. The weight vector at the next sampling time is updated based on the reference signal vector, harmonic error signal, step size factor, and weight vector at the current time, so as to realize the real-time calculation of fundamental component and the real-time extraction of harmonic error signal.

3. The method according to claim 2, characterized in that, The formula for calculating the step size factor is: in, For the first n The step size factor at each sampling time. For the first n Harmonic error signal at each sampling time, The shape parameter controls the steepness of the Sigmoid function. This is the step size scaling factor.

4. The method according to claim 1, characterized in that, The generation of harmonic compensation signals for each bridge arm based on the harmonic error signal and according to the bridge arm phase coordination strategy includes: Based on the spatial symmetry of the M3C bridge arm topology, the phase distribution rules of the harmonic compensation signals of each bridge arm are determined. Based on the harmonic error signal and phase distribution rules, harmonic compensation signals for each bridge arm are generated.

5. The method according to claim 4, characterized in that, The phase distribution rule is used to determine the phase angle of the harmonic compensation signal of each bridge arm. The phase angle of the harmonic compensation signal of each bridge arm is determined by superimposing the output phase reference phase and the input phase phase offset of the corresponding bridge arm, so that the harmonic compensation signal superimposed by each bridge arm forms a spatial cancellation effect on the output side.

6. The method according to claim 1, characterized in that, When generating the harmonic compensation signals for each bridge arm, a compensation gain coefficient is introduced to adjust the harmonic compensation signals.

7. The method according to claim 6, characterized in that, The compensation gain coefficient is dynamically adjusted based on the changing trend of the effective value of the harmonic error signal and the difference between the effective value of the harmonic error signal and the preset target threshold.

8. An M3C output power quality optimization system, used to implement the method as described in any one of claims 1 to 7, characterized in that, include: The adaptive harmonic extraction module is located on the low-frequency output side of the M3C and is configured to acquire the electrical signal on the output side of the M3C in real time and convert it into a sampling sequence, and use an adaptive filtering algorithm to extract the harmonic error signal from the sampling sequence. The bridge arm harmonic compensation control module, connected to the adaptive harmonic extraction module, is configured to generate harmonic compensation signals for each bridge arm using a bridge arm phase coordination strategy, and to superimpose the harmonic compensation signals of each bridge arm onto the basic modulation wave of the corresponding bridge arm. The output drive module is configured to convert the modulated waves of each bridge arm after compensation superposition into switching drive signals, and to achieve harmonic cancellation at the M3C output terminal by utilizing the spatial phase redundancy between the bridge arms. The passive filter module is connected in parallel to the AC bus on the low-frequency output side of the M3C to assist in filtering out residual high-frequency harmonics in the output waveform of the M3C after harmonic compensation, thereby optimizing the power quality of the M3C output.

9. An electronic device, characterized in that, It includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program that, when executed by the processing unit, causes the processing unit to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the method as described in any one of claims 1 to 7.

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