High-voltage direct-connected multi-source energy system and frequency domain harmonic separation and suppression method

Abstract

This invention belongs to the field of power electronics technology, specifically relating to a high-voltage direct-connected multi-source energy system and a frequency domain harmonic separation and suppression method. The method first acquires grid voltage, grid-connected current, and submodule capacitor voltage; then, it uses an adaptive variational mode decomposition algorithm to perform frequency domain separation of the signals; based on instantaneous frequency, volatility, and energy concentration, it dynamically classifies the mode functions and calculates their confidence levels; based on the classification results, it generates targeted harmonic suppression commands, which are then combined with the fundamental frequency command to form a total voltage reference command; in carrier phase-shift modulation, the carrier phase is dynamically adjusted according to the submodule capacitor voltage deviation to achieve voltage balance; finally, based on the grid-connected current harmonic distortion rate, DC voltage ripple, and voltage imbalance, the control parameters are adaptively optimized online. This invention solves the conflict between broadband harmonic suppression and module voltage stability in high-voltage direct-connected systems, improving power quality and operational reliability under all operating conditions.

Description

Technical Field

[0001] This invention belongs to the field of electronic power technology, specifically relating to a high-voltage direct-connected multi-source energy system and a frequency domain harmonic separation and suppression method. Background Technology

[0002] Currently, integrated photovoltaic (PV), energy storage, and charging infrastructure (V2G) systems are becoming a key component of the energy transition. Traditional solutions typically use low-voltage (e.g., 0.4kV) DC power from PV, energy storage batteries, and charging piles, then connect it to the medium-voltage distribution network (e.g., 10kV / 35kV) via a large-capacity power frequency step-up transformer. Regarding harmonic suppression, mainstream technologies focus on low-order harmonic mitigation, primarily employing phase-locked loops (PLLs) and proportional resonant controllers based on a synchronous rotating coordinate system (dq axis), combined with passive LC or LCL filters. For multi-level high-voltage grid connection, modular multilevel converters (MMCs) or cascaded H-bridge topologies are commonly used, supplemented by carrier phase-shift pulse width modulation (CPPWM) technology to increase the equivalent switching frequency and improve output waveform quality. Furthermore, for specific resonant points, existing technologies employ active damping methods such as capacitor current feedback on the inverter side to enhance system stability.

[0003] However, existing technologies introduce significant iron and copper losses into the power frequency transformer, resulting in low overall system efficiency and increased size, cost, and maintenance burden. Regarding harmonic mitigation, traditional methods struggle to address wide-band harmonic issues under complex operating conditions: dq-axis-based controllers have limited ability to suppress high-frequency harmonics; while passive filters, when suppressing high-frequency harmonics (e.g., above 2kHz), are often bulky and may introduce new resonance risks. More importantly, under severe multi-source power disturbances, high- and low-frequency harmonic components easily couple and amplify each other in the control system, rendering existing decoupling control strategies ineffective. Furthermore, in multi-level systems implementing high-frequency harmonic suppression, there is a conflict between the equalization control of submodule capacitor voltages and the system's dynamic performance, potentially leading to voltage instability. Summary of the Invention

[0004] The purpose of this invention is to provide a high-voltage direct-connected multi-source energy system and a frequency domain harmonic separation and suppression method to solve the technical problems of high-voltage direct-connected multi-source energy systems, such as the difficulty in suppressing the mutual coupling of high and low frequency harmonics under complex power disturbances, and the conflict between harmonic suppression and module voltage balancing in multi-level topologies, which leads to a decrease in system stability.

[0005] The present invention achieves the above objectives through the following technical solutions: Firstly, this invention proposes a frequency domain harmonic separation and suppression method, applied to a converter system containing multiphase cascaded H-bridge power submodules, the method comprising: Real-time acquisition of grid voltage, grid-connected current, DC bus voltage, and capacitor voltage of each submodule at the power grid point; Based on the improved variational mode decomposition algorithm, the signals of the grid voltage and grid-connected current are separated in real time in the frequency domain to obtain multiple intrinsic mode functions; Instantaneous frequency features are extracted from each intrinsic mode function, and the mode functions are classified according to the instantaneous frequency features; Based on the classification results, harmonic suppression commands for different frequency bands are generated respectively, and the total voltage reference command is determined according to the harmonic suppression command and the fundamental voltage command. In response to the total voltage reference command, a carrier phase-shift modulation algorithm is used to generate PWM drive signals for each sub-module; Based on the real-time deviation of the capacitor voltage of each submodule, the carrier phase shift angle of the carrier phase shift modulation algorithm is dynamically adjusted to achieve active equalization of the capacitor voltage.

[0006] Furthermore, the improved variational mode decomposition algorithm performs real-time frequency domain separation on the grid voltage and grid-connected current signals to obtain multiple intrinsic mode functions, including: Based on the time-domain signals of the grid voltage and grid-connected current, corresponding variational mode decomposition models are established respectively. The models decompose each signal into multiple narrowband eigenmode functions through a constrained variational optimization framework. Based on the spectral characteristics of the grid voltage signal and the degree of harmonic distortion of the grid-connected current, the total number of modes K required for each signal decomposition is determined; Based on the determined total number of modes K, the constrained variational optimization problem for each signal is constructed and solved to obtain the K eigenmode functions corresponding to each signal.

[0007] Furthermore, the extraction of instantaneous frequency features from each intrinsic mode function includes: Perform a Hilbert transform on each intrinsic mode function to obtain the corresponding analytic signal; Extract the instantaneous amplitude and instantaneous phase from the analyzed signal; The instantaneous frequency is obtained by differentiating the instantaneous phase.

[0008] Furthermore, classifying the modal functions based on the instantaneous frequency characteristics includes: For each intrinsic mode function, the frequency fluctuation rate ζ is calculated based on its instantaneous frequency time series, including the following equation: ; in, The standard deviation of instantaneous frequency. The average instantaneous frequency; According to the frequency volatility And the energy concentration η of the intrinsic mode function, determine the frequency boundary threshold [f] for classification. low, f high The energy concentration η is defined as the intrinsic mode function at its center frequency f. c The proportion of energy within the preset bandwidth Δf centered on the total energy; The intrinsic mode functions are initially classified based on the determined frequency boundary threshold for classification. Based on the ratio k of the instantaneous amplitude A of the intrinsic mode function to the current operating power P of the system, the confidence level λ = f(k, ζ) of the classification result is calculated, where λ∈ (0, 1]; Output the class label and its corresponding confidence level λ for each intrinsic mode function.

[0009] Furthermore, the frequency boundary threshold for determining the classification is obtained by the following formula: ; ; in, and The reference frequency boundary threshold, Adjustment amount for the boundary; The confidence level λ is obtained by the following formula: ; in, and This is the adjustment coefficient.

[0010] Furthermore, based on the classification results, harmonic suppression commands for different frequency bands are generated, including: For intrinsic mode functions classified as low-frequency harmonic components and with a confidence level λ greater than a preset threshold, corresponding low-frequency harmonic compensation current command components are generated based on their instantaneous amplitude and instantaneous frequency: For the eigenmode functions classified as high-frequency switching harmonic components, the corresponding high-frequency harmonic suppression current command components are generated based on their instantaneous amplitude and instantaneous frequency: The total harmonic suppression command is obtained by summing all harmonic suppression current command components.

[0011] Furthermore, the step of determining the total voltage reference command based on the harmonic suppression command and the fundamental voltage command includes: The fundamental positive sequence component of the grid voltage signal is extracted and phase-locked to obtain the grid synchronization angle; Based on the aforementioned synchronization angle, the system's active power reference value and reactive power reference value are converted into the fundamental current reference value in the synchronous rotating coordinate system. The fundamental current reference value is compared with the component of the grid-connected current in the synchronous rotating coordinate system, and the fundamental voltage command is calculated by the current loop controller. The total harmonic suppression command is converted into a voltage command component in a synchronous rotating coordinate system, and then superimposed with the fundamental voltage command to obtain the total voltage reference command.

[0012] Furthermore, the step of dynamically adjusting the carrier phase shift angle of the carrier phase shift modulation algorithm based on the real-time deviation of the capacitor voltage of each submodule includes: Calculate the deviation between the capacitor voltage of the i-th submodule in each phase and the average capacitor voltage within the phase; Based on the voltage deviation, the carrier phase adjustment amount of this submodule is calculated using a nonlinear adjustment function; The calculated phase adjustment is superimposed on the reference carrier phase of the submodule to generate the final PWM drive signal.

[0013] Furthermore, the method also includes adaptively adjusting the variational mode decomposition parameters and controller gain parameters based on real-time calculated total harmonic distortion of the grid-connected current, DC bus voltage ripple, and submodule voltage imbalance, specifically: Real-time calculation of total harmonic distortion rate of grid-connected current, DC bus voltage ripple coefficient, and submodule capacitor voltage imbalance. Based on the aforementioned performance indicators, dynamically adjust the variational mode decomposition parameters, harmonic compensation gain, and voltage equalization control parameters; When any performance indicator exceeds the preset threshold, the corresponding protection strategy is triggered and the control parameters are re-optimized.

[0014] Secondly, this invention proposes a high-voltage direct-connected multi-source energy system, applied to integrated photovoltaic, energy storage, and charging scenarios connected to a medium-voltage power distribution network. The system includes: The cascaded H-bridge power conversion unit contains multiple cascaded H-bridge power sub-modules, each sub-module including a full-bridge circuit and a DC support capacitor; The signal acquisition unit is used to acquire grid voltage, grid-connected current, DC bus voltage and capacitor voltage of each submodule in real time. The harmonic separation unit is used to perform real-time frequency domain separation of the grid voltage and grid-connected current signals based on an improved variational mode decomposition algorithm to obtain multiple intrinsic mode functions; The initial classification unit is used to extract instantaneous frequency features from each intrinsic mode function and classify the mode functions according to the instantaneous frequency features; The collaborative control unit is used to generate harmonic suppression commands for different frequency bands based on the classification results, and to determine the total voltage reference command based on the harmonic suppression command and the fundamental voltage command. The modulation execution unit is used to generate PWM drive signals for each submodule in response to the total voltage reference command using a carrier phase-shift modulation algorithm; and dynamically adjust the carrier phase-shift angle of the carrier phase-shift modulation algorithm according to the real-time deviation of the capacitor voltage of each submodule to achieve active equalization of the capacitor voltage. The power submodule's drive end is connected to the modulation execution unit, its AC side is connected in series and directly connected to the medium-voltage distribution network, and its DC side is connected to the DC bus.

[0015] The beneficial effects of this invention are as follows: This invention utilizes an improved adaptive variational mode decomposition algorithm to effectively separate low-order harmonics and high-frequency switching harmonics coupled in grid voltage and grid-connected current, solving the problem of traditional methods struggling to handle wide-band harmonic aliasing. A classification mechanism based on frequency volatility and energy concentration is introduced, assigning confidence levels to each harmonic component, thus improving the accuracy and reliability of subsequent suppression commands. At the modulation level, the total voltage reference command required for harmonic suppression is combined with dynamic carrier phase-shift control based on submodule capacitor voltage deviation. This actively maintains the internal voltage balance of the multi-level system while achieving harmonic suppression, fundamentally avoiding conflicts between the two control objectives. Furthermore, through closed-loop performance monitoring and online adaptive parameter adjustment, the system can adapt to various disturbance conditions such as photovoltaic fluctuations, energy storage charging and discharging, and V2G access, significantly improving the operational stability and power quality of the high-voltage direct-connected photovoltaic-energy storage-charging integrated system under all operating conditions. Attached Figure Description

[0016] Figure 1 This is a flowchart of a frequency domain harmonic separation and suppression method proposed in an embodiment of the present invention; Figure 2 This is another flowchart of the frequency domain harmonic separation and suppression method proposed in the embodiments of the present invention; Figure 3 This is a system block diagram of a high-voltage direct-connected multi-source energy system proposed in an embodiment of the present invention. Detailed Implementation

[0017] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0018] Please see Figures 1-2This disclosure proposes a frequency domain harmonic separation and suppression method in a specific embodiment, which is applied to a converter system containing a multi-phase cascaded H-bridge power submodule. The system is mainly used to collect DC power generated by photovoltaic, energy storage battery packs and V2G charging piles to a common DC bus, and directly convert it into medium-voltage AC power through the cascaded H-bridge converter and connect it to the distribution network, eliminating the need for a traditional step-up transformer, thereby improving the overall efficiency of the system.

[0019] Specifically, the method includes the following steps: S1: Real-time acquisition of grid voltage, grid-connected current, DC bus voltage, and capacitor voltage of each submodule at the power grid point.

[0020] The acquisition of grid voltage and grid-connected current is used for harmonic analysis and control command calculation; the acquisition of DC bus voltage is used to monitor the system power balance; and the acquisition of capacitor voltages of each submodule is used for capacitor voltage equalization control of the multi-level system. The acquisition process is completed through high-precision voltage / current sensors and synchronous analog-to-digital converters, with a sampling frequency of no less than twice the system switching frequency to ensure that major high-frequency harmonic components, including the switching frequency and its sidebands, can be captured.

[0021] S2: Based on the improved variational mode decomposition algorithm, the signals of grid voltage and grid-connected current are separated in real time in the frequency domain to obtain multiple intrinsic mode functions.

[0022] In a preferred embodiment, step S2 specifically includes: S201: Based on the time-domain signals of grid voltage and grid-connected current, establish corresponding variational mode decomposition models. The models decompose each signal into multiple narrowband eigenmode functions through a constrained variational optimization framework.

[0023] Specifically, the variational mode decomposition model finds K mode functions by solving the following constrained variational problem. and its corresponding center frequency Including the following formulas: ; The constraints are: ,in This indicates the input grid voltage or grid-connected current signal. This indicates taking the derivative with respect to time t. It is the Dirac delta function. It is the imaginary unit. This represents the convolution operation. The optimization objective aims to minimize the sum of the estimated bandwidths of all modalities, thereby ensuring that each... It revolves around the center frequency Narrowband signal.

[0024] S202: Based on the spectral characteristics of the grid voltage signal and the degree of harmonic distortion of the grid-connected current, determine the total number of modes K required for each signal decomposition; Specifically, a Fast Fourier Transform or Short-Time Fourier Transform is performed on the grid voltage signal to analyze the number N of significant peaks (exceeding a preset amplitude threshold) in its spectrum; simultaneously, the total harmonic distortion rate of the grid-connected current within one fundamental frequency cycle is calculated. The total number of modes K is determined by the following formula: ; in, This is the number of fundamental modes (usually set to 2 in this implementation scenario, corresponding to the positive and negative sequence components of the fundamental wave). These are the weighting coefficients for the peak values ​​of the voltage spectrum. The number of significant peaks in the grid voltage spectrum. These are the weighting coefficients for current harmonic distortion. The range of values ​​for these weighting coefficients can be determined experimentally based on the actual system characteristics. This is the floor function.

[0025] S203: Based on the determined total number of modes K, construct and solve the constrained variational optimization problem for each signal to obtain the K eigenmode functions corresponding to each signal.

[0026] The above solution process employs an iterative approach using the augmented Lagrangian function and alternating direction multiplier method. In each iteration, the modal functions are updated alternately. and its center frequency This continues until the convergence condition is met (e.g., the modal function update is less than a threshold or the maximum number of iterations is reached). The final output is the signal. The K eigenmode functions obtained from the decomposition .

[0027] Specifically, the improved variational mode decomposition algorithm is based on the core principle of adaptively decomposing a complex, non-stationary, and nonlinear signal into a series of narrowband eigenmode functions with specific center frequencies through a constrained variational optimization framework. In this disclosure, the total number of modes K and the penalty factor α are adaptively adjusted according to the time-frequency characteristics of the signal to adapt to different operating conditions of the system, such as steady state to sudden power changes.

[0028] Specifically, the determination of the total number of modes K takes into account the total harmonic distortion rate and power change rate of the current grid-connected current of the system, so that more modes can be decomposed in dynamic processes with high harmonic content or rapid power change to finely characterize the harmonic spectrum, while the number of modes is reduced in steady state to reduce the computational burden.

[0029] S3: Extract instantaneous frequency features from each intrinsic mode function, and classify the mode functions based on the instantaneous frequency features.

[0030] Specifically, the instantaneous frequency features are extracted by performing a Hilbert transform on each intrinsic mode function. The transformed signal is then used to calculate the instantaneous amplitude and instantaneous phase of the mode. The instantaneous frequency is obtained by differentiating the instantaneous phase.

[0031] In a preferred embodiment, step S3, extracting instantaneous frequency features from each intrinsic mode function, includes: performing a Hilbert transform on each intrinsic mode function to obtain the corresponding analytic signal; extracting the instantaneous amplitude and instantaneous phase from the analytic signal; and differentiating the instantaneous phase to obtain the instantaneous frequency.

[0032] In a preferred embodiment, step S3, classifying the modal functions based on instantaneous frequency characteristics, includes: S301: For each intrinsic mode function, calculate the frequency fluctuation rate ζ based on its instantaneous frequency time series, including the following formula: ; in, The standard deviation of instantaneous frequency. The average instantaneous frequency; Specifically, for an instantaneous frequency sequence of length N... Its mean and standard deviation The calculations are as follows: ; ; The value of the frequency fluctuation rate ζ reflects the stability of the mode frequency. The smaller ζ is, the more stable the frequency of the component is, and the more likely it is a definite harmonic or interharmonic. The larger ζ is, the more likely it is a transient disturbance or noise.

[0033] S302: Based on frequency volatility And the energy concentration η of the intrinsic mode function, determine the frequency boundary threshold [f] for classification. low , f high The energy concentration η is defined as the intrinsic mode function at its center frequency f. c The proportion of energy within the preset bandwidth Δf centered on the total energy; Center frequency f c It can be approximated by the mean value f of the instantaneous frequency of this mode. The energy concentration η is calculated as follows: ; in, for Fourier transform, For the sampling frequency, the closer the energy concentration η is to 1, the more concentrated the energy of that mode is at f. cWithin the narrow band centered on the signal, the signal purity is higher.

[0034] S303: Perform initial classification of intrinsic mode functions based on the determined frequency boundary threshold for classification; In a preferred embodiment, the frequency boundary threshold for classification is determined by the following formula: ; ; in, and This serves as the reference frequency boundary threshold, and its value can be determined based on historical system data, industry standards, or actual operating experience. For example, in power systems, for common harmonic problems, it can be initially set based on the known harmonic frequency distribution range. and . This is a boundary adjustment amount, and its value can be determined based on the signal's frequency resolution or actual requirements. For example, if the signal has a high frequency resolution, A smaller value can be chosen; if greater flexibility is required regarding the classification boundary, You can choose a slightly larger size.

[0035] Specifically, the initial classification is based on the following preset reference frequency boundary thresholds: If f c < If so, it is temporarily classified as a low-frequency harmonic component (mainly considering subsynchronous and low-order harmonics). like <f c And f c < If so, it is temporarily classified as a mid-frequency resonant component (mainly considering the area near the resonant frequency of the LC or LCL filter). If f c > Then it is temporarily classified as a high-frequency switching harmonic component (mainly considering the switching frequency and its sideband).

[0036] S304: Calculate the confidence level λ = f(k, ζ) of the classification result based on the ratio k of the instantaneous amplitude A of the intrinsic mode function to the current operating power P of the system, where λ∈ (0, 1]; In a preferred embodiment, the confidence level λ is obtained by the following formula: ; Where k is the relative amplitude, defined as k = A / P, A is the root mean square value of the instantaneous amplitude of the intrinsic mode function, and P is the total active power output of the system at present. and The range or method for determining the adjustment coefficient can be established through experimentation or simulation. For example, an initial set of values ​​can be set first, and then adjusted continuously. and Observe the changes in classification results and confidence levels, and select the value that best achieves the classification effect.

[0037] S305: Output the class label and corresponding confidence level λ for each intrinsic mode function.

[0038] This disclosure classifies modal functions based on instantaneous frequency characteristics. The aim is to categorize wide-spectrum harmonic components into different categories according to frequency range, enabling the adoption of differentiated suppression strategies. In this embodiment, the classification rules are primarily based on preset frequency boundary thresholds. To further improve classification accuracy, this embodiment introduces an adaptive classification strategy. This strategy considers not only instantaneous frequency but also the frequency stability (such as frequency volatility) and energy concentration of the modal functions, dynamically adjusting the classification boundary thresholds. This allows for more accurate differentiation of low-frequency background harmonics, mid-frequency resonant components, and high-frequency switching harmonics generated by converter switching operations.

[0039] S4: Based on the classification results, generate harmonic suppression commands for different frequency bands respectively, and determine the total voltage reference command according to the harmonic suppression command and the fundamental voltage command.

[0040] For the low-frequency harmonic components identified through classification, corresponding low-frequency harmonic compensation commands are generated. These commands achieve closed-loop cancellation of low-frequency harmonics by injecting components with amplitudes proportional to and phase opposite to the detected low-frequency harmonics into the current loop. For high-frequency switching harmonic components, high-frequency harmonic suppression commands are generated. These commands are typically designed as feedback or feedforward signals with appropriate attenuation characteristics to actively dampen high-frequency resonant paths.

[0041] In a preferred embodiment, in step S4, based on the classification results, harmonic suppression instructions for different frequency bands are generated, including: S401: For intrinsic mode functions that are classified as low-frequency harmonic components and whose confidence level λ is greater than a preset threshold, generate corresponding low-frequency harmonic compensation current command components based on their instantaneous amplitude and instantaneous frequency. Specifically, for the k-th low-frequency harmonic mode, its compensation current command component i1(t) is designed to be equal to its instantaneous amplitude A. k (t) are proportional and have opposite phases to achieve cancellation. A preferred generation method is: ; in, The compensation gain coefficient is related to the harmonic order. The value of is related to the center frequency of the harmonic. For example, different gain values ​​can be used for the 5th harmonic (250Hz) and the 7th harmonic (350Hz). The specific value can be determined by offline simulation or online self-tuning. The initial phase is determined based on the phase relationship between the harmonic component and the fundamental frequency, as well as the system control delay. Confidence level. It is used as a feedforward gain to dynamically adjust the compensation strength, reducing the compensation when the confidence level is low to avoid false amplification.

[0042] S402: For the intrinsic mode function classified as a high-frequency switching harmonic component, generate the corresponding high-frequency harmonic suppression current command component based on its instantaneous amplitude and instantaneous frequency; For high-frequency switching harmonics, the suppression command aims to provide active damping. A preferred generation method is to construct a suppression signal with attenuation characteristics: ; in, This is the suppression gain coefficient; The decay time constant is used to control the decay rate of the suppressed signal. Its reciprocal determines the duration of the suppression effect. It can be selected according to the transient characteristics of the switching frequency and its sideband harmonics. For example, the value can be several times the time constant corresponding to the switching frequency. This is the starting time at which the high-frequency harmonic component was identified. This is the phase compensation amount. It is achieved by introducing an exponential decay term. This allows the suppression command to weaken over time after it is generated, avoiding stability issues that may be caused by continuous injection.

[0043] S403: Sum all harmonic suppression current command components to obtain the total harmonic suppression command.

[0044] The total harmonic suppression command i3(t) is composed of the superposition of all low-frequency compensation components and high-frequency suppression components, as shown in the following equation: ; In a preferred embodiment, step S4, determining the total voltage reference command based on the harmonic suppression command and the fundamental voltage command, includes: S404: Extract the fundamental positive sequence component of the grid voltage signal and perform phase-locking to obtain the grid synchronization angle; Specifically, a phase-locked loop based on a second-order generalized integrator or a delay signal cancellation method is used to extract the fundamental positive-sequence component from the grid voltage signal and track its phase in order to obtain a rotating coordinate system reference angle synchronized with the grid voltage fundamental.

[0045] S405: Based on the synchronization angle, convert the system active power reference value and reactive power reference value into the fundamental current reference value in the synchronous rotating coordinate system; S406: Compare the fundamental current reference value with the grid-connected current component in the synchronous rotating coordinate system, and calculate the fundamental voltage command through the current loop controller; S407: Convert the total harmonic suppression command into a voltage command component in a synchronous rotating coordinate system, and superimpose it with the fundamental voltage command to obtain the total voltage reference command.

[0046] It should be noted that the fundamental voltage command is generated by the system-level power control loop. Specifically, firstly, the acquired grid voltage is phase-locked to obtain the grid fundamental synchronization phase; then, based on the active and reactive power reference values ​​issued by the upper-level energy management system, the fundamental current reference value is calculated by the power outer loop controller; finally, the fundamental current reference value is compared with the fundamental component in the measured grid-connected current by the current inner loop controller to generate the fundamental voltage command used to track the power command.

[0047] The harmonic suppression command is converted into a voltage command form and then vector-superimposed with the fundamental voltage command in a synchronously rotating coordinate system to finally synthesize the total voltage reference command.

[0048] S5: In response to the total voltage reference command, the PWM drive signal for each submodule is generated using a carrier phase-shift modulation algorithm.

[0049] In this step, the total voltage reference command is used as the modulation wave, and a triangular carrier wave is assigned to each H-bridge submodule in each phase. The carrier phases of adjacent submodules are successively offset by a fixed angle (for example, if there are N submodules in a phase, the phase offset is 2π / N). By comparing the modulation wave with the carrier wave corresponding to each submodule, a series of PWM pulses are generated. These pulses are amplified by the drive circuit and used to control the on / off state of the power switching devices in the corresponding submodules.

[0050] S6: Based on the real-time deviation of the capacitor voltage of each submodule, dynamically adjust the carrier phase shift angle of the carrier phase shift modulation algorithm to achieve active equalization of the capacitor voltage.

[0051] Due to differences in circuit parameters and uneven switching losses, the DC capacitor voltages of the submodules in a cascaded H-bridge may become unbalanced during operation. To achieve active balancing, this step introduces a dynamic phase adjustment mechanism based on standard carrier phase-shift modulation. Specifically, the deviation between the capacitor voltage of each submodule and the average capacitor voltage of that phase is calculated in real time. Based on this deviation, a preset nonlinear adjustment function is used to calculate the fine-tuning amount of the carrier phase for that submodule. This fine-tuning amount is superimposed on its original reference carrier phase, thereby changing the duty cycle of that submodule within one fundamental cycle, ultimately achieving a redistribution of capacitor charge and bringing the capacitor voltages of all submodules closer to uniformity. This balancing process occurs simultaneously with harmonic suppression and power transfer processes without interference.

[0052] In this disclosure, through the above steps S1-S6, the method of the present invention can effectively suppress wide-band harmonics from low frequency to high frequency while realizing high-voltage direct grid connection and power transmission, and ensure the stable operation of sub-modules within the multi-level system.

[0053] In a preferred embodiment, step S6 includes: S601: Calculate the deviation between the capacitor voltage of the i-th submodule in each phase and the average capacitor voltage within the phase. ; S602: Calculate the carrier phase adjustment amount of this submodule based on the voltage deviation using a nonlinear adjustment function; Specifically, the carrier phase adjustment is calculated using a nonlinear function. As shown in the following formula: ; in, This is the proportionality coefficient. This is for voltage deviation, used to control the adjustment intensity. Let P be the sign function and P be the exponential factor. By taking P>1 or P<1, we can achieve accelerated adjustment for large deviations or smooth adjustment for small deviations, respectively.

[0054] S603: The calculated phase adjustment amount is superimposed on the reference carrier phase of this submodule to generate the final PWM drive signal.

[0055] Let the reference carrier phase of the i-th submodule in standard CPS-SPWM be . The adjusted carrier phase is The phase-adjusted carrier wave is compared with the corresponding modulated wave to generate the final PWM signal used to drive the power switching devices of this submodule. This process indirectly adjusts the width of the output pulse by fine-tuning the turn-on timing of each submodule, thereby controlling the capacitor charging / discharging process and ultimately achieving voltage balance.

[0056] In a preferred embodiment, the method further includes adaptively adjusting the variational mode decomposition parameters and controller gain parameters based on real-time calculated total harmonic distortion of the grid-connected current, DC bus voltage ripple, and submodule voltage imbalance, specifically: Real-time calculation of total harmonic distortion rate of grid-connected current The system monitors the DC bus voltage ripple coefficient and the submodule capacitor voltage imbalance. Based on performance indicators, it dynamically adjusts the variational mode decomposition parameters, harmonic compensation gain, and voltage equalization control parameters. When any performance indicator exceeds a preset threshold, the system triggers the corresponding protection strategy and re-optimizes the control parameters.

[0057] For example, when the harmonic content of the grid-connected current is high, the penalty factor of the variational mode decomposition algorithm is adaptively increased to improve the precision of harmonic frequency separation; when the harmonic suppression effect is not as expected and the capacitor voltage imbalance increases, the gain of the harmonic compensation command is appropriately reduced to alleviate the control conflict between harmonic suppression and voltage balancing; if the capacitor voltage imbalance remains high, the adjustment strength of the voltage balancing loop is enhanced. When any performance index exceeds the preset safety threshold, the system will trigger the corresponding protection mechanism and start the parameter re-optimization process, readjusting the relevant parameters according to the preset performance objective function until all performance indexes are restored to an acceptable range.

[0058] According to the above embodiments, this disclosure achieves the separation of complex and coupled broadband harmonic components in grid voltage and grid-connected current through an improved variational mode decomposition algorithm that adaptively adjusts the total number of modes K and the penalty factor α based on operating conditions (such as THD and power change rate). Secondly, a classification mechanism integrating frequency fluctuation rate and energy concentration is introduced to assign a category label and confidence level to each separated harmonic mode, generating adjustable and differentiated low-frequency harmonic compensation commands and high-frequency damping suppression commands. Crucially, after fusing the total harmonic suppression command and the fundamental power control command into a total voltage reference command in a synchronous rotating coordinate system, the real-time deviation of the capacitor voltage of each submodule is mapped to a dynamic adjustment amount of the carrier phase through a nonlinear function in the carrier phase-shift modulation stage. This design enables the high-performance modulation required for harmonic suppression and the capacitor voltage balance necessary for maintaining system stability to be achieved in the same modulation process, fundamentally resolving the control conflict between the two in traditional schemes. Finally, by continuously monitoring the grid-connected current THD, DC bus voltage ripple, and capacitor voltage imbalance, the VMD parameters, harmonic compensation gain, and equalization control strength are dynamically adjusted based on this feedback.

[0059] Please see Figure 3 Based on the same inventive concept, another specific embodiment of this disclosure proposes a high-voltage direct-connected multi-source energy system, which is applied to a photovoltaic, energy storage and charging integrated scenario connected to a medium-voltage distribution network. The system includes a cascaded H-bridge power conversion unit, a signal acquisition unit, a harmonic separation unit, a preliminary classification unit, a collaborative control unit and a modulation execution unit.

[0060] The system collects DC power from the photovoltaic array, energy storage battery pack and V2G charging pile via a DC bus, and directly inverts it into medium-voltage AC power via the cascaded H-bridge power conversion unit, without the need for a traditional power frequency step-up transformer, thereby significantly improving overall energy efficiency.

[0061] The cascaded H-bridge power conversion unit contains multiple cascaded H-bridge power sub-modules, each of which includes a full-bridge circuit and a DC support capacitor.

[0062] Specifically, the H-bridge power submodule can be constructed using fully controllable power semiconductor devices such as IGBTs or SiC MOSFETs to form a full-bridge circuit. A parallel support capacitor on its DC side is used to maintain DC voltage stability and buffer power ripple. The AC output terminals of multiple submodules are connected in series to form a single-phase bridge arm. The three-phase bridge arms are connected in a star or delta configuration to form the converter main circuit, and its output terminal is directly connected to the medium-voltage distribution network. This topology, through multi-level superposition technology, can achieve high-quality high-voltage sinusoidal wave output at relatively low device switching frequencies and possesses excellent fault tolerance and redundancy capabilities.

[0063] The signal acquisition unit is used to acquire grid voltage, grid-connected current, DC bus voltage, and capacitor voltage of each submodule in real time. The signal acquisition unit includes a voltage sensor, a current sensor, a synchronous sample-and-hold circuit, and an analog-to-digital converter. It is configured to synchronously acquire the three-phase voltage at the grid connection point, the three-phase current at the converter output, the voltage between the positive and negative poles of the common DC bus and ground, and the voltage across the DC support capacitor of each H-bridge submodule at a sampling rate of not less than twice the system switching frequency.

[0064] The harmonic separation unit is used to perform real-time frequency domain separation of grid voltage and grid-connected current signals based on an improved variational mode decomposition algorithm, and obtain multiple intrinsic mode functions.

[0065] Specifically, the harmonic separation unit receives the time-domain sequences of grid voltage and grid-connected current from the signal acquisition unit; establishes a variational mode decomposition optimization model; adaptively determines the total number of decomposed modes K and the penalty factor α based on the spectral characteristics of the input signal and the current operating state of the system; and decomposes each input signal in real time into K eigenmode functions with adjustable center frequencies and bandwidths by solving the constrained variational optimization problem, with each function corresponding to a major frequency component of the signal.

[0066] The initial classification unit is used to extract instantaneous frequency features from each intrinsic mode function and classify the mode functions based on the instantaneous frequency features.

[0067] Specifically, the initial classification unit performs a Hilbert transform on each intrinsic mode function output by the harmonic separation unit to extract its instantaneous amplitude, instantaneous phase, and instantaneous frequency; and calculates the frequency fluctuation rate of the mode based on the instantaneous frequency sequence. ; Calculate the mode at its center frequency f c The preset bandwidth of the center Energy concentration within ;according to and Dynamically adjust the classification frequency boundary threshold [f] low , f high According to f cThe comparison with the dynamic threshold initially classifies the mode as a low-frequency harmonic, mid-frequency resonance, or high-frequency switching harmonic component. Further, based on the ratio k of the instantaneous amplitude of this mode to the current total active power of the system, combined with the frequency fluctuation rate... Calculate the confidence level of the classification result. The output is the class label and confidence level for each intrinsic mode function.

[0068] The collaborative control unit is used to generate harmonic suppression commands for different frequency bands based on the classification results, and to determine the total voltage reference command based on the harmonic suppression commands and the fundamental voltage command.

[0069] The modulation execution unit is used to generate PWM drive signals for each submodule in response to the total voltage reference command using a carrier phase-shift modulation algorithm; and dynamically adjusts the carrier phase-shift angle of the carrier phase-shift modulation algorithm according to the real-time deviation of the capacitor voltage of each submodule to achieve active equalization of the capacitor voltage.

[0070] Specifically, the modulation execution unit receives the three-phase total voltage reference command output by the cooperative control unit; employing a carrier phase-shift modulation strategy, it allocates triangular carriers with phase shifts of 2π / N (N being the number of sub-modules per phase) to each sub-module of each phase. The voltage reference command is used as a common modulation wave and compared with each carrier to generate a preliminary PWM pulse sequence. Simultaneously, it receives the capacitor voltages of each sub-module from the signal acquisition unit in real time and calculates their deviation from the average voltage within the phase. Based on this deviation, a preset nonlinear adjustment function is used to calculate the fine-tuning amount of the carrier phase for each sub-module. This fine-tuning amount is then superimposed onto the reference carrier phase of the corresponding sub-module, ultimately generating an equalized PWM signal to drive the power devices of each sub-module.

[0071] Optionally, the system also includes a performance monitoring unit that calculates the total harmonic distortion rate of the grid-connected current in real time. The ripple coefficient of the DC bus voltage and the voltage imbalance characterized by the standard deviation of the capacitor voltages of all submodules are used. Based on the comparison between the real-time values ​​of the above performance indicators and preset thresholds, the performance monitoring unit dynamically adjusts the penalty factor α of the variational mode decomposition algorithm in the harmonic separation unit and the gain coefficient of each frequency band harmonic suppression command in the collaborative control unit. and The system also includes key parameters such as the voltage equalization ratio in the modulation execution unit. When any performance indicator continuously exceeds the safe operating threshold, the unit triggers the system protection strategy and initiates the parameter re-optimization process.

[0072] The power submodule's drive end is connected to the modulation execution unit, and its AC side is connected in series and directly connected to the medium-voltage distribution network, while its DC side is connected to the DC bus.

[0073] Optionally, the DC bus can be a symmetrical bipolar or unipolar structure, used to collect DC power from photovoltaic, energy storage and charging piles, and provide a unified DC voltage support for all cascaded H-bridge power submodules.

[0074] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0075] In addition, the functional modules in the various embodiments of this application 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.

[0076] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A frequency domain harmonic separation and suppression method, characterized in that, The method, applied to a converter system containing multiphase cascaded H-bridge power submodules, includes: Real-time acquisition of grid voltage, grid-connected current, DC bus voltage, and capacitor voltage of each submodule at the power grid point; Based on the improved variational mode decomposition algorithm, the signals of the grid voltage and grid-connected current are separated in real time in the frequency domain to obtain multiple intrinsic mode functions; Instantaneous frequency features are extracted from each intrinsic mode function, and the mode functions are classified according to the instantaneous frequency features; Based on the classification results, harmonic suppression commands for different frequency bands are generated respectively, and the total voltage reference command is determined according to the harmonic suppression command and the fundamental voltage command. In response to the total voltage reference command, a carrier phase-shift modulation algorithm is used to generate PWM drive signals for each sub-module; Based on the real-time deviation of the capacitor voltage of each submodule, the carrier phase shift angle of the carrier phase shift modulation algorithm is dynamically adjusted to achieve active equalization of the capacitor voltage.

2. The frequency domain harmonic separation and suppression method according to claim 1, characterized in that, The improved variational mode decomposition algorithm performs real-time frequency domain separation on the grid voltage and grid-connected current signals to obtain multiple intrinsic mode functions, including: Based on the time-domain signals of the grid voltage and grid-connected current, corresponding variational mode decomposition models are established respectively. The models decompose each signal into multiple narrowband eigenmode functions through a constrained variational optimization framework. Based on the spectral characteristics of the grid voltage signal and the degree of harmonic distortion of the grid-connected current, the total number of modes K required for each signal decomposition is determined; Based on the determined total number of modes K, the constrained variational optimization problem for each signal is constructed and solved to obtain the K eigenmode functions corresponding to each signal.

3. The frequency domain harmonic separation and suppression method according to claim 2, characterized in that, The extraction of instantaneous frequency features from each intrinsic mode function includes: Perform a Hilbert transform on each intrinsic mode function to obtain the corresponding analytic signal; Extract the instantaneous amplitude and instantaneous phase from the analyzed signal; The instantaneous frequency is obtained by differentiating the instantaneous phase.

4. The frequency domain harmonic separation and suppression method according to claim 3, characterized in that, The classification of modal functions based on the instantaneous frequency characteristics includes: For each intrinsic mode function, the frequency fluctuation rate ζ is calculated based on its instantaneous frequency time series, including the following equation: ； in, The standard deviation of instantaneous frequency. The average instantaneous frequency; According to the frequency volatility And the energy concentration η of the intrinsic mode function, determine the frequency boundary threshold [f] for classification. low , f high The energy concentration η is defined as the intrinsic mode function at its center frequency f. c The proportion of energy within the preset bandwidth Δf centered on the total energy; The intrinsic mode functions are initially classified based on the determined frequency boundary threshold for classification. Based on the ratio k of the instantaneous amplitude A of the intrinsic mode function to the current operating power P of the system, the confidence level λ = f(k, ζ) of the classification result is calculated, where λ∈ (0, 1]; Output the class label and its corresponding confidence level λ for each intrinsic mode function.

5. The frequency domain harmonic separation and suppression method according to claim 4, characterized in that, The frequency boundary threshold for determining the classification is obtained by the following formula: ； ； in, and The reference frequency boundary threshold, Adjustment amount for the boundary; The confidence level λ is obtained by the following formula: ； in, and This is the adjustment coefficient.

6. The frequency domain harmonic separation and suppression method according to claim 5, characterized in that, Based on the classification results, harmonic suppression commands for different frequency bands are generated, including: For intrinsic mode functions classified as low-frequency harmonic components and with a confidence level λ greater than a preset threshold, corresponding low-frequency harmonic compensation current command components are generated based on their instantaneous amplitude and instantaneous frequency: For the eigenmode functions classified as high-frequency switching harmonic components, the corresponding high-frequency harmonic suppression current command components are generated based on their instantaneous amplitude and instantaneous frequency: The total harmonic suppression command is obtained by summing all harmonic suppression current command components.

7. The frequency domain harmonic separation and suppression method according to claim 6, characterized in that, The determination of the total voltage reference command based on the harmonic suppression command and the fundamental voltage command includes: The fundamental positive sequence component of the grid voltage signal is extracted and phase-locked to obtain the grid synchronization angle; Based on the aforementioned synchronization angle, the system's active power reference value and reactive power reference value are converted into the fundamental current reference value in the synchronous rotating coordinate system. The fundamental current reference value is compared with the component of the grid-connected current in the synchronous rotating coordinate system, and the fundamental voltage command is calculated by the current loop controller. The total harmonic suppression command is converted into a voltage command component in a synchronous rotating coordinate system, and then superimposed with the fundamental voltage command to obtain the total voltage reference command.

8. The frequency domain harmonic separation and suppression method according to claim 1, characterized in that, The step of dynamically adjusting the carrier phase shift angle of the carrier phase shift modulation algorithm based on the real-time deviation of the capacitor voltage of each submodule includes: Calculate the deviation between the capacitor voltage of the i-th submodule in each phase and the average capacitor voltage within the phase; Based on the voltage deviation, the carrier phase adjustment amount of this submodule is calculated using a nonlinear adjustment function; The calculated phase adjustment is superimposed on the reference carrier phase of the submodule to generate the final PWM drive signal.

9. The frequency domain harmonic separation and suppression method according to claim 1, characterized in that, The method further includes adaptively adjusting variational mode decomposition parameters and controller gain parameters based on real-time calculated total harmonic distortion rate of grid-connected current, DC bus voltage ripple, and submodule voltage imbalance. Specifically: Real-time calculation of total harmonic distortion rate of grid-connected current, DC bus voltage ripple coefficient, and submodule capacitor voltage imbalance. Based on the aforementioned performance indicators, dynamically adjust the variational mode decomposition parameters, harmonic compensation gain, and voltage equalization control parameters; When any performance indicator exceeds the preset threshold, the corresponding protection strategy is triggered and the control parameters are re-optimized.

10. A high-voltage direct-connected multi-source energy system, applied to a photovoltaic, energy storage, and charging integrated scenario connected to a medium-voltage distribution network, characterized in that, The system includes: The cascaded H-bridge power conversion unit contains multiple cascaded H-bridge power sub-modules, each sub-module including a full-bridge circuit and a DC support capacitor; The signal acquisition unit is used to acquire grid voltage, grid-connected current, DC bus voltage and capacitor voltage of each submodule in real time. The harmonic separation unit is used to perform real-time frequency domain separation of the grid voltage and grid-connected current signals based on an improved variational mode decomposition algorithm to obtain multiple intrinsic mode functions; The initial classification unit is used to extract instantaneous frequency features from each intrinsic mode function and classify the mode functions according to the instantaneous frequency features; The collaborative control unit is used to generate harmonic suppression commands for different frequency bands based on the classification results, and to determine the total voltage reference command based on the harmonic suppression command and the fundamental voltage command. The modulation execution unit is used to generate PWM drive signals for each submodule in response to the total voltage reference command using a carrier phase-shift modulation algorithm; and dynamically adjust the carrier phase-shift angle of the carrier phase-shift modulation algorithm according to the real-time deviation of the capacitor voltage of each submodule to achieve active equalization of the capacitor voltage. The power submodule's drive end is connected to the modulation execution unit, its AC side is connected in series and directly connected to the medium-voltage distribution network, and its DC side is connected to the DC bus.

Images