Broadband oscillation active damping method, system and device based on MMC sub-module cluster cooperation and storage medium

Abstract

The invention discloses a broadband oscillation active damping method, system and device based on MMC sub-module cluster collaboration and a storage medium, and relates to the technical field of power system stability control, and the method comprises the steps: collecting the electrical quantity of a power grid in real time, and recognizing a broadband oscillation mode and characteristic parameters through a signal processing algorithm; equivalent circuit parameters of the programmable virtual resonator are calculated, and the number of sub-modules of a sub-module cluster is determined in combination with the real-time states of the sub-modules of the modular multilevel converter; generating a control instruction according to the parameter and the oscillation component, and adjusting a sub-module pulse width modulation signal; oscillation amplitude attenuation, a damping ratio and a sub-module state are continuously monitored, adjustment is performed according to an evaluation result, and safe operation is ensured; the method can accurately suppress power grid oscillation, improves the utilization rate of the MMC device, saves the cost, is high in self-adaption, guarantees the reliable operation of the system, reduces the loss, is easy to expand and maintain due to the modular design, and improves the stability of the power system.

Description

Technical Field

[0001] This invention relates to the field of power system stability control technology, and in particular to a broadband oscillation active damping method, system, device and storage medium based on MMC submodule cluster collaboration. Background Technology

[0002] With the widespread application of power electronic equipment in power systems and the increasing proportion of new energy power generation (such as wind power and photovoltaics), power grids are exhibiting characteristics of low inertia and weak damping, making broadband oscillations increasingly prominent. Broadband oscillations refer to electromagnetic oscillations in power systems with a wide frequency range (from subsynchronous frequency to supersynchronous frequency of several kilohertz), which may lead to system instability, equipment damage, or even large-scale power outages.

[0003] Currently, methods for suppressing power system oscillations mainly include: Passive damping: providing damping by adding passive components such as filters or damping resistors to the system; however, their parameters are fixed, making it difficult to adapt to changes in grid operating conditions and oscillation frequencies, and may introduce additional losses; Power system stabilizers (PSS): mainly used in synchronous generators, they have a good suppression effect on low-frequency oscillations (0.1Hz~3Hz), but their effect on broadband oscillations (especially medium and high-frequency oscillations) caused by power electronic equipment is limited; Flexible AC transmission systems (FACTS) and other power electronic equipment with additional damping control: such as STATCOM, SVC, and active power filters (APF), can provide certain damping through additional control strategies. Modular multilevel converters (MMCs), as an advanced power electronic topology, are widely used in flexible DC transmission, large-scale new energy grid integration, and other fields due to their advantages such as high output voltage level number, low harmonic content, and high modularity. Existing research has begun to explore the use of MMCs for oscillation suppression, for example, by controlling the output voltage or current of the MMC as a whole to simulate virtual impedance or provide damping power. However, existing technologies suffer from drawbacks such as limited specificity and poor adaptability: traditional passive damping and PSS are insufficient in suppressing broadband oscillations, especially mid-to-high frequency oscillations; existing damping control based on power electronic devices often treats them as a whole, failing to fully explore and utilize their internal topological characteristics and control degrees of freedom. For MMCs, controlling them as a whole voltage or current source can provide some damping, but its response speed, damping effect, and consideration of the MMC's internal dynamics (such as submodule voltage equalization and circulating current) may not be refined or optimized enough; broadband oscillations often contain multiple oscillation modes at different frequencies, and existing methods struggle to provide precise, tunable damping for specific frequency oscillation modes, potentially adversely affecting signals at non-target frequencies, or requiring large device capacity to cover a wide frequency band; and the MMC itself needs to maintain submodule capacitor voltage equalization and suppress circulating current. When suppressing external oscillations, improper control strategies may worsen the internal operating state of the MMC or sacrifice external damping performance in order to maintain internal stability. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention provides a broadband oscillation active damping method, system, device and storage medium based on MMC submodule cluster collaboration.

[0005] Therefore, the technical problem solved by the present invention is that the existing technology has problems such as weak targeting of broadband oscillation suppression, poor adaptability, difficulty in achieving frequency-selective precise damping, and failure to fully utilize the characteristics of MMC topology.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a broadband oscillation active damping method based on MMC submodule cluster collaboration, comprising: Real-time acquisition of electrical quantities in the power grid, and the use of signal processing algorithms to identify the existing broadband oscillation modes and their corresponding characteristic parameters; Based on the oscillation mode characteristic parameters, the equivalent circuit parameters required for the programmable virtual resonator are calculated, and the number of sub-modules forming the sub-module cluster is dynamically selected and determined according to the real-time status data of each sub-module of the modular multilevel converter. Based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, the programmable virtual resonator control command is generated to adjust the pulse width modulation signal of the sub-module within the sub-module cluster. After the submodule cluster is put into operation, continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode, make adjustments based on the evaluation results, and monitor the status of the submodules within the submodule cluster to ensure that they are within the safe operating area.

[0007] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The real-time acquisition of power grid electrical quantities, and the identification of the current broadband oscillation mode and its corresponding characteristic parameters using signal processing algorithms, include: At the AC grid connection point or DC bus side of the modular multilevel converter, voltage and current instantaneous values ​​of the grid voltage and current are collected in real time using voltage measurement devices and current measurement devices that employ voltage division principle combined with isolation transmission technology, at a sampling rate higher than the expected maximum oscillation frequency.

[0008] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The real-time acquisition of power grid electrical quantities and the identification of existing broadband oscillation modes and corresponding characteristic parameters using signal processing algorithms also include: The acquired digital signals are input to the oscillation analysis unit for analysis to identify whether a broadband oscillation mode exists; If a wideband oscillation mode is identified, each oscillation mode is distinguished, and the corresponding oscillation frequency, amplitude of oscillation current or voltage, and initial phase are extracted, while the current damping ratio is estimated.

[0009] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The calculation of the equivalent circuit parameters required for the programmable virtual resonator based on oscillation mode characteristic parameters, and the dynamic selection and determination of the number of submodules forming the submodule cluster based on the real-time status data of each submodule of the modular multilevel converter, includes: Based on the extracted oscillation frequency and amplitude of the oscillation mode, the SMC is used to construct a decision unit to calculate the equivalent circuit parameters required for the programmable virtual resonator, aligning the resonant frequency of the PVR with the oscillation frequency of the oscillation mode and providing the expected damping strength. According to the real-time status data of each sub-module of the MMC and the calculated PVR parameters, the SMC is activated in the bridge arm of the MMC, and a sub-module is selected for each SMC. During the selection, the voltage margin, thermal margin and health status of the sub-module are comprehensively evaluated. The sub-modules are then optimized and rotated.

[0010] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The step of generating programmable virtual resonator control commands based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and adjusting the pulse width modulation signals of the submodules within the submodule cluster, includes: The PVR control law generation unit calculates the compensation voltage or current reference value that the submodule cluster needs to generate based on the determined PVR target parameters and the grid voltage or current components detected in real time at a specific oscillation frequency. The submodules selected into the SMC receive the instructions from the PVR control law generation unit and adjust the duty cycle or phase of the pulse width modulation signal through the high-frequency opening and closing of the internal power electronic switches to collaboratively synthesize a specific voltage output or current injection.

[0011] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The step of generating programmable virtual resonator control commands based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and adjusting the pulse width modulation signals of the sub-modules within the sub-module cluster, further includes: When a change in the target oscillation frequency is detected, the PVR control law generation unit adjusts the control target of the frequency parameters for calculating the compensation reference value and the PVR equivalent circuit parameters online, so that the equivalent resonant point of the PVR dynamically tracks the actual oscillation frequency.

[0012] The beneficial effects of this preferred technical solution are as follows: the PVR control law generation unit can adjust parameters online, so that the equivalent resonant point of the PVR can dynamically track the actual oscillation frequency, adapt to changes in the power grid oscillation frequency, and ensure that broadband oscillations can be continuously and effectively suppressed under different oscillation frequencies, thereby enhancing the adaptability and robustness of the system.

[0013] As a preferred scheme for a broadband oscillation active damping method based on MMC submodule cluster collaboration, wherein: The continuous monitoring of the target oscillation mode's amplitude decay rate and damping ratio improvement after the submodule cluster is deployed is adjusted based on the evaluation results. The status of the submodules within the submodule cluster is also monitored to ensure that the safe operating area includes: The oscillation analysis unit continuously monitors the oscillation amplitude decay rate or damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation. Based on the monitoring evaluation results, the closed-loop optimization unit uses an adaptive control algorithm to adjust the equivalent parameters of the programmable virtual resonator to control the target or SMC scale. The closed-loop optimization unit monitors the capacitor voltage, temperature and current of the submodules participating in the SMC to ensure that they are within the preset safe operating area. If the risk of parameter exceeding the limit is detected, the submodule rotation mechanism is activated or the damping contribution of the corresponding SMC is adjusted.

[0014] The beneficial effects of this preferred technical solution are as follows: continuous monitoring of the attenuation of the oscillation mode and adjustment of parameters and scale based on the evaluation results can continuously optimize the damping effect; monitoring the status of submodules and taking corresponding measures when parameters exceed limits can ensure that submodules operate within the safe operating range, improve the safety and stability of the system, and prevent equipment damage.

[0015] Secondly, this invention provides a broadband oscillation active damping system based on MMC submodule cluster collaboration, comprising: The wideband oscillation identification module is used to collect electrical quantities of the power grid in real time and use signal processing algorithms to identify the existing wideband oscillation modes and their corresponding characteristic parameters. The parameter calculation and module selection module is used to calculate the equivalent circuit parameters required for the programmable virtual resonator based on the oscillation mode characteristic parameters, and dynamically select and determine the number of sub-modules that make up the sub-module cluster based on the real-time status data of each sub-module of the modular multilevel converter. The control command generation module is used to generate control commands for the programmable virtual resonator based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and to adjust the pulse width modulation signals of the sub-modules within the sub-module cluster. The monitoring and adjustment module is used to continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation, make adjustments based on the evaluation results, and monitor the status of the submodules within the submodule cluster to ensure that they are within the safe operating area.

[0016] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the wideband oscillation active damping method based on MMC submodule cluster collaboration.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of a broadband oscillation active damping method based on MMC submodule cluster collaboration.

[0018] The beneficial effects of this invention are as follows: The broadband oscillation active damping method and system based on MMC submodule cluster collaboration proposed in this invention have significant practical benefits. In terms of grid oscillation suppression, it can accurately target the oscillation frequency, provide highly selective and strong damping, and has minimal impact on fundamental frequency operation and non-target frequency disturbances, avoiding the inefficiency of traditional methods. Utilizing the characteristics of the MMC topology, some submodules perform damping tasks while the rest perform normal power conversion, improving device utilization and saving on additional compensation equipment investment. It possesses flexible adjustability and adaptive capabilities, enabling rapid response to changes in oscillation frequency. Submodule-level refined management ensures long-term reliable system operation, reducing switching losses and thermal stress. The modular design facilitates expansion and maintenance, making it suitable for modern power systems containing a high proportion of power electronic equipment and renewable energy grid integration, thus improving system stability. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an overall flowchart of a broadband oscillation active damping method based on MMC submodule cluster collaboration provided by the present invention.

[0021] Figure 2 This is a topology diagram of an MMC based on a wideband oscillation active damping method using MMC submodule cluster collaboration provided by the present invention. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a broadband oscillation active damping method based on MMC submodule cluster collaboration, comprising: S1: Real-time acquisition of electrical quantities in the power grid, and use signal processing algorithms to identify the current broadband oscillation mode and its corresponding characteristic parameters; S2: Based on the oscillation mode characteristic parameters, calculate the equivalent circuit parameters required for the programmable virtual resonator, and dynamically select and determine the number of sub-modules that make up the sub-module cluster based on the real-time status data of each sub-module of the modular multilevel converter. S3: Based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, generate programmable virtual resonator control commands to adjust the pulse width modulation signals of the sub-modules within the sub-module cluster; S4: Continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation, make adjustments based on the evaluation results, and monitor the status of the submodules inside the submodule cluster to ensure that they are within the safe working area.

[0024] It should be noted that through steps S1-S4, some sub-modules within the MMC can be dynamically organized and coordinated to form a functional cluster, which is equivalent to a programmable and tunable virtual resonance characteristic, actively absorbing or dissipating the oscillation energy of a specific frequency of the power grid, thereby achieving precise, efficient and flexible suppression of broadband oscillations, while also ensuring the stable operation of the MMC itself.

[0025] Example 2, refer to Figures 1-2 As an embodiment of the present invention, based on the previous embodiment, a broadband oscillation active damping method based on MMC submodule cluster collaboration is provided, comprising: It should be noted that this invention provides a wideband oscillation active damping method based on submodule (SM) cluster collaboration, applied to modular multilevel converters (MMCs). The topology of the MMC is as follows: Figure 2 As shown, each phase consists of an upper bridge arm and a lower bridge arm, and each bridge arm contains multiple sub-modules SM connected in series and a bridge arm inductor L0. Figure 2 Between points A and B is a half-bridge submodule SM, which contains an energy storage capacitor C0. This invention detects broadband grid oscillations, dynamically selects some submodules from the MMC to form a submodule cluster (SMC), and applies specific cooperative control to the SMC, making the SMC equivalent to a programmable virtual resonator (PVR). The resonant frequency of this PVR is precisely aligned with the grid oscillation frequency, selectively absorbing oscillation energy and achieving active damping.

[0026] In this embodiment, the real-time acquisition of power grid electrical quantities in step S1 and the identification of the current broadband oscillation mode and its corresponding characteristic parameters using signal processing algorithms include: At the MMC AC grid connection point (data collection) Figure 2The three-phase AC voltage and three-phase AC current (as shown) or DC bus side are used to collect instantaneous grid voltage and current values ​​in real time at a sampling rate higher than the expected maximum oscillation frequency using high-bandwidth, high-precision voltage and current measuring devices. The voltage measuring device employs the voltage divider principle combined with isolated transmission technology, while the current measuring device uses the electromagnetic induction principle or a Hall effect sensor.

[0027] In another possible implementation, the voltage measuring device employing the voltage divider principle combined with isolated transmission technology can be implemented using fiber optic isolation technology. Utilizing the high insulation and anti-interference capabilities of optical fibers, the voltage signal after voltage division is transmitted in isolation through the fiber, avoiding the influence of electromagnetic interference on the measurement results and improving the accuracy and reliability of voltage measurement.

[0028] In another possible implementation, the voltage measuring device employing the voltage divider principle combined with isolation transmission technology can also be implemented using a combination of capacitive voltage divider and opto-isolation. A capacitive voltage divider converts the high voltage into a low voltage signal, and then an opto-isolator isolates and transmits the signal, achieving accurate measurement of the mains voltage.

[0029] Oscillation Mode Recognition and Parameter Identification: The acquired digital signal is input to the oscillation analysis unit. This unit uses advanced signal processing techniques such as the Prony algorithm, Fast Fourier Transform (FFT) combined with higher-order spectral estimation algorithms, or Empirical Mode Decomposition (EMD) to analyze the signal and identify the existence of one or more broadband oscillation modes. For each identified oscillation mode (distinguished by the serial number "Mode i"), its oscillation frequency is precisely extracted and denoted as "Mode i Oscillation Frequency"; the amplitude of its oscillation current or voltage is extracted and denoted as "Mode i Oscillation Amplitude"; its initial phase is extracted and denoted as "Mode i Initial Phase"; and its current damping ratio is estimated and denoted as "Mode i Damping Ratio".

[0030] In another possible implementation, real-time acquisition of power grid electrical quantities can be achieved by distributing high-precision smart sensors at different key nodes of the power grid. These smart sensors have high-speed data acquisition and processing capabilities, enabling them to acquire power grid electrical quantities such as voltage and current in real time with higher sampling frequency and accuracy. The data is then rapidly transmitted to the central processing unit via a wireless communication network for timely subsequent analysis.

[0031] In another possible implementation, real-time acquisition of power grid electrical quantities can be carried out using satellite communication technology in conjunction with ground monitoring stations. The ground monitoring stations are responsible for collecting local power grid electrical quantity data, while simultaneously transmitting and backing up the data remotely via satellite communication to ensure data integrity and reliability. Even in the event of communication failures in localized areas, continuous data acquisition and transmission can be guaranteed.

[0032] In another possible implementation, identifying the existing broadband oscillation modes and their corresponding characteristic parameters can also be achieved using deep learning algorithms. A large amount of collected power grid electrical quantity data can be used as training samples to train a deep neural network model, enabling it to automatically learn and identify broadband oscillation modes and their characteristic parameters, thereby improving the accuracy and efficiency of identification.

[0033] In another possible implementation, identifying the existing broadband oscillation mode and its corresponding characteristic parameters can also be achieved using multi-sensor fusion technology. By comprehensively utilizing data from multiple sensors such as voltage sensors, current sensors, and power sensors, and processing and analyzing the data through data fusion algorithms, the broadband oscillation mode and its characteristic parameters can be identified more comprehensively and accurately.

[0034] In this embodiment, step S2 above, which calculates the equivalent circuit parameters required for the programmable virtual resonator based on the oscillation mode characteristic parameters, and dynamically selects and determines the number of submodules constituting the submodule cluster based on the real-time status data of each submodule of the modular multilevel converter, includes: Based on the extracted "mode i oscillation frequency" and "mode i oscillation amplitude," the SMC (Structured Component Analysis) is used to construct a decision unit to calculate the equivalent circuit parameters required for the PVR, including the equivalent resistance (denoted as "PVR equivalent resistance i"), equivalent inductance (denoted as "PVR equivalent inductance i"), and equivalent capacitance (denoted as "PVR equivalent capacitance i"). The settings of these parameters ensure that the PVR's resonant frequency is aligned with the "mode i oscillation frequency," and that the "PVR equivalent resistance i" provides the expected damping strength. The PVR's resonant frequency is denoted as "PVR resonant frequency i," and its calculation formula is as follows: in, This represents the resonant frequency of PVR corresponding to the i-th mode, i.e., the PVR resonant frequency i. This refers to the inductance value corresponding to the i-th mode in the PVR equivalent circuit. This represents the capacitance value corresponding to the i-th mode in the PVR equivalent circuit.

[0035] Dynamic selection and quantity determination of SMC submodules: Selection Criteria: The SMC construction decision unit determines whether to activate the SMC in one or more arms of the MMC based on the real-time status data (including "submodule j capacitor voltage", "submodule j health status", and "submodule j temperature") of each submodule of the MMC (distinguished by the serial number "submodule j") and the calculated PVR parameters. It also selects a specific number of submodules (denoted as "SMC") for each SMC (corresponding to "mode i"). i (Number of submodules). When selecting, comprehensively evaluate the voltage margin, thermal margin, and health status of the submodules.

[0036] In another possible implementation, a comprehensive assessment of the voltage margin, thermal margin, and health status of a submodule can be achieved by establishing a submodule condition assessment model. Historical operating data of the submodule, including parameters such as voltage, temperature, and current, is collected. A condition assessment model is then built using machine learning algorithms to evaluate the voltage margin, thermal margin, and health status of the submodule in real time, providing a more scientific basis for submodule selection and rotation.

[0037] In another possible implementation, the comprehensive evaluation of the voltage margin, thermal margin, and health status of the submodule can be carried out by combining online monitoring with an expert system. The online monitoring device acquires the submodule's operating status data in real time, and simultaneously inputs the data into the expert system. The expert system analyzes and evaluates the data according to preset rules and experience, providing a comprehensive evaluation result for the submodule.

[0038] Balanced and rapid decision-making: Parallel processing algorithms based on FPGA are used to optimize the selection and rotation of sub-modules, so as to balance the operating pressure of each sub-module and achieve rapid response.

[0039] It should be noted that the design of this algorithm draws on the fast selection idea of ​​voltage equalization in existing MMC submodules, and is adjusted for the oscillation suppression task.

[0040] In this embodiment, step S3 above, which generates programmable virtual resonator control commands based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and adjusts the pulse width modulation signals of the sub-modules within the sub-module cluster, includes: PVR control command generation: The PVR control law generation unit calculates the compensation voltage or current reference value that the SMC needs to generate based on the determined PVR target parameters and the voltage or current components of the power grid at the "mode i oscillation frequency" detected in real time.

[0041] SMC Internal Submodule Co-modulation: Selected SMC i Number of submodules (e.g., number of submodules) Figure 2 The half-bridge module between points A and B receives instructions from the PVR control law generation unit. Through the high-frequency opening and closing action of its internal power electronic switches, it adjusts the duty cycle or phase of its pulse width modulation (PWM) signal to synthesize a specific voltage output or current injection, so that the SMC as a whole presents the impedance characteristics of the target PVR to the outside world.

[0042] PVR parameter dynamic tuning mechanism: When step S1 detects a change in the target "mode i oscillation frequency", the PVR control law generation unit adjusts the control target used to calculate the compensation reference value and the PVR equivalent circuit parameters online, so that the equivalent resonant point of the PVR dynamically tracks the actual oscillation frequency.

[0043] In this embodiment, step S4 above continuously monitors the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation, adjusts it according to the evaluation results, and monitors the status of the submodules within the submodule cluster to ensure that the safe operating area includes: Quantitative evaluation of damping effect: The system continuously monitors the decay rate of the "mode i oscillation amplitude" or the degree of improvement of the "mode i damping ratio" of the target "mode i" after the SMC is put into operation through the oscillation analysis unit.

[0044] Adaptive control parameter adjustment: Based on the evaluation results, the closed-loop optimization unit uses adaptive control algorithms such as proportional-integral-derivative PID control, fuzzy logic control, or model-based predictive control to adjust the equivalent parameter control objective or the scale of the SMC ("SMC"). i Number of submodules).

[0045] SMC internal state collaborative management: Closed-loop optimization unit monitors the capacitor voltage of sub-modules participating in the SMC (e.g., Figure 2 The C0 voltage, temperature, and current of the submodule are monitored to ensure they remain within a preset safe operating range. If a risk of exceeding these limits is detected, the submodule rotation mechanism is activated or the damping contribution of the SMC is adjusted.

[0046] Example 3: The above is a schematic scheme of a broadband oscillation active damping method based on MMC submodule cluster collaboration in this embodiment. It should be noted that the technical solution of a broadband oscillation active damping system based on MMC submodule cluster collaboration belongs to the same concept as the above-described broadband oscillation active damping method based on MMC submodule cluster collaboration. Details not described in detail in the technical solution of the broadband oscillation active damping system based on MMC submodule cluster collaboration in this embodiment can be found in the description of the above-described broadband oscillation active damping method based on MMC submodule cluster collaboration.

[0047] This embodiment also provides a broadband oscillation active damping system based on MMC submodule cluster collaboration, including: The wideband oscillation identification module is used to collect electrical quantities of the power grid in real time and use signal processing algorithms to identify the existing wideband oscillation modes and their corresponding characteristic parameters. The parameter calculation and module selection module is used to calculate the equivalent circuit parameters required for the programmable virtual resonator based on the oscillation mode characteristic parameters, and dynamically select and determine the number of sub-modules that make up the sub-module cluster based on the real-time status data of each sub-module of the modular multilevel converter. The control command generation module is used to generate control commands for the programmable virtual resonator based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and to adjust the pulse width modulation signals of the sub-modules within the sub-module cluster. The monitoring and adjustment module is used to continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation, make adjustments based on the evaluation results, and monitor the status of the submodules within the submodule cluster to ensure that they are within the safe operating area.

[0048] This embodiment also provides an electronic device applicable to a broadband oscillation active damping method based on MMC submodule cluster collaboration, including: The memory and processor are used to store computer-executable instructions and execute computer-executable instructions to implement a wideband oscillation active damping method based on MMC submodule cluster collaboration as proposed in the above embodiments.

[0049] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements a broadband oscillation active damping method based on MMC submodule cluster collaboration as proposed in the above embodiment.

[0050] The storage medium proposed in this embodiment belongs to the same inventive concept as the wideband oscillation active damping method based on MMC submodule cluster collaboration proposed in the above embodiment. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0051] Example 4 is an embodiment of the present invention, which provides a broadband oscillation active damping method based on MMC submodule cluster collaboration. To verify the beneficial effects of the present invention, a simulation experiment is conducted for scientific demonstration.

[0052] The hardware components corresponding to this invention mainly include: Unit 1: Modular Multilevel Converter (MMC).

[0053] Unit 2: Power grid condition monitoring unit, which includes high-precision, high-bandwidth voltage and current measurement devices and high-speed data acquisition circuits.

[0054] Unit 3: Wideband Oscillation Analysis and Feature Extraction Unit, which executes advanced signal processing algorithms.

[0055] Unit 4: SMC Construction and PVR Parameter Decision Unit, responsible for PVR parameter calculation and dynamic selection and optimization of SMC.

[0056] Unit 5: PVR Cooperative Control Law Generation and Execution Unit, which generates precise modulation or switching instructions for sub-modules within the SMC.

[0057] Unit 6: Closed-loop evaluation and adaptive optimization unit, responsible for performance evaluation, adaptive parameter adjustment, and collaborative management of SMC internal states. (Units 3 to 6 are integrated into a high-performance digital control system, which is built on a field-programmable gate array (FPGA) and / or a digital signal processor (DSP).)

[0058] Oscillation monitoring and feature extraction (corresponding to S1 in Example 1): Three-phase current and voltage signals are acquired in real time at a high sampling rate (e.g., 50 kHz) by using high-precision current and voltage sensors installed on the AC side of the MMC.

[0059] The acquired signal is fed into the "Wideband Oscillation Analysis and Feature Extraction Unit". This unit performs digital filtering on the current signal to remove the fundamental frequency and known switching harmonic components. Subsequently, a suitable signal analysis algorithm (such as the Prony algorithm) is used to analyze the filtered current signal. Assuming the analysis results indicate that a dominant oscillation mode is detected in the phase a current isa, its characteristic parameters are determined as follows: "Mode 1 oscillation frequency" is 750Hz, "Mode 1 oscillation amplitude" (referring to the peak value of the current at this frequency) is 5% of the rated current, "Mode 1 initial phase" is a specific phase angle value (denoted as ϕ1), and the evaluated "Mode 1 damping ratio" is close to zero. This indicates that the 750Hz oscillation component is weakly damped and needs to be actively suppressed.

[0060] SMC construction and PVR parameter determination (corresponding to S2 in Example 1): The "SMC Construction and PVR Parameter Decision Unit" determines the suppression strategy based on the received 750Hz oscillation mode information. In this embodiment, the control objective is to absorb and dissipate the 750Hz oscillation energy through the PVR in the form of equivalent resistance.

[0061] PVR Target Parameter Calculation: To achieve resistive absorption, the target for the PVR at 750Hz is to exhibit purely resistive behavior. The decision unit calculates the equivalent resistance value required for the PVR at 750Hz based on the desired oscillation energy absorption rate or equivalent damping resistance value, denoted as "PVR Equivalent Resistance 1". For example, the target value for "PVR Equivalent Resistance 1" is set to 10 ohms. The corresponding parameter control targets for "PVR Equivalent Inductance 1" and "PVR Equivalent Capacitance 1" are set to ensure that the PVR primarily exhibits this resistive characteristic at 750Hz.

[0062] SMC Submodule Selection: Assume each arm of the MMC is configured with 100 submodules. The decision unit selects 10 submodules from each of the upper and lower arms of phase a (i.e., the number of "SMC1 submodules" is 10 in each target arm) to jointly form the SMC for this 750Hz oscillation. The submodule selection is achieved through an efficient optimization decision algorithm. This algorithm evaluates in real time the "submodule j capacitor voltage" (selecting submodules with voltage close to the average value and small fluctuations), "submodule j health status" (ensuring no faulty submodules participate), and "submodule j temperature" (ensuring it is within the safe operating range), and combines this with a preset submodule rotation strategy to balance the operating pressure of each submodule and ensure the reliability of the system during long-term operation. This decision algorithm ensures that a suitable submodule is selected quickly in each control cycle.

[0063] SMC cooperative control is used to simulate PVR characteristics (corresponding to S3 in Example 1): PVR Control Command Generation: To ensure that the selected SMCs (a total of 20 sub-modules, distributed across the upper and lower arms of phase a) exhibit an equivalent resistance characteristic of 10 ohms at 750Hz, the "PVR Cooperative Control Law Generation and Execution Unit" needs to precisely control these SMC sub-modules to generate a specific 750Hz voltage component. Specifically, the system monitors the 750Hz oscillation component in the phase a current (denoted as "Mode 1 Oscillation Current Instantaneous Value"). The 750Hz voltage component to be synthesized by the SMCs (denoted as "SMC1 Reference Voltage Instantaneous Value") should be in phase with the "Mode 1 Oscillation Current Instantaneous Value," and its amplitude should be equal to the amplitude of the "Mode 1 Oscillation Current Instantaneous Value" multiplied by the target resistance value of 10 ohms.

[0064] SMC Internal Submodule Co-modulation: The pulse width modulation (PWM) signals of the 20 submodules selected into the SMC will be adjusted. The original modulation commands used by these submodules to synthesize the fundamental voltage remain unchanged. On this basis, a 750Hz modulation component is superimposed based on the "instantaneous value of the SMC1 reference voltage". Each submodule participating in the SMC undertakes a portion of the 750Hz voltage synthesis task according to its position in the bridge arm and the overall voltage synthesis requirements of the SMC. By precisely controlling the switching states (on, off, bypass) of the power electronic switching devices of these submodules, the SMC, as a whole, effectively has a 750Hz voltage source connected in series in the bridge arm. The effect of this voltage source is to simulate a 10-ohm resistor, used to absorb the 750Hz oscillating current in the power grid.

[0065] PVR parameter dynamic tuning: If subsequent monitoring detects a slight drift in the actual "Mode 1 oscillation frequency" from 750Hz (e.g., changing to 755Hz), the "Wideband Oscillation Analysis and Feature Extraction Unit" feeds this updated frequency information back to the "PVR Cooperative Control Law Generation and Execution Unit." The latter will adjust the frequency of the modulation component superimposed on the SMC modulation signal to 755Hz accordingly to ensure that the damping effect of the PVR is always precisely aligned with the actual oscillation frequency, demonstrating its tunability.

[0066] Damping effect closed-loop evaluation and SMC strategy adaptive optimization (corresponding to S4 in Example 1): The system continuously monitors the "mode 1 oscillation amplitude" of the 750Hz (or the actual drifted frequency) oscillation component in the phase a current through the "wideband oscillation analysis and feature extraction unit".

[0067] The "Closed-Loop Evaluation and Adaptive Optimization Unit" compares the real-time "Mode 1 Oscillation Amplitude" with the amplitude before the SMC is activated and evaluates its decay rate. If the amplitude decay does not reach the preset control target (e.g., decaying by 90% within a preset time of 1 second), the unit will activate an adaptive adjustment mechanism, which may include the following adjustments: Adjust the control target value of "PVR equivalent resistance 1" (for example, appropriately reduce the target resistance value, such as adjusting it to 8 ohms, to enhance the absorption capability of oscillating current, which means that the SMC needs to generate a larger 750Hz voltage or equivalently inject a larger 750Hz current).

[0068] If the submodule currently participating in SMC has reached its control limit (e.g., insufficient voltage or current margin) or the temperature rises rapidly, the system can appropriately increase the number of "SMC1 submodules" (e.g., from 10 to 12 per bridge arm) to share the damping task, provided that there are still qualified spare submodules in the bridge arm.

[0069] Meanwhile, the unit continuously monitors the C0 capacitor voltage of each submodule within the SMC. If the capacitor voltage of a submodule deviates too much from the average value, or if the temperature continues to rise and approaches the alarm threshold, the system will fine-tune its contribution to the 750Hz voltage synthesis, or rotate it with a backup submodule in better condition, in order to maintain voltage and thermal balance within the SMC and ensure the continuity and reliability of the entire damping function.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A broadband oscillation active damping method based on MMC submodule cluster collaboration, characterized in that, include: Real-time acquisition of electrical quantities in the power grid, and the use of signal processing algorithms to identify the current broadband oscillation modes and their corresponding characteristic parameters; Based on the oscillation mode characteristic parameters, the equivalent circuit parameters required for the programmable virtual resonator are calculated, and the number of sub-modules forming the sub-module cluster is dynamically selected and determined according to the real-time status data of each sub-module of the modular multilevel converter. Based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, programmable virtual resonator control commands are generated to adjust the pulse width modulation signals of the sub-modules within the sub-module cluster. After the submodule cluster is put into operation, continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode, make adjustments based on the evaluation results, and monitor the status of the submodules within the submodule cluster to ensure that they are within the safe operating area.

2. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 1, characterized in that, The real-time acquisition of power grid electrical quantities, and the identification of existing broadband oscillation modes and corresponding characteristic parameters using signal processing algorithms, include: At the AC grid connection point or DC bus side of the modular multilevel converter, voltage and current instantaneous values ​​of the grid voltage and current are collected in real time using voltage measurement devices and current measurement devices that employ voltage division principle combined with isolation transmission technology, at a sampling rate higher than the expected maximum oscillation frequency.

3. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 2, characterized in that, The real-time acquisition of power grid electrical quantities and the identification of existing broadband oscillation modes and corresponding characteristic parameters using signal processing algorithms also include: The acquired digital signals are input to the oscillation analysis unit for analysis to identify whether a broadband oscillation mode exists; If a wideband oscillation mode is identified, each oscillation mode is distinguished, and the corresponding oscillation frequency, amplitude of oscillation current or voltage, and initial phase are extracted, while the current damping ratio is estimated.

4. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 3, characterized in that, The calculation of the equivalent circuit parameters required for the programmable virtual resonator based on oscillation mode characteristic parameters, and the dynamic selection and determination of the number of submodules forming the submodule cluster based on the real-time status data of each submodule of the modular multilevel converter, include: Based on the extracted oscillation frequency and amplitude of the oscillation mode, the SMC is used to construct a decision unit to calculate the equivalent circuit parameters required for the programmable virtual resonator, aligning the resonant frequency of the PVR with the oscillation frequency of the oscillation mode and providing the expected damping strength. According to the real-time status data of each sub-module of the MMC and the calculated PVR parameters, the SMC is activated in the bridge arm of the MMC, and a sub-module is selected for each SMC. During the selection, the voltage margin, thermal margin and health status of the sub-module are comprehensively evaluated. The sub-modules are then optimized and rotated.

5. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 4, characterized in that, The step of generating programmable virtual resonator control commands based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and adjusting the pulse width modulation signals of the submodules within the submodule cluster, includes: The PVR control law generation unit calculates the compensation voltage or current reference value that the submodule cluster needs to generate based on the determined PVR target parameters and the grid voltage or current components detected in real time at a specific oscillation frequency. The submodules selected into the SMC receive the instructions from the PVR control law generation unit and adjust the duty cycle or phase of the pulse width modulation signal through the high-frequency opening and closing of the internal power electronic switches to collaboratively synthesize a specific voltage output or current injection.

6. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 5, characterized in that, The step of generating programmable virtual resonator control commands based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and adjusting the pulse width modulation signals of the sub-modules within the sub-module cluster, further includes: When a change in the target oscillation frequency is detected, the PVR control law generation unit adjusts the control target of the frequency parameters for calculating the compensation reference value and the PVR equivalent circuit parameters online, so that the equivalent resonant point of the PVR dynamically tracks the actual oscillation frequency.

7. The broadband oscillation active damping method based on MMC submodule cluster collaboration as described in claim 6, characterized in that, The continuous monitoring of the target oscillation mode's amplitude decay rate and damping ratio improvement after the submodule cluster is deployed is adjusted based on the evaluation results. The status of the submodules within the submodule cluster is also monitored to ensure that the safe operating area includes: The oscillation analysis unit continuously monitors the oscillation amplitude decay rate or damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation. Based on the monitoring evaluation results, the closed-loop optimization unit uses an adaptive control algorithm to adjust the equivalent parameters of the programmable virtual resonator to control the target or SMC scale. The closed-loop optimization unit monitors the capacitor voltage, temperature and current of the submodules participating in the SMC to ensure that they are within the preset safe operating area. If the risk of parameter exceeding the limit is detected, the submodule rotation mechanism is activated or the damping contribution of the corresponding SMC is adjusted.

8. A broadband oscillation active damping system based on MMC submodule cluster collaboration, using the method described in any one of claims 1 to 7, characterized in that, include: The wideband oscillation identification module is used to collect electrical quantities of the power grid in real time and use signal processing algorithms to identify the existing wideband oscillation modes and their corresponding characteristic parameters. The parameter calculation and module selection module is used to calculate the equivalent circuit parameters required for the programmable virtual resonator based on the oscillation mode characteristic parameters, and dynamically select and determine the number of sub-modules that make up the sub-module cluster based on the real-time status data of each sub-module of the modular multilevel converter. The control command generation module is used to generate control commands for the programmable virtual resonator based on the equivalent circuit parameters required by the programmable virtual resonator and the real-time power grid oscillation components, and to adjust the pulse width modulation signals of the sub-modules within the sub-module cluster. The monitoring and adjustment module is used to continuously monitor the oscillation amplitude decay rate and damping ratio improvement of the target oscillation mode after the submodule cluster is put into operation, make adjustments based on the evaluation results, and monitor the status of the submodules within the submodule cluster to ensure that they are within the safe operating area.

9. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.

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