A tuning control method and system for a wind power plant

Abstract

This invention relates to the field of intelligent control technology for power generation equipment, and discloses a tuning control method and system for a wind power generation device, comprising the following steps: acquiring the current wind speed and the oscillation state of the energy harvester; determining the main excitation frequency of the current wind field based on the current wind speed and the aerodynamic characteristic parameters of the energy harvester; adjusting the rotational inertia of the oscillating power generation device according to the wind speed range in which the current wind speed is located, so that the natural frequency of the oscillating power generation device tracks the main excitation frequency, or the rotational inertia is switched to an extreme value state. This invention provides a tuning control method and system for a wind power generation device, which can improve the environmental adaptability of the oscillating power generation device.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for power generation equipment, and in particular to a tuning control method and system for a wind power generation device. Background Technology

[0002] As the global energy structure accelerates its transformation towards low-carbon and clean energy, wind energy, as a abundant and widely distributed renewable energy source, is playing an increasingly prominent role in the energy strategies of various countries. Swing-type wind energy harvesting devices, as a novel type of wind energy capture mechanism, are gradually becoming a research hotspot in the field of distributed wind energy utilization due to their advantages such as simple structure, no strict wind requirements, and sensitive response at low wind speeds. Their basic working principle is that the energy harvester (airfoil or bluff body structure) generates periodic oscillations or flutter under the action of incoming wind, and the mechanical vibration is converted into electrical energy through an electromechanical conversion unit. This type of device fundamentally simplifies the energy conversion chain, reduces manufacturing and maintenance costs, has good environmental adaptability and potential for large-scale application, and is one of the important technological paths to overcome the bottlenecks of existing small-scale wind power technology.

[0003] The control method for the aforementioned swing-type power generation device aims to capture the optimal energy at a specific wind speed (i.e., the design wind speed). It can achieve a high conversion efficiency near this wind speed. However, when the actual wind speed deviates from the design point, the conversion efficiency is low and it is difficult to maintain a stable and efficient energy output. The actual annual power generation is far lower than the theoretical expectation. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a tuning control method and system for a wind power generation device, which can improve the environmental adaptability of the swing-type power generation device.

[0005] This invention provides a tuning control method for a wind power generation device, comprising the following steps: Obtain the current wind speed and the oscillation state and aerodynamic characteristic parameters of the energy harvester; Based on the current wind speed and the aerodynamic characteristics of the energy harvester, determine the main excitation frequency of the current wind field; obtain the current natural frequency of the oscillating power generation device based on the oscillation state; Based on the matching of the current wind speed with the preset wind speed range, the wind speed range in which the current wind speed is located is determined. According to the wind speed range, the rotational inertia of the oscillating generator is adjusted so that the natural frequency of the oscillating generator approaches the main excitation frequency, or the rotational inertia is switched to an extreme value state.

[0006] Specifically, determining the dominant excitation frequency of the current wind field based on aerodynamic characteristic parameters includes the following steps: Obtain the aerodynamic characteristic parameters of the energy harvester, including dimensionless constants and characteristic dimensions related to the cross-sectional shape of the energy harvester; Calculate the main excitation frequency of the current wind field based on the current wind speed, dimensionless constant, and characteristic size.

[0007] Specifically, the preset wind speed ranges include low wind speed range, high wind speed range, and high wind speed range; The lower limit of the high-efficiency wind speed range is the starting wind speed threshold, which is preset according to the minimum starting wind speed of the swing generator. The upper limit of the high-efficiency wind speed range is the high wind speed threshold. The low wind speed range is defined as wind speeds less than the activation wind speed threshold, and the high wind speed range is defined as wind speeds greater than the protection wind speed threshold. The protection wind speed threshold is greater than the high wind speed threshold, and the protection wind speed threshold is preset according to the structural strength limit of the swing generator.

[0008] Specifically, adjusting the moment of inertia of the oscillating generator according to the wind speed range includes: When the current wind speed is within the high-efficiency wind speed range, calculate the frequency deviation between the natural frequency and the main excitation frequency; generate control commands based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the swing-type generator until the frequency deviation is less than the preset tolerance. When the current wind speed is in the high wind speed range, the system enters the active protection mode, driving the inertia adjustment device to quickly adjust the rotational inertia to the maximum value, so as to reduce the natural frequency and destroy the resonance condition; when the current wind speed is in the low wind speed range, the system enters the low wind speed mode, driving the inertia adjustment device to adjust the rotational inertia to the target increase state, so as to reduce the natural frequency.

[0009] Specifically, the control command generated based on the frequency deviation drives the inertia adjustment device to change the mass distribution of the oscillating generator, including: determining the target position of the inertia adjustment device based on the frequency deviation through a preset frequency-inertia mapping relationship; generating a drive signal based on the position deviation between the target position and the current position of the inertia adjustment device, and driving the inertia adjustment device to move to the target position.

[0010] Specifically, the method also includes an amplitude safety monitoring step: in any operating mode, the amplitude of the oscillation state is calculated in real time; if the amplitude exceeds the safety threshold, the active protection mode is forcibly executed regardless of the wind speed range in which the current wind speed is located.

[0011] Specifically, the process of obtaining the current wind speed and the swing state of the energy harvester includes: collecting the swing angle data of the energy harvester through an angle sensor and collecting the swing angular velocity data through an angular velocity sensor; filtering the swing angle data to eliminate high-frequency noise interference, and extracting the swing amplitude and swing period based on the filtered data.

[0012] Specifically, obtaining the current natural frequency of the swing-type power generation device based on the swing state includes: performing spectral analysis on the swing state and extracting the dominant oscillation frequency as the natural frequency; or, calculating the swing frequency in the time domain through the extreme value of a single period of the swing state as the natural frequency.

[0013] Specifically, the oscillating power generation device includes an inertia adjustment device, which includes a mass distribution adjustment mechanism; adjusting the rotational inertia of the oscillating power generation device includes: driving the counterweight in the mass distribution adjustment mechanism to move along the guide rail, changing the instantaneous distance between the center of mass of the counterweight and the offset rotation axis of the oscillating power generation device, so as to nonlinearly adjust the rotational inertia of the oscillating power generation device.

[0014] A tuning control system for a wind-powered oscillating generator includes: a sensing module configured to acquire the current wind speed and the oscillation state of the energy harvester; a control module configured to execute a tuning control method for the wind-powered generator; and an execution module including an inertia adjustment device configured to adjust the rotational inertia of the oscillating generator in response to the control command of the control module.

[0015] Compared with the prior art, the technical solution provided by the embodiments of the present invention has the following advantages: The embodiments of the present invention acquire the current wind speed and the swing state and aerodynamic characteristic parameters of the energy harvester in real time, and determine the main excitation frequency of the wind field and the current natural frequency of the device accordingly, providing a precise deviation benchmark for subsequent frequency modulation control; on this basis, according to the matching result of the current wind speed and the preset wind speed range, the rotational inertia of the swing-type power generation device is dynamically adjusted, so that the natural frequency actively approaches and locks to the main excitation frequency within the conventional wind speed range, thereby reconstructing and maintaining the resonance condition in a wide wind speed range, fundamentally solving the problem of energy conversion under non-design conditions caused by frequency detuning in traditional devices. The technical challenge of drastically reduced efficiency has significantly improved the actual annual power generation. Simultaneously, for extreme wind conditions that deviate significantly from the design point, this method switches the moment of inertia to an extreme state, lowering the oscillation threshold to improve response sensitivity at ultra-low wind speeds and increasing the damping effect to suppress excessive sway at ultra-high wind speeds, achieving a synergistic balance between efficient capture and structural safety across the entire wind speed range. Furthermore, the entire control chain focuses solely on moment of inertia adjustment, eliminating complex pitch mechanisms or high-energy-consuming external excitations, significantly reducing system self-consumption and mechanical wear. This provides a rapid-response, reliable, and economical technical solution for distributed wind energy utilization. Attached Figure Description

[0016] Figure 1 A schematic diagram of a tuning control system for a wind-powered oscillating power generation device provided in an embodiment of the present invention; Figure 2 A flowchart of a tuning control method for a wind power generation device provided in an embodiment of the present invention; Figure 3 This is a hardware architecture diagram of a tuning control system for a wind-powered oscillating power generation device provided in an embodiment of the present invention. Detailed Implementation

[0017] The following detailed description of a specific embodiment of the present invention is provided in conjunction with the accompanying drawings. However, it should be understood that the scope of protection of the present invention is not limited to the specific embodiment.

[0018] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the technical solution of this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0019] The present invention will be described below through several specific embodiments. To keep the following description of the embodiments clear and concise, detailed descriptions of known functions and components may be omitted. When any component of an embodiment of the present invention appears in more than one drawing, the component may be represented by the same reference numerals in each drawing.

[0020] Figure 1 This is a schematic diagram of a tuning control system for a wind-powered oscillating generator provided in an embodiment of the present invention. Figure 2 A flowchart illustrating a tuning control method for a wind power generation device provided in an embodiment of the present invention. Figure 3 This is a hardware architecture diagram of a tuning control system for a wind-powered oscillating power generation device provided in an embodiment of the present invention.

[0021] like Figure 1 and Figure 2 As shown, this invention provides a tuning control method and system for a wind power generation device. This method dynamically reconstructs the device's dynamic characteristics to adapt to time-varying wind fields by real-time sensing of the environment and system state. The control method mainly includes the following steps: Obtaining the current wind speed and the oscillation state of the energy harvester.

[0022] Specifically, the current wind speed V represents the energy input level of the external wind field and is a fundamental variable for judging operating conditions and calculating excitation sources; the oscillation state of the energy harvester (such as the oscillation angle θ) reflects the current mechanical response characteristics of the device, including but not limited to motion parameters such as oscillation angle θ, angular velocity, or acceleration. In this embodiment, the acquisition of these two parameters constitutes the sensing basis of the control closed loop, providing both a quantitative basis for external environmental excitation and real-time feedback on the internal system response. It should be understood that although this embodiment uses wind speed and oscillation state as the main sensing objects, in other embodiments, auxiliary parameters such as wind direction, turbulence intensity, or structural stress can be combined to enrich the environmental sensing dimensions, as long as they can support subsequent operating condition judgment and frequency matching.

[0023] Based on the current wind speed and the aerodynamic characteristics of the energy harvester, the main excitation frequency of the current wind field is determined.

[0024] Among these, aerodynamic characteristic parameters are inherent properties describing the interaction between the geometry of the energy harvester and the fluid, establishing a mapping relationship between macroscopic wind speed and microscopic vortex shedding or aerodynamic fluctuation frequency. Specifically, for an energy harvester with a specific cross-sectional shape, the frequency of the periodic excitation force generated in the fluid is usually linearly or quasi-linearly related to the flow velocity, and this correlation is determined by the aerodynamic characteristic parameters. By obtaining these parameters through pre-calibration or simulation, the control system can quickly calculate the theoretical dominant excitation frequency based on the real-time wind speed during operation, without relying on complex real-time flow field calculations. This step transforms the fluid excitation, which cannot be directly measured, into a quantifiable control target value, providing a precise benchmark for subsequent frequency tracking. It should be noted that the dominant excitation frequency here refers to the dominant frequency component with the highest energy proportion acting on the energy harvester by the wind field, rather than the instantaneous pulsating frequency.

[0025] Based on the current wind speed range, adjust the rotational inertia of the oscillating generator so that its natural frequency tracks the main excitation frequency, or switch the rotational inertia to an extreme state, i.e., the maximum rotational inertia state that the system can achieve.

[0026] This is the core decision-making and execution step for achieving adaptive tuning in this embodiment. Specifically, the system presets multiple wind speed ranges, each corresponding to a different control objective. When the wind speed is within a range suitable for efficient energy capture, the control objective is to make the system's natural frequency as close as possible to or even equal to the main excitation frequency, i.e., to enter frequency tracking mode and maximize energy conversion efficiency using the resonance effect. When the wind speed exceeds the safe range or falls below the activation threshold, the control objective changes to adjusting the moment of inertia to a preset maximum or minimum value, etc., to actively deviate from the resonance zone or optimize low-frequency response characteristics.

[0027] From a physical perspective, there is a definite coupling relationship between the natural frequency and the moment of inertia of a swing-type power generation device, typically manifested as a decrease in natural frequency with increasing moment of inertia. Therefore, adjusting the moment of inertia by actively changing the mass distribution of the device essentially involves continuously reshaping the dynamic characteristics of the system. This adjustment method breaks through the limitation of the fixed natural frequency of traditional devices, allowing the device to adjust its characteristic parameters according to environmental changes, much like a living organism. For example, when frequency tracking is required, the adjustment amount of the moment of inertia is a continuous variable dynamically calculated based on the frequency deviation; while when switching to an extreme state is required, the moment of inertia is rapidly driven to a mechanical limit or a preset safety boundary position. It should be understood that although this embodiment uses the moment of inertia as the adjustment object, its essence is to affect the natural frequency by changing the system's inertial parameters, and any equivalent adjustment means that can achieve this physical effect should be included within the scope of protection of this invention.

[0028] Through the coordinated efforts of the above steps, this embodiment constructs a complete "perception-decision-execution" adaptive control framework. This framework not only solves the problem of sharp efficiency drops in fixed-parameter devices under non-design wind speeds, but also balances structural safety under extreme conditions with start-up performance at low wind speeds through a multi-condition zoning strategy, significantly improving the environmental adaptability of swing-type power generation devices to complex natural wind fields.

[0029] In some embodiments, to achieve precise capture of wind field energy, it is necessary to specifically design the calculation model of the main excitation frequency and the tracking mechanism of the natural frequency. As one implementation method, aerodynamic characteristic parameters include dimensionless constants and characteristic dimensions related to the cross-sectional shape of the energy trap. Specifically, the dimensionless constant is a key coefficient characterizing the vortex shedding behavior or aerodynamic fluctuation characteristics when fluid flows through a specific geometry; its value is usually determined by the cross-sectional profile of the energy trap. For example, for a bluff body flow scenario, this constant can be expressed as the Strouhal number St, but in a more refined control model, a Reynolds number correction factor can be introduced to reflect the nonlinear influence of viscous effects on the vortex shedding frequency, thus making it a comprehensive aerodynamic similarity criterion number. The characteristic dimension refers to the effective projected length of the energy trap perpendicular to the incoming flow direction; it is the geometric reference that determines the scale of fluid-structure interaction. By calibrating these parameters in advance in wind tunnel experiments or numerical simulations, the control system establishes a physical mapping channel from the macroscopic wind speed V to the microscopic excitation frequency f_ex.

[0030] Based on a dimensionless constant, characteristic size, and current wind speed, the dominant excitation frequency is calculated. In actual operation, the control module uses a pre-stored parameter model and substitutes the real-time acquired wind speed into the calculation to quickly determine the dominant excitation frequency f_ex exerted by the wind field on the energy harvester at the current moment. Specifically, the formula for calculating the dominant excitation frequency f_ex is as follows: ,in For Strauhal numbers, The current wind speed, The characteristic dimension is defined as follows. This frequency determination method based on a parametric model avoids the computationally intensive real-time fluid simulation in embedded controllers, significantly reducing system latency while ensuring computational accuracy, thus enabling high-frequency adaptive tuning. It should be understood that although this embodiment uses a specific dimensionless constant as an example, any aerodynamic characteristic description method that can establish a definite functional relationship between wind speed and excitation frequency falls within the protection scope of this invention.

[0031] Specifically, the preset wind speed ranges include a low wind speed range, a high-efficiency wind speed range, and a high wind speed range. The lower limit of the high-efficiency wind speed range is the starting wind speed threshold, which is preset based on the minimum starting wind speed of the swing-type power generation device. The upper limit of the high-efficiency wind speed range is the high wind speed threshold. The low wind speed range is defined as wind speeds less than the starting wind speed threshold, and the high wind speed range is defined as wind speeds greater than the protection wind speed threshold. The protection wind speed threshold is greater than the high wind speed threshold, which is preset based on the structural strength limit of the swing-type power generation device.

[0032] Specifically, adjusting the rotational inertia of the oscillating generator according to the wind speed range includes: when the current wind speed is in the high-efficiency wind speed range, calculating the frequency deviation between the natural frequency and the main excitation frequency; generating control commands based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating generator until the frequency deviation is less than the preset tolerance; when the current wind speed is in the high wind speed range, entering the active protection mode, driving the inertia adjustment device to quickly adjust the rotational inertia to the maximum value to reduce the natural frequency and destroy the resonance condition; when the current wind speed is in the low wind speed range, entering the low wind speed mode, driving the inertia adjustment device to adjust the rotational inertia to the target increase state to reduce the natural frequency.

[0033] Furthermore, after determining the target excitation frequency, the system needs to bring the device into a resonant state through closed-loop regulation. As one implementation method, when the current wind speed is within the high-efficiency wind speed range, the current natural frequency of the oscillating generator is obtained based on the oscillation state. This natural frequency is not a fixed design value, but a dynamic variable that changes in real time with the moment of inertia. The control system processes the time-series data collected by angle or angular velocity sensors to identify the device's true oscillation frequency f_sys under the current mass distribution, which is then used as feedback in the closed-loop calculation.

[0034] Subsequently, the frequency deviation Δf between the natural frequency f_sys and the main excitation frequency f_ex is calculated. This frequency deviation Δf quantifies the degree of mismatch between the current dynamic state of the system and the external wind farm excitation. If Δf is positive, it indicates that the system's natural frequency f_sys is higher than the wind farm excitation frequency f_ex, requiring an increase in rotational inertia to lower the frequency; conversely, if Δf is negative, the rotational inertia needs to be decreased to increase the frequency. Control commands are generated based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating generator until the frequency deviation Δf is less than the preset tolerance. Figure 2 As shown, this process constitutes a complete frequency tracking closed loop. Control commands convert the frequency domain deviation into displacement or torque commands for the actuator, driving the mass distribution adjustment mechanism. When the frequency deviation converges to a preset tolerance range, it indicates that the system has entered an effective resonance or quasi-resonance energy capture region. At this point, the control system can switch to steady-state maintenance mode or reduce the adjustment gain to prevent mechanical jitter or energy loss due to oversensitivity. This closed-loop mechanism effectively overcomes instantaneous disturbances caused by natural wind speed turbulence, ensuring that the device continuously maintains optimal energy conversion within a wide range of efficient wind speeds, significantly improving the average output power of the power generation system.

[0035] Based on the frequency tracking closed loop constructed in the aforementioned embodiments, this embodiment further provides a multi-condition adaptive extreme value switching strategy to cope with the complex, variable, and even extremely harsh operating conditions of natural wind fields. Adjusting the rotational inertia of the oscillating power generation device according to the current wind speed range also includes the following specific scenarios.

[0036] Specifically, when the current wind speed is within the high-efficiency wind speed range, the system maintains the aforementioned frequency tracking mode. This involves acquiring the current natural frequency of the oscillating generator based on its oscillation state, calculating the frequency deviation between it and the main excitation frequency, and generating control commands based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating generator until the frequency deviation Δf is less than the preset tolerance. Within this range, the control objective is refined dynamic matching. By continuously fine-tuning the rotational inertia, the system is kept locked in a resonant or quasi-resonant state, thereby maximizing energy capture efficiency. The high-efficiency wind speed range [V_opt_min, V_opt_max] is typically determined by the device's design parameters and the generator's rated power. Its upper limit, V_opt_max, is less than or equal to the protection wind speed threshold, V_protect, and its lower limit, V_opt_min, is greater than or equal to the start-up wind speed threshold, constituting the core operating zone for normal power generation.

[0037] When the current wind speed V exceeds the protection wind speed threshold V_protect, the system enters active protection mode, driving the inertia adjustment device to rapidly adjust the rotational inertia to its maximum value, thereby reducing the natural frequency and disrupting the resonance condition. It is important to clarify that the use of a "maximum state" rather than a "minimum state" for protection is based on rigorous vibration dynamics principles. This is determined according to the formula for calculating the natural frequency of a single-degree-of-freedom torsional vibration system. ,in For the system's equivalent torsional stiffness, This refers to the total moment of inertia. When the wind speed exceeds the safety threshold, the excitation frequency of the wind field on the energy harvester is usually high and the energy is enormous. If the moment of inertia is reduced at this time, the system's natural frequency will actually increase, making it very easy to couple with the high-frequency wind excitation, leading to amplitude divergence or even structural damage. Conversely, by moving the counterweight to its extreme position far from the axis of rotation, the moment of inertia can reach the maximum value allowed by the mechanical structure, which can significantly lower the system's natural frequency, forcing it to deviate from the current high-frequency excitation band, achieving "active detuning" or "passive vibration isolation." This protection mechanism based on inertia reconstruction, compared to traditional mechanical braking or damping energy dissipation methods, not only avoids the risk of wear and thermal failure of friction components, but also can quickly recover to an efficient tracking state after the wind speed drops, balancing safety and operational continuity.

[0038] When the current wind speed V is less than the starting wind speed threshold V_opt_min, the system enters a low-wind-speed mode, driving the inertia adjustment device to adjust the rotational inertia to the target increase state, thereby reducing the natural frequency and matching the low-frequency excitation. This control logic also follows the aforementioned dynamic laws, but its technical purpose is completely different from the protection mode. In light wind or low-wind-speed environments, the vortex shedding frequency or aerodynamic fluctuation frequency generated by fluid flowing over the energy harvester is inherently low. If the device maintains a small rotational inertia (i.e., a high natural frequency), the system will be unable to be effectively excited by the weak wind due to "frequency mismatch," resulting in difficulty starting or stalling. By adjusting the rotational inertia to the target increase state (this state can be a maximum value or a specific preset value between the maximum value and the optimal value in the high-efficiency zone), the system's natural frequency decreases accordingly, thereby achieving resonance matching with the low-frequency wind excitation and significantly reducing the device's cut-in wind speed threshold. It should be understood that although both the low-wind-speed mode and the active protection mode involve the action of "increasing rotational inertia," the former is to "cater" to low-frequency excitation for activation, while the latter is to "avoid" high-frequency excitation for protection. The triggering conditions, adjustment rates, and target final states of the two are clearly different. For example, the active protection mode requires a rapid response at the millisecond or second level to suppress sudden overload, while the low-wind-speed mode allows for a smoother adjustment process to adapt to steady-state light winds.

[0039] By classifying and differentiating the three operating conditions described above, this embodiment establishes an adaptive tuning system covering the entire wind speed range. This system corrects the misconception in traditional understanding regarding the direction of inertia adjustment, clarifies the correct logic of rotational inertia changes under different physical targets, and ensures the performance balance of the oscillating power generation device in three dimensions: efficient energy capture, safe survival, and low wind speed start-up.

[0040] Based on the closed-loop tuning framework established in the aforementioned embodiments, this embodiment further specifies the execution transition logic and state feedback mechanism in the control loop to provide a feasible algorithm implementation path. As one implementation method, generating control commands based on frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating power generation device includes: determining the target position of the inertia adjustment device based on the frequency deviation through a preset frequency-inertia mapping relationship. Specifically, since the natural frequency and moment of inertia of the oscillating system typically exhibit a nonlinear relationship (e.g., inversely proportional to the square root of the moment of inertia), and the moment of inertia itself is quadratic with the displacement of the counterweight, the frequency deviation cannot be directly and linearly converted into mechanical displacement. To improve the real-time response speed of the controller and reduce the online computational load, this invention pre-establishes a frequency-inertia mapping relationship. This mapping relationship can be obtained through offline calibration, for example, by traversing the system's natural frequencies at different counterweight positions in a wind tunnel or simulation environment to generate a "frequency-position" lookup table; or by deriving analytical expressions or piecewise fitting polynomials based on the system dynamics equations and storing them in the control module. Once the controller calculates the current frequency deviation, it can quickly calculate the target position of the inertia adjustment device required to eliminate the deviation by looking up a table or substituting into a formula, thus avoiding the complex real-time solution process of inverse dynamics.

[0041] Subsequently, a drive signal is generated based on the position deviation between the target position and the current position of the inertia adjustment device, driving the inertia adjustment device to move to the target position. This step realizes the final conversion from frequency domain control target to spatial domain mechanical execution. The control module compares the calculated target position with the current position fed back by the sensor to obtain the position deviation, and then generates a corresponding drive signal (such as PWM duty cycle, pulse sequence, or current command) through motion control algorithms (such as PID, sliding mode control, or fuzzy control) to drive the motor or hydraulic actuator to drive the mass distribution adjustment mechanism. It should be understood that although this embodiment uses a position closed loop as an example, in other embodiments, a composite control strategy of velocity feedforward plus position feedback can also be used, or an open-loop stepping control can be used in scenarios where high accuracy is not required, as long as the inertia adjustment device can be driven to the target state according to the frequency deviation. This hierarchical conversion mechanism not only ensures the accuracy of tuning, but also shields the nonlinear characteristics of the underlying mechanical structure through a preset mapping relationship, making the upper-level control strategy have good portability and robustness.

[0042] On the other hand, to ensure accurate state feedback in closed-loop control, this embodiment also provides specific means for obtaining the current natural frequency of the system. As one implementation method, obtaining the current natural frequency of the oscillating power generation device based on the oscillation state includes: performing spectral analysis on the oscillation state and extracting the dominant oscillation frequency as the natural frequency. Specifically, the control module performs Fourier transform (FFT) or power spectral density estimation on the time-series data collected by the angle sensor or angular velocity sensor within a certain time window, identifying the frequency component with the most concentrated energy as the current true natural frequency of the system. The advantage of this method is that it can effectively filter out high-frequency noise and non-dominant harmonic interference, providing extremely high frequency identification accuracy when the system is in steady-state oscillation or quasi-steady-state operation, and is particularly suitable for fine-tuning in the high-efficiency wind speed range. However, spectral analysis usually requires accumulating a certain amount of data to obtain sufficient frequency resolution, so there may be some lag during sudden changes in wind speed or during the transient process at the initial stage of system startup.

[0043] As another parallel implementation method, obtaining the current natural frequency of the oscillating generator based on its oscillation state can further include: calculating the oscillation frequency in the time domain using the extreme values ​​of a single cycle of the oscillation state as the natural frequency. Specifically, the control module monitors the zero-crossing points, peaks, or troughs of the oscillation angle or angular velocity signal in real time, and calculates the instantaneous period by recording the time interval between two adjacent extreme points or zero-crossing points in the same direction; the reciprocal of this period is the current oscillation frequency. This method does not require complex data caching and transformation operations, has extremely low computational latency and millisecond-level dynamic response capabilities, and is very suitable for rapid frequency capture during low-wind-speed start-up phases, transitional periods between operating conditions, or sudden gusts. In practical applications, the control system can adaptively switch between the two methods or use a weighted fusion based on the current operating mode or signal quality indicators. For example, during steady-state tracking, the spectral analysis method can be prioritized to ensure accuracy, while automatically switching to the time-domain extreme value method to improve response speed when the wind speed gradient exceeds a threshold or the frequency deviation diverges. This multimodal frequency identification strategy effectively compensates for the limitations of a single method, ensuring that the adaptive tuning system can obtain reliable state feedback across the entire operating range, and providing a solid data foundation for the aforementioned closed-loop control.

[0044] In some embodiments, to ensure the accuracy and reliability of adaptive tuning control, it is necessary to refine the sensing data and establish an independent safety protection mechanism. As one implementation method, acquiring the current wind speed and the oscillation state of the energy harvester includes: collecting oscillation angle data of the energy harvester through an angle sensor and oscillation angular velocity data through an angular velocity sensor; filtering the oscillation angle data to eliminate high-frequency noise interference, and extracting the oscillation amplitude and oscillation period based on the filtered data. Specifically, the angle sensor (such as a photoelectric encoder or inclinometer) provides reference information for the absolute position of the energy harvester, while the angular velocity sensor (such as a gyroscope) captures the dynamically changing rate characteristics. The two sensors complement and verify each other, effectively addressing the drift or distortion problems of a single sensor in a specific frequency band. Due to the complex environment of outdoor wind fields, the original acquired signals often contain high-frequency noise caused by mechanical vibration, electromagnetic interference, or turbulent pulsation. If directly used for frequency identification or closed-loop control, this can easily lead to malfunctions or system oscillations. Therefore, the control module integrates digital filtering algorithms, such as using a Butterworth low-pass filter to cut off noise components above the system's operating frequency band, or employing a Kalman filter algorithm combined with the system dynamics model to optimally correct the state estimate. Based on the filtered high signal-to-noise ratio data, the system uses a peak detection algorithm to identify the difference between adjacent peaks and troughs to calculate the oscillation amplitude, and accurately determines the oscillation period using the zero-crossing timing method or the extreme point interval method. This preprocessed, high-quality state parameter provides a solid data foundation for frequency tracking and operating condition judgment in the aforementioned embodiments, significantly improving the robustness of the control strategy in harsh environments.

[0045] Building upon this, to prevent structural damage due to sensor failure, control algorithm malfunction, or extreme gusts exceeding design limits, this embodiment also introduces a highest-priority hardware-level safety fallback mechanism. As one implementation method, this also includes an amplitude safety monitoring step: in any operating mode, the amplitude θ_amp of the swing angle θ is calculated in real time; if the amplitude θ_amp exceeds the safety threshold θ_max, the active protection mode is forcibly executed regardless of the wind speed range where the current wind speed V is located. The amplitude θ_amp can be calculated as follows: within a single swing cycle, the maximum and minimum values ​​output by the angle sensor are recorded, and half the difference between the two is taken as the swing amplitude θ_amp for the current cycle; or, in continuously sampled angle data, the peak angle within a preset time window is extracted as θ_amp. The core design of this mechanism lies in its independence and enforceability. Regardless of whether the system is currently in high-efficiency tracking, low-wind-speed startup, or any other normal operating state, and regardless of whether the wind speed sensor readings indicate safety, as long as the detected physical swing amplitude exceeds the preset structural safety boundary, the monitoring logic will immediately trigger an interrupt signal, directly taking over control and driving the inertia adjustment device to perform the maximum inertia adjustment action described in the aforementioned embodiments. From a systems engineering perspective, this constitutes a second line of defense, distinct from conventional protection strategies based on wind speed judgment. This is because wind speed sensors may have risks such as response lag, installation position deviation, or icing failure, while the actual swing amplitude of the energy harvester is the most accurate reflection of the structural load. By using amplitude exceeding the limit as an unconditional trigger condition, the system can cut off feedback loops that may lead to resonance divergence within milliseconds, forcing the system to switch to a detuned state. This effectively avoids catastrophic overload accidents caused by control logic deadlock or environmental perception errors, greatly improving the operational safety and survivability of the swing-type power generation device throughout its entire life cycle.

[0046] Building upon the control methods and algorithm logic described in the foregoing embodiments, this embodiment further provides a hardware platform to support the implementation of the aforementioned methods. As one implementation method, the oscillating power generation device includes an inertia adjustment device, which in turn includes a mass distribution adjustment mechanism. For example... Figure 1 and Figure 3As shown, the mass distribution adjustment mechanism is a physical execution unit that changes the dynamic characteristics of the system. In this embodiment, the mass distribution adjustment mechanism specifically includes a counterweight and a guide rail. The guide rail extends longitudinally along the energy trap, and its extension direction is approximately parallel to the height direction of the energy trap or perpendicular to the radial direction of the offset rotation axis. The counterweight is slidably connected to the guide rail and reciprocates along the guide rail under the drive of the drive motor and transmission components (such as a lead screw and nut pair or a synchronous belt). It should be understood that although this embodiment uses the linear motion form of "counterweight + guide rail" as a preferred example, this is not the only limitation on the mass distribution adjustment mechanism. In other embodiments, the mechanism can also adopt any mechanical structure that can adjust the rotational inertia of the system by changing the spatial distribution of mass relative to the rotation axis, such as a rotating flywheel assembly, a centrifugal pendulum, fluid mass transfer in a hydraulic chamber, or a multi-stage telescopic arm, as long as it can achieve the inertia adjustment function described in the foregoing embodiments.

[0047] Furthermore, adjusting the rotational inertia of the oscillating generator includes: moving the counterweight in the mass distribution adjustment mechanism along the guide rail, changing the instantaneous distance between the center of mass of the counterweight and the offset rotation axis of the oscillating generator, thereby nonlinearly adjusting the rotational inertia of the oscillating generator. The physical essence of this adjustment process is based on the definition of the rotational inertia of a rigid body. Let the mass of the counterweight be... The instantaneous distance from its center of mass to the offset rotation axis is Then the moment of inertia of the counterweight about the total rotation of the system is... The contribution amount approximately satisfies (Ignoring the moment of inertia of the counterweight about its center of mass). Therefore, it can be seen that when the drive mechanism causes the counterweight to make a linear displacement along the guide rail, the distance... A linear change occurs, while the moment of inertia... Then follow The square of exhibits a non-linear variation. This non-linear mapping relationship brings significant technical advantages to the adaptive tuning of this invention.

[0048] Specifically, this nonlinear adjustment characteristic firstly helps to broaden the system's frequency modulation range. Since the moment of inertia is proportional to the square of the distance, even if the movement of the counterweight is physically limited by the internal space of the energy harvester, the system can still achieve a large inertia change ratio, thus covering a wider natural frequency adjustment range, enabling it to adapt to all operating conditions from light wind start-up to strong wind protection. Secondly, the nonlinear characteristic endows the system with differentiated adjustment sensitivity. When the counterweight moves to a position far from the bias rotation axis (i.e., When the displacement increment is large, the same displacement increment will cause a larger change in inertia, which gives the system a high adjustment resolution when performing fine frequency tracking in the efficient wind speed range; while when the counterweight is close to the offset rotation axis (i.e., When the inertia is relatively small, the change in inertia is relatively gradual. This is beneficial for rapid and smooth large-range inertia switching during low-wind-speed startup or high-wind protection mode, avoiding system oscillations caused by adjustment overshoot. Through this ingenious combination of structure and physical principles, this embodiment provides a solid and efficient material basis for the aforementioned control method, enabling "linear displacement input" to be transformed into "nonlinear frequency response," effectively improving the dynamic adaptability of the oscillating power generation device to environmental wind conditions.

[0049] like Figure 3 As shown, this embodiment provides an adaptive tuning control system for a swing-type power generation device. This system, serving as the hardware carrier for the aforementioned method embodiments, achieves a complete closed loop from environmental perception to dynamic adjustment through a modular architecture. The adaptive tuning control system includes a sensing module, a control module, and an execution module.

[0050] The sensing module is configured to acquire the current wind speed and the oscillation state of the energy harvester. Specifically, the sensing module serves as the perception window for the system to interact with the external environment and its own mechanical state. In this embodiment, the sensing module may include a wind speed sensor and an angle sensor, used to collect real-time wind speed data flowing through the energy harvester and oscillation angle data of the energy harvester around its offset rotation axis, respectively. It should be understood that although only these two types of sensors are shown in the figure, in actual engineering applications, the sensing module can also integrate various sensing units such as angular velocity sensors, accelerometers, strain gauges, or wind vanes as needed to provide richer dimensions of state observation. At the hardware interface level, the sensing module can establish a data transmission link with the control module through analog signal lines, RS485 bus, CAN bus, or wireless communication protocols to ensure that the sensed data can be transmitted to the decision-making level with low latency and high reliability. In addition, the installation location of the sensor is not limited to the specific orientation shown in the figure, as long as it can effectively characterize the wind field excitation characteristics and system motion response. For example, the wind speed sensor can be installed at the upstream inflow point of the energy harvester or integrated on the top of the tower. This flexibility of layout allows the system to adapt to different on-site installation conditions.

[0051] The control module is configured to execute the adaptive tuning control method for the oscillating power generation device as described in any of the aforementioned method embodiments. Specifically, the control module is the core of the entire system's computation and decision-making, internally storing program code that implements logic such as frequency calculation, operating condition judgment, closed-loop tracking, and safety monitoring. In terms of hardware configuration, the control module should not be understood as being limited to a specific processor model or circuit board structure. For example, it can be an embedded microcontroller (MCU), digital signal processor (DSP), field-programmable gate array (FPGA), programmable logic controller (PLC), or even a distributed processing unit based on an industrial PC or edge computing gateway. For scenarios with high computing power requirements, a multi-core heterogeneous architecture can also be adopted, with a dedicated coprocessor responsible for high-frequency signal processing and spectrum analysis, and the main processor responsible for strategy scheduling and human-machine interaction. The control module receives raw data from the sensing module through an input interface, and after filtering, feature extraction, and algorithm calculation, generates corresponding control commands and sends them to the execution module through an output interface. This design approach, which decouples functional definition from hardware, ensures the portability of the technical solution of this invention across different computing power platforms and hardware generations, reserving ample space for subsequent product upgrades and iterations.

[0052] The execution module includes an inertia adjustment device configured to adjust the rotational inertia of the oscillating power generation device in response to control commands from the control module. Specifically, the execution module is the execution layer that converts digital control signals into physical mechanical actions. In this embodiment, the execution module mainly includes a drive motor, a transmission mechanism, and the counterweight and guide rail assembly described in the preceding embodiments. The drive motor receives PWM signals, pulse sequences, or current commands from the control module and converts the rotational motion into linear displacement of the counterweight along the guide rail through transmission mechanisms such as a lead screw and nut pair, synchronous belt, or gear and rack, thereby changing the mass distribution and rotational inertia of the system. It should be understood that although this embodiment uses a motor-driven linear motion mechanism as an example, the specific implementation of the execution module is not limited to this. In other embodiments, hydraulic cylinders, pneumatic actuators, shape memory alloy actuators, or electromagnetic actuators can also be used as power sources; the transmission method can also be wire rope traction, linkage mechanism, or centrifugal pendulum, etc. As long as the execution module can accurately and reliably change the inertial parameters of the energy harvester relative to the rotation axis according to the control commands, it falls within the protection scope of this invention. In addition, the execution module usually includes a position feedback unit (such as an encoder or limit switch) to transmit the actual position of the counterweight back to the control module in real time, forming a position servo closed loop to ensure the accuracy and safety of inertia adjustment.

[0053] Through the coordinated operation of the aforementioned sensing, control, and execution modules, this embodiment constructs a complete adaptive tuning hardware system. This system not only physically supports the complex frequency tracking and multi-condition switching strategies described in the previous method embodiments, but also decouples the sensing, decision-making, and execution functions through a modular interface design. This architectural design allows each part of the system to be selected and upgraded independently, reducing R&D and maintenance costs while enhancing the product's adaptability to different application scenarios and hardware supply chains. This ensures efficient and safe operation of the swing-type power generation device throughout its entire lifecycle at the engineering implementation level.

[0054] To more intuitively demonstrate the collaborative working effect of the adaptive tuning control methods in the aforementioned embodiments in actual operation, this embodiment provides a typical application scenario demonstration covering the entire life cycle from light wind start-up, efficient energy capture to extreme wind condition protection. It should be understood that the wind condition sequence described below is merely an exemplary scenario to illustrate the practicality of the technical solution of this invention, and is not intended to limit the applicable environment of this invention. In actual applications, the system can adapt to more complex and variable natural wind fields.

[0055] In the initial stage, it is assumed that the ambient wind speed is low, for example, below the preset start-up wind speed threshold. At this time, the energy harvester may be stationary or only in a state of weak irregular oscillation, unable to generate effective electrical energy output. After the control module detects this low wind speed condition through the sensing module, it automatically enters the low wind speed mode. In this mode, the control system does not pursue precise frequency tracking, but prioritizes solving the problem of "difficulty in starting up". Specifically, the control module generates a drive command, and the control execution module drives the counterweight block to move along the guide rail in a direction away from the bias rotation axis, adjusting the rotational inertia of the system to the target increase state. According to the dynamic principle explained in the aforementioned embodiment, the increase in rotational inertia will significantly reduce the natural frequency of the system, making it able to match the low-frequency vortex shedding excitation generated by the fluid under low wind speed. This active frequency reduction strategy effectively overcomes the defect of traditional fixed parameter devices that cannot resonate and start up in a light wind environment due to excessively high natural frequency, enabling the energy harvester to successfully establish a stable oscillating motion at low wind speeds, thereby widening the effective lower limit of the device's operating wind speed.

[0056] As the ambient wind speed gradually increases and enters the high-efficiency wind speed range, the system automatically switches to efficiency optimization mode. In this stage, the control objective becomes maximizing energy capture efficiency. Based on real-time collected wind speed and aerodynamic characteristic parameters, the control module continuously calculates the main excitation frequency of the current wind field, while simultaneously acquiring the system's current natural frequency through real-time identification of the oscillation state. When a frequency deviation is detected, the control system, through the aforementioned frequency-inertia mapping relationship, accurately calculates the target position of the counterweight required to eliminate the deviation and drives the execution module to make corresponding displacement adjustments. For example, when the wind speed increases, causing the main excitation frequency to increase, the system automatically fine-tunes the counterweight towards the rotation axis, reducing the moment of inertia to increase the natural frequency, thus relocking it to the new excitation frequency. Throughout the wind speed increase process, this closed-loop tracking mechanism ensures that the system's natural frequency dynamically matches the wind field's main frequency, maintaining a highly efficient resonant energy capture state and avoiding efficiency drops due to wind speed changes.

[0057] During normal operation, if a sudden gust of wind or turbulence occurs, causing the instantaneous wind speed to exceed the protected wind speed threshold, or if the amplitude safety monitoring step detects that the sway amplitude has exceeded the safety threshold, the system will immediately trigger the active protection mode. This is a high-priority safety interruption mechanism with a response speed far faster than conventional efficiency optimization adjustments. Once triggered, the control module ignores the current frequency tracking target and forcibly outputs limit control commands, driving the counterweight to move to the outermost limit point of the guide rail at the fastest speed, causing the system's moment of inertia to reach its maximum value. As mentioned earlier, the extremely large moment of inertia will lower the system's natural frequency to a level far below the current high-frequency wind excitation, thereby physically disrupting the resonance condition and achieving active detuning. In this state, the sway amplitude of the energy harvester will be quickly suppressed within a safe range, effectively preventing structural fatigue or mechanical damage caused by severe resonance. It is worth noting that even if the wind speed sensor reading does not exceed the limit, this protection mechanism will still be activated if the amplitude monitoring data is abnormal, providing the system with double safety assurance.

[0058] Once the gusts pass, the wind speed drops to a safe range, and the oscillation amplitude returns to normal, the system automatically exits the active protection mode and reassesses whether to enter the efficiency optimization mode or the low-wind-speed mode based on the current wind speed. For example, if the wind speed is still higher than the activation threshold but lower than the lower limit of the high-efficiency range, the system may temporarily maintain a large moment of inertia to ensure stable oscillation; if the wind speed returns to the high-efficiency range, the counterweight will be repositioned to the optimal tracking position, restarting the efficient energy capture cycle. This complete dynamic process verifies the ability of the invention's technical solution to smoothly switch between different operating conditions, as well as its comprehensive technical effect of balancing activation performance, energy capture efficiency, and structural safety across the entire wind speed range. Through this adaptive tuning strategy based on dynamic inertia reconfiguration, the oscillating power generation device exhibits excellent environmental adaptability and operational reliability.

[0059] The above inventions are merely a few specific embodiments of the present invention. However, the embodiments of the present invention are not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A tuning control method for a wind power generation device, characterized in that, Includes the following steps: Obtain the current wind speed and the oscillation state and aerodynamic characteristic parameters of the energy harvester; Based on the current wind speed and the aerodynamic characteristic parameters of the energy harvester, determine the main excitation frequency of the current wind field; based on the oscillation state, obtain the current natural frequency of the oscillating power generation device; Based on the matching of the current wind speed with the preset wind speed range, the wind speed range in which the current wind speed is located is determined. Based on the wind speed range, the rotational inertia of the oscillating power generation device is adjusted so that the natural frequency of the oscillating power generation device approaches the main excitation frequency, or the rotational inertia is switched to an extreme value state.

2. The tuning control method for a wind power generation device as described in claim 1, characterized in that, Determining the dominant excitation frequency of the current wind field based on aerodynamic characteristic parameters includes the following steps: The aerodynamic characteristic parameters of the energy harvester are obtained, including dimensionless constants and characteristic dimensions related to the cross-sectional shape of the energy harvester. The main excitation frequency of the current wind field is calculated based on the current wind speed, the dimensionless constant, and the characteristic size.

3. The tuning control method for a wind power generation device as described in claim 2, characterized in that, The preset wind speed range includes a low wind speed range, a high-efficiency wind speed range, and a high wind speed range. The lower limit of the high-efficiency wind speed range is the starting wind speed threshold, which is preset according to the minimum starting wind speed of the swing-type power generation device, and the upper limit of the high-efficiency wind speed range is the high wind speed threshold. The low wind speed range is defined as wind speed less than the start-up wind speed threshold, and the high wind speed range is defined as wind speed greater than the protection wind speed threshold. The protective wind speed threshold is greater than the high wind speed threshold, and the protective wind speed threshold is preset according to the structural strength limit of the swing-type power generation device.

4. The tuning control method for a wind power generation device as described in claim 3, characterized in that, The adjustment of the rotational inertia of the oscillating power generation device according to the wind speed range includes: When the current wind speed is within the high-efficiency wind speed range, the frequency deviation between the natural frequency and the main excitation frequency is calculated; a control command is generated based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating power generation device until the frequency deviation is less than the preset tolerance. When the current wind speed is in the high wind speed range, the system enters active protection mode, driving the inertia adjustment device to quickly adjust the rotational inertia to a maximum value, thereby reducing the natural frequency and breaking the resonance condition; when the current wind speed is in the low wind speed range, the system enters low wind speed mode, driving the inertia adjustment device to adjust the rotational inertia to a target increase value, thereby reducing the natural frequency.

5. The tuning control method for a wind power generation device as described in claim 4, characterized in that, The step of generating a control command based on the frequency deviation to drive the inertia adjustment device to change the mass distribution of the oscillating power generation device includes: determining the target position of the inertia adjustment device based on the frequency deviation through a preset frequency-inertia mapping relationship; generating a drive signal based on the position deviation between the target position and the current position of the inertia adjustment device, and driving the inertia adjustment device to move to the target position.

6. The tuning control method for a wind power generation device as described in claim 4, characterized in that, The method also includes an amplitude safety monitoring step: calculating the amplitude of the swing state in real time under any operating mode; If the amplitude exceeds the safety threshold, the active protection mode will be forcibly executed regardless of the wind speed range in which the current wind speed is located.

7. The tuning control method for a wind power generation device as described in claim 1, characterized in that, Obtaining the current wind speed and the swing state of the energy harvester includes: acquiring the swing angle data of the energy harvester through an angle sensor and acquiring the swing angular velocity data through an angular velocity sensor; filtering the swing angle data to eliminate high-frequency noise interference, and extracting the swing amplitude and swing period based on the filtered data.

8. The tuning control method for a wind power generation device as described in claim 3, characterized in that, The step of obtaining the current natural frequency of the swing-type power generation device based on the swing state includes: performing spectral analysis on the swing state and extracting the dominant oscillation frequency as the natural frequency; or, calculating the swing frequency in the time domain through the extreme value of a single period of the swing state as the natural frequency.

9. The tuning control method for a wind power generation device as described in claim 1, characterized in that, The oscillating power generation device includes an inertia adjustment device, which includes a mass distribution adjustment mechanism. Adjusting the rotational inertia of the oscillating power generation device includes: driving a counterweight in the mass distribution adjustment mechanism to move along a guide rail, changing the instantaneous distance between the center of mass of the counterweight and the offset rotation axis of the oscillating power generation device, so as to nonlinearly adjust the rotational inertia of the oscillating power generation device.

10. A tuning control system for a wind-powered oscillating generator, characterized in that, include: The sensing module is configured to acquire the current wind speed and the oscillation state of the energy harvester; the control module is configured to execute the tuning control method of the wind power generation device as described in any one of claims 1 to 9; the execution module includes an inertia adjustment device, configured to adjust the rotational inertia of the oscillating power generation device in response to the control command of the control module.

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