Grid-connected inversion control method and system for wind power generation

Abstract

The invention provides a grid-connected inversion control method and system for wind power generation, and belongs to the technical field of inverter control. The method comprises the following steps: pre-storing power optimization curves respectively corresponding to a plurality of different wind speed intervals; monitoring the real-time wind speed, recognizing the current wind speed interval according to the real-time wind speed, and calling the power optimization curve corresponding to the current wind speed interval as the maximum power point tracking reference to control the fan; when the braking requirement of the fan is detected, regenerative electric energy generated by the fan is converted into alternating current through a bidirectional power conversion circuit, and the alternating current is connected into a power grid or charges an energy storage device; the wind speed, output power and direct current bus voltage parameters are monitored in real time, when the super wind speed, super power or super voltage condition is detected, regenerative electric energy recovery braking is started firstly, and if the rotating speed still exceeds a safety threshold value, a mechanical braking mechanism is triggered. The economical efficiency and reliability of wind power generation can be improved.

Description

Technical Field

[0001] This invention relates to the field of inverter control technology, and in particular to a grid-connected inverter control method and system for wind power generation. Background Technology

[0002] Wind power is a crucial pillar of the renewable energy sector, directly impacting the clean transformation of the energy structure and the stability of power supply. In real-world wind farm environments, wind speeds fluctuate constantly, ranging from light breezes to strong winds within a short period. This necessitates continuous adjustments to the power generation system to maximize wind energy capture while ensuring equipment is not damaged by overload.

[0003] Most current wind power grid-connected inverters employ a fixed power point tracking (PPT) method, which is often optimized based on a specific typical wind speed condition during design. When wind speeds are low, the system can effectively capture energy, but once wind speeds increase, the same tracking method causes the output power to quickly approach or exceed the equipment's rated value, forcing the system to limit power to protect itself. Conversely, if safety-based power limiting at high wind speeds is prioritized, energy capture efficiency at low wind speeds will significantly decrease. Further complicating matters, frequent shifts in wind speed across different ranges can lead to power fluctuations or response lags, impacting grid stability. The core of this contradiction lies in the diversity of wind speed ranges and the varying power optimization requirements. Different wind speed ranges correspond to entirely different optimal operating points. At low wind speeds, tracking needs to be as loose as possible to maximize wind energy utilization, while at high wind speeds, power must be strictly limited to prevent excessive speed increases or voltage rises. However, the rapid fluctuations in wind speed make it difficult for the system to achieve smooth and precise power adjustments between these ranges. When a sudden strong wind arrives, the output power may momentarily exceed the safe range. If the power is simply limited at this time, some kinetic energy will be wasted during braking. If there is no timely intervention, it can easily lead to speed loss or electrical overload. The recovery of regenerative kinetic energy faces the same dilemma. If the energy generated during braking cannot be fed back in an orderly manner, it will further aggravate energy waste and heat loss.

[0004] How to achieve optimal power tracking across the entire wind speed range, effective energy recovery during braking, and reliable protection under extreme wind speed conditions in real-world environments with frequent wind speed fluctuations has become a key issue in improving the overall performance and reliability of wind power generation systems. Summary of the Invention

[0005] This invention provides a grid-connected inverter control method and system for wind power generation, which aims to effectively improve wind energy utilization efficiency, system stability and protection capabilities under extreme weather conditions, and significantly improve the economy and reliability of wind power generation.

[0006] In a first aspect, the present invention provides a grid-connected inverter control method for wind power generation, comprising: Multiple power optimization curves corresponding to different wind speed ranges are pre-stored, and the power optimization curves are power reference trajectories customized for each wind speed range; Monitor real-time wind speed, identify the current wind speed range based on the real-time wind speed, and call the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine; When a wind turbine braking demand is detected, the regenerative power generated by the wind turbine is converted into AC power through a bidirectional power conversion circuit and fed into the power grid or used to charge the energy storage device. The system monitors wind speed, output power, and DC bus voltage parameters in real time. When excessive wind speed, excessive power, or excessive voltage conditions are detected, the system first initiates regenerative braking. If the rotational speed still exceeds the safety threshold, the system triggers the mechanical braking mechanism.

[0007] Furthermore, the pre-stored power optimization curves corresponding to multiple different wind speed ranges include: The multiple different wind speed ranges cover low wind speed range, medium wind speed range and high wind speed range, and the power optimization curve is generated based on the wind turbine aerodynamic efficiency, transmission system loss and generator efficiency. The power optimization curves are stored in the form of power-speed relationship or power-DC voltage relationship, and each power optimization curve corresponds to a wind speed range as a maximum power point tracking reference trajectory.

[0008] Furthermore, based on the real-time wind speed, the current wind speed range is identified, and the power optimization curve corresponding to the current wind speed range is used as the maximum power point tracking reference trajectory, including: Real-time wind speed is obtained by wind speed sensors or estimated based on the back electromotive force of generators; The current wind speed range is determined and identified based on the average value of the real-time wind speed. When the real-time wind speed transitions from one wind speed range to another, it automatically switches to the power optimization curve corresponding to the other wind speed range. After switching, adjust the generator torque and speed to match the corresponding power optimization curve.

[0009] Furthermore, the step of converting the regenerative electrical energy generated by the wind turbine into alternating current via a bidirectional power conversion circuit for connection to the power grid or charging of the energy storage device includes: The bidirectional power conversion circuit includes a rectifier bridge, a boost DC / DC converter, and a DC / AC inverter. When braking is required, the bidirectional power converter is switched to energy feedback mode. The generator-side converter is controlled to apply electromagnetic braking torque, so that the wind turbine's kinetic energy is converted into regenerative electrical energy; The regenerated electrical energy is processed by the bidirectional power conversion circuit and then fed into the power grid or energy storage device in an orderly manner.

[0010] Furthermore, when excessive wind speed, excessive power, or excessive voltage conditions are detected, regenerative braking is first initiated. If the rotational speed still exceeds the safety threshold, a mechanical braking mechanism is triggered, including: When the above-peak wind conditions are detected, the power optimization curve corresponding to the high wind speed range is switched to first to limit the power. Then, the regenerative braking system is activated to reduce the rotational speed. The rotational speed is continuously monitored, and if the rotational speed still exceeds the safety threshold, the mechanical braking mechanism is triggered. When the overpower or overvoltage condition is detected, the regenerative energy recovery braking is directly activated.

[0011] Furthermore, the real-time monitoring of wind speed, output power, and DC bus voltage parameters includes: The wind speed parameters are obtained through sensors or estimation, and the output power is calculated through current and voltage sampling. The DC bus voltage parameters are obtained by voltage sampling; The wind speed parameters, output power, and DC bus voltage parameters are used to simultaneously support maximum power point tracking control and braking protection judgment.

[0012] Furthermore, the automatic switching to the power optimization curve corresponding to the other wind speed range includes: When the real-time wind speed remains within the other wind speed range, the automatic switching is performed; After automatic switching, torque adjustment is performed with the new power optimization curve as the target, so that the fan can smoothly transition to the new operating point.

[0013] Secondly, the grid-connected inverter control system for wind power generation provided by the present invention includes: The storage module is used to pre-store power optimization curves corresponding to multiple different wind speed ranges. The power optimization curves are power reference trajectories customized for each wind speed range. The monitoring module is used to monitor real-time wind speed, identify the current wind speed range based on the real-time wind speed, and call the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine. The conversion module is used to convert the regenerative electrical energy generated by the wind turbine into AC power through a bidirectional power conversion circuit when the wind turbine braking demand is detected, so as to connect it into the power grid or charge the energy storage device. The trigger module is used to monitor wind speed, output power and DC bus voltage parameters in real time. When excessive wind speed, excessive power or excessive voltage conditions are detected, the regenerative braking is activated first. If the speed still exceeds the safety threshold, the mechanical braking mechanism is triggered.

[0014] Furthermore, the storage module includes: The generation unit is used to generate the power optimization curve based on the wind turbine aerodynamic efficiency, transmission system losses, and generator efficiency. The curve optimization unit stores the power-speed relationship or the power-DC voltage relationship. Each power optimization curve corresponds to a wind speed range as a maximum power point tracking reference trajectory.

[0015] Furthermore, the monitoring module includes: The estimation unit is used to obtain real-time wind speed by acquiring it through a wind speed sensor or by estimating it based on the back electromotive force of a generator. The determination and identification unit is used to determine and identify the current wind speed range based on the average value of the real-time wind speed; An automatic switching unit is used to automatically switch to the power optimization curve corresponding to the other wind speed range when the real-time wind speed transitions from one wind speed range to another. The adjustment matching unit is used to adjust the generator torque and speed after switching to match the corresponding power optimization curve.

[0016] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a grid-connected inverter for wind power generation. By pre-storing customized power optimization curves for multiple specific wind speed ranges (e.g., 3-4 m / s to 11-12 m / s), it intelligently switches the MPPT (Maximum PowerPoint Tracking) reference trajectory based on real-time wind speed (estimated by sensors or back EMF), achieving optimal power tracking and smooth transition across the entire wind speed range. Simultaneously, a bidirectional power conversion circuit uses regenerative kinetic energy to be orderly fed back to the grid or energy storage device during electromagnetic braking, avoiding energy loss. When exceeding wind speed, power, or voltage limits is detected, a tiered protection mechanism is implemented sequentially, from power curve limiting and electromagnetic braking energy recovery to mechanical braking, ensuring system safety. This mechanism effectively improves wind energy utilization efficiency, system stability, and protection capabilities under extreme weather conditions, significantly enhancing the economics and reliability of wind power generation. Attached Figure Description

[0017] Figure 1 This is a flowchart of a grid-connected inverter control method for wind power generation, provided as an embodiment of the present invention.

[0018] Figure 2This is a schematic diagram of the module structure of a grid-connected inverter control method for wind power generation provided in an embodiment of the present invention.

[0019] Figure 3 This is a flowchart illustrating a grid-connected inverter control method for wind power generation, provided as an embodiment of the present invention.

[0020] Figure 4 This is a functional block diagram of a grid-connected inverter control system for wind power generation, provided as an embodiment of the present invention. Detailed Implementation

[0021] To further understand the content of this invention, a detailed description of the invention is provided in conjunction with the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0022] This invention discloses a grid-connected inverter for wind power generation. It innovatively provides a fusion control mechanism based on segmented power optimization curves for different wind speed ranges, combined with regenerative energy recovery and hierarchical protection. This solves the technical problem that in actual wind farms, frequent wind speed fluctuations make it difficult for traditional single MPPT curves to simultaneously achieve efficient capture at low wind speeds and safe power limiting at high wind speeds, and that sudden wind speed surges can easily lead to speed runaway or energy waste.

[0023] like Figures 1-4 The grid-connected inverter control method for wind power generation provided in this embodiment of the invention may specifically include: S100: Pre-stores power optimization curves corresponding to multiple different wind speed ranges.

[0024] In this embodiment, the power optimization curve is a power reference trajectory customized for each wind speed range. Real-time wind speed information is obtained from the operating data of the wind power generation equipment, and this wind speed information is compared with multiple pre-established wind speed ranges to determine the specific range to which the current wind speed belongs. For the determined wind speed range, the corresponding power optimization curve is retrieved from the microprocessor control unit. This power optimization curve serves as the power reference trajectory at the current wind speed, guiding the speed and torque adjustment of the power generation equipment. After obtaining the power reference trajectory, it is applied to the control logic of the power conversion circuit. By adjusting the operating parameters of the power generation equipment, its output power is made to closely match the power reference trajectory. If a change in wind speed is detected during operation, the wind speed range is re-compared, and a new power optimization curve is retrieved for parameter adjustment to ensure that the power output always dynamically matches the power reference trajectory in response to wind speed changes.

[0025] In one possible implementation, the process of obtaining real-time wind speed information from the operating data of wind power generation equipment involves sensors monitoring wind speed signals in real time, such as capturing data through anemometers installed on the wind turbine tower. This acquisition method ensures the immediacy and accuracy of wind speed information, thereby providing a reliable basis for subsequent comparisons. This approach can lead to more accurate range determination and helps avoid control deviations caused by data delays.

[0026] It should be noted that the specific method for comparing the wind speed information with multiple pre-established wind speed ranges is through comparison logic within the microprocessor. For example, if the current wind speed is 8 meters per second, and the preset ranges include 5-7 meters per second and 7-9 meters per second, then the comparison determines that it belongs to the 7-9 meters per second range. This comparison serves to quickly locate the adaptation curve because different ranges correspond to different aerodynamic characteristics, which can improve energy capture efficiency. For the determined wind speed range, the corresponding power optimization curve is retrieved from the microprocessor control unit. For example, the curve is pre-stored in the form of a lookup table. Once the range is determined, the corresponding table entry is directly indexed as a power reference trajectory to guide the speed and torque adjustment of the power generation equipment. The reason for this retrieval method is to reduce computational overhead, resulting in a fast response, and simultaneously supporting the system's adaptability from multiple perspectives. For instance, in low wind speed ranges, the curve emphasizes the maximum efficiency point, while in high wind speed ranges, the curve focuses on power limitation to avoid overload.

[0027] It should be noted that after obtaining the power reference trajectory, the process of applying it to the control logic of the power conversion circuit is to adjust the inverter output through pulse width modulation (PWM). For example, when the reference trajectory indicates a specific speed, the circuit correspondingly modifies the duty cycle to adjust the torque, making the output power fit the trajectory. This achieves fine control, and the technical effects include reducing mechanical wear and optimizing energy output, thus supporting overall stability from another perspective. For example, compared with traditional methods, this application can better match fluctuating wind speeds. If a change in wind speed is detected during operation, the wind speed range is re-compared. For example, when the wind speed increases from 8 m / s to 10 m / s, a re-comparison is triggered, switching to the new range, and a new power optimization curve is retrieved for parameter adjustment. This ensures that the power output always follows the wind speed change and dynamically matches the power reference trajectory. The reason for this dynamic adjustment is to cope with the randomness of wind speed, bringing continuous optimization effects. From multiple aspects, such as real-time and continuity, the robustness of the system is supported by each other. For example, in gust scenarios, the curve is quickly switched to prevent excessive power fluctuations, thereby maintaining grid stability.

[0028] S200: Monitors real-time wind speed, identifies the current wind speed range based on the real-time wind speed, and calls the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine.

[0029] The microprocessor control unit acquires real-time wind speed signals from an anemometer or calculates estimated wind speed signals from the generator's back electromotive force to obtain the current real-time wind speed value. The microprocessor control unit compares the obtained real-time wind speed value with pre-established threshold values ​​for multiple wind speed intervals to determine the wind speed interval to which the real-time wind speed value belongs, thus identifying the current wind speed interval. The microprocessor control unit retrieves a preset power optimization curve corresponding to the identified current wind speed interval from its memory and sets this power optimization curve as the maximum power point tracking reference curve. Using the set maximum power point tracking reference curve as a target, the microprocessor control unit adjusts the power conversion circuit to control the generator torque, achieving power output tracking of the wind turbine within the current wind speed interval.

[0030] In one embodiment, the microprocessor control unit acquires real-time wind speed signals from a wind speed sensor. These signals are obtained by directly measuring the ambient wind speed through the sensor and converting it into an electrical signal, which is then transmitted to the control unit. Alternatively, an estimated wind speed signal can be calculated from the back electromotive force of a generator. This calculation is based on the physical principle of the relationship between the voltage and rotational speed of the generator. The wind speed value is derived through a preset voltage-rotational speed mapping relationship, thereby obtaining the current real-time wind speed value. This approach ensures the accuracy and real-time nature of the wind speed data, which is beneficial for the precise response of subsequent control. For example, in environments with frequent wind speed fluctuations, this dual acquisition mechanism can avoid control interruptions caused by the failure of a single sensor and improve the robustness of the system.

[0031] In one embodiment, the microprocessor control unit compares the obtained real-time wind speed value with pre-established threshold values ​​for multiple wind speed intervals. These threshold values ​​are fixed boundary values ​​divided according to the aerodynamic characteristics of the wind turbine. By comparing step by step, the wind speed interval to which the real-time wind speed value belongs is determined, thereby identifying the current wind speed interval. This comparison process helps to map continuous wind speed changes to discrete optimization intervals, which is beneficial for achieving segmented fine control. For example, when the wind speed transitions from a low interval to a high interval, this judgment can trigger curve switching in a timely manner, reducing energy capture loss and improving overall efficiency.

[0032] In one embodiment, the microprocessor control unit retrieves a preset power optimization curve from memory corresponding to the identified current wind speed range. These curves are power-speed relationship curves optimized in advance based on experimental data or simulation. The power optimization curve is set as the maximum power point tracking reference curve. This retrieval and setting process ensures the relevance of the control reference, which is beneficial for maximizing the energy output of the wind turbine in a specific range. For example, in the medium wind speed range, retrieving the corresponding curve can guide the wind turbine to operate at the high efficiency point. Compared with the traditional single curve method, this segmented curve can better match the mechanical characteristics of the wind turbine, resulting in a higher energy recovery rate.

[0033] In one embodiment, the microprocessor control unit targets a set maximum power point tracking reference curve and adjusts the power conversion circuit to control the generator torque. This adjustment changes the electromagnetic torque of the generator by adjusting the switching signals of the circuit, enabling the wind turbine to track its power output within the current wind speed range. This control mechanism helps maintain the stable operation of the wind turbine and optimize power output. For example, in high wind speed ranges, torque regulation can prevent overspeed while ensuring the effective conversion of regenerative energy. This approach, closely integrated with the aforementioned wind speed identification and curve recall, forms a complete adaptive control chain, improving the overall performance and reliability of small wind power generation systems.

[0034] S300: When a wind turbine braking demand is detected, the regenerative power generated by the wind turbine is converted into AC power through a bidirectional power conversion circuit and fed into the power grid or used to charge the energy storage device.

[0035] The grid-connected inverter includes a bidirectional power conversion circuit, which supports energy flow from the generator side to the grid side or the energy storage side. When the wind turbine brakes, the microprocessor control unit controls the bidirectional power conversion circuit to convert regenerated electrical energy into AC power for grid connection or to charge the energy storage device.

[0036] When a wind turbine requires braking, the microprocessor control unit first acquires the turbine's operating status data, including rotational speed, power output, and wind speed information, to determine if braking conditions are met. If braking is required, the bidirectional power conversion circuit activates its energy conversion function to initially collect the regenerative energy generated by the turbine. After collecting the regenerative energy, the bidirectional power conversion circuit adjusts the voltage and frequency of the collected energy, converting it into AC power that meets grid requirements, or into DC power suitable for charging energy storage devices, ensuring the correct energy flow direction. After energy conversion, the microprocessor control unit determines the specific energy flow path based on grid connection status or the capacity requirements of the energy storage device. If grid connection conditions are met, the converted AC power is preferentially connected to the grid; if the energy storage device requires charging, the energy is directed to the storage device for storage. After the energy flow path is determined, the bidirectional power conversion circuit continuously monitors voltage and current parameters during energy transmission to ensure transmission stability. Simultaneously, the microprocessor control unit records the amount of energy recovered in real time to optimize the subsequent energy management process for wind turbine braking, ensuring the efficient utilization of regenerative energy.

[0037] For example, when a wind turbine requires braking, the microprocessor control unit acquires the turbine's operating status data. This acquisition process involves integrating sensors to collect real-time information on turbine speed, power output, and wind speed to determine whether braking conditions have been met. This determination is based on a preset threshold comparison; for instance, when the turbine speed exceeds a safe upper limit, the energy conversion function of the bidirectional power conversion circuit is activated to initially collect the regenerative electrical energy generated by the turbine. The advantage of this method is that it responds promptly to braking demands, avoids energy waste, and provides foundational data for subsequent conversion, thereby improving overall energy recovery efficiency.

[0038] In one possible implementation, after collecting regenerated electrical energy, a bidirectional power conversion circuit adjusts the voltage and frequency of the collected energy. This adjustment is achieved through a built-in transformer and rectifier, converting the energy into AC power that meets grid requirements, or into DC power suitable for charging energy storage devices, ensuring the correct direction of energy flow. This process matches different output demands, reduces transmission losses, and ensures system compatibility, thereby making energy utilization more stable and reliable.

[0039] For example, after the power conversion is completed, the microprocessor control unit determines the specific energy flow path based on the grid connection status or the capacity requirements of the energy storage device. This determination process involves real-time monitoring of grid voltage fluctuations and the remaining energy storage capacity. If the grid connection conditions are met, the converted AC power is preferentially connected to the grid. If the energy storage device has charging needs, the power is directed to the energy storage device for storage. This path selection optimizes energy allocation, prioritizes meeting grid demand to reduce peak loads, and provides backup for energy storage, thereby improving the system's flexibility and sustainability.

[0040] In one possible implementation, after the energy flow path is determined, the bidirectional power conversion circuit continuously monitors the voltage and current parameters during the power transmission process. This monitoring is achieved through a feedback loop to ensure transmission stability. Simultaneously, the microprocessor control unit records the amount of energy recovered in real time to optimize the energy management process of subsequent wind turbine brakes, ensuring the efficient utilization of regenerated electricity. This continuous monitoring and recording serves to prevent transmission failures, accumulate data for future adjustments, and ultimately achieve zero energy waste, thereby extending equipment lifespan and enhancing the reliability of protection mechanisms.

[0041] For example, from multiple perspectives, this energy recovery process is particularly effective in high-wind-speed scenarios. For instance, when wind speed suddenly increases, the initial collection of regenerated energy can quickly reduce the rotational speed, while subsequent conversion and path determination support the smooth transfer of energy to the grid or energy storage. These directions support each other, forming a complete braking chain, improving power generation efficiency and reducing mechanical wear. In another scenario, such as when power output is abnormal, voltage regulation combined with monitoring ensures safe charging and avoids overload risks. These examples collectively demonstrate the practicality of the method and bring the beneficial effect of improved energy utilization.

[0042] S400: Real-time monitoring of wind speed, output power and DC bus voltage parameters. When over-wind speed, over-power or over-voltage conditions are detected, regenerative braking is initiated first. If the speed still exceeds the safety threshold, the mechanical braking mechanism is triggered.

[0043] The microprocessor control unit continuously acquires DC bus voltage, output power, and wind speed parameters from sensors and compares these parameters with preset thresholds. If at least one parameter exceeds the corresponding preset threshold, the generator-side converter is switched to torque control mode and electromagnetic braking torque is applied, causing the wind turbine speed to decrease and generating regenerative energy. This regenerative energy is converted into AC power by a power conversion circuit and fed into the power grid or used to charge an energy storage device. Simultaneously, the wind turbine speed is acquired in real time and compared with a safety threshold. If the wind turbine speed still exceeds the safety threshold, a mechanical braking mechanism is triggered to perform braking.

[0044] In one embodiment, the microprocessor control unit acquires DC bus voltage, output power, and wind speed parameters from sensors. By continuously monitoring these parameters and comparing them with preset thresholds, it can identify potential risks in a timely manner. For example, when the wind speed parameter suddenly increases, this comparison helps to avoid overloading the wind turbine, thereby improving the stability and durability of the system.

[0045] Specifically, this monitoring mechanism is similar to a real-time sentinel. Sensors such as voltage sensors and anemometers provide data directly, while the microprocessor runs an embedded program to compare thresholds. If the voltage value exceeds the threshold, this not only prevents electrical damage but also reduces energy waste through early intervention, which is beneficial to maintaining overall power generation efficiency.

[0046] In one embodiment, if at least one of the parameter values ​​exceeds a threshold, the generator-side converter is controlled to switch to torque control mode and apply electromagnetic braking torque to reduce the wind turbine speed and generate regenerative power. For example, in the case of wind speed exceeding 12 m / s, the converter switches from normal power generation mode to applying reverse torque, which is similar to the regenerative braking system of a car. The speed reduction process converts kinetic energy into electrical energy, avoiding the mechanical stress caused by direct hard stop. The beneficial effect is to extend the life of wind turbine components and recover energy, supporting sustainable operation.

[0047] In one embodiment, the regenerated electrical energy is converted into AC power by a power conversion circuit and fed into the grid or used to charge an energy storage device. At the same time, the wind turbine speed value is acquired in real time and compared with a safety threshold. For example, the conversion circuit includes a DC / AC inverter to convert DC regenerated electrical energy into standard 50Hz AC power and feed it into the grid. This not only recovers energy that might otherwise be wasted, but also provides backup power when charging the energy storage device. The comparison of the speed value ensures continuous monitoring of the braking process, which is beneficial for achieving a smooth transition and enhancing the system's adaptability to sudden wind changes.

[0048] In one embodiment, if the turbine speed still exceeds the safety threshold, a mechanical braking mechanism is triggered to perform braking. For example, when electromagnetic braking is insufficient to control the speed, a mechanical brake such as a disc brake is activated. This serves as a secondary protection layer to supplement the shortcomings of the electromagnetic approach. The beneficial effect is that graded protection reduces the burden of a single mechanism, ensuring that the turbine can be safely shut down under extreme conditions. At the same time, this strategy of combining recovery and braking improves overall energy efficiency and reliability.

[0049] Specifically, the process from monitoring to final braking forms a closed loop. The application of electromagnetic torque first recovers energy, while the intervention of mechanical braking serves as a backup. Multiple aspects, such as energy utilization and safety assurance, support each other, jointly achieving an effective response to conditions of excessive wind speed, excessive power, or excessive voltage. For example, in gusty wind environments, electrical energy is first recovered through torque control; if this is ineffective, mechanical braking is then used. This not only reduces the impact but also optimizes resource utilization, contributing to a reduction in long-term operating costs.

[0050] In one embodiment, this mechanism is extended to different wind speed ranges. The judgment of monitoring parameters directly affects the mode switching. The reduction of the rotation speed of the electromagnetic brake is closely linked to the subsequent comparison to ensure that the conversion of regenerative power is not interrupted. The triggering of the mechanical brake depends on the comparison result, forming a progressive protection chain. The beneficial effects are reflected in reducing the failure rate and improving the continuity of power generation.

[0051] The multiple different wind speed ranges include at least the 3-4 m / s range, the 5-6 m / s range, the 7-8 m / s range, the 9-10 m / s range, and the 11-12 m / s range. The power optimization curve is generated by integrating the aerodynamic efficiency of the wind turbine, transmission loss, and generator efficiency. Each curve corresponds to a wind speed range as the MPPT reference trajectory.

[0052] The current wind speed value is obtained from real-time monitored wind speed data and compared with a pre-established wind speed range to determine the range to which the current wind speed belongs. This range includes at least five intervals: 3-4 m / s, 5-6 m / s, 7-8 m / s, 9-10 m / s, and 11-12 m / s, resulting in a corresponding wind speed range identifier. For each identified wind speed range identifier, a corresponding power optimization curve is extracted from a pre-set power optimization curve library. This curve comprehensively considers the wind turbine's aerodynamic efficiency, transmission losses, and generator efficiency, ensuring that each curve corresponds one-to-one with a specific wind speed range, forming a reference trajectory for maximum power point tracking. The extracted power optimization curve is loaded into the control unit, and based on the correspondence between power and speed or DC voltage on the curve, the wind turbine's operating parameters are adjusted in real time to bring its operating point close to the optimal position on the reference trajectory. After adjusting the wind turbine operating parameters, the wind speed changes are continuously monitored. If the wind speed crosses into a new range, the new wind speed range identifier is re-acquired, and the process of extracting curves and adjusting parameters is repeated to ensure that the power optimization curve always matches the current wind speed range and maintain the accuracy of maximum power point tracking.

[0053] The current wind speed value is obtained from a real-time wind speed sensor and matched against a pre-established wind speed range, which includes at least 3-4 m / s, 5-6 m / s, 7-8 m / s, 9-10 m / s, and 11-12 m / s, to obtain a current wind speed range identifier. For each wind speed range identifier, a corresponding curve is selected from a pre-set set of power optimization curves. The curve generation process involves first obtaining the aerodynamic efficiency from the wind turbine blades' aerodynamic characteristics and determining the power input level by calculating the wind energy capture ratio; secondly, obtaining the transmission losses from the mechanical transmission components and determining the energy consumption ratio by evaluating friction and gear meshing losses; thirdly, obtaining the generator efficiency from the generator's electromagnetic conversion characteristics and determining the output power ratio by analyzing coil resistance and magnetic flux density; and finally, subtracting the transmission losses from the aerodynamic efficiency and multiplying by the generator efficiency to synthesize a power-speed relationship, forming a curve corresponding to a wind speed range. The selected corresponding curve is input into the control unit, and the wind turbine blade tilt angle and generator load are adjusted in real time according to the power-speed relationship in the curve, ensuring the operating trajectory follows the points on the curve. After following the operating trajectory, the system continuously acquires updated wind speed values ​​from the wind speed sensor. If the updated wind speed value exceeds the current wind speed interval, a new wind speed interval is determined through re-matching and the corresponding curve is selected as the maximum power point tracking reference trajectory. The microprocessor control unit determines the wind speed interval switching based on the average value or duration of the real-time wind speed. When the wind speed transitions from one interval to an adjacent interval, the microprocessor control unit automatically switches the MPPT reference from the current curve to the target curve and adjusts the generator torque and speed to match the target curve.

[0054] The microprocessor control unit acquires wind speed measurements from a wind speed sensor or wind speed values ​​estimated based on the generator's back electromotive force in real time. It then calculates the average wind speed to determine the current average wind speed. The microprocessor control unit compares the current average wind speed with pre-established threshold values ​​for multiple wind speed intervals to determine if the current average wind speed has crossed into an adjacent wind speed interval. If it has, it determines the target power optimization curve corresponding to the target wind speed interval. The microprocessor control unit automatically switches from the current power optimization curve to the determined target power optimization curve and adjusts the generator torque according to the target power optimization curve to match the speed point corresponding to the target curve. The microprocessor control unit continuously monitors the generator speed and torque matching status and performs fine-tuning based on the target power optimization curve to achieve a stable match between generator torque and speed.

[0055] In one possible implementation, the microprocessor control unit collects wind speed data in real time through a wind speed sensor. For example, in an environment with large wind speed fluctuations, the sensor collects data once per second to capture instantaneous changes. This acquisition method ensures the timeliness of the data, thus providing a reliable basis for subsequent average value calculation. Furthermore, estimating the wind speed value based on the generator's back electromotive force involves monitoring the relationship between the voltage and speed generated by the generator. The wind speed is derived through a preset voltage-speed mapping relationship. This estimation method serves as a backup in case of sensor failure, improving the robustness of the system and facilitating continuous monitoring.

[0056] Specifically, when calculating the average value of the acquired wind speed, the sliding window averaging method can be used to average multiple wind speed samples over a recent period to smooth out short-term fluctuations. This can accurately reflect the current average wind speed and avoid misjudgments caused by instantaneous gusts, thereby improving the accuracy of wind speed range judgment.

[0057] In one possible implementation, the current average wind speed is compared with multiple pre-established wind speed range thresholds. For example, the thresholds could be set as ranges from low to high, such as low-wind-speed zones to high-wind-speed zones. Each range corresponds to a specific power optimization curve. When the average wind speed crosses from below a threshold to above it, a range switch is identified. This comparison process is implemented through step-by-step threshold checks to ensure the accuracy of the switch determination. It should be noted that if a range is crossed, the target power optimization curve corresponding to the target wind speed range is determined. This curve is based on a pre-stored power-speed relationship diagram based on the wind turbine's characteristics. The determination process involves retrieving the matching curve from the storage unit. This approach facilitates rapid response to wind speed changes and optimizes power output.

[0058] In one possible implementation, the microprocessor control unit automatically switches from the current power optimization curve to a predetermined target power optimization curve, for example, switching to a curve in a higher wind speed range when the wind speed increases. This switching is achieved by updating control parameters to avoid power output interruption. Furthermore, the generator torque is adjusted according to the target power optimization curve to match the speed point corresponding to the target curve. The adjustment process involves adjusting the converter output to change the electromagnetic torque so that the speed tracks the optimal point on the curve. This enables efficient energy conversion and helps improve power generation efficiency.

[0059] In one possible implementation, the microprocessor control unit continuously monitors the generator speed and torque matching status. For example, it compares the actual speed with the speed set on the target curve in real time through a feedback loop. If a deviation exists, it performs fine adjustments to the target power optimization curve, such as fine-tuning the torque increment to reduce the deviation, thereby achieving a stable match between the generator torque and speed. It should be noted that this monitoring and adjustment forms a closed-loop control, which is beneficial for maintaining stable operation under dynamic wind conditions and reducing mechanical stress.

[0060] The bidirectional power conversion circuit includes a three-phase rectifier bridge, a BOOST boost DC / DC converter, and a DC / AC inverter. The microprocessor control unit switches the DC / DC converter and inverter to operate in energy feedback mode in braking mode, converting wind power into electrical energy and feeding it into the power grid or energy storage device in an orderly manner.

[0061] The bidirectional power conversion circuit includes a three-phase rectifier bridge, a boost DC-DC converter, and a DC-AC inverter. Upon detecting a braking command, the microprocessor control unit switches the boost DC-DC converter to operate in the energy feedback direction, boosting the electrical energy generated by the generator to the DC bus voltage level. Once the DC bus voltage level is maintained, the microprocessor control unit instructs the DC-AC inverter to operate in active inverter mode, converting the electrical energy on the DC bus into AC power that meets the grid phase and voltage requirements. The AC power output from the DC-AC inverter is fed into the grid in an orderly manner through a grid-connected switch, or, when an energy storage device is connected, is preferentially directed to the charging interface of the energy storage device, achieving an orderly conversion and feedback of wind turbine energy into electrical energy. Throughout the feedback process, the microprocessor control unit continuously adjusts the duty cycle and phase of the boost DC-DC converter and the DC-AC inverter to ensure a smooth feedback current that meets grid harmonic requirements until the wind turbine speed drops to a safe range.

[0062] For example, in practical applications of bidirectional power conversion circuits, the coordinated operation of the three-phase rectifier bridge, boost DC-DC converter, and DC-AC inverter is crucial for achieving energy feedback. The three-phase rectifier bridge is responsible for converting the AC power generated by the generator side into DC power, especially in braking mode where the electrical energy generated when the wind turbine speed decreases needs to be effectively collected. At this time, the three-phase rectifier bridge converts the unstable AC power into DC power through rectification, laying the foundation for subsequent energy boosting. The advantage of this is that it can maximize the capture of the wind turbine's kinetic energy and avoid energy waste.

[0063] Specifically, when the boost DC converter receives rectified DC power, it adjusts its operating state according to instructions from the microprocessor control unit, boosting the voltage to a level suitable for the DC bus. This boosting process ensures the stability of power transmission, especially when the wind turbine speed fluctuates significantly; maintaining voltage stability is crucial for subsequent inversion. This method not only protects circuit components but also guarantees efficient energy feedback.

[0064] In one embodiment, once the DC bus voltage stabilizes, the DC-AC inverter begins converting the DC power into AC power that meets grid requirements. For example, in grid-connected scenarios, the inverter precisely matches the grid's phase and frequency to ensure that the output AC power does not interfere with the grid. This precise conversion improves the compatibility of energy feedback while reducing the impact of harmonics on the grid, thus ensuring grid-connected safety.

[0065] Furthermore, during energy feedback, the continuous adjustment of the duty cycle and phase of the boost DC-DC converter and DC-AC inverter by the microprocessor control unit is particularly important. For example, in scenarios where energy storage devices are connected, the control unit will prioritize directing electrical energy to the charging interface of the energy storage device to ensure that energy is effectively stored. The advantage of this adjustment mechanism is that it can flexibly allocate electrical energy according to actual needs, satisfying both the grid feedback requirements and the energy storage needs.

[0066] It is important to note that orderly transmission via grid-connected switches is crucial during the energy feedback to the grid or energy storage devices. For example, when the grid load is low, electrical energy can be preferentially stored in energy storage devices, while during periods of high load, it can be directly fed back to the grid. This flexible allocation method effectively improves energy utilization efficiency while reducing mechanical losses during wind turbine braking, thus extending equipment lifespan.

[0067] Finally, the ultimate goal is to gradually reduce the turbine speed to a safe range throughout the entire energy conversion and feedback process. For example, by combining electromagnetic braking with energy feedback, the turbine can smoothly decelerate without relying on mechanical brakes. This method not only reduces wear on mechanical parts but also maximizes the conversion of kinetic energy into usable electrical energy, demonstrating the dual advantages of energy saving and protection.

[0068] After the microprocessor control unit issues a braking command, the generator-side converter operates in torque control mode to apply an adjustable electromagnetic braking torque. The regenerated electrical energy is processed by the bidirectional power conversion circuit. When the speed drops to a safe threshold, energy recovery stops and mechanical braking is prepared.

[0069] Upon detecting excessive wind speed or power conditions, the microprocessor control unit issues a braking command. The generator-side converter switches to torque control mode and applies adjustable electromagnetic braking torque by adjusting the reference torque value, causing the wind turbine speed to decrease. The regenerative electrical energy generated during the turbine speed reduction process is rectified by the generator-side converter and transmitted to the bidirectional power conversion circuit. The bidirectional power conversion circuit converts this regenerative electrical energy into AC power that meets grid requirements and connects it to the grid or charges the energy storage device. The microprocessor control unit continuously monitors the speed signal. When the speed drops to a preset safety threshold, it stops the electromagnetic braking torque adjustment in torque control mode, terminating the regenerative energy recovery process. After the speed stabilizes at the safety threshold, the microprocessor control unit sends a trigger signal to the mechanical braking mechanism, preparing to execute the mechanical brake to complete the final stop.

[0070] Specifically, the process of wind turbine speed control and energy recovery can be analyzed and illustrated from multiple perspectives to demonstrate its implementation and beneficial effects. First, when the microprocessor control unit detects abnormal conditions, it issues a braking command. The generator-side converter enters torque control mode, applying electromagnetic braking force by adjusting the torque value, thus gradually reducing the wind turbine speed. The core of this method lies in the dynamic adjustment of the electromagnetic torque, which can flexibly adjust the braking force based on real-time speed and load conditions. For example, in a scenario where wind speed suddenly increases, the microprocessor can quickly calculate a suitable torque value and apply a gradually increasing braking force to avoid mechanical stress concentration caused by a rapid decrease in speed, thereby protecting the equipment.

[0071] Next, the regenerative electrical energy generated during the turbine's deceleration is effectively utilized. The generator-side converter converts kinetic energy into electrical energy, which is then processed by a bidirectional power conversion circuit to output AC power that meets requirements for grid connection or to charge energy storage devices. For example, in a wind power generation scenario, when the turbine enters braking mode due to high wind speeds, the excess electrical energy generated can be rectified and converted into standard frequency AC power, directly fed back into the grid, reducing energy waste and improving overall energy efficiency.

[0072] Furthermore, the microprocessor continuously monitors the speed signal, and once the speed reaches a safe range, it stops adjusting the electromagnetic braking torque, terminating the energy recovery process. The real-time nature of this monitoring and control is crucial. For example, when the speed approaches a safe value, the microprocessor can gradually reduce the torque value, allowing the fan speed to smoothly transition to the target range, avoiding the shock caused by sudden changes, and preparing for subsequent mechanical braking.

[0073] Finally, once the rotational speed stabilizes, the microprocessor sends a signal to the mechanical braking mechanism, preparing to execute the final shutdown operation. This staged braking method significantly reduces wear on mechanical components. For example, in a long-running wind turbine, frequent direct use of the mechanical brake can lead to rapid wear of the brake pads. However, by combining electromagnetic braking with mechanical braking, the number of mechanical brake activations can be minimized, extending equipment lifespan while ensuring a smooth and safe shutdown process. Through these multi-layered implementation methods, the comprehensive advantages of this control method in terms of energy utilization and equipment protection can be seen.

[0074] The graded protection process sequentially switches to the highest wind speed range optimization curve for power limitation. The highest wind speed range optimization curve is the curve corresponding to the 11-12 m / s range that limits the maximum power output. Then, the regenerative energy recovery braking is initiated. If the rotation speed still cannot be controlled, the mechanical braking mechanism is triggered.

[0075] The control unit continuously monitors real-time wind speed. When it detects that the wind speed consistently exceeds the preset cutoff wind speed, it immediately switches the maximum power point tracking control to the power optimization curve corresponding to the highest wind speed range. This curve pre-limits the maximum power output for the highest wind speed range to reduce the turbine speed. After switching to the power optimization curve for the highest wind speed range, the control unit continues to monitor the turbine speed. If the speed is still higher than the safety threshold, it initiates regenerative braking, converting the turbine's kinetic energy into electrical energy through a power conversion circuit and feeding it into the grid or charging the energy storage device to further reduce the speed. During regenerative braking, the control unit continuously determines whether the speed has dropped below the safety threshold. If the speed still cannot be controlled within the safety threshold, it triggers the mechanical braking mechanism to achieve final braking. The entire tiered protection process is executed by the control unit in the order of switching the power optimization curve, regenerative braking, and triggering the mechanical braking mechanism, until the turbine speed is fully controlled.

[0076] The control unit continuously monitors the real-time wind speed signal during wind turbine operation. When it is determined that the wind speed continuously exceeds the preset cut-out wind speed, it first performs a switching operation, adjusting the maximum power point tracking control target from the current power optimization curve to the power optimization curve corresponding to the highest wind speed range. This curve is pre-set with a lower maximum power output limit for the highest wind speed range to actively reduce the generator torque, thereby causing the wind turbine speed to begin to decrease.

[0077] In one embodiment, the power optimization curve corresponding to the highest wind speed range is realized through a pre-stored multi-segment wind speed-power correspondence. When the wind speed enters the range, the control unit directly calls the segment of the curve as a reference to limit the output power within a safe range. This switching enables the wind turbine to switch from pursuing maximum power to a priority protection state, quickly responding to over-wind speed conditions and preventing the speed from increasing further.

[0078] After switching to the power optimization curve in the highest wind speed range, the control unit continues to monitor the wind turbine speed change in real time. If the speed still does not drop below the preset safety threshold, the regenerative energy recovery braking process is immediately started. The generator is put into electromagnetic braking mode by controlling the power conversion circuit to convert the remaining kinetic energy into electrical energy and feed it back to the grid or energy storage device in an orderly manner, further enhancing the speed reduction effect.

[0079] Specifically, regenerative braking relies on a power conversion circuit with bidirectional energy flow control. An adjustable electromagnetic torque is applied to the generator-side converter, and the generated regenerative energy is transmitted to the inverter side via the DC bus and converted into AC power that conforms to the grid standard. This method not only reduces the speed but also achieves orderly energy utilization and extends the buffer time of the protection process.

[0080] During the continuous execution of the regenerative braking, the control unit maintains real-time judgment of the rotation speed. If the rotation speed is still higher than the safety threshold after the braking, the mechanical braking mechanism is directly triggered to achieve hard braking to ensure that the wind turbine stops completely.

[0081] In one possible implementation, the mechanical braking mechanism acts as the final protection layer, intervening only when electromagnetic braking cannot fully control the rotational speed. This hierarchical sequence ensures that the protection process gradually transitions from soft power limiting to energy recovery and then to mechanical intervention, progressively improving overall safety and stability.

[0082] It should be noted that the entire graded protection process is strictly executed by the control unit in a fixed sequence of power optimization curve switching, regenerative energy recovery braking, and mechanical brake triggering, until the speed is confirmed to be fully controlled. This sequential design ensures that the protection measures at each stage are closely linked, and the speed reduction result of the previous stage directly determines whether to enter the next stage, thus achieving continuous and reliable overwind protection.

[0083] When the microprocessor control unit continuously monitors the DC bus voltage and the output power, if the voltage exceeds the preset threshold or the output power exceeds the rated value, the microprocessor control unit immediately activates the electromagnetic braking and recovers energy. The over-wind speed condition is when the wind speed continuously exceeds 12m / s, the graded protection steps are executed sequentially.

[0084] The microprocessor control unit continuously monitors the DC bus voltage and output power, obtaining the DC bus voltage and output power values ​​from the monitoring data. It determines that a trigger condition has been met when the DC bus voltage exceeds a preset threshold or the output power exceeds the rated value. Upon triggering, the microprocessor control unit immediately sends a command to the generator-side converter, causing it to enter torque control mode and apply electromagnetic braking torque. The regenerative energy generated during the turbine speed reduction process is extracted from this applied electromagnetic braking torque. This regenerative energy is then converted into AC power that meets grid requirements via a bidirectional DC-DC converter and a grid-connected inverter and fed back to the grid, or directly used to charge the energy storage device. During charging or feedback, the system continuously monitors whether the turbine speed has dropped to a safe threshold. If, after the turbine speed drops to the safe threshold, the wind speed is simultaneously detected to continuously exceed 12 meters per second, the microprocessor control unit sequentially switches to the highest wind speed range power optimization curve for power limiting and initiates energy recovery braking until the mechanical braking mechanism is triggered to achieve graded protection.

[0085] In one embodiment, the microprocessor control unit collects DC bus voltage and output power data in real time through integrated sensors. This continuous monitoring mechanism ensures that the system responds quickly to abnormal conditions. For example, when the DC bus voltage exceeds a preset threshold, the system can promptly identify potential overload risks, thereby avoiding equipment damage and maintaining stable operation. This results in higher system reliability and helps extend the inverter's lifespan.

[0086] Specifically, during the operation of a wind turbine, if the output power suddenly exceeds the rated value, the microprocessor will extract specific values ​​from these monitoring data for comparison to determine if the triggering condition is met. This step provides a basis for active protection and has the beneficial effect of reducing the probability of sudden failures.

[0087] In one embodiment, once the triggering condition is met, the microprocessor sends a command to the generator-side converter to switch to torque control mode and apply electromagnetic braking torque. In this mode, the converter adjusts the current to generate a reverse torque, and the wind turbine speed decreases accordingly, thereby obtaining regenerative electrical energy. For example, in high wind speed scenarios, this torque application can efficiently convert kinetic energy into electrical energy and avoid energy waste. The reason for doing so is to optimize energy utilization and improve overall power generation efficiency.

[0088] Specifically, after the generator-side converter enters this mode, it adjusts the torque by controlling the electromagnetic field strength to ensure a smooth decrease in speed. This not only protects the mechanical components but also lays the foundation for subsequent energy recovery, and the beneficial effect is to reduce maintenance costs.

[0089] In one embodiment, the acquired regenerated electrical energy is converted into standard frequency AC power by a grid-connected inverter after the voltage level is regulated by a bidirectional DC-DC converter. Alternatively, it can be directly injected into an energy storage device for charging. For example, during peak grid load periods, feeding back into the grid can alleviate power supply pressure, thus improving grid stability and contributing to sustainable energy management. Specifically, during the charging or feedback process, the system continuously determines whether the wind turbine speed has reached a safe threshold. This involves real-time comparison of speed sensor data with preset values ​​to ensure the process is safe and controllable. A beneficial effect is preventing secondary damage caused by excessive braking.

[0090] In one embodiment, when the rotational speed drops to a safe threshold and the wind speed exceeds 12 meters per second, the microprocessor sequentially executes curve switching and energy recovery braking until mechanical braking intervenes. For example, it first switches to the power optimization curve at the highest wind speed to limit the output power. This smoothly transitions to the protection state, avoiding abrupt shutdown. The rationale for this is to achieve tiered protection, which helps reduce mechanical shock and extend the wind turbine's lifespan. Specifically, this sequential execution includes first adjusting the power to match the wind speed via curve adjustment, then strengthening regenerative braking, and triggering mechanical braking if further control is still needed. The entire process forms a continuous protection chain, which enhances system adaptability and improves safety.

[0091] In one embodiment, from multiple perspectives, such as in low-load environments, monitoring and triggering can quickly respond to small fluctuations, while during sustained high wind speeds, tiered protection ensures maximum energy recovery. These aspects support each other, jointly enhancing the system's robustness and facilitating efficient operation under various wind conditions. Specifically, the combination of electromagnetic braking and energy conversion not only recovers otherwise wasted kinetic energy but also seamlessly integrates with subsequent mechanical braking, resulting in energy-saving technical effects and contributing to the achievement of environmentally friendly power generation goals.

[0092] In one embodiment, considering practical applications such as coastal wind farms, continuous monitoring can detect voltage anomalies early and trigger torque control to recover electrical energy and feed it back to the local grid. Combined with tiered protection, this supports smooth shutdown, resulting in increased power generation and reduced operational risks. Specifically, from the perspective of extended protection mechanisms, if wind speed fluctuations are frequent, the system optimizes the charging process by judging speed thresholds, ensuring that the energy storage device efficiently utilizes regenerated electrical energy. These implementation methods, progressing from core monitoring to final protection, enrich the diversity of solutions and are beneficial for adapting to wind power systems of different scales.

[0093] This invention provides a grid-connected inverter control system for wind power generation, comprising: The storage module is used to pre-store power optimization curves corresponding to multiple different wind speed ranges. The power optimization curves are power reference trajectories customized for each wind speed range. The monitoring module is used to monitor real-time wind speed, identify the current wind speed range based on the real-time wind speed, and call the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine. The conversion module is used to convert the regenerative electrical energy generated by the wind turbine into AC power through a bidirectional power conversion circuit when the wind turbine braking demand is detected, so as to connect it into the power grid or charge the energy storage device. The trigger module is used to monitor wind speed, output power and DC bus voltage parameters in real time. When excessive wind speed, excessive power or excessive voltage conditions are detected, the regenerative braking is activated first. If the speed still exceeds the safety threshold, the mechanical braking mechanism is triggered.

[0094] Furthermore, the storage module includes: The generation unit is used to generate the power optimization curve based on the wind turbine aerodynamic efficiency, transmission system losses, and generator efficiency. The curve optimization unit stores the power-speed relationship or the power-DC voltage relationship. Each power optimization curve corresponds to a wind speed range as a maximum power point tracking reference trajectory.

[0095] Furthermore, the monitoring module includes: The estimation unit is used to obtain real-time wind speed by acquiring it through a wind speed sensor or by estimating it based on the back electromotive force of a generator. The determination and identification unit is used to determine and identify the current wind speed range based on the average value of the real-time wind speed; An automatic switching unit is used to automatically switch to the power optimization curve corresponding to the other wind speed range when the real-time wind speed transitions from one wind speed range to another. The adjustment matching unit is used to adjust the generator torque and speed after switching to match the corresponding power optimization curve.

[0096] It should be noted that the modules provided in the embodiments of the present invention have the same implementation principle and technical effects as those in the aforementioned method embodiments. For the sake of brevity, the specific working process of the modules described above can be referred to the corresponding process in the aforementioned method embodiments, and will not be repeated here.

[0097] The above description of the embodiments is only for the purpose of helping to understand the technical solutions and core ideas of this application; those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A grid-connected inverter control method for wind power generation, characterized in that, include: Multiple power optimization curves corresponding to different wind speed ranges are pre-stored, and the power optimization curves are power reference trajectories customized for each wind speed range; Monitor real-time wind speed, identify the current wind speed range based on the real-time wind speed, and call the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine; When a wind turbine braking demand is detected, the regenerative power generated by the wind turbine is converted into AC power through a bidirectional power conversion circuit and fed into the power grid or used to charge the energy storage device. The system monitors wind speed, output power, and DC bus voltage parameters in real time. When excessive wind speed, excessive power, or excessive voltage conditions are detected, the system first initiates regenerative braking. If the rotational speed still exceeds the safety threshold, the system triggers the mechanical braking mechanism.

2. The method as described in claim 1, characterized in that, The pre-stored power optimization curves corresponding to multiple different wind speed ranges include: The multiple different wind speed ranges cover low wind speed range, medium wind speed range and high wind speed range, and the power optimization curve is generated based on the wind turbine aerodynamic efficiency, transmission system loss and generator efficiency. The power optimization curves are stored in the form of power-speed relationship or power-DC voltage relationship, and each power optimization curve corresponds to a wind speed range as a maximum power point tracking reference trajectory.

3. The method as described in claim 1, characterized in that, The monitoring of real-time wind speed, identification of the current wind speed range based on the real-time wind speed, and use of the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory, includes: Real-time wind speed is obtained by wind speed sensors or estimated based on the back electromotive force of generators; The current wind speed range is determined and identified based on the average value of the real-time wind speed. When the real-time wind speed transitions from one wind speed range to another, it automatically switches to the power optimization curve corresponding to the other wind speed range. After switching, adjust the generator torque and speed to match the corresponding power optimization curve.

4. The method as described in claim 1, characterized in that, The process of converting regenerative electrical energy generated by the wind turbine into alternating current via a bidirectional power conversion circuit and feeding it into the power grid or charging an energy storage device includes: The bidirectional power conversion circuit includes a rectifier bridge, a boost DC / DC converter, and a DC / AC inverter. When braking is required, the bidirectional power converter is switched to energy feedback mode. The generator-side converter is controlled to apply electromagnetic braking torque, so that the wind turbine's kinetic energy is converted into regenerative electrical energy; The regenerated electrical energy is processed by the bidirectional power conversion circuit and then fed into the power grid or energy storage device in an orderly manner.

5. The method as described in claim 1, characterized in that, When excessive wind speed, excessive power, or excessive voltage conditions are detected, regenerative braking is first initiated. If the rotational speed still exceeds the safety threshold, a mechanical braking mechanism is triggered, including: When the above-peak wind conditions are detected, the power optimization curve corresponding to the high wind speed range is switched to first to limit the power. Then, the regenerative braking system is activated to reduce the rotational speed. The rotational speed is continuously monitored, and if the rotational speed still exceeds the safety threshold, the mechanical braking mechanism is triggered. When the overpower or overvoltage condition is detected, the regenerative energy recovery braking is directly activated.

6. The method as described in claim 1, characterized in that, The real-time monitoring parameters for wind speed, output power, and DC bus voltage include: The wind speed parameters are obtained through sensors or estimation, and the output power is calculated through current and voltage sampling. The DC bus voltage parameters are obtained by voltage sampling; The wind speed parameters, output power, and DC bus voltage parameters are used to simultaneously support maximum power point tracking control and braking protection judgment.

7. The method as described in claim 3, characterized in that, The automatic switching to the power optimization curve corresponding to the other wind speed range includes: When the real-time wind speed remains within the other wind speed range, the automatic switching is performed; After automatic switching, torque adjustment is performed with the new power optimization curve as the target, so that the fan can smoothly transition to the new operating point.

8. A grid-connected inverter control system for wind power generation, used to implement the method as described in any one of claims 1-7, characterized in that, The system includes: The storage module is used to pre-store power optimization curves corresponding to multiple different wind speed ranges. The power optimization curves are power reference trajectories customized for each wind speed range. The monitoring module is used to monitor real-time wind speed, identify the current wind speed range based on the real-time wind speed, and call the power optimization curve corresponding to the current wind speed range as the maximum power point tracking reference trajectory to control the wind turbine. The conversion module is used to convert the regenerative electrical energy generated by the wind turbine into AC power through a bidirectional power conversion circuit when the wind turbine braking demand is detected, so as to connect it into the power grid or charge the energy storage device. The trigger module is used to monitor wind speed, output power and DC bus voltage parameters in real time. When excessive wind speed, excessive power or excessive voltage conditions are detected, the regenerative braking is activated first. If the speed still exceeds the safety threshold, the mechanical braking mechanism is triggered.

9. The method as described in claim 8, characterized in that, The storage module includes: The generation unit is used to generate the power optimization curve based on the wind turbine aerodynamic efficiency, transmission system losses, and generator efficiency. The curve optimization unit stores the power-speed relationship or the power-DC voltage relationship. Each power optimization curve corresponds to a wind speed range as a maximum power point tracking reference trajectory.

10. The method as described in claim 8, characterized in that, The monitoring module includes: The estimation unit is used to obtain real-time wind speed by acquiring it through a wind speed sensor or by estimating it based on the back electromotive force of a generator. The determination and identification unit is used to determine and identify the current wind speed range based on the average value of the real-time wind speed; An automatic switching unit is used to automatically switch to the power optimization curve corresponding to the other wind speed range when the real-time wind speed transitions from one wind speed range to another. The adjustment matching unit is used to adjust the generator torque and speed after switching to match the corresponding power optimization curve.

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