A control method and system for preventing wind turbine generator set from overspeeding

Abstract

The present invention discloses a control method and system for preventing a wind turbine from overspeeding, which relates to the field of wind power generation technology, including correcting the obtained operating parameters through a compensation model and constructing an extreme gust prediction model; constructing a wind field simulation model based on the output of the extreme gust prediction model and judging whether to make adjustments; adjusting the blade angle of attack and yaw adjustment in the wind field simulation model, and summarizing the adjustment strategy. The present invention greatly improves the accuracy of the data by real-time monitoring of key operating parameters and introducing a compensation model to correct the measured values. Accurate data is the basis for effective analysis and prediction, especially under extreme weather conditions, such as the prediction of extreme gusts. This not only helps to improve the operating efficiency of the wind farm, but also significantly reduces the risks and losses caused by inaccurate data. Through the wind field simulation model and optimization algorithm, the optimal adjustment of the blade angle of attack and yaw angle under extreme gust conditions is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a control method and system for preventing a wind generator set from overspeeding. Background Art

[0002] As a clean, renewable, and green energy source, wind power is becoming increasingly important in the global energy mix. Improving the safety and efficiency of wind power generation has also become a key focus of the industry. During wind turbine operation, extreme weather conditions, such as strong gusts, often pose serious safety risks. Therefore, effectively preventing and controlling wind turbine overspeed in harsh conditions like gusty winds is crucial to ensuring safe and reliable operation.

[0003] Currently, the main technical approaches to address wind turbine overspeed control include active control strategies based on real-time monitoring data and passive protection devices. The former primarily adjusts turbine power by adjusting parameters such as blade pitch and yaw angle to maintain a safe speed. The latter, on the other hand, often employs passive protection devices such as clutches and brakes to directly cut off power transmission in the event of an overspeed, reducing structural loads. However, existing technical solutions still have some shortcomings in practical application. First, the accuracy of existing real-time monitoring systems for detecting parameters such as wind speed and direction in extreme weather conditions needs to be further improved. Due to the high temporal and spatial variability of severe weather conditions such as gusty winds, conventional sensors cannot fully reflect the actual operating conditions, resulting in a lag in the implementation of subsequent control strategies, which in turn affects control effectiveness. Second, existing control algorithms and models often fail to fully account for various influencing factors when dealing with complex and variable extreme operating conditions, lacking accuracy and real-time performance. This can not only lead to insufficient or excessive adjustments, but can also trigger new problems such as resonance and stall, failing to fundamentally address the potential for overspeeding. Third, most passive protection devices are only effective in emergency situations following an overspeeding event and are unable to provide proactive prevention and precise control. Once overspeed occurs, the physical cut-off and braking measures will have a great impact on the normal operation of the unit. Summary of the Invention

[0004] In view of the problems existing in the existing overspeed control of wind turbines, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is the lag in control strategy for severe weather such as gusts.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a control method for preventing overspeed of a wind turbine generator set, which comprises:

[0008] The obtained operating parameters are corrected through the compensation model, and an extreme gust prediction model is constructed;

[0009] Build a wind field simulation model based on the output of the extreme gust prediction model and determine whether to make adjustments;

[0010] Adjust the blade angle of attack and yaw in the wind field simulation model, and summarize the adjustment strategy.

[0011] As a preferred solution of the control method for preventing overspeed of a wind turbine generator set according to the present invention, the compensation model is shown as follows:

[0012]

[0013] Where V is the original measurement value, p1, p2, ..., p n Represents the current state value of various environmental and time factors that affect measurement accuracy, f i (p i ) is for factor p i The designed compensation function, C represents the measured value after compensation;

[0014] The compensation function includes temperature compensation, fitness compensation and electromagnetic interference compensation, as shown in the following formula:

[0015] f T (T) = a T ·(TT ref )

[0016] f H (H) = β H ·(exp(γ H ·(HH ref ))-1)

[0017] f E (E) = δ E ·ln(1+ε E ·|EE ref |)

[0018] Among them, a T is the temperature compensation coefficient, T is the current temperature, T ref is the reference temperature, β H ,γ H is the humidity compensation coefficient, H is the current humidity, H ref is the reference humidity value, δ E ,ε E is the electromagnetic interference compensation coefficient, E is the current electromagnetic interference level, and E ref is the reference electromagnetic interference level.

[0019] As a preferred solution of the control method for preventing overspeed of a wind turbine generator set according to the present invention, the extreme gust prediction model is shown as follows:

[0020]

[0021] Among them, C(t) represents the compensated operating parameters at time t, E(t) represents the environmental data at time t, α, β, γ are weight coefficients, ε C is the adjustment coefficient, C avg is the average value of the running parameter after compensation, κ is the slope parameter, E thres is the threshold of environmental data, λ is the attenuation coefficient, t last is when the last extreme gust event occurred.

[0022] As a preferred solution of the control method for preventing overspeed of wind turbine generator sets according to the present invention, the generator speed of each unit in the wind farm simulation model is calculated as follows:

[0023]

[0024] Where Ω is the speed of the wind turbine, v1 represents the volume of the space considered, ρ is the density of the wind, M represents the wind speed vector, σ θ is the stability coefficient of the extreme gust prediction model, λ is the stabilization parameter, L is the characteristic length, γ is the unit load response coefficient, P i is the power output of the i-th unit, a i is the sensitivity coefficient of the i-th unit to extreme gusts, ΔM i is the change in wind speed relative to the average wind speed.

[0025] As a preferred solution of the control method for preventing overspeed of a wind turbine generator set according to the present invention, the blade attack angle is adjusted according to the calculated optimal blade attack angle, and the optimal blade attack angle is shown in the following formula:

[0026]

[0027] Among them, v2 represents wind speed, a opt is the calculated optimal angle of attack, a is the blade angle of attack, k and α0 are the parameters of the normalized function, and are the standard deviation and mean of the wind speed distribution.

[0028] As a preferred solution of the control method for preventing overspeed of a wind turbine generator set according to the present invention, the yaw adjustment includes the following steps:

[0029] Activate the speed protection module, the normally open electric contact is closed;

[0030] Activate the yaw contactor and the time delay relay starts in time;

[0031] When the delay relay reaches the preset time, the yaw stops;

[0032] When the speed drops to a safe range, the overspeed module starts again and sends a signal to the main control system.

[0033] As a preferred solution of the control method for preventing overspeed of a wind turbine generator set according to the present invention, the formulation of the adjustment strategy includes:

[0034] The speed is calculated based on the gust conditions predicted by the gust prediction model. If the generator speed exceeds the safety threshold, adjustment is initiated.

[0035] Substitute the gust conditions into the wind field simulation model to calculate the optimal blade angle of attack, and then substitute it back into the wind field simulation model to calculate the generator speed at the current blade angle of attack;

[0036] If the generator speed is still greater than the safety threshold, further yaw adjustment is performed. If the generator speed is less than the safety threshold, the blade angle of attack is slightly adjusted to enable the generator to reach maximum power generation.

[0037] In a second aspect, an embodiment of the present invention provides a control system for preventing overspeed of a wind turbine generator set, comprising:

[0038] A real-time monitoring module is used to collect key operating parameters such as wind speed and rotational speed and build an extreme gust prediction model;

[0039] The wind field simulation module is used to simulate the operating status of the unit under different wind conditions based on the output of the extreme gust prediction model and determine whether adjustments are needed;

[0040] Angle of attack adjustment module: Develop an optimization algorithm in the wind farm simulation model to calculate the optimal blade angle of attack under gusty conditions to improve power generation efficiency;

[0041] The yaw adjustment module calculates the appropriate yaw angle to offset the nacelle, reduce the frontal area, and control the speed when the speed still exceeds the limit after adjusting the angle of attack.

[0042] The collaborative control module further fine-tunes the angle of attack and yaw adjustments to keep the rotational speed within the optimal power generation range, achieving safe and efficient operation under gusty conditions.

[0043] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein when the processor executes the computer program, any step of the above-mentioned control method for preventing overspeed of a wind turbine is implemented.

[0044] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned control method for preventing overspeed of a wind turbine generator set is implemented.

[0045] The beneficial effect of the present invention is that by real-time monitoring of key operating parameters and introducing compensation models to correct measured values, the accuracy of the data is greatly improved. Accurate data is the basis for effective analysis and prediction, especially in extreme weather conditions, such as the prediction of extreme gusts. This not only helps to improve the operating efficiency of wind farms, but also significantly reduces the risks and losses caused by inaccurate data. Through the wind farm simulation model and optimization algorithm, the optimal adjustment of the blade angle of attack and yaw angle under extreme gust conditions is achieved. This adjustment strategy not only ensures the safe operation of wind turbines under extreme conditions and avoids overspeed damage to equipment, but also ensures the highest possible power generation efficiency. While ensuring safety, it maximizes power output and improves the economic benefits of wind farms. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0047] Figure 1 Flowchart of a control method for preventing overspeed of a wind turbine generator set.

[0048] Figure 2 Simulation diagram of the generator speed at a wind speed of 5m / s, which is a control method to prevent the wind turbine from overspeeding.

[0049] Figure 3 Simulation diagram of the generator speed at a wind speed of 10m / s, which is a control method to prevent the wind turbine from overspeeding. DETAILED DESCRIPTION

[0050] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0051] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0053] The present invention is described in detail with reference to schematic diagrams. For ease of illustration, cross-sectional views of device structures may be partially enlarged and not to scale when describing embodiments of the present invention. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0054] In the description of the present invention, it should be noted that the terms "upper, lower, inner, and outer" and other references to orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0055] In this disclosure, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they may refer to fixed, removable, or integral connections. They may also refer to mechanical, electrical, or direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this disclosure.

[0056] Example 1

[0057] Reference Figure 1 , which is the first embodiment of the present invention, provides a control method for preventing overspeed of a wind turbine generator set, comprising:

[0058] S1: Real-time monitoring of key operating parameters and construction of extreme gust prediction models.

[0059] Select the appropriate wind speed sensor and speed sensor based on indicators such as measurement range, accuracy, and anti-interference ability. The wind speed sensor is generally placed at the top of the tower or the center of the impeller, as close to the actual wind sweeping surface as possible to avoid interference from obstacles. The speed sensor is installed at an appropriate position on the generator shaft or main shaft to facilitate the acquisition of accurate speed signals.

[0060] After integrating the wind speed and rotation speed sensors with the control system through hardware and software integration, real-time data collection for these two key parameters is performed. To ensure data quality, the sensors must be calibrated and calibrated on-site to eliminate measurement deviations caused by environmental and time-related factors. Furthermore, a comprehensive data collection, storage, and management mechanism must be established to ensure data integrity and security.

[0061] In terms of software, a real-time data acquisition program is developed to continuously read the latest data from the sensor end and cache the data or directly transmit it to the subsequent processing module according to the set sampling frequency. Based on the calibration results and on-site calibration data, the measured values are corrected in real time for known environmental factors. A compensation model is introduced to correct the measured values. This is embedded in the data processing flow of the measurement system in the form of an algorithm. The current state value of each influencing factor is obtained in real time, and the corresponding correction value is calculated. Finally, this correction value is combined with the original measurement value to obtain the compensated final output value. The specific formula is as follows:

[0062]

[0063] Where V is the original measurement value, p1, p2, ..., p n Represents the current state value of various environmental and time factors that affect measurement accuracy, f i (p i ) is for factor p i The designed compensation function, C represents the measured value after compensation.

[0064] It should be noted that f i (p i The design of ) is based on various factors and needs to be comprehensively considered based on environmental factors, equipment aging, etc. Three common influences are given as examples for reference. In practice, these factors are included but not limited to. As shown in the following formula:

[0065] f T (T) = a T ·(TT ref )

[0066] f H (H) = β H ·(exp(γ H ·(HH ref ))-1)

[0067] f E (E) = δ E ·ln(1+ε E ·|EE ref |)

[0068] Among them, a T is the temperature compensation coefficient, T is the current temperature, T ref is the reference temperature, β H ,γ H is the humidity compensation coefficient, H is the current humidity, H ref is the reference humidity value, δ E ,ε E is the electromagnetic interference compensation coefficient, E is the current electromagnetic interference level, and E ref is the reference electromagnetic interference level (which can usually be assumed to be zero or background level).

[0069] After deploying the compensation algorithm, its correction effects are continuously monitored, field data is collected, and the compensation model coefficients are regularly recalibrated and optimized based on the new data, allowing it to continuously adapt to environmental changes. Through these steps, a high-precision compensation correction model is constructed, effectively eliminating measurement deviations caused by various environmental and time factors, significantly improving the accuracy and reliability of measurement data and laying a solid foundation for subsequent analysis and application.

[0070] The extreme gust prediction model is further constructed based on the compensated operating parameter set. The specific compensation function logic is shown in the following formula. The multi-source parameters are integrated to predict extreme gusts, which is expressed in the mathematical formula:

[0071]

[0072] Where C(t) represents the compensated operating parameters at time t, E(t) represents the environmental data at time t, α, β, and γ are weight coefficients used to balance the impact of different data sources on the prediction results, and ε C is the adjustment coefficient, C avg is the average value of the operating parameter after compensation, κ is the slope parameter, the sensitivity of the control function, E thres is the threshold of environmental data, used to distinguish between normal and extreme environmental conditions, λ is the attenuation coefficient, which represents the impact of an extreme gust event in time distance, t last is when the last extreme gust event occurred.

[0073] The gust-related form is determined by the size of the output value. The larger the output value, the higher the possibility and expected intensity of extreme gusts. The specific time of the gust is determined by the integral interval [t0,t last ]Sure.

[0074] S2: Construct a wind field simulation model based on the output of the extreme gust prediction model and determine whether to make adjustments.

[0075] Aerodynamic and dynamic models are developed for different types of generator sets. The aerodynamic model describes the aerodynamic behavior of the blades at various angles of attack, while the dynamic model describes the motion response characteristics of the entire unit under various operating conditions. Furthermore, based on geographic information data, a three-dimensional digital model of the power generation site is constructed.

[0076] The site model is integrated with the unit physical model, and computational fluid dynamics (CFD) technology is used to simulate the wind field and flow field under different meteorological conditions, and analyze the impact of different wind conditions on the aerodynamic force and load of the unit.

[0077] Preferably, the rotational speeds of different units in the wind farm simulation model are shown in the following formula:

[0078]

[0079] Where Ω is the speed of the wind turbine, v1 represents the volume of the space considered, ρ is the density of the wind, M represents the wind speed vector, σ θ is the stability coefficient of the extreme gust prediction model, λ is the stabilization parameter, L is the characteristic length, γ is the unit load response coefficient, P i is the power output of the i-th unit, a i is the sensitivity coefficient of the i-th unit to extreme gusts, ΔM i is the change in wind speed relative to the average wind speed.

[0080] When the generator speed of the unit exceeds the high-speed protection parameter setting value (2300rpm) in the wind farm simulation model, it indicates that in the extreme gusts at this stage, it is easy to cause the variable pitch system to malfunction, unable to properly feather the propeller, or even runaway.

[0081] S3: Adjust blade angle of attack and yaw in the wind field simulation model and summarize the adjustment strategy.

[0082] In the wind field simulation model, the blade root to tip is divided into multiple cross-sections along the span direction. The shape curve and aerodynamic surface of each cross-section are accurately simulated. According to the type and amplitude of the blade movement, the appropriate solution method is selected to avoid mesh quality degradation.

[0083] Establish a body coordinate system for each blade, determine the center of rotation and the axis of rotation, and align the blade root with the axis of rotation to facilitate setting the rotational motion. In the motion setting module of the CFD solver, select "Rotational Degree of Freedom".

[0084] Based on a wind farm simulation model, an optimization algorithm was developed and implemented. This algorithm aims to maximize power generation efficiency by using a mathematical model to correlate the complex relationships between blade angle of attack, wind speed, wind direction, and power generation efficiency. This mathematical model takes into account the aerodynamic characteristics of the wind turbine and the blade's response to wind speed changes, providing the algorithm with a theoretical basis for calculating the optimal blade angle of attack. Through an iterative process, the algorithm dynamically calculates the blade angle of attack that achieves the highest power generation efficiency under given wind farm conditions, as shown in the following equation:

[0085]

[0086] Among them, v2 represents wind speed, a opt is the calculated optimal angle of attack, a is the blade angle of attack, k and α0 are the parameters of the normalization function, which control the slope and center position of the curve respectively. and are the standard deviation and mean of the wind speed distribution, which are used to describe the normal distribution of wind speed.

[0087] The algorithm is used to calculate the optimal angle of attack in gusty conditions in the wind field simulation model, ensuring that the generator speed does not exceed the safe speed while ensuring the maximum power generation.

[0088] Furthermore, the calculated optimal angle of attack under gusty conditions is set in the wind field simulation model, and the speed calculation formula is used to calculate the generator speed under the current angle of attack conditions. If the generator speed still exceeds the high-speed protection parameter setting value, the next step of yaw adjustment is carried out as follows:

[0089] The overspeed protection module is activated, and its normally open contacts close. This action is an emergency response measure used to immediately deal with operating conditions that exceed safety limits and prevent equipment damage due to overspeed. Upon receiving the signal from the overspeed module, the intermediate relay is immediately energized and maintained, while the yaw contactor is activated. This causes the wind turbine to perform a preset 90-degree right yaw operation to reduce the direct impact of the wind on the blades and reduce the speed of the wind turbine. At the same time as the yaw operation, the delay relay starts timing, and the duration of this timing is set based on the estimated time to complete the yaw action.

[0090] Once the delay relay reaches the preset time, the yaw operation stops, indicating that the wind turbine has completed a 90-degree yaw adjustment. At this point, the wind turbine blades are no longer facing the wind direction, effectively reducing the risk of abnormally high wind speeds.

[0091] When the fan speed drops to a safe range (such as 500rpm), the overspeed module will be activated again. This time it is not to start the protection measures, but to send a signal to the main control system to inform that the crosswind yaw has been successfully executed and the fan speed has dropped to the normal range.

[0092] To ensure turbine safety, this yaw protection is designed to execute automatically only once and not automatically reset. This means that once the overspeed protection triggers and yaw is complete, the system requires manual inspection and reset before normal operation can resume. This ensures mandatory safety checks and prevents the turbine from being exposed to high wind speeds again without thorough inspection and safety assurance.

[0093] Furthermore, based on the given adjustment strategy, the rotational speed is first calculated in the wind field simulation model according to the gust conditions predicted by the gust prediction model. If the rotational speed exceeds the safety threshold, the adjustment strategy needs to be initiated. The first step is to calculate the optimal blade angle of attack under the gust and apply this angle of attack value to the actual unit blades. The adjusted angle of attack is then substituted into the model to recalculate the predicted rotational speed. If the predicted rotational speed still exceeds the safety threshold, further yaw adjustment measures need to be taken. By calculating a suitable yaw angle, the cabin is offset at a certain angle relative to the wind direction, thereby reducing the effective frontal area and controlling the rotational speed to a safe range.

[0094] Once the speed is controlled within a safe range, it is necessary to determine whether the current speed is in the speed range for optimal power generation efficiency. If it is too fast or too slow, it will affect power capture. The speed can be adjusted to the optimal range by fine-tuning the angle of attack and yaw angle, while maximizing the power coefficient as much as possible. In this case, it is necessary to balance the relationship between power capture and structural loads, and through real-time monitoring and continuous fine-tuning of parameters, ultimately achieve the goal of safe and efficient operation under gusty conditions. Throughout the process, the coordinated adjustment of the angle of attack and yaw is the key, and it is necessary to systematically weigh various constraints to ensure the long-term stable operation of the unit.

[0095] Furthermore, this embodiment also provides a control system for preventing a wind turbine generator set from overspeeding, comprising:

[0096] A real-time monitoring module is used to collect key operating parameters such as wind speed and rotational speed and build an extreme gust prediction model;

[0097] The wind field simulation module is used to simulate the operating status of the unit under different wind conditions based on the output of the extreme gust prediction model and determine whether adjustments are needed;

[0098] Angle of attack adjustment module: Develop an optimization algorithm in the wind farm simulation model to calculate the optimal blade angle of attack under gusty conditions to improve power generation efficiency;

[0099] The yaw adjustment module calculates the appropriate yaw angle to offset the nacelle, reduce the frontal area, and control the speed when the speed still exceeds the limit after adjusting the angle of attack.

[0100] The collaborative control module further fine-tunes the angle of attack and yaw adjustments to keep the rotational speed within the optimal power generation range, achieving safe and efficient operation under gusty conditions.

[0101] This embodiment also provides a computer device suitable for the control method of preventing overspeed of a wind turbine generator set, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the control method of preventing overspeed of a wind turbine generator set proposed in the above embodiment.

[0102] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0103] This embodiment further provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the control method for preventing overspeed of a wind turbine generator set as proposed in the above embodiment is implemented.

[0104] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. Technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0105] Example 2

[0106] Reference Figure 2 and Figure 3 , which is the second embodiment of the present invention, provides a control method for preventing overspeed of a wind turbine generator set. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0107] In this example, a wind farm was selected as the test subject. This wind farm consists of 20 2MW wind turbines located in a complex mountainous terrain. To verify the effectiveness of the invention, three turbines of different models (denoted as A, B, and C) were selected for comparative testing.

[0108] First, following the methods outlined in the invention summary, the wind speed and rotational speed sensors for the three turbines were optimized and calibrated on-site. The wind speed sensors were placed near the center of each turbine's impeller, minimizing interference from surrounding obstacles. The rotational speed sensors were installed on the generator shaft to directly acquire torque and rotational speed signals.

[0109] The calibrated sensors were connected to the control systems of each unit, and a corresponding data acquisition program was developed to collect wind speed and rotational speed data in real time at a frequency of 1 Hz. Compensation algorithms were introduced to correct the raw measurement data for known influencing factors (such as temperature, humidity, and electromagnetic interference), improving data quality.

[0110] At the same time, a data storage and management platform is deployed to ensure the integrity and security of measurement data. At the software level, the correction effect of the compensation algorithm is monitored in real time, and the algorithm coefficients are recalibrated and optimized monthly to enable it to continuously adapt to environmental changes.

[0111] Next, based on this high-precision operational data, an extreme gust prediction model was constructed. This model incorporates compensated operational parameters such as wind speed and rotational speed, as well as on-site environmental and historical event data. Through mathematical modeling, it was possible to predict the timing and intensity of extreme gusts.

[0112] To verify the accuracy of the forecast model, experts and scholars from the local meteorological department were invited to evaluate the model's output. The evaluation concluded that the forecast model was able to accurately capture the onset of gusts, providing a reliable trigger for initiating adjustment strategies.

[0113] Next, aerodynamic and dynamic models were developed for the three turbine types A, B, and C. A three-dimensional digital site model of the wind farm was constructed using measured geographic data. Then, using CFD technology, the impact of various wind conditions on the three turbines was simulated and analyzed.

[0114] It's worth noting that a new formula for calculating the computer group's rotational speed was derived, effectively accounting for multiple factors, including the output of the extreme gust prediction model. The resulting formula's deviation from measured values is within 5%, significantly outperforming existing empirical formulas.

[0115] This formula defines the generator speed overspeed threshold at 2300 rpm. If the simulation results exceed this threshold, an adjustment strategy must be initiated. A comparative analysis revealed that during the simulation, Unit A experienced overspeed three times, Unit B twice, and Unit C once. These situations could potentially lead to pitch system failure or even runaway. The specific experimental data is shown in the table below:

[0116] Table 1 Experimental data table

[0117] Test subjects Wind speed measurement accuracy (%) Speed measurement accuracy (%) Extreme gust forecast accuracy (%) Number of speeding (times) Unit A 99.3 99.6 92.7 3 Unit B 99.1 99.5 93.1 2 Unit C 99.5 99.7 94.5 1 Existing technology 97.8 98.2 85.6 N / A

[0118] As can be seen from the table above, compared with the prior art, the invention has shown obvious advantages in multiple key indicators:

[0119] 1. Wind speed and rotational speed measurement accuracy reaches a high level of over 99%. This is due to optimized sensor layout, on-site calibration, and correction of compensation algorithms, which effectively eliminate many interference factors and ensure the reliability of measurement data.

[0120] 2. The accuracy of extreme gust predictions ranges from 92.7% to 94.5%, significantly higher than the current level of 85.6%. This prediction model integrates multi-source heterogeneous data and uses novel mathematical modeling methods to improve the relevance and accuracy of predictions both theoretically and practically.

[0121] 3. During the simulation test, units A, B, and C overspeeded three times, twice, and once, respectively. This demonstrates that the invention can effectively predict extreme situations and promptly initiate adjustment strategies, fundamentally avoiding the occurrence of overspeed, demonstrating the invention's practical application value.

[0122] It's important to note that the invention not only improves measurement and prediction accuracy but also demonstrates significant innovations over existing technologies in its implementation examples: New formulas consider more influencing factors, resulting in more realistic simulations; and adjustment strategies, based on wind farm simulations, enable targeted fine-tuning of angle of attack and yaw, maximizing efficiency while ensuring safety. These unique features highlight the invention's creativity and will undoubtedly inject new impetus into the development of the wind power industry.

[0123] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A control method for preventing overspeed of a wind turbine generator set, characterized by: include, The obtained operating parameters are corrected through the compensation model, and an extreme gust prediction model is constructed; Build a wind field simulation model based on the output of the extreme gust prediction model and determine whether to make adjustments; Adjust blade angle of attack and yaw in wind farm simulation models and summarize adjustment strategies; The compensation model is shown below: Where V is the original measurement value, p1, p2, ..., p n Represents the current state value of various environmental and time factors that affect measurement accuracy, f i (p i ) is for factor p i The designed compensation function, C represents the measured value after compensation; The compensation function includes temperature compensation, humidity compensation and electromagnetic interference compensation, as shown in the following formula: f T (T)=a T ·(T-T ref ) f H (H)=β H ·(exp(γ H ·(H-H ref ))-1) f E (E)Zδ E ·ln(1+ε E ·|YES ref |) Among them, a T is the temperature compensation coefficient, T is the current temperature, T ref is the reference temperature, β H ,γ H is the humidity compensation coefficient, H is the current humidity, H ref is the reference humidity value, δ E ,ε E is the electromagnetic interference compensation coefficient, E is the current electromagnetic interference level, and E ref is the reference electromagnetic interference level; The extreme gust prediction model is shown below: Among them, C(t) represents the compensated operating parameters at time t, E(t) represents the environmental data at time t, α, β, γ are weight coefficients, ε C is the adjustment coefficient, C avg is the average value of the running parameter after compensation, κ is the slope parameter, E thres is the threshold of environmental data, λ is the attenuation coefficient, t last is when the last extreme gust event occurred.

2. The control method for preventing overspeed of a wind turbine generator set according to claim 1, wherein: The generator speed calculation of each unit in the wind farm simulation model is shown in the following formula: Where Ω is the speed of the wind turbine, v1 represents the volume of the space considered, ρ is the density of the wind, M represents the wind speed vector, σ θ is the stability coefficient of the extreme gust prediction model, λ is the stabilization parameter, L is the characteristic length, γ is the unit load response coefficient, P i is the power output of the i-th unit, a i is the sensitivity coefficient of the i-th unit to extreme gusts, ΔM i is the change in wind speed relative to the average wind speed.

3. The control method for preventing overspeed of a wind turbine generator set according to claim 2, wherein: The blade angle of attack is adjusted according to the calculated optimal blade angle of attack, which is shown in the following formula: Among them, v2 represents wind speed, a opt is the calculated optimal angle of attack, a is the blade angle of attack, k and α0 are the parameters of the normalized function, and are the standard deviation and mean of the wind speed distribution.

4. The control method for preventing overspeed of a wind turbine generator set according to claim 3, wherein: The yaw adjustment comprises the following steps: Activate the speed protection module, the normally open electric contact is closed; Activate the yaw contactor and the time delay relay starts timing; When the delay relay reaches the preset time, the yaw stops; When the speed drops to a safe range, the overspeed module starts again and sends a signal to the main control system.

5. The control method for preventing overspeed of a wind turbine generator set according to claim 4, wherein: The formulation of the adjustment strategy includes: The speed is calculated based on the gust conditions predicted by the gust prediction model. If the generator speed exceeds the safety threshold, adjustment is initiated. Substitute the gust conditions into the wind field simulation model to calculate the optimal blade angle of attack, and then substitute it back into the wind field simulation model to calculate the generator speed at the current blade angle of attack; If the generator speed is still greater than the safety threshold, further yaw adjustment is performed. If the generator speed is less than the safety threshold, the blade angle of attack is slightly adjusted to enable the generator to reach maximum power generation.

6. A control system for preventing a wind turbine generator set from overspeeding, based on the control method for preventing a wind turbine generator set from overspeeding according to any one of claims 1 to 5, characterized in that: include, A real-time monitoring module is used to collect key operating parameters such as wind speed and rotational speed and build an extreme gust prediction model; The wind field simulation module is used to simulate the operating status of the unit under different wind conditions based on the output of the extreme gust prediction model and determine whether adjustments are needed; Angle of attack adjustment module: Develop an optimization algorithm in the wind farm simulation model to calculate the optimal blade angle of attack under gusty conditions to improve power generation efficiency; The yaw adjustment module calculates the appropriate yaw angle to offset the nacelle, reduce the frontal area, and control the speed when the speed still exceeds the limit after adjusting the angle of attack. The collaborative control module further fine-tunes the angle of attack and yaw adjustments to keep the rotational speed within the optimal power generation range, achieving safe and efficient operation under gusty conditions.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the control method for preventing overspeed of a wind turbine generator set according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the control method for preventing overspeed of a wind turbine generator set according to any one of claims 1 to 5 are implemented.

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