Power optimization method for wind turbines

Abstract

The present invention discloses a power optimization method for a wind turbine generator set, which relates to the technical field of wind turbine generator sets. The dynamic adjustment and optimization of the tip speed ratio further improves the conversion efficiency of wind energy. By calculating the tip speed ratio under different wind speed conditions and combining the variation range of the rotor angular velocity, the relatively optimal interval of the tip speed ratio is accurately obtained, and the mechanical energy conversion efficiency of the wind wheel is monitored and evaluated, and the wind wheel power coefficient under different wind speed conditions is calculated to ensure that better power output can be achieved under various wind speed conditions. Finally, the feedback adjustment of the rotor angular velocity further smoothes the output power. After obtaining the standard conversion conditions, the system can trace and adjust the angular velocity of the rotor, so that the wind turbine generator set can adapt to different wind speed changes and achieve smooth power output.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine generator systems, and in particular to a power optimization method for wind turbine generator systems. Background Art

[0002] Wind turbines are key devices for converting wind energy into electricity. Their operating efficiency and stability are crucial to the overall wind farm's power generation capacity and the stability of the power grid. In practical applications, wind turbines are affected by wind speed fluctuations, resulting in unstable output power and, in turn, fluctuations in the power supply to the grid. This power fluctuation not only affects the safe operation of the grid but can also reduce wind turbine efficiency and increase equipment fatigue. To improve power generation efficiency and ensure grid stability, research is underway to optimize wind turbine operating strategies by monitoring key parameters. This can effectively reduce power output fluctuations and achieve smooth power output. This leads to the need for smooth optimization of wind turbine power. To address these issues, a power optimization method for wind turbines has been proposed.

[0003] These issues arise from the uncontrollable nature of wind speed and the complexity of wind turbine internal systems. In actual operation, wind speed fluctuates frequently and unpredictably, directly impacting rotor speed and power output. Existing wind turbine control methods, however, mostly rely on single-speed feedback, making it difficult to dynamically respond to multivariable conditions. Unstable power output can trigger a series of adverse effects, such as power fluctuations that cause instability in grid frequency and voltage, potentially leading to grid overload or power shortages. Especially during rapid wind speed fluctuations, the rotor's inertia struggles to fully absorb and buffer these fluctuations, resulting in unstable power output. Furthermore, real-time monitoring and control of power output lags, making rapid adjustment and optimization difficult. Furthermore, frequent power fluctuations expose mechanical components, particularly rotors and blades, to increased mechanical stress, leading to premature fatigue and increased maintenance and operating costs. Consequently, power output fluctuations not only impact grid stability but also impose additional operational and maintenance burdens. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a power optimization method for a wind turbine generator set, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A power optimization method for a wind turbine generator system comprises the following steps:

[0006] S1. Deploy several sets of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information of the wind turbine in real time;

[0007] S2. Preprocessing the relevant power output data and the relevant rotor status data to generate a wind turbine operating data set, and standardizing the information in the wind turbine operating data set using dimensionless technology;

[0008] S3. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, and compare the power output difference coefficient Scxs with the preset safety range [a, b] to preliminarily screen out a matching range of rotor kinetic energy absorption;

[0009] S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of the rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. Combined with the range of the rotor angular velocity Jsd, obtain the range of the tip speed ratio Jsb;

[0010] S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction;

[0011] S6. Based on the standard conversion condition, trace back and adjust the rotor angular velocity Jsd to smooth the output power of the wind turbine.

[0012] Preferably, the specific steps of S1 include:

[0013] S11. Pre-deploy several sets of monitoring equipment in the wind farm, wherein the several sets of monitoring equipment include power sensors, strain gauges, laser rangefinders, speed sensors, wind speed sensors, and torque sensors;

[0014] S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions;

[0015] The relevant rotor state data information includes the mass Zg of each divided region of the rotor, the distance Jz of each divided region from the rotation axis, and the angular velocity Jsd of the rotor.

[0016] Preferably, the specific steps of S2 include:

[0017] S21. Preprocessing the relevant power output data information and the relevant rotor status data information to identify and remove abnormal values ​​in the relevant power output data information and the relevant rotor status data information, and filling in missing data using an interpolation method. At the same time, time-aligning the relevant power output data information and the relevant rotor status data information is performed, and finally generating a wind power operation data set;

[0018] S22. Convert the information in the wind power operation data set into unitless data through dimensionless processing technology, and standardize the dimensionless wind power operation data set so that the corresponding data values ​​are mapped to the interval [0,1].

[0019] Preferably, the specific steps of S3 include:

[0020] S31. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, which can be obtained specifically in the following manner:

[0021]

[0022] Where n represents the number of monitored wind speed conditions, i = 1, 2, 3, ..., n, Scg i Expressed as the output power value under wind speed condition i, Scg avg Expressed as the average output power value.

[0023] Preferably, the specific step S3 further includes:

[0024] S32. Preset a safety range [a, b] and compare it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out a matching range of rotor kinetic energy absorption. The specific judgment content is as follows:

[0025] S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time;

[0026] S322: If the power output difference coefficient Scxs falls within the safety range [a, b], relevant rotor status data information under the corresponding wind speed conditions will be extracted and analyzed;

[0027] S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group. The rotor kinetic energy Znn is specifically obtained in the following manner:

[0028]

[0029] Where m represents the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia;

[0030] S34. Statistically analyze the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

[0031] Preferably, the specific steps of S4 include:

[0032] S41. Based on the initially screened matching range of rotor kinetic energy absorption and in combination with the method of obtaining the rotor kinetic energy Znn, determine the range of the rotor angular velocity Jsd;

[0033] S42. Calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. The specific method is as follows:

[0034]

[0035] Where Bjz is the radius of the wind wheel, Jsd is the angular velocity of the rotor, and Fs is the wind speed.

[0036] Preferably, the specific step S4 further includes:

[0037] S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratios Jsb under different wind speed conditions obtained in S42, a range of the tip speed ratio Jsb is obtained.

[0038] Preferably, the specific steps of S5 include:

[0039] S51. Based on the tip speed ratio Jsb range obtained in S43, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition. mechanical and the wind energy P captured by the wind rotor wind .

[0040] Preferably, the specific step S5 further includes:

[0041] S52. Based on the relevant energy conversion data information, calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions. The wind rotor power coefficient Fgxs under the corresponding wind speed conditions is specifically obtained in the following manner:

[0042]

[0043] Where, P mechanical is the mechanical power value generated by the wind wheel, P wind Expressed as the wind energy captured by the wind rotor, the wind energy captured by the wind rotor Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density; π is the circumference of a circle;

[0044] S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

[0045] Preferably, the specific steps of S6 include:

[0046] S61. Based on the standard conversion condition, trace back the wind speed condition corresponding to the standard conversion condition, and trace back to the corresponding tip speed ratio Jsb according to the wind speed condition, and extract the angular velocity Jsd of the rotor under the corresponding wind speed condition from the range of the rotor angular velocity Jsd according to the tip speed ratio Jsb under the wind speed condition, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

[0047] The present invention provides a power optimization method for a wind turbine generator set, which has the following beneficial effects:

[0048] (1) First, the combination of real-time monitoring and data processing improves the system's ability to perceive the operating status of wind turbines. Through pre-deployed monitoring equipment, the power output and rotor status data of the wind turbine can be recorded in real time. Secondly, the calculation and analysis of the power output difference coefficient can dynamically identify the power output fluctuation under different wind speed conditions. By calculating the power output difference coefficient and comparing it with the preset safety range, a relatively suitable rotor kinetic energy absorption range can be preliminarily screened out. This can effectively absorb mechanical kinetic energy under large wind speed fluctuations, reduce the fluctuation amplitude of output power, and ensure the safe and stable operation of the system. Third, the dynamic adjustment and optimization of the tip speed ratio further improves the wind energy conversion efficiency. By calculating the tip speed ratio under different wind speed conditions and combining it with the range of change of the rotor angular velocity, the relatively optimal range of the tip speed ratio is accurately obtained, and the mechanical energy conversion efficiency of the wind wheel is monitored and evaluated. The wind wheel power coefficient under different wind speed conditions is calculated to ensure that the best power output can be achieved under various wind speed conditions. Finally, the feedback adjustment of the rotor angular velocity further smoothes the output power. After obtaining the standard conversion conditions, the system can trace and adjust the rotor's angular velocity, allowing the wind turbine to adapt to varying wind speeds and achieve stable power output. This feedback regulation mechanism effectively reduces the negative impact of wind speed fluctuations on power output, improving the operating efficiency and stability of the entire wind turbine. Therefore, through the coordinated operation of the above steps, this method can further improve the power output stability of the wind turbine, reduce the impact of wind speed fluctuations on the power grid, optimize the utilization efficiency of wind energy, and achieve safe, efficient, and stable operation of wind power generation.

[0049] (2) By calculating the power output variation coefficient Scxs, the power output fluctuation of the generator set can be accurately assessed under different wind speed conditions. This step dynamically calculates the variation coefficient based on the deviation between the actual power output and the average power under each wind speed condition, reflecting the output fluctuation of the system under different wind speed conditions. In this way, the system can understand the stability of the power output in real time and determine whether the system is within the safe range based on the calculated variation coefficient.

[0050] (3) Based on the screening and data analysis of the safety range, the accuracy of data processing is further improved. By comparing and analyzing the calculated power output difference coefficient Scxs with the preset safety range, when the difference coefficient falls into the safety range, the system will extract and analyze the relevant rotor state data, screen out the more suitable rotor kinetic energy absorption range, and then optimize the adjustment of the rotor angular velocity and tip speed ratio, and reduce errors and interference. On this basis, by monitoring the energy conversion efficiency under different wind speed conditions, the system can calculate and extract the maximum value of the wind wheel power coefficient, and use it as the standard conversion condition to achieve precise adjustment of the rotor angular velocity. Through these steps, the system can achieve better power output and smooth operation under different wind speed conditions, reduce the impact of wind speed fluctuations on the power grid, and improve the utilization efficiency of wind energy. Compared with existing technical means, this method can better cope with wind speed changes through fine power difference analysis, precise matching of rotor kinetic energy absorption and real-time adjustment, further improving the stability of power output and power generation efficiency. This method not only improves the overall operational stability of wind turbines, but also extends the service life of equipment by reducing power fluctuations and energy waste, thereby improving the economy and safety of wind power generation systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Schematic diagram of the power optimization method of the wind turbine generator system according to the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] Example 1

[0054] See also Figure 1 The present invention provides a power optimization method for a wind turbine generator system, comprising the following steps:

[0055] S1. Deploy several sets of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information of the wind turbine in real time;

[0056] S2. Preprocessing the relevant power output data and the relevant rotor status data to generate a wind power operation data set, and standardizing the information in the wind power operation data set using dimensionless technology;

[0057] S3. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, and compare the power output difference coefficient Scxs with the preset safety range [a, b] to preliminarily screen out a matching range of rotor kinetic energy absorption;

[0058] S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of the rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. Combined with the range of the rotor angular velocity Jsd, obtain the range of the tip speed ratio Jsb;

[0059] S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction;

[0060] S6. Based on the standard conversion condition, trace back and adjust the rotor angular velocity Jsd to smooth the output power of the wind turbine.

[0061] In this embodiment, first, monitoring equipment is deployed within the wind farm to collect real-time data on wind turbine power output and rotor status. Data preprocessing and dimensionless transformation techniques are then combined to ensure standardized data processing, making the data under different wind speed conditions more uniform and comparable, facilitating subsequent analysis. Secondly, by analyzing the power output variance coefficient under different wind speed conditions and comparing it with a preset safety range, a relatively optimal range for rotor kinetic energy absorption can be identified, further laying the foundation for adjusting the rotor angular velocity. On this basis, based on the calculation of the tip speed ratio and the determination of the rotor angular velocity, preparations are made to ensure that the rotor can always operate within a relatively optimal range under different wind speed conditions. Subsequently, the system monitors the wind energy conversion efficiency under these conditions and, by extracting characteristic parameters and calculating the corresponding wind rotor power coefficient, optimizes the wind energy utilization efficiency under different wind speeds and maximizes the energy capture efficiency of the wind rotor. Finally, by adjusting the rotor angular velocity based on standard conversion conditions, this method can effectively smooth the output power of the wind turbine, reduce power fluctuations caused by wind speed fluctuations, and ensure more stable output power. This optimization method not only improves the efficiency of wind energy utilization through multiple data analysis and real-time adjustment, but also reduces power fluctuations during system operation, extends the service life of the equipment, and reduces the impact on the power grid, thereby achieving efficient, safe and stable power generation.

[0062] Example 2

[0063] Please refer to Figure 1, specifically: S1 specific steps include:

[0064] S11. Pre-deploy several sets of monitoring equipment in the wind farm, wherein the several sets of monitoring equipment include power sensors, strain gauges, laser rangefinders, speed sensors, wind speed sensors, and torque sensors;

[0065] S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions;

[0066] The relevant rotor state data information includes the mass Zg of each divided region of the rotor, the distance Jz of each divided region from the rotation axis, and the angular velocity Jsd of the rotor.

[0067] The specific steps of S2 include:

[0068] S21. Preprocess the relevant power output data information and the relevant rotor status data information to identify and remove outliers in the relevant power output data information and the relevant rotor status data information, and fill in the missing data using an interpolation method (such as linear interpolation, spline interpolation, etc.). At the same time, time align the relevant power output data information and the relevant rotor status data information to ensure that the data have a consistent time dimension. This operation is generally called data synchronization, and finally a wind power operation data set is generated;

[0069] S22. Through dimensionless processing technology, the information in the wind power operation data set is converted into unitless data through dimensionless technology for unified analysis. The dimensionless wind power operation data set is standardized so that the corresponding data values ​​are mapped to the interval [0,1] and the scale is unified. In this way, the operating status of the wind power generation system can be separated from the specific physical units and can be uniformly analyzed and compared.

[0070] In this embodiment, by deploying several sets of real-time monitoring devices within the wind farm, it is possible to accurately record wind turbine power output data under different wind speed conditions, as well as detailed rotor status data, such as the mass of each rotor region, distance from the rotation axis, and rotor angular velocity. This high-precision monitoring ensures the comprehensiveness and accuracy of the data, providing high-quality input data for subsequent optimization processes. Secondly, data preprocessing and synchronization effectively improve data quality. By identifying and removing outliers, the system eliminates interference caused by noise and abnormal data. Interpolation methods are also used to properly fill in missing data, ensuring data integrity and continuity. Data time alignment ensures that all types of data are compared and analyzed within the same time dimension, eliminating errors caused by acquisition time differences. This preprocessing further improves the accuracy and reliability of data analysis. Finally, dimensionless and normalized processing converts the data into a unitless form, further avoiding differences in units and magnitudes between different physical quantities and enabling analysis of all types of data on a unified scale. After dimensionless data is normalized, the data is mapped to a uniform interval for easier comparison and processing. This process not only simplifies the data analysis process but also improves the stability of data processing and control algorithms, making the system optimization process more efficient and robust. Therefore, through the comprehensive collection, preprocessing, dimensionless data, and normalization of monitoring data, this method can significantly improve data quality and consistency, ensuring a more accurate and efficient power optimization process, thereby achieving better power output smoothing and system stability.

[0071] Example 3

[0072] Please refer to Figure 1 , specifically: S3 specific steps include:

[0073] S31. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, which can be obtained specifically in the following manner:

[0074]

[0075] Where n represents the number of monitored wind speed conditions, i = 1, 2, 3, ..., n, Scg i Expressed as the output power value under wind speed condition i, Scg avg Expressed as the average output power value.

[0076] The above output power value Scg is monitored and obtained through a power sensor or an electric energy meter;

[0077] The specific steps of S3 also include:

[0078] S32. Preset a safety range [a, b] and compare it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out a matching range of rotor kinetic energy absorption. The specific judgment content is as follows:

[0079] S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time;

[0080] S322: If the power output difference coefficient Scxs falls within the safety range [a, b], relevant rotor status data information under the corresponding wind speed conditions will be extracted and analyzed;

[0081] The setting method of the safety range [a, b] is as follows: obtain the power output difference coefficient Scxs under each wind speed condition, and combine it with the statistical algorithm to calculate the average power output difference coefficient And the standard deviation of the power output variation coefficient σ, and according to the average power output variation coefficient And the standard deviation σ of the power output difference coefficient, set the safety range Where k is a constant, usually ranging from 1 to 3, corresponding to different confidence levels. The specific value is set by the user (according to actual conditions);

[0082] S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group. The rotor kinetic energy Znn is specifically obtained in the following manner:

[0083]

[0084] Where m represents the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia, rotor inertia is a physical quantity that represents the rotor's resistance to changes in its rotational speed. The greater the inertia, the more difficult it is for the rotor to accelerate or decelerate quickly when rotating;

[0085] The distribution state of the mass Zg on each divided area of ​​the above-mentioned rotor can be monitored and obtained through strain gauges or vibration sensors. The strain gauges are used to monitor the stress and strain on the wind wheel blades and other rotating components, thereby reflecting the changes in the mass distribution of the rotor during rotation, which helps to detect mass imbalance or blade damage.

[0086] The distance Jz of each segmented area from the rotation axis can be periodically calibrated or monitored by a laser rangefinder or a visual sensing system; these devices can be used to detect whether the blade or rotor position has changed, ensuring that the wind wheel operates normally and maintains the designed geometric relationship.

[0087] The angular velocity Jsd of the rotor can be monitored by a speed sensor or an encoder to obtain the real-time angular velocity of the rotor (ie, the number of rotations of the rotor per minute).

[0088] The rotor kinetic energy Znn refers to the mechanical energy stored in the rotor due to its rotation. In a wind turbine, this energy comes from the wind energy captured by the wind wheel.

[0089] S34. Statistically analyze the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

[0090] In this embodiment, first, by calculating the power output variation coefficient Scxs, the power output variation under different wind speed conditions can be effectively analyzed. This variation coefficient reflects the degree of deviation between the actual power output and the average output power. Based on this coefficient, the power fluctuation of the generator set under different wind speed conditions can be accurately assessed, laying the foundation for subsequent power smoothing optimization. This analysis can effectively identify situations where the power output fluctuates significantly or is unstable, making the system's response to wind speed changes more intelligent and dynamic. Secondly, based on a comparison and screening of the safety range, the power output variation coefficient Scxs is compared with a preset safety range to screen out the power fluctuation range that can be absorbed by the rotor kinetic energy under the corresponding wind speed conditions. This screening step ensures that relevant rotor status data is extracted and analyzed only under reasonable and safe power output variation conditions, thereby avoiding ineffective or excessive energy absorption adjustments in unstable or excessive fluctuations, and improving the stability and safety of the system. Finally, through the calculation and analysis of the rotor kinetic energy, the present invention can accurately quantify the mechanical energy stored in the rotor under different wind speed conditions. The rotor kinetic energy is calculated based on parameters such as the mass of each region of the rotor, the distance from the axis of rotation, and the angular velocity. In this way, by constructing a conditional data set and combining it with specific wind speed conditions, the system can accurately determine how much kinetic energy the rotor can absorb at a specific wind speed, thereby precisely controlling the acceleration and deceleration response of the rotor. This process not only optimizes the utilization of the rotor inertia, but also makes the response of the wind turbine smoother and more efficient when the wind speed fluctuates. Finally, through statistical analysis of the rotor kinetic energy absorption range, the present invention can accurately determine the range of rotor kinetic energy absorption based on the power output difference under specific wind speed conditions. This statistical processing based on precise data not only ensures that the wind turbine can effectively absorb kinetic energy under wind speed fluctuations, but also further reduces the sharp fluctuations in power output, thereby improving the stability of the power output of the generator set and the utilization rate of wind energy. In summary, this method can achieve power smoothing optimization of wind turbines more efficiently and safely through the calculation of the power output difference coefficient, precise analysis and dynamic adjustment of the rotor kinetic energy, significantly reducing power fluctuations and improving system stability.

[0091] Example 4

[0092] Please refer to Figure 1 , specifically: S4 specific steps include:

[0093] S41. Based on the initially screened matching range of rotor kinetic energy absorption and in combination with the method of obtaining the rotor kinetic energy Znn, determine the range of the rotor angular velocity Jsd;

[0094] S42. Calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. The specific method is as follows:

[0095]

[0096] Where Bjz is the radius of the wind wheel, Jsd is the angular velocity of the rotor, and Fs is the wind speed.

[0097] The radius Bjz of the wind wheel can be regularly calibrated by a laser rangefinder or a visual inspection system to check the wear or damage of the blades.

[0098] The wind speed Fs can be monitored and obtained through a wind speed sensor (common types include ultrasonic anemometers or mechanical anemometers);

[0099] The specific steps of S4 also include:

[0100] S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratios Jsb under different wind speed conditions obtained in S42, a range of the tip speed ratio Jsb is obtained.

[0101] In this embodiment, first, the rotor angular velocity range is determined based on a preliminarily screened matching rotor kinetic energy absorption range. Combined with the rotor kinetic energy calculation method, a reasonable range of rotor angular velocity is determined. This process ensures that the system can reasonably absorb and buffer energy under different wind speed conditions by precisely matching rotor kinetic energy with angular velocity, further avoiding excessively fast or slow rotor responses, thereby achieving smoother power output control. Secondly, by calculating the tip speed ratio, the system can accurately assess the ratio of the rotor blade tip speed to the wind speed under different wind speed conditions. The calculation formula for the tip speed ratio is based on the relationship between the rotor radius, the rotor angular velocity, and the wind speed, ensuring that the system can accurately measure the wind energy utilization efficiency. This step optimizes the rotor power coefficient by dynamically adjusting the tip speed ratio, helping to maximize wind energy conversion efficiency and improve the overall output performance of the generator set. Finally, the tip speed ratio range is determined by combining the rotor angular velocity range with the calculated tip speed ratio under different wind speed conditions. This determines the tip speed ratio range that is suitable for various wind speed conditions. Through this step, the system can automatically adjust the operating parameters of the wind turbine according to wind speed changes, ensuring that the turbine is always in a relatively optimal operating state under different wind speed conditions, thereby achieving stable power output and reducing power fluctuations. Therefore, by accurately determining the rotor angular velocity range and tip speed ratio range, this method optimizes the operating state of the wind turbine under different wind speed conditions. This method not only improves the utilization efficiency of wind energy and ensures the smooth operation of the system, but also significantly reduces power fluctuations, enhancing the overall performance and stability of the wind turbine.

[0102] Example 5

[0103] Please refer to Figure 1 , specifically: S5 specific steps include:

[0104] S51. Based on the tip speed ratio Jsb range obtained in S43, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition. mechanical and the wind energy P captured by the wind rotor wind .

[0105] The specific steps of S5 also include:

[0106] S52. Based on the relevant energy conversion data information, calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions. The wind rotor power coefficient Fgxs under the corresponding wind speed conditions is specifically obtained in the following manner:

[0107]

[0108] Where, P mechanical is the mechanical power value generated by the wind wheel, that is, the mechanical energy extracted by the wind wheel from the wind, P wind It is expressed as the wind energy captured by the wind rotor, that is, the wind energy swept by the wind rotor, the wind energy captured by the wind rotor Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density, usually 1.225 kg / m 3 ;π is the circumference of a circle, and its value is approximately 3.14159;

[0109] The mechanical power value P generated by the above wind wheel is mechanical The torque sensor and speed sensor can be used for monitoring and acquisition. The torque sensor is installed on the main shaft or gearbox to measure the torque generated by the wind rotor. The speed sensor is usually installed on the main shaft of the wind turbine generator set to calculate the mechanical power value through the torque generated by the wind rotor and the speed.

[0110] S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

[0111] In this embodiment, energy conversion efficiency monitoring within the tip speed ratio range is performed. By monitoring the tip speed ratio under different wind speed conditions, the system can determine the efficiency of the wind rotor in converting wind energy into mechanical energy at different wind speeds. This not only provides detailed energy conversion data, including the wind energy captured by the wind rotor and the mechanical power generated by the wind rotor, but also enables real-time evaluation of the wind rotor's energy conversion efficiency under different wind speed conditions. This provides a precise basis for subsequent optimization, enabling the system to dynamically adjust power output to improve overall power generation efficiency. Secondly, the precise calculation of the wind rotor power coefficient measures the efficiency of the wind rotor in extracting energy from the wind. By comparing the mechanical power generated by the wind rotor with the captured wind energy, it provides an accurate efficiency assessment for wind turbine power optimization. Finally, the power coefficient is characterized and used as a standard conversion condition. The maximum value represents the relatively optimal energy conversion efficiency of the wind rotor. The system can dynamically adjust the wind turbine's operating state based on this maximum value to ensure that the optimal wind energy capture efficiency is always maintained during actual operation.

[0112] Example 6

[0113] Please refer to Figure 1 , specifically: S6 specific steps include:

[0114] S61. Based on the standard conversion condition, trace back the wind speed condition corresponding to the standard conversion condition, and trace back to the corresponding tip speed ratio Jsb according to the wind speed condition, and extract the angular velocity Jsd of the rotor under the corresponding wind speed condition from the range of the rotor angular velocity Jsd according to the tip speed ratio Jsb under the wind speed condition, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

[0115] In this embodiment, firstly, the tracing of the standard conversion conditions ensures that the wind turbine can operate in a better working state under different wind speed conditions. By tracing the corresponding wind speed conditions based on the standard conversion conditions, the system can automatically identify the better tip speed ratio under the wind speed conditions, thereby providing an accurate reference basis for the control and adjustment of the wind turbine. This process enables the system to quickly identify the situation of wind speed changes and quickly make adjustments to avoid unstable power output due to wind speed fluctuations. Secondly, the extraction and dynamic adjustment of the rotor angular velocity further optimizes the operating state of the wind turbine. By extracting the rotor angular velocity under the corresponding wind speed conditions from the rotor angular velocity range based on the tip speed ratio, the system can accurately adjust the operating speed of the wind turbine to meet the requirements of different wind speeds. Based on the extracted rotor angular velocity value, the system can adjust the angular velocity of the wind turbine in real time to keep it within the better range, thereby achieving dynamic and smooth control of the wind turbine output power. In short, by adjusting the rotor angular velocity, the system can effectively reduce the impact of wind speed fluctuations on the power output of the generator set and achieve smooth power output. This smooth control not only improves the output stability of the wind turbine, but also reduces the impact on the power grid, ensuring the continuity and stability of the power supply.

[0116] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A power optimization method for a wind turbine generator system, characterized by: The following steps are included: S1. Deploy several sets of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information of the wind turbine in real time; S2. Preprocessing the relevant power output data and the relevant rotor status data to generate a wind power operation data set, and standardizing the information in the wind power operation data set using dimensionless technology; S3. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, and compare the power output difference coefficient Scxs with the preset safety range [a, b] to preliminarily screen out a matching range of rotor kinetic energy absorption; S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of the rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. Combined with the range of the rotor angular velocity Jsd, obtain the range of the tip speed ratio Jsb; S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction; S6. Based on the standard conversion conditions, trace back and adjust the rotor angular velocity Jsd to the output power of the wind turbine.

2. The power optimization method for a wind turbine generator system according to claim 1, wherein: The specific steps of S1 include: S11. Pre-deploy several sets of monitoring equipment in the wind farm, wherein the several sets of monitoring equipment include power sensors, strain gauges, laser rangefinders, speed sensors, wind speed sensors, and torque sensors; S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions; The relevant rotor state data information includes the mass Zg of each divided region of the rotor, the distance Jz of each divided region from the rotation axis, and the angular velocity Jsd of the rotor.

3. The power optimization method of a wind turbine generator system according to claim 2, characterized in that: The specific steps of S2 include: S21, preprocessing the relevant power output data information and the relevant rotor status data information to identify and remove abnormal values ​​in the relevant power output data information and the relevant rotor status data information, and filling in missing data using an interpolation method, while simultaneously time-aligning the relevant power output data information and the relevant rotor status data information, and finally generating a wind turbine operation data set; S22. Using dimensionless processing technology, convert the information in the wind turbine operating data set into unitless data through dimensionless technology, and standardize the dimensionless wind turbine operating data set so that the corresponding data values ​​are mapped to the interval [0,1].

4. The power optimization method for a wind turbine generator system according to claim 3, wherein: The specific steps of S3 include: S31. Based on the relevant power output data information, analyze and calculate the power output difference coefficient Scxs under different wind speed conditions, which can be obtained specifically in the following manner: Where n represents the number of monitored wind speed conditions, i = 1, 2, 3, ..., n, Scg i Expressed as the output power value under wind speed condition i, Scg avg Expressed as the average output power value.

5. The power optimization method for a wind turbine generator system according to claim 3, characterized in that: The specific steps of S3 also include: S32. Preset a safety range [a, b] and compare it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out a matching range of rotor kinetic energy absorption. The specific judgment content is as follows: S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time; S322: If the power output difference coefficient Scxs falls within the safety range [a, b], relevant rotor status data information under the corresponding wind speed conditions will be extracted and analyzed; S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group. The rotor kinetic energy Znn is specifically obtained in the following manner: Where m represents the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia; S34. Statistically analyze the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

6. The power optimization method for a wind turbine generator system according to claim 5, characterized in that: The specific steps of S4 include: S41. Based on the initially screened matching range of rotor kinetic energy absorption and in combination with the method of obtaining the rotor kinetic energy Znn, determine the range of the rotor angular velocity Jsd; S42. Calculate the tip speed ratio Jsb under different wind speed conditions based on the ratio of the speed of the rotor blade tip to the corresponding wind speed. The specific method is as follows: Where Bjz is the radius of the wind wheel, Jsd is the angular velocity of the rotor, and Fs is the wind speed.

7. The power optimization method for a wind turbine generator system according to claim 6, characterized in that: The specific steps of S4 also include: S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratios Jsb under different wind speed conditions obtained in S42, a range of the tip speed ratio Jsb is obtained.

8. The power optimization method for a wind turbine generator system according to claim 7, characterized in that: The specific steps of S5 include: S51. Based on the tip speed ratio Jsb range obtained in S43, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition. mechanical and the wind energy P captured by the wind rotor wind .

9. The power optimization method for a wind turbine generator system according to claim 8, characterized in that: The specific steps of S5 also include: S52. Based on the relevant energy conversion data information, calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions. The wind rotor power coefficient Fgxs under the corresponding wind speed conditions is specifically obtained in the following manner: Where, P mechanical is the mechanical power value generated by the wind wheel, P wind Expressed as the wind energy captured by the wind rotor, the wind energy captured by the wind rotor Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density; π is the circumference of a circle; S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

10. The power optimization method of a wind turbine generator system according to claim 1, characterized in that: The specific steps of S6 include: S61. Based on the standard conversion condition, trace back the wind speed condition corresponding to the standard conversion condition, and trace back to the corresponding tip speed ratio Jsb according to the wind speed condition, and extract the angular velocity Jsd of the rotor under the corresponding wind speed condition from the range of the rotor angular velocity Jsd according to the tip speed ratio Jsb under the wind speed condition, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

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