A wind turbine operating status monitoring system

Abstract

The present invention relates to the technical field of wind power generation, and in particular to a wind turbine operating state monitoring system, comprising: an information acquisition module for acquiring environmental data and wind turbine operating data in real time, and also for acquiring historical operating data of the wind turbine, a historical data analysis module for analyzing the historical operating state of the wind turbine, and setting a monitoring level according to the analysis result of the historical operating state, an operation monitoring module for analyzing wind power anomalies, and analyzing the wind power conversion state of the wind turbine within the monitoring period, an adjustment and optimization module for adjusting and optimizing the analysis process of wind power anomalies, an operation state analysis module for analyzing the operating state of the wind turbine within the monitoring period, and an operation control module for generating a control scheme for the wind turbine. The present invention effectively improves the monitoring efficiency of the operating state of the wind turbine.

Description

Technical Field

[0001] The invention relates to the technical field of wind power generation, and in particular to a wind generator operation status monitoring system. Background Art

[0002] As an important part of renewable energy, wind power is rapidly being promoted around the world. However, wind turbines are usually located in remote and harsh environments, which makes their maintenance and fault detection a major challenge. Although existing condition monitoring systems can provide certain data, they often have problems such as slow response speed, limited monitoring range and insufficient data processing capabilities.

[0003] Chinese patent publication number CN111812504A discloses a method and system for diagnosing faults of wind turbines. The method includes: collecting operating parameter signals of wind turbines; extracting characteristic components of operating parameter signals using a characteristic component extraction model; determining operating data of wind turbines based on characteristic components, performing closed-loop differential operations based on fault thresholds on operating data and power quality indicators of wind turbines; determining fault information of wind turbine faults based on differential operation results, and generating fault warning information. According to the embodiment of the invention, it is possible to accurately and efficiently diagnose faults of wind turbines and achieve a fault warning effect based on power quality indicators; it can be seen that the invention only analyzes the operating parameters of the wind turbine itself to judge the fault of the generator, and does not analyze the environmental factors of the wind turbine operation process, and cannot achieve accurate monitoring of the operating status of the wind turbine, and there is a problem of low efficiency in monitoring the operating status of the wind turbine. Summary of the invention

[0004] To this end, the present invention provides a wind turbine operating status monitoring system to overcome the problem of low efficiency in wind turbine operating status monitoring in the prior art.

[0005] To achieve the above object, the present invention provides a wind turbine operating status monitoring system, comprising:

[0006] An information acquisition module is used to acquire environmental data and wind turbine operation data in real time, and is also used to acquire historical operation data of wind turbines;

[0007] A historical data analysis module is used to analyze the historical operating status of the wind turbine according to the historical operating data of the wind turbine, and to set the monitoring level according to the analysis results of the historical operating status;

[0008] An operation monitoring module is used to analyze wind power anomalies according to environmental data within a monitoring period, and to analyze the wind power conversion state of the wind turbine within the monitoring period according to the wind power anomaly analysis results and the wind turbine operation data within the monitoring period;

[0009] An adjustment and optimization module is used to adjust the analysis process of wind anomaly according to the wind direction data within the monitoring period, and is also used to optimize the adjustment process of wind anomaly according to meteorological data;

[0010] An operation status analysis module is used to analyze the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis results and the monitoring level analysis results of the wind turbine within the monitoring period;

[0011] The operation control module is used to generate a control plan for the wind turbine according to the analysis results of the wind turbine operation status within the monitoring period.

[0012] Further, the historical data analysis module is provided with a historical analysis unit, and the historical analysis unit analyzes the historical operation status of the wind turbine according to the historical operation data;

[0013] The historical analysis unit calculates the historical operation index α(i) in each historical monitoring period according to the historical operation data, and sets α(i)=exp{fs(i) / FS×s(i) / P};

[0014] Where, s(i) is the output power of the wind turbine in the i-th historical monitoring period, P is the rated power of the wind turbine, fs(i) is the average wind speed in the i-th historical monitoring period, and FS is the rated maximum power of the wind turbine;

[0015] The historical analysis unit compares the historical operation index α(i) in each historical monitoring period with each preset wind turbine operation index, and analyzes the historical operation status of each historical monitoring period according to the comparison result, wherein:

[0016] When α(i)<A1, the history analysis unit determines that the historical operation state in the historical monitoring period is a low-load operation abnormal state;

[0017] When A1≤α(i)<A2, the history analysis unit determines that the historical operation state within the historical monitoring period is a normal operation state;

[0018] When α(i)≥A2, the history analysis unit determines that the historical operation state in the historical monitoring period is a high-load operation state;

[0019] Wherein, A1 is a first preset wind turbine operating index, A2 is a second preset wind turbine operating index, and A1<A2.

[0020] Furthermore, the historical data analysis module is further provided with a level classification unit, and the level classification unit analyzes the monitoring level of the wind turbine according to the historical operating status analysis result of the wind turbine;

[0021] The level classification unit counts the number n1 of low-load operating states in the historical operation state of each historical monitoring period and the number n2 of high-load operating states in the historical operation state of each historical monitoring period;

[0022] The level classification unit analyzes the monitoring level of the wind turbine according to the statistical results, wherein:

[0023] When (n1+n2) / N≥K and n1<n2, the level classification unit sets the monitoring level of the wind turbine to level one and sets a first offset coefficient β1, setting β1=(n1+n2) / N / K;

[0024] When (n1+n2) / N≥K and n1≥n2, the level classification unit sets the monitoring level of the wind turbine to level 2 and sets a second offset coefficient β2, setting β2=K / [(n1+n2) / N];

[0025] When (n1+n2) / N<K, the level classification unit sets the monitoring level of the wind turbine to level 3, and sets the third offset coefficient β3, setting β3=1;

[0026] Among them, K is the preset abnormality ratio and N is the number of historical monitoring cycles.

[0027] Further, the operation monitoring module is provided with a wind monitoring unit, and the wind monitoring unit analyzes the wind state according to the environmental data within the monitoring period;

[0028] The wind force monitoring unit calculates the wind force f carried by the blades according to the environmental data in the monitoring period. The calculation process of the wind force f carried by the blades is as follows:

[0029] f = P × S × cosθ;

[0030] θ = a·b / |a|×|b|;

[0031] Among them, p is the real-time wind pressure, S is the blade area, a is the real-time unit wind direction vector, b is the blade plane normal vector, and θ is the angle between the wind speed direction and the blade normal vector direction;

[0032] The wind force monitoring unit compares the wind force f carried by the blade with each preset wind force, and analyzes the wind force state according to the comparison result, wherein:

[0033] When n×f<F1, the wind force monitoring unit determines that the wind force carried by the blade is low;

[0034] When F1≤n×f<F2, the wind force monitoring unit determines that the wind force carried by the blade is normal;

[0035] When n×f≥F2, the wind force monitoring unit determines that the wind force carried by the blade is high;

[0036] Wherein, F1 is the first preset bearing wind force, F2 is the second preset bearing wind force, n is the number of blades of the wind power generation equipment, and F1<F2.

[0037] Furthermore, the operation monitoring module is further provided with an abnormality analysis unit, which analyzes the wind abnormality according to the wind state analysis result within the monitoring period, wherein:

[0038] When a1×t1 / T+a2×t2 / T<B, the abnormality analysis unit determines that the wind force is normal during the monitoring period;

[0039] When a1×t1 / T+a2×t2 / T≥B, the abnormality analysis unit determines that the wind force is abnormal during the monitoring period;

[0040] Among them, a1 is the low wind force anomaly weight, a2 is the high wind force anomaly weight, and a1+a2=1, t1 is the duration of the wind state analysis result during the monitoring period when the blade-bearing wind force is low, t2 is the duration of the wind state analysis result during the monitoring period when the blade-bearing wind force is high, T is the duration of the monitoring period, and B is the preset anomaly coefficient.

[0041] Furthermore, the operation monitoring module is further provided with a conversion state analysis unit, which analyzes the wind power conversion state according to the wind power abnormality analysis result and the operation data of the wind turbine within the monitoring period, wherein:

[0042] When the analysis result of wind power abnormality is that the wind power is normal, if γ<Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal;

[0043] When the analysis result of wind power abnormality is wind power abnormality, if γ<Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal;

[0044] Where γ is the power conversion efficiency.

[0045] Further, the adjustment optimization module is provided with a fluctuation adjustment unit, and the fluctuation adjustment unit analyzes the wind direction volatility according to the wind direction vector within the monitoring period;

[0046] The fluctuation adjustment unit calculates the wind direction variation coefficient CV, and the calculation formula of the wind direction variation coefficient is as follows:

[0047] CV = σ / E × 100%;

[0048] E=[c(1)+c(2)+...+c(T / t)] / (T / t);

[0049] σ = {{[c(1)-E] 2 +[c(2)-E] 2 +...+[c(T / t)-E] 2} / (T / t)} 1 / 2 ;

[0050] Wherein, t is the real-time acquisition interval duration, c(1) represents the modulus of the first real-time wind volume vector in the monitoring period, c(2) represents the modulus of the second real-time wind volume vector in the monitoring period, and c(T / t) represents the modulus of the T / tth real-time wind volume vector in the monitoring period;

[0051] The fluctuation adjustment unit compares the wind direction variation coefficient CV with the fluctuation threshold value YC, and adjusts the analysis process of wind force anomaly according to the comparison result, wherein:

[0052] When CV<YC, the fluctuation adjustment unit determines that the wind force fluctuation is normal and does not make any adjustment;

[0053] When CV≥YC, the fluctuation adjustment unit determines that the wind power fluctuation is abnormal, and adjusts the first preset wind turbine generator rotation efficiency to Y1', setting Y1'=Y1×cos{arctan[(CV-YC) / YC]}, and adjusts the second preset wind turbine generator rotation efficiency to Y2', setting Y2'=Y2×sin[(CV-YC) / YC];

[0054] The adjustment optimization module is provided with an optimization unit, which optimizes the adjustment process of wind abnormality according to meteorological data within the monitoring period, wherein:

[0055] When sd<SD, the optimization unit determines that the air humidity in the monitoring period is normal;

[0056] When sd≥SD, the optimization unit determines that the air humidity in the monitoring period is abnormal, and optimizes the fluctuation threshold YC to YC', setting YC'=YC×{2-exp[(sd-SD) / SD]};

[0057] Among them, sd is the average absolute air humidity during the monitoring period, and SD is the absolute air humidity threshold.

[0058] Furthermore, the operation status analysis module is provided with an operation status analysis unit, which analyzes the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis result and the monitoring level analysis result of the wind turbine within the monitoring period, wherein:

[0059] When the wind power conversion state of the wind turbine is normal, if (γ-Y1) / Y1×βj<R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is adjustable low-load operation; if (γ-Y1) / Y1×βj≥R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is unadjustable low-load operation;

[0060] When the wind power conversion state of the wind turbine is abnormal, if (γ-Y1) / Y1×βj<R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is normal operation; if (γ-Y1) / Y1×βj≥R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is adjustable and highly compliant operation;

[0061] Wherein, j is set to 1, 2, 3, R1 is the first preset operating state coefficient, R2 is the second preset operating state coefficient, and R1<R2.

[0062] Furthermore, the operating status monitoring module is also provided with an alarm unit, which alarms the user according to the analysis result of the operating status of the wind turbine in the monitoring period, wherein:

[0063] When the wind turbine generator is in the operating state of adjustable low load operation, the alarm unit sends a corresponding adjustment alarm to the user;

[0064] When the wind turbine generator is in an uncontrollable low-load operation state, the alarm unit does not send an alarm to the user;

[0065] When the wind turbine generator is in normal operation, the alarm unit does not send an alarm to the user;

[0066] When the wind turbine generator is in the controllable high compliance operation state, if TC < T×q, the alarm unit sends a yaw control alarm to the user; if TC < T×q, the alarm unit does not send an alarm to the user;

[0067] Among them, TC is the duration of the wind turbine's adjustable high-compliance operation, and q is the preset continuous monitoring duration.

[0068] Furthermore, the operation control module generates a control scheme for the wind turbine according to the analysis result of the wind turbine operation status within the monitoring period, wherein:

[0069] When the wind turbine generator operating state is adjustable low-load operation during the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ1, and sets Jθ1=Jθ×cos{[R1-(γ-Y1) / Y1×βj] / R1};

[0070] When the wind turbine generator operating state is uncontrollable low-load operation or normal operation during the monitoring period, the operation control module does not control the wind turbine generator pitch angle in the next monitoring period;

[0071] When the wind turbine generator operating state is adjustable high compliance operation in the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ2, and sets Jθ2=Jθ×exp{[(γ-Y1) / Y1×βj-R2] / R2};

[0072] Wherein, Jθ is the pitch angle of the wind turbine blades during the monitoring period;

[0073] The operation control module outputs the wind turbine pitch angle of the next monitoring cycle to the user as a control scheme.

[0074] Compared with the prior art, the beneficial effects of the present invention lie in that the information required for the present embodiment is acquired by the information acquisition module, thereby improving the accuracy of information acquisition; the monitoring level is set by the historical data analysis module, thereby improving the accuracy of monitoring level analysis; the wind power conversion state is analyzed by the operation monitoring module, thereby improving the accuracy of wind power conversion state analysis; the analysis process of wind power abnormality is adjusted and optimized by the adjustment and optimization module, thereby improving the accuracy of wind power conversion state analysis; the operation state analysis module analyzes the operation state of the wind turbine, and an alarm is issued to the user according to the analysis result, thereby improving the accuracy of wind turbine operation state analysis; the operation control module generates a control plan for the wind turbine according to the analysis result of the wind turbine operation state within the monitoring period, thereby improving the accuracy of wind turbine operation state control, and thereby improving the efficiency of wind turbine operation state monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 Schematic diagram of the structure of the wind turbine operating status monitoring system of this embodiment.

[0076] Figure 2 Schematic diagram of the structure of the historical data analysis module of this embodiment.

[0077] Figure 3 This is a schematic diagram of the structure of the operation monitoring module of this embodiment.

[0078] Figure 4 This is a schematic diagram of the structure of the adjustment and optimization module in this embodiment.

[0079] Figure 5 Schematic diagram of the structure of the running status analysis module of this embodiment. DETAILED DESCRIPTION

[0080] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0081] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0082] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0083] See also Figure 1 As shown, it is a structural diagram of the wind turbine operating status monitoring system of this embodiment, including:

[0084] An information acquisition module is used to acquire environmental data and wind turbine operation data in real time, and is also used to acquire historical operation data of wind turbines;

[0085] The historical operation data include the output power and average wind speed of the wind turbine within the historical monitoring period; the wind turbine operation data include the blade area, the wind speed with rated maximum power of the wind turbine, the pitch angle of the wind turbine blades, the average output power of the wind turbine within the monitoring period, and the average wind force carried by the blades within the monitoring period; the environmental data include wind direction data and meteorological data; the wind direction data include real-time wind direction vector, real-time wind pressure, real-time wind speed, and real-time unit wind direction vector, and the meteorological data include absolute air humidity; this embodiment does not specifically limit the method for obtaining environmental data and wind turbine operation data, and those skilled in the art can freely set it, as long as the environmental data is satisfied and the need to obtain the operating data of the wind turbine, such as obtaining environmental data by setting real-time sensors, obtaining the blade area and the wind speed with rated maximum power of the wind turbine through user interactive input, obtaining the pitch angle of the wind turbine blades, the average output power of the wind turbine during the monitoring period, and the average wind force carried by the blades during the monitoring period through monitoring the generator monitoring equipment, and obtaining the wind direction data through the wind direction measuring instrument; the historical operating data is the operating data within multiple historical monitoring periods, and the historical operating data includes the historical generator output power, the historical generator power factor, the historical generator winding temperature and the historical generator speed; the duration of the historical monitoring period is the same as the monitoring period;

[0086] This embodiment does not specifically limit the number of historical operation data of the wind turbine to be obtained. Those skilled in the art can freely set it as long as the demand for the number of historical operation data of the wind turbine is met. For example, the operation data in each historical monitoring period within a week can be used as the historical operation data, and the number of historical monitoring periods is the number of historical operation data to be obtained.

[0087] A historical data analysis module, used to analyze the historical operating status of the wind turbine according to the historical operating data of the wind turbine, and to set the monitoring level according to the analysis results of the historical abnormal status, the historical data analysis module is connected to the information acquisition module;

[0088] An operation monitoring module is used to analyze wind power anomaly according to environmental data within the monitoring period, and to analyze the wind power conversion state of the wind turbine within the monitoring period according to the wind power anomaly analysis result and the operation data of the wind turbine within the monitoring period. The operation monitoring module is connected to the information acquisition module. This embodiment does not specifically limit the duration of the monitoring period, and those skilled in the art can freely set it as long as the duration of the monitoring period is met. For example, the duration of the monitoring period can be set to 5 minutes, 10 minutes, etc.

[0089] An adjustment and optimization module, used to adjust the analysis process of wind anomaly according to the wind direction vector within the monitoring period, and also used to optimize the adjustment process of wind anomaly according to meteorological data, the adjustment and optimization module is connected to the operation monitoring module;

[0090] An operation status analysis module, used to analyze the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis results and the monitoring level analysis results of the wind turbine within the monitoring period, and to warn the user according to the wind turbine operation status analysis results, and the operation status analysis module is connected with the adjustment and optimization module and the historical data analysis module;

[0091] The operation control module is used to control the pitch angle of the wind generator according to the analysis result of the operation status of the wind generator within the monitoring period, and the operation control module is connected to the operation status analysis module.

[0092] Specifically, a wind turbine operating status monitoring system described in this embodiment is applied to the operating status monitoring of wind turbines of variable-speed wind power generation equipment established on ridges in mountainous areas; the present invention analyzes historical data and sets monitoring levels, analyzes the status of wind power conversion, and then analyzes the operating status of the wind turbine according to the monitoring level and the wind power conversion status analysis results, thereby improving the efficiency of wind turbine operating status monitoring.

[0093] See also Figure 2 As shown, it is a schematic diagram of the structure of the historical data analysis module of this embodiment, including:

[0094] A historical analysis unit, used to analyze the historical operating status of the wind turbine according to the historical operating data;

[0095] The level classification unit is used to analyze the monitoring level of the wind turbine according to the historical operating status analysis result of the wind turbine, and the level classification unit is connected to the historical analysis unit.

[0096] Specifically, the historical data analysis module is provided with a historical analysis unit, and the historical analysis unit analyzes the historical operating status of the wind turbine according to the historical operating data;

[0097] The historical analysis unit calculates the historical operation index α(i) in each historical monitoring period according to the historical operation data, and sets α(i)=exp{fs(i) / FS×s(i) / P};

[0098] Where, s(i) is the output power of the wind turbine in the i-th historical monitoring period, P is the rated power of the wind turbine, fs(i) is the average wind speed in the i-th historical monitoring period, and FS is the rated maximum power of the wind turbine;

[0099] The historical analysis unit compares the historical operation index α(i) in each historical monitoring period with each preset wind turbine operation index, and analyzes the historical operation status of each historical monitoring period according to the comparison result, wherein:

[0100] When α(i)<A1, the history analysis unit determines that the historical operation state in the historical monitoring period is a low-load operation abnormal state;

[0101] When A1≤α(i)<A2, the history analysis unit determines that the historical operation state within the historical monitoring period is a normal operation state;

[0102] When α(i)≥A2, the history analysis unit determines that the historical operation state in the historical monitoring period is a high-load operation state;

[0103] Wherein, A1 is a first preset wind turbine operating index, A2 is a second preset wind turbine operating index, and A1<A2.

[0104] Specifically, the historical analysis unit improves the accuracy of the analysis of the historical data of the wind turbine by analyzing the historical operating status, thereby improving the accuracy of the monitoring level setting, thereby improving the accuracy of the analysis of the operating status of the wind turbine, and ultimately improving the efficiency of monitoring the operating status of the wind turbine; it can be understood that this embodiment does not make specific limitations on the values ​​of the first preset wind turbine operating index A1 and the second preset wind turbine operating index A2, and technical personnel in this field can set them freely, as long as the value requirements of the first preset wind turbine operating index A1 and the second preset wind turbine operating index A2 are met. For example, the first preset wind turbine operating index A1 can be set to 1.3, and the second preset wind turbine operating index A2 can be set to 1.7.

[0105] Specifically, the historical data analysis module is further provided with a level classification unit, and the level classification unit analyzes the monitoring level of the wind turbine according to the historical operating status analysis result of the wind turbine;

[0106] The level classification unit counts the number n1 of low-load operating states in the historical operation state of each historical monitoring period and the number n2 of high-load operating states in the historical operation state of each historical monitoring period;

[0107] The level classification unit analyzes the monitoring level of the wind turbine according to the statistical results, wherein:

[0108] When (n1+n2) / N≥K and n1<n2, the level classification unit sets the monitoring level of the wind turbine to level one and sets a first offset coefficient β1, setting β1=1+[(n1+n2) / NK] / K;

[0109] When (n1+n2) / N≥K and n1≥n2, the level classification unit sets the monitoring level of the wind turbine to level 2 and sets a second offset coefficient β2, setting β2=1-[(n1+n2) / NK] / K;

[0110] When (n1+n2) / N<K, the level classification unit sets the monitoring level of the wind turbine to level 3, and sets the third offset coefficient β3, setting β3=1;

[0111] Among them, K is the preset abnormality ratio and N is the number of historical monitoring cycles.

[0112] Specifically, the level division unit improves the accuracy of the monitoring level setting by analyzing the monitoring level of the wind turbine, thereby improving the accuracy of the analysis of the operating status of the wind turbine, and ultimately improving the efficiency of monitoring the operating status of the wind turbine; it can be understood that this embodiment does not make a specific limitation on the value of the preset abnormality ratio K, and technical personnel in this field can set it freely, as long as the value requirement of the preset abnormality ratio K is met, such as the preset abnormality ratio K can be set to 0.1.

[0113] It can be understood that the monitoring level of the present embodiment is level one, which means that in the next monitoring period, the operating status monitoring of the wind turbine needs to be judged according to strict standards for the high-load operating status; the monitoring level is level two, which means that in the next monitoring period, the operating status monitoring of the wind turbine needs to be judged according to strict standards for the high-load operating status; the monitoring level is level three, which means that in the next monitoring period, the operating status monitoring of the wind turbine only needs to maintain normal standard monitoring.

[0114] See also Figure 3 As shown, it is a schematic diagram of the structure of the operation monitoring module of this embodiment, including:

[0115] A wind monitoring unit for analyzing wind conditions based on environmental data during a monitoring period;

[0116] An abnormality analysis unit, used to analyze wind abnormality according to the wind state analysis result within the monitoring period, and the abnormality analysis unit is connected to the wind monitoring unit;

[0117] The conversion state analysis unit is used to analyze the wind power conversion state according to the wind power abnormality analysis result and the operation data of the wind turbine generator within the monitoring period, and the conversion state analysis unit is connected to the abnormality analysis unit.

[0118] Specifically, the operation monitoring module is provided with a wind monitoring unit, and the wind monitoring unit analyzes the wind state according to the environmental data within the monitoring period;

[0119] The wind force monitoring unit calculates the wind force f carried by the blades according to the environmental data in the monitoring period. The calculation process of the wind force f carried by the blades is as follows:

[0120] f = P × S × cosθ;

[0121] θ = a·b / |a|×|b|;

[0122] Among them, p is the real-time wind pressure, S is the blade area, a is the real-time unit wind direction vector, b is the blade plane normal vector, and θ is the angle between the wind speed direction and the blade normal vector direction;

[0123] The wind force monitoring unit compares the wind force f carried by the blade with each preset wind force, and analyzes the wind force state according to the comparison result, wherein:

[0124] When n×f<F1, the wind force monitoring unit determines that the wind force carried by the blade is low;

[0125] When F1≤n×f<F2, the wind force monitoring unit determines that the wind force carried by the blade is normal;

[0126] When n×f≥F2, the wind force monitoring unit determines that the wind force carried by the blade is high;

[0127] Wherein, F1 is the first preset bearing wind force, F2 is the second preset bearing wind force, n is the number of blades of the wind power generation equipment, and F1<F2.

[0128] It can be understood that the calculation process of "a·b / |a|×|b|" described in this embodiment is the dot product of vector a and vector b divided by the product of the modulus of vector a and vector b, and the result is the angle between the two vectors; at the same time, the real-time unit wind direction vector described in this embodiment is a vector with a unit length of 1, which only represents the wind direction but not the wind force.

[0129] Specifically, the wind monitoring unit improves the accuracy of wind state analysis by performing real-time analysis of wind state, thereby improving the accuracy of wind abnormality analysis, thereby improving the accuracy of wind power conversion state analysis, and ultimately improving the efficiency of wind turbine operating state monitoring; it can be understood that this embodiment does not make specific limitations on the values ​​of the first preset bearing wind force F1 and the second preset bearing wind force F2, and technical personnel in this field can set them freely, as long as the value requirements of the first preset bearing wind force F1 and the second preset bearing wind force F2 are met. For example, the first preset bearing wind force F1 can be set to 5% of the maximum bearing wind force of the blade, and the second preset bearing wind force F2 can be set to 60% of the maximum bearing wind force of the blade.

[0130] Specifically, the operation monitoring module is further provided with an abnormality analysis unit, which analyzes the wind abnormality according to the wind state analysis result within the monitoring period, wherein:

[0131] When a1×t1 / T+a2×t2 / T<B, the abnormality analysis unit determines that the wind force is normal during the monitoring period;

[0132] When a1×t1 / T+a2×t2 / T≥B, the abnormality analysis unit determines that the wind force is abnormal during the monitoring period;

[0133] Among them, a1 is the low wind force anomaly weight, a2 is the high wind force anomaly weight, and a1+a2=1, t1 is the duration of the wind state analysis result during the monitoring period when the blade-bearing wind force is low, t2 is the duration of the wind state analysis result during the monitoring period when the blade-bearing wind force is high, T is the duration of the monitoring period, and B is the preset anomaly coefficient.

[0134] Specifically, the abnormality analysis unit analyzes the wind abnormality according to the wind state analysis results within the monitoring period, thereby improving the accuracy of the wind abnormality analysis, thereby improving the accuracy of the wind power conversion state analysis, and ultimately improving the efficiency of wind turbine operating state monitoring; it can be understood that this embodiment does not make specific limitations on the value of the preset abnormality coefficient B, and technical personnel in this field can set it freely, as long as the value requirements of the preset abnormality coefficient B are met, such as the preset abnormality coefficient B can be set to 0.2.

[0135] Specifically, the operation monitoring module is further provided with a conversion state analysis unit, which analyzes the wind power conversion state according to the wind power abnormality analysis result and the operation data of the wind turbine within the monitoring period, wherein:

[0136] When the analysis result of wind power abnormality is that the wind power is normal, if γ<Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal;

[0137] When the analysis result of wind power abnormality is wind power abnormality, if γ<Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal;

[0138] Among them, γ is the power conversion efficiency, set γ=f 均 / FS×p 均 / P,f 均 is the average wind force on the blades during the monitoring period, p 均 is the average output power of the wind turbine generator during the monitoring period, Y1 is the first preset wind turbine generator rotation efficiency, and Y2 is the second preset wind turbine generator rotation efficiency.

[0139] Specifically, the conversion state analysis unit analyzes the wind power conversion state according to the wind abnormality analysis results within the monitoring period and the operating data of the wind turbine, thereby improving the accuracy of the wind power conversion state analysis and ultimately improving the efficiency of monitoring the operating state of the wind turbine. It can be understood that the present embodiment does not specifically limit the values ​​of the first preset wind turbine rotation efficiency Y1 and the second preset wind turbine rotation efficiency Y2, and those skilled in the art can set them freely, as long as the value requirements of the first preset wind turbine rotation efficiency Y1 and the second preset wind turbine rotation efficiency Y2 are met. For example, the first preset wind turbine rotation efficiency Y1 can be set to 0.3, and the second preset wind turbine rotation efficiency Y2 can be set to 0.4.

[0140] See also Figure 4 As shown, it is a schematic diagram of the structure of the adjustment and optimization module of this embodiment, including:

[0141] A fluctuation adjustment unit is used to analyze the wind direction fluctuation according to the wind direction data within the monitoring period, and to adjust the analysis process of wind force anomaly according to the wind direction fluctuation analysis result;

[0142] The optimization unit is used to optimize the adjustment process of wind anomaly according to the meteorological data in the monitoring period, and the optimization unit is connected to the fluctuation adjustment unit.

[0143] Specifically, the adjustment optimization module is provided with a fluctuation adjustment unit, which analyzes the wind direction volatility according to the wind direction data within the monitoring period;

[0144] The fluctuation adjustment unit calculates the wind direction variation coefficient CV, and the calculation formula of the wind direction variation coefficient is as follows:

[0145] CV = σ / E × 100%;

[0146] E=[c(1)+c(2)+...+c(T / t)] / (T / t);

[0147] σ = {{[c(1)-E] 2 +[c(2)-E] 2 +...+[c(T / t)-E] 2} / (T / t)} 1 / 2 ;

[0148] Wherein, t is the real-time acquisition interval duration, c(1) represents the modulus of the first real-time wind volume vector in the monitoring period, c(2) represents the modulus of the second real-time wind volume vector in the monitoring period, and c(T / t) represents the modulus of the T / tth real-time wind volume vector in the monitoring period;

[0149] The fluctuation adjustment unit compares the wind direction variation coefficient CV with the fluctuation threshold value YC, and adjusts the analysis process of wind force anomaly according to the comparison result, wherein:

[0150] When CV<YC, the fluctuation adjustment unit determines that the wind force fluctuation is normal and does not make any adjustment;

[0151] When CV≥YC, the fluctuation adjustment unit determines that the wind fluctuation is abnormal, and adjusts the first preset wind turbine rotation efficiency to Y1', setting Y1'=Y1×cos{arctan[(CV-YC) / YC]}, and adjusts the second preset wind turbine rotation efficiency to Y2', setting Y2'=Y2×sin[(CV-YC) / YC].

[0152] Specifically, the fluctuation adjustment unit analyzes the wind direction volatility according to the wind direction vector within the monitoring period, and adjusts the analysis process of wind abnormality according to the wind direction volatility analysis result, thereby improving the accuracy of wind power conversion state analysis, and ultimately improving the efficiency of wind turbine operating state monitoring; it can be understood that this embodiment does not make specific limitations on the value of the fluctuation threshold value YC, and technical personnel in this field can set it freely, as long as the value requirements of the fluctuation threshold value YC are met, such as the fluctuation threshold value YC can be set to 20%.

[0153] Specifically, the adjustment optimization module is provided with an optimization unit, and the optimization unit optimizes the adjustment process of wind abnormality according to the meteorological data within the monitoring period, wherein:

[0154] When sd<SD, the optimization unit determines that the air humidity in the monitoring period is normal;

[0155] When sd≥SD, the optimization unit determines that the air humidity in the monitoring period is abnormal, and optimizes the fluctuation threshold YC to YC', setting YC'=YC×{2-exp[(sd-SD) / SD]};

[0156] Among them, sd is the average absolute air humidity during the monitoring period, and SD is the absolute air humidity threshold.

[0157] Specifically, the optimization unit optimizes the adjustment process of wind abnormality according to the meteorological data within the monitoring period, thereby improving the accuracy of wind power conversion state analysis, and ultimately improving the efficiency of wind turbine operating state monitoring; it can be understood that this embodiment does not specifically limit the value of the air absolute humidity threshold SD, and technical personnel in this field can set it freely, as long as the value requirements of the air absolute humidity threshold SD are met, such as the air absolute humidity threshold SD can be set to 90%.

[0158] See also Figure 5 As shown, it is a schematic diagram of the structure of the running status analysis module of this embodiment, including:

[0159] An operation status analysis unit, used to analyze the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis result and the monitoring level analysis result of the wind turbine within the monitoring period;

[0160] The alarm unit is used to warn the user according to the analysis result of the wind turbine operating status within the monitoring period, and the alarm unit is connected to the operating status analysis unit.

[0161] Specifically, the operation status analysis module is provided with an operation status analysis unit, and the operation status analysis unit analyzes the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis result and the monitoring level analysis result of the wind turbine within the monitoring period, wherein:

[0162] When the wind power conversion state of the wind turbine is normal, if (γ-Y1) / Y1×βj<R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is adjustable low-load operation; if (γ-Y1) / Y1×βj≥R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is unadjustable low-load operation;

[0163] When the wind power conversion state of the wind turbine is abnormal, if (γ-Y1) / Y1×βj<R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is normal operation; if (γ-Y1) / Y1×βj≥R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is adjustable and highly compliant operation;

[0164] Wherein, j=1, 2, 3 is set, R1 is the first preset operating state coefficient, R2 is the second preset operating state coefficient, and R1<R2.

[0165] Specifically, the operating status analysis unit analyzes the operating status of the wind turbine within the monitoring period according to the wind power conversion status analysis results and the monitoring level analysis results of the wind turbine within the monitoring period, thereby improving the accuracy of the wind turbine operating status analysis, and further improving the efficiency of wind turbine operating status monitoring; it can be understood that this embodiment does not make specific limitations on the values ​​of the first preset operating status coefficient R1 and the second preset operating status coefficient R2, and technical personnel in this field can set them freely, as long as the value requirements of the first preset operating status coefficient R1 and the second preset operating status coefficient R2 are met, such as the first preset operating status coefficient R1 can be set to 0.5, and the second preset operating status coefficient R2 can be set to 0.6.

[0166] Specifically, the operating status monitoring module is further provided with an alarm unit, which alarms the user according to the analysis result of the operating status of the wind turbine within the monitoring period, wherein:

[0167] When the wind turbine generator is in the operating state of adjustable low load operation, the alarm unit sends a corresponding adjustment alarm to the user;

[0168] When the wind turbine generator is in an uncontrollable low-load operation state, the alarm unit does not send an alarm to the user;

[0169] When the wind turbine generator is in normal operation, the alarm unit does not send an alarm to the user;

[0170] When the wind turbine generator is in the controllable high compliance operation state, if TC<T×q, the alarm unit sends a yaw control alarm to the user; if TC<T×q, the alarm unit does not send an alarm to the user;

[0171] Among them, TC is the duration of the wind turbine's adjustable high-compliance operation, and q is the preset continuous monitoring duration.

[0172] Specifically, the alarm unit alerts the user based on the analysis results of the wind turbine operating status during the monitoring period, thereby improving the accuracy of the wind turbine operating status alarm and further improving the efficiency of wind turbine operating status monitoring; it can be understood that this embodiment does not make specific limitations on the value of the preset continuous monitoring time length q, and technical personnel in this field can set it freely, as long as the value requirements of the preset continuous monitoring time length q are met, such as the preset continuous monitoring time length q can be set to 3.

[0173] Specifically, the operation control module generates a control scheme for the wind turbine according to the analysis results of the wind turbine operation status within the monitoring period, wherein:

[0174] When the wind turbine generator operating state is adjustable low-load operation during the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ1, and sets Jθ1=Jθ×cos{[R1-(γ-Y1) / Y1×βj] / R1};

[0175] When the wind turbine generator operating state is uncontrollable low-load operation or normal operation during the monitoring period, the operation control module does not control the wind turbine generator pitch angle in the next monitoring period;

[0176] When the wind turbine generator operating state is adjustable high compliance operation in the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ2, and sets Jθ2=Jθ×exp{[(γ-Y1) / Y1×βj-R2] / R2};

[0177] Wherein, Jθ is the pitch angle of the wind turbine blades during the monitoring period;

[0178] The operation control module outputs the wind turbine pitch angle of the next monitoring cycle to the user as a control scheme.

[0179] Specifically, the operation control module generates a control scheme for the wind turbine according to the analysis results of the wind turbine operation status within the monitoring period, thereby improving the accuracy of the wind turbine operation status control and further improving the efficiency of the wind turbine operation status monitoring.

[0180] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A wind turbine operating status monitoring system, characterized in that: include, An information acquisition module is used to acquire environmental data and wind turbine operation data in real time, and is also used to acquire historical operation data of wind turbines; A historical data analysis module is used to analyze the historical operating status of the wind turbine according to the historical operating data of the wind turbine, and to set the monitoring level according to the analysis results of the historical operating status; An operation monitoring module is used to analyze wind power anomalies according to environmental data within a monitoring period, and to analyze the wind power conversion state of the wind turbine within the monitoring period according to the wind power anomaly analysis results and the wind turbine operation data within the monitoring period; An adjustment and optimization module is used to adjust the analysis process of wind anomaly according to the wind direction data within the monitoring period, and is also used to optimize the adjustment process of wind anomaly according to meteorological data; An operation status analysis module is used to analyze the operation status of the wind turbine within the monitoring period according to the wind power conversion status analysis results and the monitoring level analysis results of the wind turbine within the monitoring period; An operation control module is used to generate a control plan for the wind turbine according to the analysis results of the wind turbine operation status within the monitoring period; The operation monitoring module is provided with a wind monitoring unit, and the wind monitoring unit analyzes the wind state according to the environmental data within the monitoring period; The wind force monitoring unit calculates the wind force f carried by the blades according to the environmental data in the monitoring period. The calculation process of the wind force f carried by the blades is as follows: f = P × S × cosθ; θ = a·b / |a|×|b|; Among them, p is the real-time wind pressure, S is the blade area, a is the real-time unit wind direction vector, b is the blade plane normal vector, and θ is the angle between the wind speed direction and the blade normal vector direction; The wind force monitoring unit compares the wind force f carried by the blade with each preset wind force, and analyzes the wind force state according to the comparison result, wherein: When n×f<F1, the wind force monitoring unit determines that the wind force carried by the blade is low; When F1≤n×f<F2, the wind force monitoring unit determines that the wind force carried by the blade is normal; When n×f≥F2, the wind force monitoring unit determines that the wind force carried by the blade is high; Wherein, F1 is the first preset bearing wind force, F2 is the second preset bearing wind force, n is the number of blades of the wind power generation equipment, and F1<F2; The operation monitoring module is further provided with an abnormality analysis unit, which analyzes wind abnormality according to the wind state analysis results within the monitoring period, wherein: When a1×t1 / T+a2×t2 / T<B, the abnormality analysis unit determines that the wind force is normal during the monitoring period; When a1×t1 / T+a2×t2 / T≥B, the abnormality analysis unit determines that the wind force is abnormal during the monitoring period; Wherein, a1 is the low wind force anomaly weight, a2 is the high wind force anomaly weight, and a1+a2=1, t1 is the duration of the wind force state analysis result during the monitoring period when the blade load wind force is low, t2 is the duration of the wind force state analysis result during the monitoring period when the blade load wind force is high, T is the duration of the monitoring period, and B is the preset anomaly coefficient; The operation monitoring module is further provided with a conversion state analysis unit, which analyzes the wind power conversion state according to the wind power abnormality analysis result and the operation data of the wind turbine within the monitoring period, wherein: When the analysis result of wind power abnormality is that the wind power is normal, if γ<Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y1, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal; When the analysis result of wind power abnormality is wind power abnormality, if γ<Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is normal; if γ≥Y2, the conversion state analysis unit determines that the wind power conversion state within the monitoring period is abnormal; Wherein, γ is the power conversion efficiency, Y1 is the first preset wind turbine rotation efficiency, and Y2 is the second preset wind turbine rotation efficiency.

2. The wind turbine operating status monitoring system according to claim 1, characterized in that: The historical data analysis module is provided with a historical analysis unit, and the historical analysis unit analyzes the historical operation status of the wind turbine according to the historical operation data; The historical analysis unit calculates the historical operation index α(i) in each historical monitoring period according to the historical operation data, and sets α(i)=exp{fs(i) / FS×s(i) / P}; Where, s(i) is the output power of the wind turbine in the i-th historical monitoring period, P is the rated power of the wind turbine, fs(i) is the average wind speed in the i-th historical monitoring period, and FS is the rated maximum power of the wind turbine; The historical analysis unit compares the historical operation index α(i) in each historical monitoring period with each preset wind turbine operation index, and analyzes the historical operation status of each historical monitoring period according to the comparison result, wherein: When α(i)<A1, the history analysis unit determines that the historical operation state in the historical monitoring period is a low-load operation abnormal state; When A1≤α(i)<A2, the history analysis unit determines that the historical operation state within the historical monitoring period is a normal operation state; When α(i)≥A2, the history analysis unit determines that the historical operation state in the historical monitoring period is a high-load operation state; Wherein, A1 is a first preset wind turbine operating index, A2 is a second preset wind turbine operating index, and A1<A2.

3. The wind turbine operating status monitoring system according to claim 2, characterized in that: The historical data analysis module is further provided with a level classification unit, which analyzes the monitoring level of the wind turbine according to the historical operating status analysis results of the wind turbine; The level classification unit counts the number n1 of low-load operating states in the historical operation state of each historical monitoring period and the number n2 of high-load operating states in the historical operation state of each historical monitoring period; The level classification unit analyzes the monitoring level of the wind turbine according to the statistical results, wherein: When (n1+n2) / N≥K and n1<n2, the level classification unit sets the monitoring level of the wind turbine to level one and sets a first offset coefficient β1, setting β1=(n1+n2) / N / K; When (n1+n2) / N≥K and n1≥n2, the level classification unit sets the monitoring level of the wind turbine to level 2 and sets a second offset coefficient β2, setting β2=K / [(n1+n2) / N]; When (n1+n2) / N<K, the level classification unit sets the monitoring level of the wind turbine to level 3, and sets the third offset coefficient β3, setting β3=1; Among them, K is the preset abnormality ratio and N is the number of historical monitoring cycles.

4. The wind turbine operating status monitoring system according to claim 3, characterized in that: The adjustment optimization module is provided with a fluctuation adjustment unit, which analyzes the wind direction volatility according to the wind direction vector within the monitoring period; The fluctuation adjustment unit calculates the wind direction variation coefficient CV, and the calculation formula of the wind direction variation coefficient is as follows: CV = σ / E × 100%; E=[c(1)+c(2)+...+c(T / t)] / (T / t); σ={{[c(1)-E] 2 +[c(2)-E] 2 +...+[c(T / t)-E] 2 } / (T / t)} 1 / 2 ; Wherein, t is the real-time acquisition interval duration, c(1) represents the modulus of the first real-time wind volume vector in the monitoring period, c(2) represents the modulus of the second real-time wind volume vector in the monitoring period, and c(T / t) represents the modulus of the T / tth real-time wind volume vector in the monitoring period; The fluctuation adjustment unit compares the wind direction variation coefficient CV with the fluctuation threshold value YC, and adjusts the analysis process of wind force anomaly according to the comparison result, wherein: When CV<YC, the fluctuation adjustment unit determines that the wind force fluctuation is normal and does not make any adjustment; When CV≥YC, the fluctuation adjustment unit determines that the wind power fluctuation is abnormal, and adjusts the first preset wind turbine generator rotation efficiency to Y1', setting Y1'=Y1×cos{arctan[(CV-YC) / YC]}, and adjusts the second preset wind turbine generator rotation efficiency to Y2', setting Y2'=Y2×sin[(CV-YC) / YC]; The adjustment optimization module is provided with an optimization unit, which optimizes the adjustment process of wind abnormality according to the meteorological data in the monitoring period, wherein: When sd<SD, the optimization unit determines that the air humidity in the monitoring period is normal; When sd≥SD, the optimization unit determines that the air humidity in the monitoring period is abnormal, and optimizes the fluctuation threshold YC to YC', setting YC'=YC×{2-exp[(sd-SD) / SD]}; Among them, sd is the average absolute air humidity during the monitoring period, and SD is the absolute air humidity threshold.

5. The wind turbine operating status monitoring system according to claim 4, characterized in that: The operation status analysis module is provided with an operation status analysis unit, and the operation status analysis unit analyzes the operation status of the wind turbine in the monitoring period according to the wind power conversion status analysis result and the monitoring level analysis result of the wind turbine in the monitoring period, wherein: When the wind power conversion state of the wind turbine is normal, if (γ-Y1) / Y1×βj<R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is adjustable low-load operation; if (γ-Y1) / Y1×βj≥R1, the operation state analysis unit determines that the operation state of the wind turbine during the monitoring period is unadjustable low-load operation; When the wind power conversion state of the wind turbine is abnormal, if (γ-Y1) / Y1×βj<R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is normal operation; if (γ-Y1) / Y1×βj≥R2, the operation state analysis unit determines that the operation state of the wind turbine in the monitoring period is adjustable high-load operation; Wherein, j is set to 1, 2, 3, R1 is the first preset operating state coefficient, R2 is the second preset operating state coefficient, and R1<R2.

6. The wind turbine operating status monitoring system according to claim 5, characterized in that: The operation status monitoring module is also provided with an alarm unit, which alarms the user according to the analysis result of the operation status of the wind turbine in the monitoring period, wherein: When the wind turbine generator is in the operating state of adjustable low load operation, the alarm unit sends a corresponding adjustment alarm to the user; When the wind turbine generator is in an uncontrollable low-load operation state, the alarm unit does not send an alarm to the user; When the wind turbine generator is in normal operation, the alarm unit does not send an alarm to the user; When the wind turbine is in the controllable high-load operation state, if TC < T×q, the alarm unit sends a yaw control alarm to the user; if TC < T×q, the alarm unit does not send an alarm to the user; Among them, TC is the duration of the wind turbine's controllable high-load operation, and q is the preset continuous monitoring duration.

7. The wind turbine operating status monitoring system according to claim 6, characterized in that: The operation control module generates a control scheme for the wind turbine according to the analysis result of the wind turbine operation status within the monitoring period, wherein: When the wind turbine generator operating state is adjustable low-load operation during the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ1, and sets Jθ1=Jθ×cos{[R1-(γ-Y1) / Y1×βj] / R1}; When the wind turbine generator operating state is uncontrollable low-load operation or normal operation during the monitoring period, the operation control module does not control the wind turbine generator pitch angle in the next monitoring period; When the wind turbine generator operating state is adjustable high-load operation during the monitoring period, the operation control module adjusts the wind turbine generator pitch angle of the next monitoring period to Jθ2, and sets Jθ2=Jθ×exp{[(γ-Y1) / Y1×βj-R2] / R2}; Wherein, Jθ is the pitch angle of the wind turbine blades during the monitoring period; The operation control module outputs the wind turbine pitch angle of the next monitoring cycle to the user as a control scheme.

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