Wind generating set intelligent control system and method based on multi-dimensional sensing

Abstract

The invention discloses a wind generating set intelligent control system and method based on multi-dimensional sensing, and relates to the field of power generation equipment control, and the system comprises a distinguishing module which is used for uploading distribution information of wind generating sets and distinguishing the wind generating sets based on the distribution information of the wind generating sets; the sensing module is used for sensing wind power related information in real time and storing the wind power related information; the calling module is used for calling the latest wind power related information from the stored wind power related information; the wind generating sets with synchronous control conditions are distinguished through recognition of terrain distribution of the wind generating sets, the real-time optimal yaw directions of the wind generating sets are further analyzed based on multi-directional perception of wind power related information, the wind generating sets with the synchronous control conditions are synchronously networked, and the wind generating sets with the synchronous control conditions are synchronously networked. And the optimal yaw direction is adaptively distributed, so that the wind generating set can synchronously adjust the yaw direction, and the energy conversion efficiency of the wind generating set is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation equipment control, and in particular to an intelligent control system and method for a wind turbine generator set based on multi-dimensional sensing. Background Art

[0002] Wind turbines are devices that convert wind energy into electrical energy. They are usually composed of wind rotors, generators, towers, etc. The wind rotors rotate under the action of wind power, and drive the generators to operate through the transmission device, thereby generating electrical energy. They are widely used in the field of wind power and are important equipment for realizing the utilization of clean energy.

[0003] The invention patent application with application number 202111025620.7 discloses a management system based on a wind turbine generator set, including: a machine-side control system for controlling the wind turbine generator set, a field-side intelligent monitoring system for monitoring the wind farm, a regional-side dispatching system for dispatching the power of each wind farm in the wind power generation area, and a cloud management system for managing each wind power generation area; wherein, the machine-side control system includes an adaptive optimization module, the field-side intelligent monitoring system includes an equipment degradation early warning module, the regional-side dispatching system includes a power dispatching module and an electricity market trading module, and the cloud management system includes a regional electricity market trading module; the adaptive optimization module is used to record and The power curve of the wind turbine generator set is adaptively optimized for wind and yaw; the equipment degradation warning module is used to monitor the fault conditions and life conditions of each wind turbine generator set in the wind farm, and display alarm and maintenance information; the power scheduling module is used to perform optimal power allocation according to the real-time adjustable active power of each wind farm, and send the pre-allocated power to each wind farm. This application aims to solve the problem that "for wind turbine generator sets, the main control components of in-service wind turbine generator sets have low degree of openness and low intelligence. With the increasing demand for big data and edge computing applications, the demand for complex data processing functions is gradually increasing. It is difficult for existing controllers to meet the requirements of openness, efficiency and safety at the same time."

[0004] However, the wind turbines currently in use do not have interactive functions with each other, and the yaw adjustment logic in response to wind direction is fixed and independent, resulting in weak group control capabilities of wind turbine groups and low levels of intelligence.

[0005] Therefore, an intelligent control system for wind turbines based on multi-dimensional sensing is proposed. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides an intelligent control system and method for a wind turbine generator set based on multi-dimensional sensing, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] The present invention discloses an intelligent control system for a wind turbine generator set based on multi-dimensional sensing, comprising:

[0009] A differentiation module is used to upload wind turbine distribution information and differentiate wind turbines based on the wind turbine distribution information; a perception module is used to perceive wind-related information in real time and store wind-related information; a retrieval module is used to retrieve the latest wind-related information from the stored wind-related information; an analysis module is used to receive wind-related information retrieved by the retrieval module and analyze the optimal yaw angle of the wind turbine using the wind-related information; a sharing module is used to obtain the optimal yaw angle of the wind turbine analyzed in the analysis module and feed back the optimal yaw angle to other wind turbines in the differentiation interval where the source wind turbine is located in the differentiation module; a driving module is used to drive the wind turbine to adjust to the optimal yaw angle;

[0010] The system continuously operates based on a user-defined cycle at the system end to continuously control the wind turbine generator set.

[0011] Furthermore, the wind turbine generator set is not unique, and the wind turbine generator set distribution information uploaded during the operation phase of the differentiation module comes from the system end user, and the wind turbine generator set distribution information includes the land surface model of the wind turbine generator set distribution area and the location information of the wind turbine generator set in the land surface model of the wind turbine generator set distribution area;

[0012] During the operation phase of the differentiation module, the system end user synchronizes and customizes the height difference allowable threshold, and the differentiation module differentiates the wind turbine generator sets based on the height difference allowable threshold and the position information of the wind turbine generator sets in the land surface model of the generator generator set distribution area, so that the difference between the maximum value and the minimum value of the height determined based on the position coordinates of the wind turbine generator sets in the same differentiation interval is less than the height difference allowable threshold;

[0013] Among them, after distinguishing each wind turbine generator set, the distinguishing module networks the wind turbine generator sets belonging to each distinguishing interval. When there is only one wind turbine generator set in the distinguishing interval, the networking operation is not performed.

[0014] Furthermore, the wind-related information sensed by the sensing module includes: wind speed, wind direction angle, and air density. The sensing module is integrated with sensors capable of sensing wind-related information. The sensing module is arranged on each wind turbine generator set. The sensors deployed on each wind turbine generator set are not unique, and the number of sensors deployed on each wind turbine generator set is equal.

[0015] The sensors are deployed in a ring shape on the tower surface of the wind turbine generator set.

[0016] Furthermore, a storage unit is provided at the lower level of the perception module, and the storage unit is used to receive wind-related information perceived by the perception module and to distinguish and store wind-related information;

[0017] Each partitioned storage interval is named based on the location information of the wind turbine generator set to which the wind power related information stored therein belongs, so that the wind power related information stored in each partitioned storage interval all comes from the same wind turbine generator set;

[0018] Among them, after the wind turbine generator sets are divided and networked, the storage unit is networked with any wind turbine generator sets in each division interval, so that the storage unit and at least one wind turbine generator set in each wind turbine generator set division interval have data exchange conditions.

[0019] Furthermore, a storage unit is provided at the lower level of the perception module, and the storage unit is used to receive wind-related information perceived by the perception module and to distinguish and store wind-related information;

[0020] Each partitioned storage interval is named based on the location information of the wind turbine generator set to which the wind power related information stored therein belongs, so that the wind power related information stored in each partitioned storage interval all comes from the same wind turbine generator set;

[0021] Among them, after the wind turbine generator sets are divided and networked, the storage unit is networked with any wind turbine generator sets in each division interval, so that the storage unit and at least one wind turbine generator set in each wind turbine generator set division interval have data exchange conditions.

[0022] Furthermore, a screening unit is provided at the lower level of the analysis module, and the screening unit is used to traverse the wind-related information currently retrieved by the retrieval module, sort the wind-related information based on the position relationship of its source sensor on the tower surface of the wind turbine generator set, identify the highest wind speed source sensor, and use the wind-related information of the identified sensor itself and the sensors adjacent to it and of equal number on its left and right sides as analysis targets;

[0023] The wind-related information used as the analysis target is one half of the wind-related information received by the analysis module during operation.

[0024] Furthermore, when analyzing the optimal yaw angle of the wind turbine generator set in the analysis module, the following is obeyed:

[0025] The three wind speeds, wind direction angles, and air density sensed by each sensor are averaged respectively;

[0026] After the averaging operation, the corresponding sensors are denoted as v1 , α 1 , 1 ;v 2 , α 2 , 2 ;v 3 , α 3 , 3 ; ..., the parameter subscript indicates the sensor number;

[0027]

[0028] Where: P i (a i ) is the wind energy captured by the wind turbine when the yaw angle is a; ρ i is the air density; A is the swept area of ​​the wind wheel; v i is the wind speed; C p (λ,β) is the wind energy utilization coefficient;

[0029] Among them, A, C p (λ,β) is derived from the parameter P i (a i ) The subscript corresponds to the wind turbine generator set where the sensor is located. Based on the above calculation, the P i (a i ) value is maximum, P i (a i ) The subscript corresponds to the sensor to which the sensor serial number belongs. The wind direction angle in the latest wind-related information sensed by the sensor is used as the optimal yaw angle. The sensor is used as a reference target, and the optimal yaw angle is rotated toward the direction of the reference target.

[0030] Furthermore, the wind turbine generator sets in the same division interval in the division module execute the same yaw control movement.

[0031] Furthermore, the differentiation module is interactively connected to a perception module via a wireless network, the perception module is interactively connected to a storage unit via a wireless network, the perception module is interactively connected to a retrieval module and an analysis module via a wireless network, the retrieval module is interactively connected to a storage unit via a wireless network, the analysis module is interactively connected to a screening unit via a wireless network, and the analysis module is interactively connected to a sharing module and a driving module via a wireless network.

[0032] In a second aspect, a wind turbine generator intelligent control method based on multi-dimensional sensing comprises the following steps:

[0033] The wind turbine distribution information is obtained, the wind turbines are differentiated based on the wind turbine distribution information, and the wind turbines in each zone are networked so that each wind turbine in the same zone has the conditions for data exchange; based on the sensing device, the wind-related information is sensed on the surface of the wind turbine tower in real time, the wind-related information is retrieved, the wind-related information is screened, and the screened wind-related information is used to analyze the optimal yaw angle of the wind turbine; the optimal yaw angle of the wind turbine is shared with other wind turbines based on the networking result of the zone where it is located; the wind turbine is controlled to make yaw adjustments based on the optimal yaw angle to adapt to the current ambient wind.

[0034] Compared with the known prior art, the technical solution provided by the present invention has the following beneficial effects:

[0035] The present invention distinguishes wind turbines with synchronous control conditions by identifying the terrain distribution of wind turbines, and further analyzes the real-time optimal yaw direction of the wind turbines based on the multi-directional perception of wind-related information, synchronously networks the wind turbines with synchronous control conditions, and adaptively distributes the optimal yaw direction, so that the wind turbines can synchronously adjust the yaw direction, improve the energy conversion efficiency of the wind turbines, and realize real-time linkage and comprehensive intelligent control of the wind turbines.

[0036] At the same time, during the analysis stage of the optimal yaw direction, the wind-related information used in the analysis process is screened, which effectively reduces the system operation processing data, and based on the screening, high-value data is obtained and applied to the analysis of the optimal yaw direction to ensure the effectiveness of the control of the optimal yaw direction of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 It is a structural schematic diagram of an intelligent control system for a wind turbine generator set based on multi-dimensional sensing;

[0039] Figure 2 The figure is a flow chart of an intelligent control method for a wind turbine generator set based on multi-dimensional sensing. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 work are within the scope of protection of the present invention.

[0041] The present invention will be further described below in conjunction with the embodiments.

[0042] Embodiment 1:

[0043] The present embodiment is a wind turbine generator intelligent control system based on multi-dimensional sensing, such as Figure 1 As shown, including:

[0044] A differentiation module, used for uploading wind turbine distribution information and distinguishing wind turbines based on the wind turbine distribution information;

[0045] Wind turbines are not unique. The wind turbine distribution information uploaded during the operation phase of the distinguishing module comes from the system end user. The wind turbine distribution information includes the land surface model of the wind turbine distribution area and the location information of the wind turbine in the land surface model of the wind turbine distribution area.

[0046] During the operation phase of the differentiation module, the system end user synchronously customizes the height difference allowable threshold, and the differentiation module differentiates the wind turbine generator sets based on the height difference allowable threshold and the location information of the wind turbine generator sets in the land surface model of the generator generator distribution area, so that the difference between the maximum and minimum heights of the wind turbine generator sets determined based on the location coordinates in the same differentiation interval is less than the height difference allowable threshold;

[0047] Among them, after distinguishing each wind turbine generator set, the distinguishing module networks the wind turbine generator sets belonging to each distinguishing interval. When there is only one wind turbine generator set in the distinguishing interval, the networking operation is not performed;

[0048] A sensing module, used to sense wind-related information in real time and store wind-related information;

[0049] The wind-related information sensed by the sensing module includes: wind speed, wind direction angle, and air density. The sensing module is integrated with sensors that can sense wind-related information. The sensing module is arranged on each wind turbine generator set. The sensors deployed on each wind turbine generator set are not unique, and the number of sensors deployed on each wind turbine generator set is equal.

[0050] The sensors are deployed in a ring-shaped manner on the tower surface of the wind turbine generator set;

[0051] A storage unit is provided at the lower level of the perception module, and the storage unit is used to receive wind force related information perceived by the perception module and distinguish and store the wind force related information;

[0052] Each partitioned storage interval is named based on the location information of the wind turbine generator set to which the wind power related information stored therein belongs, so that the wind power related information stored in each partitioned storage interval all comes from the same wind turbine generator set;

[0053] After the wind turbine generator sets are divided and networked, the storage unit is networked with any wind turbine generator set in each division interval, so that the storage unit and at least one wind turbine generator set in each division interval of the wind turbine generator set have data exchange conditions;

[0054] A retrieval module, used to retrieve the latest wind-related information from the stored wind-related information;

[0055] In the operation phase of the retrieval module, the wind power related information is retrieved from the storage unit. When the retrieval module performs the retrieval operation of the wind power related information, the differentiation results of the wind turbine generator sets corresponding to each differentiated storage interval in the storage unit are identified in the differentiation module. Based on the differentiation results in the differentiation module, the latest wind power related information stored in the differentiated storage interval corresponding to each wind turbine generator set in the same differentiated interval is selected as the retrieval target;

[0056] The retrieval module retrieves a set of wind-related information from the storage interval each time it runs, and each set of wind-related information includes the wind speed, wind direction angle and air density sensed by the sensors deployed on the tower surface of the corresponding wind turbine generator set for the last three times;

[0057] An analysis module is used to receive wind-related information retrieved by the retrieval module and analyze the optimal yaw angle of the wind turbine generator set using the wind-related information;

[0058] A screening unit is provided at the lower level of the analysis module, and the screening unit is used to traverse the wind-related information currently retrieved by the retrieval module, sort the wind-related information based on the position relationship of its source sensor on the tower surface of the wind turbine generator set, identify the highest wind speed source sensor, and use the wind-related information of the identified sensor itself and the sensors adjacent to it and of equal number on its left and right sides as the analysis target;

[0059] The wind-related information used as the analysis target is one-half of the wind-related information received by the analysis module during operation;

[0060] The optimal yaw angle of the wind turbine in the analysis module is subject to:

[0061] The three wind speeds, wind direction angles, and air density sensed by each sensor are averaged respectively;

[0062] After the averaging operation, the corresponding sensors are denoted as v 1 , α 1 , 1 ;v 2 , α 2 , 2 ;v 3 , α 3 , 3 ; ..., the parameter subscript indicates the sensor number;

[0063]

[0064] Where: P i (a i ) is the wind energy captured by the wind turbine when the yaw angle is a; ρ i is the air density; A is the swept area of ​​the wind wheel; v i is the wind speed; C p (λ,β) is the wind energy utilization coefficient;

[0065] Among them, A, C p (λ,β) is derived from the parameter P i (a i ) The subscript corresponds to the wind turbine generator set where the sensor is located. Based on the above calculation, the P i (a i ) value is maximum, P i (a i ) The subscript corresponds to the sensor to which the sensor number belongs, the wind direction angle in the latest wind force information sensed by the sensor is used as the optimal yaw angle, the sensor is used as the reference target, and the optimal yaw angle is rotated toward the reference target direction;

[0066] The optimal yaw angle is calculated through the above logic formula and output;

[0067] It should be noted that the wind energy utilization coefficient is a function of the tip speed ratio λ and the pitch angle β;

[0068]

[0069] Where: C 1 , C 2 , C 3 , C 4 , C 5 It is an empirical coefficient related to the design of wind turbine blades. Different wind turbines may have different values.

[0070] A sharing module is used to obtain the optimal yaw angle of the wind turbine generator set analyzed in the analysis module, and to feed back the optimal yaw angle to other wind turbine generator sets in the partitioning interval where the source wind turbine generator set is located in the partitioning module;

[0071] A driving module, used for driving the wind turbine generator set to adjust to an optimal yaw angle;

[0072] The wind turbine generator sets in the same partition interval in the partition module perform the same yaw control movement;

[0073] Among them, the system operates continuously based on a user-defined cycle on the system end to continuously control the wind turbine generator set;

[0074] The distinguishing module is interactively connected to the perception module through a wireless network, the perception module is interactively connected to the storage unit through a wireless network, the perception module is interactively connected to the retrieval module and the analysis module through a wireless network, the retrieval module is interactively connected to the storage unit through a wireless network, the analysis module is interactively connected to the screening unit through a wireless network, and the analysis module is interactively connected to the sharing module and the driving module through a wireless network.

[0075] In this embodiment, the distinguishing module is operated to upload the distribution information of the wind turbine generator sets, and the wind turbine generator sets are distinguished based on the distribution information of the wind turbine generator sets. The perception module is post-operated to perceive the wind related information in real time and store the wind related information. The storage unit synchronously receives the wind related information perceived by the perception module, distinguishes and stores the wind related information, and the retrieval module further retrieves the latest wind related information from the stored wind related information. The analysis module then receives the wind related information retrieved by the retrieval module, and uses the wind related information to analyze the optimal yaw angle of the wind turbine generator set. The screening unit synchronously traverses the current information of the retrieval module. The wind-related information retrieved before is sorted based on the position relationship of its source sensor on the tower surface of the wind turbine generator set, and the sensor with the highest wind speed source is identified. The wind-related information of the identified sensor itself and the sensors adjacent to it and of equal number on its left and right sides are used as analysis targets, and the optimal yaw angle of the wind turbine generator set analyzed in the analysis module is obtained through the sharing module, and the optimal yaw angle is fed back to other wind turbine generator sets in the differentiation interval where its source wind turbine generator set is located in the differentiation module, and finally the driving module drives the wind turbine generator set to adjust to the optimal yaw angle.

[0076] In the above embodiment, the system can reasonably group the wind turbines according to the land surface model and location information of the wind turbine distribution area provided by the user, as well as the customized height difference allowable threshold. With the help of numerous sensors, it can collect data such as wind speed, wind direction angle, air density, etc. in real time, and store them by unit location. The system will screen the latest data and calculate the optimal yaw angle. The units in the same group will adjust the yaw angle synchronously accordingly, so that the units can better operate against the wind and greatly improve the efficiency of wind energy capture. Moreover, the system runs continuously according to the set cycle, which can achieve uninterrupted control of the units, improve power generation efficiency, reduce operating costs, and effectively promote the intelligent upgrade of the wind power industry.

[0077] Embodiment 2:

[0078] In terms of specific implementation, based on Example 1, this example refers to Figure 2 The wind turbine generator intelligent control system based on multi-dimensional sensing in Example 1 is further described in detail:

[0079] A wind turbine generator intelligent control method based on multi-dimensional sensing comprises the following steps:

[0080] Step 1: Obtain wind turbine distribution information, differentiate wind turbines based on the wind turbine distribution information, network the wind turbines in each zone, and make each wind turbine in the same zone have data exchange conditions;

[0081] Step 2: Based on the sensing device, the wind-related information is sensed in real time on the surface of the wind turbine tower, the wind-related information is retrieved, the wind-related information is screened, and the screened wind-related information is used to analyze the optimal yaw angle of the wind turbine;

[0082] Step 3: The optimal yaw angle of the wind turbine generator set is shared with other wind turbine generator sets based on the networking results of the zone in which it is located;

[0083] Step 4: Control the wind turbine to adjust the yaw angle based on the optimal yaw angle to adapt to the current environmental wind

[0084] In summary, in the above embodiment, the system distinguishes wind turbines that meet the conditions for synchronous control by identifying the terrain distribution of wind turbines, and further analyzes the real-time optimal yaw direction of the wind turbines based on multi-directional perception of wind-related information, and synchronously networks the wind turbines that meet the conditions for synchronous control, and adaptively distributes the optimal yaw direction, so that the wind turbines can synchronously adjust the yaw direction, improve the energy conversion efficiency of the wind turbines, and realize real-time linkage and comprehensive intelligent control of the wind turbines. At the same time, in the analysis stage of the optimal yaw direction, the wind-related information used in the analysis process is screened, which effectively reduces the system operation processing data, and obtains high-value data based on the screening and applies it to the analysis of the optimal yaw direction to ensure the effectiveness of the control of the optimal yaw direction of the wind turbine.

[0085] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent control system for wind turbine generators based on multi-dimensional sensing, characterized in that: include: A differentiation module, used for uploading wind turbine distribution information and distinguishing wind turbines based on the wind turbine distribution information; A sensing module, used to sense wind-related information in real time and store the wind-related information; A retrieval module, used to retrieve the latest wind-related information from the stored wind-related information; An analysis module is used to receive wind-related information retrieved by the retrieval module and analyze the optimal yaw angle of the wind turbine generator set using the wind-related information; A sharing module is used to obtain the optimal yaw angle of the wind turbine generator set analyzed in the analysis module, and to feed back the optimal yaw angle to other wind turbine generator sets in the partitioning interval where the source wind turbine generator set is located in the partitioning module; A driving module, used for driving the wind turbine generator set to adjust to an optimal yaw angle; Among them, the system runs continuously based on the user-defined cycle on the system side to continuously control the wind turbine generator set.

2. According to claim 1, a wind turbine generator intelligent control system based on multi-dimensional sensing is characterized in that: The wind turbine generator set is not unique, and the wind turbine generator set distribution information uploaded during the operation phase of the differentiation module comes from the system end user, and the wind turbine generator set distribution information includes the land surface model of the wind turbine generator set distribution area and the location information of the wind turbine generator set in the land surface model of the wind turbine generator set distribution area; During the operation phase of the differentiation module, the system end user synchronizes and customizes the height difference allowable threshold, and the differentiation module differentiates the wind turbine generator sets based on the height difference allowable threshold and the position information of the wind turbine generator sets in the land surface model of the generator generator set distribution area, so that the difference between the maximum value and the minimum value of the height determined based on the position coordinates of the wind turbine generator sets in the same differentiation interval is less than the height difference allowable threshold; Among them, after distinguishing each wind turbine generator set, the distinguishing module networks the wind turbine generator sets belonging to each distinguishing interval. When there is only one wind turbine generator set in the distinguishing interval, the networking operation is not performed.

3. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1 is characterized in that: The wind-related information sensed by the sensing module includes: wind speed, wind direction angle, and air density. The sensing module is integrated with sensors capable of sensing wind-related information. The sensing module is arranged on each wind turbine generator set. The sensors deployed on each wind turbine generator set are not unique, and the number of sensors deployed on each wind turbine generator set is equal. The sensors are deployed in a ring shape on the tower surface of the wind turbine generator set.

4. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1 is characterized in that: The sensing module is provided with a storage unit at a lower level, and the storage unit is used to receive wind force related information sensed by the sensing module and distinguish and store wind force related information; Each partitioned storage interval is named based on the location information of the wind turbine generator set to which the wind power related information stored therein belongs, so that the wind power related information stored in each partitioned storage interval all comes from the same wind turbine generator set; Among them, after the wind turbine generator sets are divided and networked, the storage unit is networked with any wind turbine generator sets in each division interval, so that the storage unit and at least one wind turbine generator set in each wind turbine generator set division interval have data exchange conditions.

5. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1 is characterized in that: During the operation phase of the retrieval module, the wind power related information is retrieved from the storage unit. When the retrieval module performs the retrieval operation of the wind power related information, the retrieval module identifies the differentiation results of the wind turbine generator sets corresponding to each differentiated storage interval in the storage unit in the differentiation module, and based on the differentiation results in the differentiation module, selects the latest wind power related information stored in the differentiated storage interval corresponding to each wind turbine generator set in the same differentiated interval as the retrieval target; Among them, the retrieval module retrieves a set of wind-related information from the different storage intervals each time it runs, and each set of wind-related information includes the wind speed, wind direction angle and air density sensed by each sensor deployed on the tower surface of the corresponding wind turbine generator set for the last three times.

6. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1, characterized in that: The analysis module is provided with a screening unit at a lower level, and the screening unit is used to traverse the wind-related information currently retrieved by the retrieval module, sort the wind-related information based on the position relationship of its source sensor on the tower surface of the wind turbine generator set, identify the highest wind speed source sensor, and use the identified sensor itself and the wind-related information of the sensors adjacent to it and equal in number on its left and right sides as the analysis target; The wind-related information used as the analysis target is one half of the wind-related information received by the analysis module during operation.

7. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1 is characterized in that: When analyzing the optimal yaw angle of the wind turbine generator set in the analysis module, the following is followed: The three wind speeds, wind direction angles, and air density sensed by each sensor are averaged respectively; After the averaging operation, the corresponding sensors are recorded as v1, α1, ρ1; v2, α2, ρ2; v3, α3, ρ3; ..., and the parameter subscript indicates the sensor number; Where: P i (a i ) is the wind energy captured by the wind turbine when the yaw angle is a; ρ i is the air density; A is the swept area of ​​the wind wheel; v i is the wind speed; C p (λ,β) is the wind energy utilization coefficient; Among them, A, C p (λ,β) is derived from the parameter P i (a i ) The subscript corresponds to the wind turbine generator set where the sensor is located. Based on the above calculation, the P i (a i ) value is maximum, P i (a i ) The subscript corresponds to the sensor to which the sensor serial number belongs. The wind direction angle in the latest wind-related information sensed by the sensor is used as the optimal yaw angle. The sensor is used as a reference target, and the optimal yaw angle is rotated toward the direction of the reference target.

8. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1, characterized in that: The wind turbine generator sets in the same division interval in the division module perform the same yaw control movement.

9. The wind turbine generator intelligent control system based on multi-dimensional sensing according to claim 1, characterized in that: The distinguishing module is interactively connected to the perception module via a wireless network, the perception module is interactively connected to the storage unit via a wireless network, the perception module is interactively connected to the retrieval module and the analysis module via a wireless network, the retrieval module is interactively connected to the storage unit via a wireless network, the analysis module is interactively connected to the screening unit via a wireless network, and the analysis module is interactively connected to the sharing module and the driving module via a wireless network.

10. A method for intelligent control of a wind turbine generator set based on multi-dimensional sensing, the method being an implementation method of an intelligent control system of a wind turbine generator set based on multi-dimensional sensing as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Obtain wind turbine distribution information, differentiate wind turbines based on the wind turbine distribution information, network the wind turbines in each zone, and make each wind turbine in the same zone have data exchange conditions; Step 2: Based on the sensing device, the wind-related information is sensed in real time on the surface of the wind turbine tower, the wind-related information is retrieved, the wind-related information is screened, and the screened wind-related information is used to analyze the optimal yaw angle of the wind turbine; Step 3: The optimal yaw angle of the wind turbine generator set is shared with other wind turbine generator sets based on the networking results of the zone in which it is located; Step 4: Control the wind turbine to adjust the yaw based on the optimal yaw angle to adapt to the current ambient wind.

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