CN114113683A - Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium - Google Patents
Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium Download PDFInfo
- Publication number
- CN114113683A CN114113683A CN202111289692.2A CN202111289692A CN114113683A CN 114113683 A CN114113683 A CN 114113683A CN 202111289692 A CN202111289692 A CN 202111289692A CN 114113683 A CN114113683 A CN 114113683A
- Authority
- CN
- China
- Prior art keywords
- fan
- sector
- wind
- target
- target fan
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000012544 monitoring process Methods 0.000 title claims abstract description 48
- 230000002159 abnormal effect Effects 0.000 claims abstract description 75
- 230000005856 abnormality Effects 0.000 claims abstract description 63
- 230000005611 electricity Effects 0.000 claims 1
- 230000015654 memory Effects 0.000 description 10
- 101100182247 Caenorhabditis elegans lat-1 gene Proteins 0.000 description 4
- 101100182248 Caenorhabditis elegans lat-2 gene Proteins 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 101150061388 LON1 gene Proteins 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 101150004293 lon2 gene Proteins 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 239000003208 petroleum Substances 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P21/00—Testing or calibrating of apparatus or devices covered by the preceding groups
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P13/00—Indicating or recording presence, absence, or direction, of movement
- G01P13/02—Indicating direction only, e.g. by weather vane
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Wind Motors (AREA)
Abstract
The embodiment of the invention provides a method and a system for monitoring a wind vane anemoscope in a wind power plant and a computer readable storage medium. The monitoring method comprises the following steps: acquiring spatial position information of each fan in a wind power plant and wind direction angles measured by a wind direction meter of each fan, wherein the wind direction angles comprise current wind direction angles of each fan in an actual running state; selecting a target fan; determining each reference fan of a target fan based on the spatial position information of every two fans in the wind power plant; determining each abnormal judgment sector of the target fan based on the spatial position information of the target fan and each reference fan; determining an abnormal judgment sector where the target fan is located currently based on the current wind direction angle of the target fan; and monitoring the abnormality of the anemoscope in the unit pair consisting of the target fan and the reference fan falling into the current abnormality judgment sector based on the current wind direction angles of the target fan and the reference fan falling into the current abnormality judgment sector.
Description
Technical Field
The embodiment of the invention relates to the technical field of wind power generation, in particular to a method and a system for monitoring a wind vane anemoscope in a wind power plant and a computer readable storage medium.
Background
With the gradual depletion of energy sources such as coal and petroleum, human beings increasingly pay more attention to the utilization of renewable energy sources. Wind energy is increasingly gaining attention as a clean renewable energy source in all countries of the world. With the continuous development of wind power technology, the application of fans in power systems is increasing day by day. The wind turbine is a large-scale device for converting wind energy into electric energy, and is usually arranged in areas with rich wind energy resources.
The anemoscope is an important part of the fan, can be used for measuring the wind direction in real time, timely knows the change condition of the wind direction and completes the accurate wind alignment of the fan. The accuracy of the wind direction information measured by the anemoscope is very important for the actual operation of the fan. Therefore, how to monitor the anemoscope of the wind turbine to ensure the accuracy of the measured wind direction information is a major technical challenge.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a system for monitoring a wind vane of a wind turbine in a wind power plant and a computer readable storage medium, which can effectively solve the problem of fault diagnosis of the wind vane of the wind turbine.
One aspect of the embodiment of the invention provides a method for monitoring a wind vane anemoscope in a wind farm. The method comprises the following steps: acquiring spatial position information of each fan in a wind power plant and a wind direction angle measured by a wind direction meter of each fan, wherein the wind direction angle comprises a current wind direction angle of each fan in an actual running state; selecting a target fan; determining each reference fan of the target fan based on the spatial position information of every two fans in the wind power plant; determining each abnormal judgment sector of the target fan based on the spatial position information of the target fan and each reference fan; determining an abnormal judgment sector where the target fan is located currently based on the current wind direction angle of the target fan; and monitoring the abnormality of the anemoscope in the unit pair consisting of the target fan and the reference fan falling into the current abnormality judgment sector based on the current wind direction angles of the target fan and the reference fan falling into the current abnormality judgment sector.
The embodiment of the invention also provides a monitoring system of the anemoscope of the wind turbine in the wind power plant. The system comprises one or more processors and is used for realizing the monitoring method of the wind vane anemoscope in the wind farm.
Yet another aspect of an embodiment of the present invention also provides a computer-readable storage medium. The computer readable storage medium has a program stored thereon, which when executed by a processor, implements the method for monitoring a anemoscope in a wind farm as described above.
The monitoring method and the system of the wind vane anemoscope in the wind power plant and the computer readable storage medium can determine the reference fan of the target fan based on the spatial position information of the fan, the selection of the reference fan is simple and convenient, and the selection difficulty of the reference fan is greatly reduced.
The monitoring method, the system and the computer readable storage medium of the anemoscope of the wind power plant in the embodiment of the invention can determine the real-time abnormal judgment sector where the target fan is located according to the real-time wind direction angle of the target fan, select the corresponding reference fan falling into the real-time abnormal judgment sector, and monitor the abnormality of the anemoscope of the unit pair consisting of the target fan and the reference fan according to the real-time wind direction angles of the target fan and the selected corresponding reference fan, thereby effectively solving the problem of abnormal deviation diagnosis of the wind direction angles of the target fan and the reference fan in the corresponding abnormal judgment sector.
The method and the system for monitoring the wind vane of the fan in the wind power plant and the computer readable storage medium can identify and monitor whether the wind vane of the fan in the wind power plant is abnormal or not in real time on line, thereby ensuring that the fan can accurately aim at the wind and realizing the maximization of the generated energy of the fan.
Drawings
FIG. 1 is a flow chart of a method for monitoring a anemoscope of a wind turbine in a wind farm according to an embodiment of the present invention;
FIG. 2 is a detailed step of determining each reference fan of a target fan based on spatial position information of every two fans in a wind farm according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of various reference fans identifying a target fan in accordance with one embodiment of the present invention;
FIG. 4 is a detailed step of determining each abnormal judgment sector of the target fan based on the spatial location information of the target fan and each reference fan according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of determining each abnormal judgment sector of a target fan according to an embodiment of the present invention;
fig. 6 is a specific step of determining whether an anemoscope in a unit pair composed of a target fan and a reference fan falling into a current abnormality determination sector is abnormal according to an embodiment of the present invention;
FIG. 7 is a detailed step of obtaining the set threshold of each abnormal judgment sector according to an embodiment of the present invention;
FIG. 8 is a flow chart of a method of monitoring a anemoscope of a wind farm in accordance with another embodiment of the present invention;
FIG. 9 is a schematic illustration of power curves for a target and reference fan in a unit pair according to one embodiment of the present invention;
FIG. 10 is a schematic block diagram of a monitoring system for a wind vane in a wind farm according to one embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Unless otherwise defined, technical or scientific terms used in the embodiments of the present invention should have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. The use of "first," "second," and similar terms in the description and in the claims does not indicate any order, quantity, or importance, but rather is used to distinguish one element from another. Also, the use of the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one. "plurality" or "a number" means two or more. Unless otherwise indicated, "front", "rear", "lower" and/or "upper" and the like are for convenience of description and are not limited to one position or one spatial orientation. The word "comprising" or "comprises", and the like, means that the element or item listed as preceding "comprising" or "includes" covers the element or item listed as following "comprising" or "includes" and its equivalents, and does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
The embodiment of the invention provides a method for monitoring a wind vane of a fan in a wind power plant. Fig. 1 discloses a flow chart of a method for monitoring a wind vane in a wind farm according to an embodiment of the present invention. As shown in fig. 1, the method for monitoring a wind vane of a wind farm according to an embodiment of the present invention may include steps S1 to S6.
In step S1, spatial position information of each wind turbine 10 (as shown in fig. 3) in the wind farm 1 and a wind direction angle measured by a wind direction indicator of each wind turbine 10 are obtained, where the wind direction angle of each wind turbine 10 includes a current wind direction angle of each wind turbine 10 in an actual operating state.
As shown in FIG. 3, a plurality of wind turbines 10 are included in a wind farm 1. The wind turbine 10 generates a large amount of status Data during operation, And an SCADA (Supervisory Control And Data Acquisition) system (not shown) of the wind farm 1 collects And stores the Data, for example: wind speed data measured by an anemometer of the fan 10, wind direction angle and power data measured by a anemoscope of the fan 10, and the like, so as to develop intelligent operation and maintenance data mining work. The spatial position information, the impeller diameter, the owner information, and the like of the wind turbine 10 are also typically recorded in the configuration information table of the wind turbine 10 and stored in the database of the SCADA system as the record information of the wind farm 1.
At present, along with the rapid development of intelligent operation and maintenance, the database data of the SCADA system can be transmitted into a remote monitoring center of a fan manufacturer through a cloud. Therefore, the spatial position information of each wind turbine 10 in the wind farm 1 and the wind direction angle measured by the anemoscope of each wind turbine 10 can be obtained from the SCADA system of the wind farm 1. By using the data, the abnormity monitoring work of the wind turbine vane instrument in the wind power plant, which is described in the embodiment of the invention, can be effectively carried out.
In step S2, a target wind turbine 11 to be monitored is selected in the wind farm 1, as shown in fig. 3.
In step S3, each reference fan 12 of the target fan 11 may be determined based on the spatial position information of two fans 10 in the wind farm 1.
In some embodiments, the spatial location information of the wind turbine 10 may include longitude and latitude coordinates of the wind turbine 10. As shown in fig. 2, the step S3 of determining each reference fan 12 of the target fan 11 based on the spatial position information of two fans 10 in the wind farm 1 may further include a step S31 and a step S32.
In step S31, the distance between two wind turbines 10 in the wind farm 1 may be calculated based on the longitude and latitude coordinates of the two wind turbines 10.
As shown in fig. 3, for any two wind turbines 10 in the wind farm 1, the longitude and latitude coordinates of one wind turbine 10 are (lat1, lon1), and the longitude and latitude coordinates of the other wind turbine 10 are (lat2, lon2), and the calculation formula of the Distance (Distance, abbreviated as D) between two wind turbines 10 is shown as the following formula:
D＝Re×(x+Ob/8×(C1-C2))
wherein, ObIs the oblateness of the earth, the oblateness of the earth ObThe calculation formula of (a) is as follows:
Ob＝(Re-Rb)/Re
wherein R iseThe equatorial radius of the earth, its value is 6378137 m; rbIs the polar radius of the earth, with a value of 6356752 m;
x＝arccos(sin(Pa)×sin(Pb)+cos(Pa)×cos(Pb)×cos(lon1–lon2))
C1＝(sin(x)-x)×(sin(Pa)+sin(Pb))^2/cos(x/2)^2
C2＝(sin(x)+x)×(sin(Pa)-sin(Pb))^2/sin(x/2)^2
Pa＝arctan(Rb/Re×tan(lat1))
Pb＝arctan(Rb/Re×tan(lat2))
therefore, when the longitude and latitude coordinates of any two fans 10 are obtained, the distance D between any two fans 10 can be calculated through the above formula. By analogy, the distance D between every two fans 10 in the wind farm 1 can be calculated according to the longitude and latitude coordinates between every two fans 10 in the wind farm 1.
Referring back to fig. 2, in step S32, the respective reference fans 12 of the target fan 11 may be determined based on the distance D between the two fans 10 calculated in step S31.
How to determine the respective reference fan 12 of the target fan 11 based on the distance D between two fans 10 will be described in detail below with continued reference to fig. 3.
Referring to fig. 3, after the distance D between every two fans 10 in the wind farm 1 is calculated, the distance D between the target fan 11 and the other fans 10 in the wind farm 1 is extracted from the calculated distance D between every two fans 10 in the wind farm 1, and each reference fan 12 of the target fan 11 may be determined based on the distance D between the target fan 11 and the other fans 10 in the wind farm 1.
In some embodiments, when the distance D between the target fan 11 and any other fan 10 in the wind farm 1 is less than or equal to a predetermined distance threshold, then that fan 10 is determined to be the reference fan 12 of the target fan 11.
In one embodiment, the distance threshold may be determined at a predetermined multiple of the impeller diameter of the wind turbine 10. The preset multiple of the diameter of the impeller is used as a distance threshold value, the distance threshold value is based on the position relation between the fans 10 and the consideration of terrain, climate factors and the like, and in order to eliminate the wake flow influence between the fans 10, the distance between the fans 10 is usually larger than the preset multiple of the diameter of the impeller; in addition, if the distance is too far away, the wind direction data is greatly different and difficult to model due to the fact that the wind direction data is easily interfered by terrain and weather factors. Thus, for example, the distance threshold may be determined at 5 impeller diameters, thereby both reducing wake effects between the wind turbines 10 and facilitating modeling. Specifically, as shown in fig. 3, a circle may be drawn with a radius of 5 times the diameter of the impeller with the target fan 11 as the center, and all fans 10 drawn within the circle may be regarded as the reference fans 12 of the target fan 11. In fig. 3, distances D between the target fan 11 and four fans in the front, rear, left, and right directions of the target fan 11 are all smaller than the distance threshold, and therefore, the four fans in the front, rear, left, and right directions of the target fan 11 can be respectively determined as the reference fans 12 of the target fan 11.
In another embodiment, the distance threshold may be determined according to the layout of the wind turbines 10 in the wind farm 1, for example, for a wind farm 1 arranged in a matrix, the maximum of the row spacing and the column spacing of the wind turbines 10 in the wind farm 1.
According to the monitoring method of the wind vane of the wind turbine in the wind farm, provided by the embodiment of the invention, each reference fan 12 of the target fan 11 can be determined according to the spatial position information among the fans 10, the determination mode of the reference fan 12 is simple and convenient, and the difficulty in selecting the reference fan 12 is reduced.
With continued reference to fig. 1, in step S4, after the respective reference fans 12 of the target fan 11 are determined in step S3, the respective abnormality judgment sectors of the target fan 11 may be determined based on the spatial position information of the target fan 11 and the respective reference fans 12.
As shown in fig. 4, the determining of each abnormality judgment sector of the target fan 11 based on the spatial position information of the target fan 11 and each reference fan 12 in step S4 may further include steps S41 and S42.
In step S41, an azimuth angle of a connection line between the target fan 11 and each reference fan 12 may be calculated based on the longitude and latitude coordinates of the target fan 11 and each reference fan 12.
In the embodiment of the present invention, the azimuth angle of the connection line between the target fan 11 and each reference fan 12 refers to an included angle between the connection line between the target fan 11 and each reference fan 12 and the north.
Referring to fig. 5, for example, if the longitude and latitude coordinates of the target fan 11 are (lat1, lon1) and the longitude and latitude coordinates of a certain reference fan 12 are (lat2, lon2), the calculation formula of the included angle between the connection line between the target fan 11 and the reference fan 12 is shown as the following formula:
angle＝(atan2(y,x))×180/π
wherein, angle is the angle between the connecting lines of the target fan 11 and the reference fan 12,
y＝sin(dLon)×cos(radLatB)
x＝cos(radLatA)×sin(radLatB)-sin(radLatA)×cos(radLatB)×cos(dLon)
dLon＝radLonB–radLonA
radLatA＝π×lat1/180
radLonA＝π×lon1/180
radLatB＝π×lat2/180
radLonB＝π×lon2/180
considering that the angle of the connection line between the target fan 11 and the reference fan 12 may not be in the range of 0 to 360 degrees, and the azimuth angle of the connection line between the target fan 11 and the reference fan 12 is in the range of 0 to 360 degrees, the azimuth angle of the connection line between the target fan 11 and the reference fan 12 needs to be processed in the range of the angle of the connection line between the target fan 11 and the reference fan 12, which is obtained by the above formula, for example, the remainder calculation shown by the following formula:
angle1＝(angle+360)mod 360
here, angle1 is the azimuth angle of the line between the target fan 11 and the reference fan 12.
Therefore, the remainder obtained by dividing the sum of the angle of the connecting line between the target fan 11 and the reference fan 12 and 360 ° by 360 ° is the azimuth angle1 of the connecting line between the target fan 11 and the reference fan 12.
Therefore, by analogy, after the longitude and latitude coordinates of the target fan 11 and each reference fan 12 are obtained, the azimuth angle1 of the connection line between the target fan 11 and each reference fan 12 can be calculated through the above formula according to the longitude and latitude coordinates between the target fan 11 and each reference fan 12.
In step S42 shown in fig. 4, each abnormality judgment sector may be determined based on the azimuth of the connection line between the target fan 11 and each reference fan 12.
As shown in fig. 5, in some embodiments, each abnormality determination sector may be obtained by adding or subtracting a predetermined threshold angle to or from an azimuth angle of a connection line between the target fan 11 and each reference fan 12. For example, in fig. 5, for the reference fan 12A, if the azimuth angle of the connection line between the target fan 11 and the reference fan 12A is 45 degrees, and the predetermined threshold angle is set to 15 degrees, the abnormality determination sector of the target fan 11 is between 30 degrees and 60 degrees; for the reference fan 12B, the azimuth angle of the connection line between the target fan 11 and the reference fan 12B is 310 degrees, and the predetermined threshold angle is set to 15 degrees, then the abnormality determination sector of the target fan 11 is 295 degrees to 325 degrees.
Referring back to fig. 1, in step S15, the abnormality determination sector in which the target fan 11 is currently located may be determined based on the current wind direction angle of the target fan 11 acquired in step S1.
As shown in fig. 5, for example, when the current wind direction angle of the target fan 11 is 35 degrees, it may be determined that the abnormality determination sector in which the target fan 11 is currently located is between 30 degrees and 60 degrees.
In step S6 shown in fig. 1, an anemoscope in a unit pair consisting of the target fan 11 and the reference fan 12 falling in the current abnormality judgment sector may be monitored for abnormality based on the current wind direction angles of the target fan 11 and the reference fan 12 falling in the current abnormality judgment sector.
As shown in fig. 5, if the current wind direction angle of the target fan 11 is 35 degrees, the current abnormality determination sector of the target fan 11 is determined to be between 30 degrees and 60 degrees, and therefore, the reference fan 12 falling in the current abnormality determination sector between 30 degrees and 60 degrees is the reference fan 12A (hereinafter, the reference fan 12A is taken as the reference fan in the current abnormality determination sector for example to be schematically described). The anemoscope in the unit pair formed by the target fan 11 and the reference fan 12A can be monitored for abnormality according to the current wind direction angles of the target fan 11 and the reference fan 12A.
In some embodiments, whether there is an abnormality in the anemoscope in the unit pair composed of the target fan 11 and the reference fan 12A falling in the current abnormality determination sector may be determined based on the current wind direction angle difference between the target fan 11 and the reference fan 12A falling in the current abnormality determination sector.
In one embodiment, determining whether there is an abnormality in the anemoscope in the unit pair consisting of the target fan 11 and the reference fan 12A falling in the current abnormality determination sector based on the current wind direction angle difference between the target fan 11 and the reference fan 12A falling in the current abnormality determination sector may further include steps S61 and S62.
In step S61, the set threshold values of the respective abnormality determination sectors are obtained.
How to obtain the set threshold value of each abnormality determination sector will be described in detail below with reference to fig. 7.
The wind direction angles of the respective fans 10 acquired in step S1 may further include historical wind direction angles for a predetermined period of time in the normal operation state of the respective fans 10. As shown in fig. 7, in some embodiments, the obtaining of the set threshold value of each abnormality determination sector in step S61 may further include step S611 and step S612.
In step S611, it is determined that the historical wind direction angles of the target fan 11 in the predetermined time period respectively fall into the historical time corresponding to each abnormal determination sector.
In step S612, the set threshold value of each abnormality determination sector may be determined based on the historical time, the historical wind direction angle of the target fan 11 and the reference fan 12 falling in each abnormality determination sector corresponding to the history time, the historical wind direction angle, and the historical wind direction angle of each abnormality determination sector.
For example, taking fig. 5 as an example, if the historical wind direction angle of the target fan 11 is 40 degrees at a certain historical time, the abnormal determination sector of the target fan 11 is 30 degrees to 60 degrees, and therefore the reference fan falling between the abnormal determination sector 30 degrees to 60 degrees at this time is 12A, so the set threshold between the abnormal determination sector 30 degrees to 60 degrees can be determined according to the historical wind direction angles of the target fan 11 and the reference fan 12A at this time. Similarly, at another historical time, the historical wind direction angle of the target fan 11 is 305 degrees, the abnormality judgment sector of the target fan 11 is 295 degrees to 325 degrees, and therefore the reference fan falling between 295 degrees to 325 degrees at this time is 12B, so the set threshold between 295 degrees to 325 degrees of the abnormality judgment sector can be determined according to the historical wind direction angles of the target fan 11 and the reference fan 12B at this time. And by analogy, determining the set threshold of each abnormal judgment sector.
With continued reference to fig. 7, in one embodiment, step S612 may further include step S6121 to step S6123. In step S6121, the historical wind direction angle difference between the target fan 11 and the reference fan 12 falling in each abnormality determination sector at the historical time corresponding to each abnormality determination sector is calculated.
In step S6122, the mean μ and variance σ of the angle difference of the historical wind direction obtained in step S6121 are further calculated.
In step S6123, the set threshold of each abnormality determination sector may be determined based on the mean μ and the variance σ of the historical wind direction angle differences of the target fan 11 and the reference fan 12 falling in each abnormality determination sector at the historical time corresponding to the falling in each abnormality determination sector calculated in step S6122.
For example, the set threshold value of each abnormality determination sector may be set to μ ± 3 × σ. However, the threshold value set for each abnormality determination sector according to the embodiment of the present invention is not limited to μ ± 3 × σ, and may be set to another value according to actual needs.
Referring back to fig. 6, in step S62, it may be determined whether there is an abnormality in the anemoscope in the unit pair consisting of the target fan 11 and the reference fan 12 falling in the currently located abnormality determination sector based on the current wind direction angle difference between the target fan 11 and the reference fan 12A falling in the currently located abnormality determination sector and the set threshold value of the currently located abnormality determination sector obtained in step S61.
When the current wind direction angle difference between the target fan 11 and the reference fan 12A falling into the current abnormal judgment sector exceeds the set threshold of the current abnormal judgment sector, the number of abnormal times may be added by 1, and if the number of continuous abnormal times exceeds the predetermined number (set according to experience, for example, 5 times), it is determined that the anemoscope in the unit pair composed of the target fan 11 and the reference fan 12 falling into the current abnormal judgment sector is abnormal; if the discontinuity phenomenon occurs before the preset times are exceeded, resetting the abnormal times and counting the times again.
Therefore, when the current wind direction angle difference between the target fan 11 and the reference fan 12 falling into the current abnormality judgment sector exceeds the set threshold of the current abnormality judgment sector for a predetermined number of times, it may be determined that the anemoscope in the unit pair consisting of the target fan 11 and the reference fan 12 falling into the current abnormality judgment sector is abnormal.
FIG. 8 discloses a flow chart of a method for monitoring a anemoscope in a wind farm according to another embodiment of the present invention. As shown in fig. 8, in other embodiments of the present invention, when it is detected that an anemoscope in a unit pair consisting of the target fan 11 and the reference fan 12 falling into the current abnormality determination sector is abnormal, the method for monitoring a anemoscope of a wind turbine in a wind farm may further include step S7 and step S8.
In step S7, power curves of the target fan 11 and the reference fan 12A in the unit pair consisting of the target fan 11 and the reference fan 12A falling in the current abnormality determination sector are obtained.
In step S8, it may be further determined whether the anemoscope of the target fan 11 or the reference fan 12A in the set pair is abnormal based on the power curves of the target fan 11 and the reference fan 12A in the set pair acquired in step S8.
Because the anemoscope is abnormal, the wind direction of the fan 10 is usually inaccurate, and the generated power of the fan 10 is reduced, so that when the anemoscope of the fan 10 in the set pair is determined to be abnormal, the power curves of the target fan 11 and the reference fan 12A in the set pair can be analyzed to further determine whether the anemoscope of the target fan 11 or the reference fan 12A is abnormal.
Fig. 9 discloses a schematic diagram of power curves of the target fan 11 and the reference fan 12A in a unit pair consisting of the target fan 11 and the reference fan 12A falling into the current abnormality determination sector according to an embodiment of the present invention. As shown in fig. 9, P1 represents the power curve of the target fan 11 in the gang pair, and P2 represents the power curve of the reference fan 12A in the gang pair. Since the target fan 11 and the reference fan 12A in the set are generally regarded as having a high correlation, when the deviation between the power curve P1 of the target fan 11 and the power curve P2 of the reference fan 12A exceeds a predetermined power threshold, it may be determined that the anemoscope of the fan 10 corresponding to the poor power curve is abnormal. For example, as can be seen in fig. 9, the power curve P2 of the reference fan 12 is significantly shifted to the right by a large amount with respect to the power curve P1 of the target fan 11, and therefore, it can be confirmed that an abnormality has occurred in the anemoscope for the reference fan 12 having the poor power curve P2.
Of course, in other embodiments, the power curve P1 of the target fan 11 and the power curve P2 of the reference fan 12A may be compared with the set power curve, respectively, and when the deviation from the set power curve exceeds a predetermined power threshold, it may be determined that the anemoscope of the fan 10 corresponding to the poor power curve is abnormal.
With continued reference to fig. 8, in some embodiments, the method for monitoring a wind vane of a wind farm according to an embodiment of the present invention may further include step S9. In step S9, when it is detected that the anemoscope of the fan 10 in the unit pair is abnormal, a fault alarm of the anemoscope may be triggered.
According to the monitoring method of the wind vane of the wind turbine in the wind farm, disclosed by the embodiment of the invention, the reference fan 12 of the target fan 11 can be determined based on the spatial position information of the fan 10, the selection of the reference fan 12 is simple, and the selection difficulty of the reference fan 12 is greatly reduced.
The monitoring method of the wind vane of the wind farm in the embodiment of the invention can determine the real-time abnormal judgment sector where the target fan 11 is located according to the real-time wind direction angle of the target fan 11, select the corresponding reference fan 12 falling into the real-time abnormal judgment sector, and monitor the abnormality of the wind vane of the unit pair consisting of the target fan 11 and the reference fan 12 according to the real-time wind direction angles of the target fan 11 and the selected corresponding reference fan 12, thereby effectively solving the problem of the deviation abnormality diagnosis of the wind direction angles of the target fan 11 and the reference fan 12 in the corresponding abnormal judgment sector.
In addition, the monitoring method of the anemoscope of the wind turbine in the wind farm of the embodiment of the invention can further determine that the anemoscope of the wind turbine set is abnormal from the middle to the bottom of the wind turbine set, namely the target fan 11 or the reference fan 12, so that the abnormal wind turbine 10 can be accurately judged, and further, the fault early warning of the corresponding anemoscope can be carried out, and the problem of fault diagnosis of the anemoscope of the wind turbine 10 is effectively solved.
The embodiment of the invention also provides a monitoring system 200 of the anemoscope of the wind turbine in the wind power plant. FIG. 10 discloses a schematic block diagram of a monitoring system 200 for a anemorumbometer in a wind farm according to an embodiment of the present invention. As shown in fig. 10, a monitoring system 200 for anemorumbometers in wind farms may include one or more processors 201 for implementing the method for monitoring anemorumeters in wind farms according to any of the embodiments described above. In some embodiments, the monitoring system 200 for a anemometer in a wind farm may include a computer-readable storage medium 202, and the computer-readable storage medium 202 may store a program that may be invoked by the processor 201, and may include a non-volatile storage medium. In some embodiments, a wind vane monitoring system 200 for a wind farm may include a memory 203 and an interface 204. In some embodiments, the monitoring system 200 for a wind vane in a wind farm according to an embodiment of the present invention may further include other hardware according to practical applications.
The monitoring system 200 of the anemoscope of the wind turbine in the wind farm in the embodiment of the present invention has similar beneficial technical effects to the above-mentioned monitoring method of the anemoscope of the wind farm, and therefore, the details are not repeated herein.
The embodiment of the invention also provides a computer readable storage medium. The computer readable storage medium stores a program, and the program is executed by a processor to implement the monitoring method for the anemoscope of the wind turbine in the wind farm according to any of the above embodiments.
Embodiments of the invention may take the form of a computer program product embodied on one or more storage media including, but not limited to, disk storage, CD-ROM, optical storage, and the like, in which program code is embodied. Computer-readable storage media include permanent and non-permanent, removable and non-removable media and may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer readable storage media include, but are not limited to: phase change memory/resistive random access memory/magnetic memory/ferroelectric memory (PRAM/RRAM/MRAM/FeRAM) and like new memories, Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.
The monitoring method and the system for the anemoscope of the wind turbine in the wind farm and the computer readable storage medium thereof in one or more embodiments of the invention can identify and monitor whether the anemoscope of the wind turbine in the wind farm is abnormal or not on line in real time, thereby ensuring that the wind turbine 10 can accurately aim at the wind and realizing the maximization of the generated energy of the wind turbine 10.
The method for monitoring the anemoscope of the wind turbine in the wind farm, the system thereof and the computer readable storage medium provided by the embodiment of the invention are described in detail above. The method for monitoring a wind vane indicator in a wind farm, the system thereof and the computer-readable storage medium thereof are described in the present application with specific examples, and the description of the above embodiments is only for assisting understanding of the core idea of the present invention and is not intended to limit the present invention. It should be noted that, for those skilled in the art, various improvements and modifications can be made without departing from the spirit and principle of the present invention, and these improvements and modifications should fall within the scope of the appended claims.
Claims (17)
1. A monitoring method of a wind vane anemoscope in a wind power plant is characterized by comprising the following steps: it includes:
acquiring spatial position information of each fan in a wind power plant and a wind direction angle measured by a wind direction meter of each fan, wherein the wind direction angle comprises a current wind direction angle of each fan in an actual running state;
selecting a target fan;
determining each reference fan of the target fan based on the spatial position information of every two fans in the wind power plant;
determining each abnormal judgment sector of the target fan based on the spatial position information of the target fan and each reference fan;
determining an abnormal judgment sector where the target fan is located currently based on the current wind direction angle of the target fan; and
and carrying out abnormity monitoring on a anemoscope in a unit pair consisting of the target fan and the reference fan falling into the current abnormity judgment sector based on the current wind direction angles of the target fan and the reference fan falling into the current abnormity judgment sector.
2. The method of claim 1, wherein: the method for acquiring the spatial position information of each fan in the wind power plant and the wind direction angle measured by the anemoscope of each fan comprises the following steps:
and acquiring the spatial position information of each fan in the wind power plant and the wind direction angle measured by a wind direction instrument of each fan from an SCADA system of the wind power plant.
3. The method of claim 1, wherein: the spatial position information of the wind turbine includes longitude and latitude coordinates of the wind turbine, and the determining of each reference wind turbine of the target wind turbine based on the spatial position information of every two wind turbines in the wind farm includes:
calculating the distance between every two fans based on the longitude and latitude coordinates of every two fans in the wind power plant; and
determining each reference fan of the target fan based on a distance between two fans.
4. The method of claim 3, wherein: the determining each reference fan of the target fan based on the distance between every two fans comprises:
determining the distance between the target fan and other fans in the wind power plant; and
and when the distance between the target fan and any other fan in the wind power plant is smaller than or equal to a preset distance threshold value, determining that the fan is a reference fan of the target fan.
5. The method of claim 4, wherein: the distance threshold is determined as a predetermined multiple of the impeller diameter of the wind turbine or as the maximum of the row and column spacing of the wind turbines in the wind farm.
6. The method of claim 3, wherein: the determining each abnormality determination sector based on the spatial position information of the target fan and the respective reference fans includes:
calculating an azimuth angle of a connecting line between the target fan and each reference fan based on longitude and latitude coordinates of the target fan and each reference fan; and
determining the respective abnormality judgment sectors based on the azimuth angles of the connecting lines between the target fan and the respective reference fans.
7. The method of claim 6, wherein: the determining the respective abnormality determination sectors based on the azimuth of a connection line between the target fan and the respective reference fans includes:
and respectively adding or subtracting a preset threshold angle on the azimuth angle of the connecting line between the target fan and each reference fan to obtain each abnormal judgment sector.
8. The method of claim 1, wherein: the abnormal monitoring of the anemoscope in the unit pair formed by the target fan and the reference fan falling into the abnormal judgment sector at present based on the current wind direction angle of the target fan and the reference fan falling into the abnormal judgment sector at present comprises:
and determining whether an anemoscope in a unit pair consisting of the target fan and the reference fan falling into the current abnormal judgment sector is abnormal or not based on the current wind direction angle difference between the target fan and the reference fan falling into the current abnormal judgment sector.
9. The method of claim 8, wherein: the determining whether an anemoscope in a unit pair consisting of the target fan and a reference fan falling into the current abnormal judgment sector is abnormal or not based on the current wind direction angle difference between the target fan and the reference fan falling into the current abnormal judgment sector comprises:
obtaining a set threshold value of each abnormal judgment sector; and
and determining whether the anemoscope in the unit pair consisting of the target fan and the reference fan falling into the current abnormal judgment sector is abnormal or not based on the current wind direction angle difference value between the target fan and the reference fan falling into the current abnormal judgment sector and the set threshold value of the current abnormal judgment sector.
10. The method of claim 9, wherein: the wind direction angle further includes a historical wind direction angle in a predetermined time period in a normal operation state of each fan, and the obtaining of the set threshold of each abnormal judgment sector includes:
determining that the historical wind direction angles of the target fan in the preset time period respectively fall into the historical time corresponding to each abnormal judgment sector;
and determining the set threshold of each abnormal judgment sector based on the historical wind direction angles of the target fan at the historical moment corresponding to each abnormal judgment sector and the reference fan falling into each abnormal judgment sector.
11. The method of claim 10, wherein: the determining the set threshold of each abnormality determination sector based on historical wind direction angles of the target fan at the historical time corresponding to the abnormality determination sector and the reference fan falling in the abnormality determination sector includes:
calculating the mean value and the variance of the historical wind direction angle difference values of the target fan at the historical moment corresponding to each abnormal judgment sector and the reference fan falling into each abnormal judgment sector; and
determining the set threshold value of each abnormal judgment sector based on the mean value and the variance of the historical wind direction angle difference values of the target fan and the reference fan falling into each abnormal judgment sector at the historical moment corresponding to each abnormal judgment sector.
12. The method of claim 9, wherein: and when the current wind direction angle difference value between the target fan and the reference fan falling into the current abnormal judgment sector exceeds the set threshold value of the current abnormal judgment sector for a preset number of times, determining that the anemoscope in the unit pair consisting of the target fan and the reference fan falling into the current abnormal judgment sector is abnormal.
13. The method of claim 1, wherein: when the condition that the anemoscope of the fan in the unit pair is abnormal is monitored, the method further comprises the following steps:
acquiring power curves of a target fan and a reference fan in the unit pair; and
further determining whether an anemoscope of the target fan or the reference fan in the unit pair is abnormal based on power curves of the target fan and the reference fan in the unit pair.
14. The method of claim 13, wherein: and when the deviation between the power curves of the target fan and the reference fan exceeds a preset power threshold value, determining that the anemoscope of the fan corresponding to the poor power curve is abnormal.
15. The method of claim 13, wherein: it still includes:
and triggering a fault alarm of the anemoscope when the anemoscope of the fan in the set pair is monitored to be abnormal.
16. The utility model provides a monitoring system of fan anemoscope in wind-powered electricity generation field which characterized in that: comprising one or more processors for implementing a method for monitoring a anemoscope of a wind turbine in a wind farm according to any of claims 1-15.
17. A computer-readable storage medium, characterized in that it has a program stored thereon, which, when being executed by a processor, carries out a method of monitoring a wind vane in a wind farm according to any one of claims 1 to 15.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111289692.2A CN114113683A (en) | 2021-11-02 | 2021-11-02 | Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111289692.2A CN114113683A (en) | 2021-11-02 | 2021-11-02 | Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114113683A true CN114113683A (en) | 2022-03-01 |
Family
ID=80380220
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111289692.2A Pending CN114113683A (en) | 2021-11-02 | 2021-11-02 | Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114113683A (en) |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102619687A (en) * | 2012-04-18 | 2012-08-01 | 北车风电有限公司 | Emergency control method with failure of anemorumbometer of wind generating set |
| CN105065201A (en) * | 2015-07-22 | 2015-11-18 | 天津瑞源电气有限公司 | Control method for ensuring normal running after damage of wind indicator of wind turbine unit |
| CN105863970A (en) * | 2016-05-06 | 2016-08-17 | 华北电力大学（保定） | Draught fan fault recognition method and device |
| CN105891546A (en) * | 2016-01-26 | 2016-08-24 | 沈阳工业大学 | Wind vane fault diagnosis method in wind turbine yaw system based on big data |
| CN106246465A (en) * | 2016-08-16 | 2016-12-21 | 中车株洲电力机车研究所有限公司 | A kind of Wind turbines wind speed and direction acquisition methods and wind power generation set system |
| CN106321368A (en) * | 2016-08-12 | 2017-01-11 | 峰能斯格尔（北京）可再生能源科技有限公司 | Offshore wind power plant wake flow loss measuring method based on running draught fan SCADA data |
| CN106922162A (en) * | 2014-09-29 | 2017-07-04 | 维斯塔斯风力系统有限公司 | The checking of Wind turbine nacelle yaw attitude sensor |
| US20170352010A1 (en) * | 2016-06-02 | 2017-12-07 | Doosan Heavy Industries & Construction Co., Ltd. | Wind farm supervision monitoring system |
| CN108035853A (en) * | 2017-12-01 | 2018-05-15 | 北京金风科创风电设备有限公司 | Method and device for determining wind angle of wind generating set |
| CN108533452A (en) * | 2018-04-09 | 2018-09-14 | 北京金风慧能技术有限公司 | Untie the mooring rope control method and the control device that unties the mooring rope of wind power generating set |
| CN109752566A (en) * | 2017-11-03 | 2019-05-14 | 北京金风科创风电设备有限公司 | Detection method, device and the wind power generating set at wind azimuth angle |
| CN110110439A (en) * | 2019-05-08 | 2019-08-09 | 固安华电天仁控制设备有限公司 | A kind of wind power plant SCADA system based on threedimensional model |
| CN110985309A (en) * | 2019-12-09 | 2020-04-10 | 远景智能国际私人投资有限公司 | Yaw wind anomaly detection method, device, equipment and storage medium |
| CN111794909A (en) * | 2020-06-23 | 2020-10-20 | 国电新能源技术研究院有限公司 | Sector regulation-oriented wind power plant level yaw dynamic optimization method and system |
| DE102019117985A1 (en) * | 2019-07-03 | 2021-01-07 | ENERTRAG Windstrom GmbH | Method for optimizing the technical management of individual wind turbines in a wind farm |
| CN112348244A (en) * | 2020-10-31 | 2021-02-09 | 华能新能源上海发电有限公司 | Wind power plant generator set overhauling method based on wind resource assessment |
| CN113030516A (en) * | 2019-12-24 | 2021-06-25 | 华能如东八仙角海上风力发电有限责任公司 | Anemometer fault detection method, device, equipment and storage medium |
| CN113530769A (en) * | 2021-08-30 | 2021-10-22 | 上海电气风电集团股份有限公司 | Anti-ice-throwing control method and system for wind generating set and computer readable storage medium |
-
2021
- 2021-11-02 CN CN202111289692.2A patent/CN114113683A/en active Pending
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102619687A (en) * | 2012-04-18 | 2012-08-01 | 北车风电有限公司 | Emergency control method with failure of anemorumbometer of wind generating set |
| CN106922162A (en) * | 2014-09-29 | 2017-07-04 | 维斯塔斯风力系统有限公司 | The checking of Wind turbine nacelle yaw attitude sensor |
| CN105065201A (en) * | 2015-07-22 | 2015-11-18 | 天津瑞源电气有限公司 | Control method for ensuring normal running after damage of wind indicator of wind turbine unit |
| CN105891546A (en) * | 2016-01-26 | 2016-08-24 | 沈阳工业大学 | Wind vane fault diagnosis method in wind turbine yaw system based on big data |
| CN105863970A (en) * | 2016-05-06 | 2016-08-17 | 华北电力大学（保定） | Draught fan fault recognition method and device |
| US20170352010A1 (en) * | 2016-06-02 | 2017-12-07 | Doosan Heavy Industries & Construction Co., Ltd. | Wind farm supervision monitoring system |
| CN106321368A (en) * | 2016-08-12 | 2017-01-11 | 峰能斯格尔（北京）可再生能源科技有限公司 | Offshore wind power plant wake flow loss measuring method based on running draught fan SCADA data |
| CN106246465A (en) * | 2016-08-16 | 2016-12-21 | 中车株洲电力机车研究所有限公司 | A kind of Wind turbines wind speed and direction acquisition methods and wind power generation set system |
| CN109752566A (en) * | 2017-11-03 | 2019-05-14 | 北京金风科创风电设备有限公司 | Detection method, device and the wind power generating set at wind azimuth angle |
| CN108035853A (en) * | 2017-12-01 | 2018-05-15 | 北京金风科创风电设备有限公司 | Method and device for determining wind angle of wind generating set |
| CN108533452A (en) * | 2018-04-09 | 2018-09-14 | 北京金风慧能技术有限公司 | Untie the mooring rope control method and the control device that unties the mooring rope of wind power generating set |
| CN110110439A (en) * | 2019-05-08 | 2019-08-09 | 固安华电天仁控制设备有限公司 | A kind of wind power plant SCADA system based on threedimensional model |
| DE102019117985A1 (en) * | 2019-07-03 | 2021-01-07 | ENERTRAG Windstrom GmbH | Method for optimizing the technical management of individual wind turbines in a wind farm |
| CN110985309A (en) * | 2019-12-09 | 2020-04-10 | 远景智能国际私人投资有限公司 | Yaw wind anomaly detection method, device, equipment and storage medium |
| CN113030516A (en) * | 2019-12-24 | 2021-06-25 | 华能如东八仙角海上风力发电有限责任公司 | Anemometer fault detection method, device, equipment and storage medium |
| CN111794909A (en) * | 2020-06-23 | 2020-10-20 | 国电新能源技术研究院有限公司 | Sector regulation-oriented wind power plant level yaw dynamic optimization method and system |
| CN112348244A (en) * | 2020-10-31 | 2021-02-09 | 华能新能源上海发电有限公司 | Wind power plant generator set overhauling method based on wind resource assessment |
| CN113530769A (en) * | 2021-08-30 | 2021-10-22 | 上海电气风电集团股份有限公司 | Anti-ice-throwing control method and system for wind generating set and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | Short-term wind power prediction based on extreme learning machine with error correction | |
| CA2892898C (en) | Systems and methods for wind turbine nacelle-position recalibration and wind direction estimation | |
| CA2997644C (en) | Simulation method and system | |
| CN105205569B (en) | State of fan gear box online evaluation method for establishing model and online evaluation method | |
| Yoder et al. | Short‐term forecasting of categorical changes in wind power with Markov chain models | |
| JP6054998B2 (en) | How to determine lost energy | |
| CN113530769B (en) | Ice-throwing prevention control method and system for wind generating set and computer readable storage medium | |
| CN113586336B (en) | Control method and control device of wind generating set and computer readable storage medium | |
| CN112345250B (en) | Bearing vibration monitoring method and system and computer readable storage medium | |
| CN114113683A (en) | Wind direction indicator monitoring method and system for wind turbine in wind power plant and computer readable storage medium | |
| CN113884705A (en) | Monitoring method and system of cluster fan anemometer and computer readable storage medium | |
| Wang et al. | Reliability assessment of wind farm active power based on sequential monte-carlo method | |
| CN114862043A (en) | Wind power plant generated power prediction method and system and computer readable storage medium | |
| CN113775481A (en) | CMS vibration protection method and device and computer readable storage medium | |
| CN113449985B (en) | Gearbox monitoring method and system and computer readable storage medium | |
| CN113283035A (en) | Method, system, equipment and storage medium for constructing cabin transfer function of double-parameter wind turbine | |
| Martin et al. | New Wake Effects Identified Using SCADA Data Analysis and Visualization. | |
| CN114781711A (en) | Method and device for predicting residual life of rotating part and computer readable storage medium | |
| ES2963166T3 (en) | Method for determining wind speed in the plane of the rotor of a wind turbine | |
| CN117349573B (en) | Wind power plant wind speed prediction method, electronic equipment and storage medium | |
| CN115855500A (en) | Bearing monitoring method and system and computer readable storage medium | |
| CN113435705A (en) | Bearing monitoring method and system and computer readable storage medium | |
| CN114993670A (en) | Gear rotating speed determining method and system and computer readable storage medium | |
| Chen et al. | Automated wind turbine pitch fault prognosis using ANFIS | |
| Lawan et al. | ANN, GPS AND GIS APPLICATIONS METHODOLOGY FOR WIND ENERGY MAPPING IN KANO STATE, NIGERIA |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |