A Method and System for Calculating the Power Curve of Wind Turbines Based on Nacelle Control Wind Measurement Radar

Abstract

This invention discloses a method and system for calculating the power curve of a wind turbine based on a nacelle-controlled anemometer radar. It employs lidar to simultaneously test and acquire both the long-range wind speed in front of the rotor (meeting the requirements for power curve testing) and the short-range wind speed in front of the rotor (used for turbine control). The radar anemometer data at both distances are then cleaned and fitted twice to obtain the transfer function between the two sets of data. This transforms the short-range radar anemometer data used for turbine control into the incoming wind speed that meets the requirements for power curve testing. This short-range radar anemometer data then replaces the nacelle anemometer data and is used to clean and fit the turbine's operating data to obtain the true power curve of the turbine. The resulting power curve is more accurate and reliable, effectively avoiding distortion caused by inaccurate nacelle anemometer transfer functions or anemometer malfunctions. It accurately reflects the power generation performance of the wind turbine and fully utilizes radar anemometer data, avoiding resource waste.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wind power generation, and particularly relates to a wind turbine power curve calculation method and system based on a nacelle control wind radar. BACKGROUND

[0002] According to the wind turbine momentum theory, the airflow will be distorted before reaching the wind wheel, the wind speed will decrease, and the kinetic energy of the wind will be converted into pressure potential energy. In order to ensure the accuracy of the wind turbine power curve, the wind speed at a certain distance in front of the wind wheel is usually selected as the reference. The GB / T 18451.2 Wind Turbine Power Performance Test stipulates that the distance between the wind measuring equipment and the wind turbine should be 2D-4D, and the recommended distance is 2.5D, where D is the diameter of the wind wheel.

[0003] The power curve of the wind turbine can usually be obtained by two methods.

[0004] One method is to process and fit the wind speed, active power and other operating data of the nacelle anemometer, wherein the wind speed of the wind turbine is converted into the standard required wind speed at a distance of 2D-4D in front of the wind wheel by processing the original current signal of the nacelle anemometer through the transfer function. However, the accuracy of the transfer function of the nacelle anemometer needs to be verified, and in addition, the nacelle anemometer is usually affected by the wake and inertia, resulting in a decrease in the accuracy of the measured wind speed. Therefore, the accuracy of the power curve of the wind turbine obtained based on the nacelle anemometer data will also decrease.

[0005] The other method is to measure the wind speed at a certain distance between 2D-4D in front of the wind wheel by using a wind measuring laser radar and other wind measuring equipment according to the standard, and to process and fit the wind speed with the active power and other operating data of the wind turbine to obtain the power curve of the wind turbine. This method can obtain a more accurate power curve of the wind turbine, which can truly reflect the power generation performance of the wind turbine. However, this testing method has a high cost and is not suitable for long-term testing and evaluation during the operation of the wind turbine.

[0006] In addition, many wind turbines have installed nacelle control wind radars at present, which can measure the wind speed information at a fixed distance in front of the wind wheel in real time and participate in the control of the wind turbine to improve the control effect of the wind turbine. The laser wind radar used for the control of the wind turbine usually has a short wind measuring distance and a lower cost than the laser radar used for the power curve test, and has a further space for exploration and utilization. SUMMARY

[0007] The technical problem to be solved by the present application is to provide a wind turbine power curve calculation method and system based on a nacelle control wind radar to solve the technical problem of power curve distortion caused by inaccurate transfer function of the anemometer or anemometer failure.

[0008] The application adopts the following technical solutions:

[0009] The wind turbine power curve calculation method based on the nacelle control wind measuring radar comprises the following steps:

[0010] S1, obtaining the wind turbine rotor diameter D and the nacelle control wind measuring radar wind measuring distance H, and calculating the wind measuring distance D2 for the wind turbine power curve;

[0011] S2, continuously and synchronously testing the wind speed information at the wind measuring distance D2 and H distance in front of the rotor for several days through the nacelle wind laser radar;

[0012] S3, obtaining the mean value of the axis projection wind speed at the D2 and H distance in front of the rotor and the mean value of the data validity rate in the test time period of step S2 to form a data set N1, defining the mean value of the axis projection wind speed at the D2 distance in front of the rotor in the data set N1 as V D2 , defining the mean value of the axis projection wind speed at the H distance in front of the rotor in the data set N1 as V H , defining the mean value of the data validity rate at the D2 distance in front of the rotor in the data set N1 as e1, and defining the mean value of the data validity rate at the H distance in front of the rotor in the data set N1 as e2;

[0013] S4, screening the wind measuring data in the data set N1 obtained in step S3 to form a data set N2, wherein V D2 and V H are greater than 0 and the data validity rate is 100%, taking V H and V D2 in the data set N2 as the horizontal and vertical coordinates respectively to draw a wind speed scatter plot, and performing linear fitting on V H and V D2 in the wind speed scatter plot to obtain a straight line L1;

[0014] S5, calculating the distance of each data point in the wind speed scatter plot obtained in step S4 to the straight line L1 to obtain a distance set M, and obtaining a data set N3 after cleaning;

[0015] S6, taking V H and V D2 in the data set N3 obtained in step S5 as the horizontal and vertical coordinates respectively to perform linear fitting again to obtain the transfer function between V H and V D2 ;

[0016] S7, for the wind turbine with the installed control laser radar, extracting the historical data of the previous 90 days of the wind turbine in the running process every 30 days and forming a data set N4;

[0017] S8, data cleaning is performed on the data set N4 obtained in step S7, data in which the unit operation state is not normal power generation is removed, and a data set N5 is obtained;

[0018] S9, V H greater than 0 and e2 is 100% in the data set N6, and the data set N6 is converted into the wind speed V H at the distance D2 in front of the wind wheel through the transfer function obtained in step S6. D2 The data set N5 is defined as N7 after conversion.

[0019] S10, the wind speed V D2 in the data set N7 is arranged according to the size of the wind speed V D2 in the data set N7, and a data set N8 is obtained, and the data in the data set N8 is divided into bins with every 0.5 m / s as a wind speed interval, the average value μ and the standard deviation σ of the power in each wind speed interval are calculated, and each sub-wind speed interval is obtained.

[0020] S11, the average value of the wind speed V D2 corresponding to each data point in each sub-wind speed interval obtained in step S10 and the average value of the active power are calculated, the wind speed-power data is saved, and the wind speed-power curve of the unit within 90 days based on radar wind measurement is obtained through difference fitting, and it is drawn in a figure together with the guaranteed power curve of the unit for display.

[0021] Specifically, in step S1, the power curve of the wind turbine is measured at a distance range of 2D-4D.

[0022] Specifically, in step S2, if the nacelle control wind radar can directly measure the wind speed information at the distances D2 and H in front of the wind wheel through setting, the nacelle control wind radar is set to continuously and synchronously test the wind speed information at the distances D2 and H in front of the wind wheel for at least 60 days. If the nacelle control wind radar cannot simultaneously measure the wind speed at the distances D2 and H in front of the wind wheel through setting, a laser wind radar suitable for performance calculation of the unit is installed on the nacelle to continuously and synchronously test the wind speed information at the distances D2 and H in front of the wind wheel for at least 60 days.

[0023] Specifically, in step S3, the axis projection wind speed at the distances D2 and H in front of the wind wheel, the data availability, the axis projection wind speed at the distance D2 in front of the wind wheel in N1, the axis projection wind speed at the distance H in front of the wind wheel in N1, the data availability at the distance D2 in front of the wind wheel in N1, and the data availability at the distance H in front of the wind wheel in N1 are all 10-minute average data.

[0024] Specifically, in step S5, the quartile method is used to clean the data set N2 according to the size of the distance set M, and the cleaned data set is defined as N3.

[0025] Specifically, in step S6, V H and V D2 are transmitted between the functions as follows:

[0026] V D2 = aV H +b

[0027] wherein a is the slope of the transmission function between V H and V D2 , and b is the intercept of the transmission function between V H and V D2 .

[0028] Specifically, in step S7, the radar wind measurement data and the historical operation data corresponding to the same time row are the mean values of the same 10min radar wind measurement data and the historical operation data, and the historical data include 10min radar wind measurement data V H , e2 and 10min unit operation data such as unit state, active power, wind wheel speed, blade pitch angle, etc.

[0029] Specifically, in step S8, the abnormal power generation data includes shutdown, idling, fault, maintenance, start and limited power data.

[0030] Specifically, in step S10, the large range outlier data points with active power less than μ-3σ and active power greater than μ+3σ in each wind speed interval are removed to obtain each sub-wind speed interval.

[0031] In a second aspect, the embodiments of the present application provide a wind turbine power curve calculation system based on a nacelle control wind measurement radar, which comprises:

[0032] A data module obtains the wind turbine rotor diameter D and the nacelle control wind measurement radar wind measurement distance H, and calculates the wind measurement distance D2 used for the wind turbine power curve;

[0033] A test module synchronously tests the wind speed information at the wind measurement distance D2 and H distance in front of the rotor for several days at least continuously through the laser wind measurement radar;

[0034] A synthesis module obtains the mean value of the axial projection wind speed at the D2 and H distance in front of the rotor and the mean value of the data efficiency of the laser radar measured in the test time period of the test module to form a data set N1, defines the mean value of the axial projection wind speed at the wind measurement distance D2 in front of the rotor in the data set N1 as V D2 , and defines the mean value of the axial projection wind speed at the H distance in front of the rotor in the data set N1 as V H, define the mean value of the data effective rate at the distance D2 in front of the wind wheel in the data set N1 as e1, and define the mean value of the data effective rate at the distance H in front of the wind wheel in the data set N1 as e2;

[0035] The screening module screens the data set N1 obtained by the synthesis module to obtain the data set N2 composed of the wind measurement data in which V D2 and V H are greater than 0 and the data effective rate is 100%. H and V D2 are the horizontal coordinate and the vertical coordinate respectively to draw a wind speed scatter plot, and linear fitting is performed on V H and V D2 in the wind speed scatter plot to obtain a straight line L1.

[0036] The cleaning module calculates the distance of each data point in the wind speed scatter plot obtained by the screening module to the straight line L1 to obtain a distance set M, and obtains the data set N3 after cleaning.

[0037] The fitting module performs linear fitting again with V H and V D2 as the horizontal coordinate and the vertical coordinate respectively in the data set N3 obtained by the cleaning module to obtain the transfer function between V H and V D2 .

[0038] The extraction module extracts the historical data of the wind turbine in which the control laser radar is installed in the first 90 days before the operation every 30 days during the operation process to form a data set N4.

[0039] The elimination module performs data cleaning on the data set N4 obtained by the extraction module to eliminate the data in which the unit operation state is not normal power generation to obtain a data set N5.

[0040] The conversion module screens the data set N5 obtained by the elimination module to obtain the data set N6 composed of the data in which V H is greater than 0 and e2 is 100%, and converts V H in the data set N6 into the wind speed V D2 at the distance D2 in front of the wind wheel through the transfer function obtained by the fitting module, and defines the data set obtained after the conversion of the data set N5 as N7.

[0041] The arrangement module arranges the wind speed V D2 and the active power in the data set N7 according to the size of the wind speed V D2 in the data set N7 obtained by the conversion module to obtain a data set N8, and divides the data in the data set N8 into bins with every 0.5 m / s as a wind speed interval, calculates the power average μ and the standard deviation σ in each wind speed interval to obtain each sub-wind speed interval.

[0042] an output module, which calculates the wind speed V corresponding to each data point in each sub-wind speed interval obtained by the arrangement module D2 The mean value and the mean value of active power save the wind speed-power data, and obtain the wind speed-power curve of the unit within 90 days based on radar wind measurement through difference fitting, and plot the wind speed-power curve of the unit and the guaranteed power curve of the unit in a graph for display.

[0043] Compared with the prior art, the present application has at least the following beneficial effects:

[0044] The wind turbine power curve calculation method based on the cabin control wind measurement radar of the present application can effectively avoid the distortion of the power curve caused by the inaccurate transfer function of the cabin anemometer or the failure of the anemometer, and can truly reflect the power generation performance of the wind turbine, and can also make full use of the radar wind measurement data to avoid waste of resources.

[0045] Further, the wind turbine power curve measurement distance D2 should not be too close or too far from the wind turbine, because the measured wind speed will be affected by airflow distortion if the distance is too close, and the correlation between the measured wind speed and the output power will decrease if the distance is too far. The recommended wind turbine power curve measurement distance D2 should be 2D-4D, and 2.5D can be selected generally.

[0046] Further, the data is 10-minute average value, which can reduce the calculation amount while ensuring the accuracy of the results.

[0047] Further, the data points far from the straight line L1 are removed by the quartile method to improve the data fitting effect.

[0048] Further, the transfer function between the meaning V H and the meaning V D2 can convert V H into V D2 that meets the power curve test requirements.

[0049] Further, the time stamps of the historical radar wind data and the historical operation data need to be strictly matched, that is, the radar wind data and the historical operation data corresponding to the same time need to be the average values of the radar wind data and the historical operation data within the same 10 minutes. If there is a difference between the time stamps of the historical radar wind data and the historical operation data, the accuracy of the finally obtained power curve will be affected.

[0050] Further, the abnormal power generation data includes data of the wind turbine in the abnormal power generation states such as shutdown, idling, failure, maintenance, start-up and limited power.

[0051] Further, the large-range outlier data in the wind speed-power scatter plot is removed by using the Relyada criterion (3σ criterion), that is, the data with the active power less than μ-3σ and the active power greater than μ+3σ in each wind speed interval is removed.

[0052] It can be understood that the beneficial effects of the above-mentioned second aspect can be referred to the related description in the above-mentioned first aspect, which will not be described here.

[0053] In summary, the present application converts the laser radar wind data for unit control into wind data meeting the test distance requirement of the power curve, so as to further obtain the real power curve and power generation performance of the unit, and the wind data of the wind radar is fully utilized. The obtained power curve is more in line with the real situation of the unit and has higher reference value compared with the power curve obtained based on the anemometer data.

[0054] The technical solutions of the present application will be further described in detail below by means of the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 is a flowchart of the present application;

[0056] Figure 2 is a schematic diagram of linear fitting of V H and V D2 ;

[0057] Figure 3 is a schematic diagram of the transfer function between V H and V D2 obtained by linear fitting after cleaning the data set N2 by the quartile method;

[0058] Figure 4 is a schematic diagram of data cleaning of the data set N4;

[0059] Figure 5 is a schematic diagram of the unit power curve obtained after cleaning the large-range outlier data points from the data set N8. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the scope of the present application.

[0061] In the description of the present application, it should be understood that the terms "comprising" and "including" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0062] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0063] It should be further understood that the term "and / or" used in the specification and the appended claims of the present application means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations, for example, A and / or B can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0064] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present application to describe the preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range without departing from the scope of the embodiments of the present application.

[0065] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if it is determined" or "if (a stated condition or event) is detected" can be interpreted to mean "when it is determined" or "in response to determining" or "when (a stated condition or event) is detected" or "in response to detecting (a stated condition or event)".

[0066] The various structural diagrams according to the disclosed embodiments of the present application are shown in the drawings. These diagrams are not drawn to scale, in which certain details are exaggerated for clarity of presentation and may omit certain details. The shapes of various regions, layers shown in the drawings and their relative sizes and positional relationships may deviate in actuality due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes, relative positions may be additionally designed according to actual needs by those skilled in the art.

[0067] Referring to Figure 1 , the present application is a wind turbine power curve calculation method based on a nacelle control wind measuring radar, comprising the following steps:

[0068] S1, obtaining the wind turbine rotor diameter D, the nacelle control wind measuring radar wind measuring distance H, and calculating the wind measuring distance D2 that can be used for wind turbine power curve;

[0069] Wherein, D2 should be within the range of 2D and 4D distance, generally selected as 2.5D.

[0070] S2, continuously and synchronously testing the wind speed information at the wind measuring distance D2 and H distance in front of the rotor for at least 60 days through the nacelle wind measuring radar;

[0071] If the nacelle control wind measuring radar directly measures the wind speed information at the D2 and H distance in front of the rotor through setting, the nacelle control wind measuring radar is set to continuously and synchronously test the wind speed information at the wind measuring distance D2 and H distance in front of the rotor for at least 60 days. If the nacelle control wind measuring radar;

[0072] The nacelle control wind measuring radar is set to continuously and synchronously test the wind speed information at the wind measuring distance D2 and H distance in front of the rotor for at least 60 days. If the nacelle control wind measuring radar cannot simultaneously measure the wind speed at the D2 and H distance in front of the rotor through setting, a laser wind measuring radar suitable for wind turbine performance calculation is installed on the nacelle, and the wind speed information at the D2 and H distance in front of the rotor is continuously and synchronously tested for at least 60 days.

[0073] S3, obtaining the 10min average of the axial projection wind speed at the D2 and H distance in front of the rotor and the 10min average of the data availability rate of the laser radar measured in the test period of step S2 to form a data set N1, defining the 10min average of the axial projection wind speed at the D2 distance in front of the rotor in N1 as V D2 , defining the 10min average of the axial projection wind speed at the H distance in front of the rotor in N1 as V H , defining the 10min average of the data availability rate at the D2 distance in front of the rotor in N1 as e1, and defining the 10min average of the data availability rate at the H distance in front of the rotor in N1 as e2;

[0074] S4, screening out the wind data set N2 composed of the wind data in the data set N1 obtained in step S3, V D2 and V H are greater than 0 and the data validity rate is 100%. H and V D2 are the abscissa and ordinate respectively to draw a wind speed scatter plot, and linear fitting is performed on V H and V D2 in the obtained wind speed scatter plot to obtain a straight line L1.

[0075] S5, calculating the distance of each data point in the wind speed scatter plot obtained in step S4 to the straight line L1 to obtain a distance set M, and further cleaning the data set N2 according to the size of the distance set M by using the quartile method, and the cleaned data set is defined as N3.

[0076] S6, taking V H and V D2 in the cleaned data set N3 obtained in step S5 as the abscissa and ordinate respectively to perform linear fitting again to obtain the transfer function between V H and V D2 .

[0077] The transfer function between V H and V D2 is:

[0078] V D2 =aV H +b

[0079] wherein a is the slope of the transfer function between V H and V D2 , and b is the intercept of the transfer function between V H and V D2 .

[0080] S7, for the wind turbine equipped with the control laser radar, in the running process, historical data of the wind turbine in the previous 90 days is extracted every 30 days to form a data set N4.

[0081] The historical data should at least include 10-minute radar wind data V H , e2, and 10-minute turbine state, active power, rotor speed, blade pitch angle and other turbine operation data.

[0082] It should be noted that the timestamps of the historical radar wind data and the historical operation data extracted in step S7 need to be strictly matched, that is, the radar wind data and the historical operation data corresponding to the same time need to be the same 10 min average of the radar wind data and the historical operation data. If there is a difference between the timestamps of the historical radar wind data and the historical operation data, the accuracy of the power curve obtained finally will be affected.

[0083] S8, data cleaning is performed on the data set N4 obtained in step S7, data in non-normal power generation states such as shutdown, idling, fault, maintenance, start-up and power limitation is removed, and a data set N5 is obtained;

[0084] S9, the data set N5 obtained in step S8 is screened out, and the data set N5 is composed of V H > 0 and e2 is 100%, and the data set N6 is composed of V H converted into a wind speed V D2 at a distance D2 in front of the wind wheel through the transfer function obtained in step S6, and the data set N5 is defined as a data set N7 after conversion;

[0085] S10, according to the size of the wind speed V D2 in the data set N7 obtained in step S9, the wind speed V D2 and the active power in the data set N7 are arranged to obtain a data set N8, and the data in the data set N8 is divided into bins with every 0.5 m / s as a wind speed interval, the average power (μ) and the standard deviation (σ) in each wind speed interval are calculated, the large-range outlier data points with the active power less than μ-3σ and the active power greater than μ+3σ in each wind speed interval are removed, and each sub-wind speed interval is obtained.

[0086] S11, the average of the wind speed V D2 corresponding to each data point in each sub-wind speed interval and the average of the active power are calculated, the wind speed-power data are saved, the wind speed-power curve of the unit in the last 90 days based on the radar wind measurement is obtained through difference fitting, and the wind speed-power curve is drawn in a figure together with the guaranteed power curve of the unit for display.

[0087] In another embodiment of the present application, a wind turbine power curve calculation system based on a machine cabin control wind measurement radar is provided, which can be used to implement the wind turbine power curve calculation method based on the machine cabin control wind measurement radar. Specifically, the wind turbine power curve calculation system based on the machine cabin control wind measurement radar comprises a data module, a test module, a synthesis module, a screening module, a cleaning module, a fitting module, an extraction module, a removal module, a conversion module, an arrangement module and an output module.

[0088] Wherein, the data module, obtains the wind turbine rotor diameter D and the cabin control wind measuring radar wind measuring distance H, and calculates the wind measuring distance D2 for the wind turbine power curve;

[0089] The test module synchronously tests the wind speed information at the wind measuring distance D2 and H in front of the rotor for several days at least by the laser wind radar;

[0090] The synthesis module obtains the average value of the axis projection wind speed at the distance D2 and H in front of the rotor and the average value of the data efficiency in the test period of the laser radar, forms a data set N1, defines the average value of the axis projection wind speed at the distance D2 in front of the rotor in the data set N1 as V D2 , defines the average value of the axis projection wind speed at the distance H in front of the rotor in the data set N1 as V H , defines the average value of the data efficiency at the distance D2 in front of the rotor in the data set N1 as e1, and defines the average value of the data efficiency at the distance H in front of the rotor in the data set N1 as e2;

[0091] The screening module screens the wind measuring data in which V D2 and V H are greater than 0 and the data efficiency is 100% from the data set N1 obtained by the synthesis module to form a data set N2, draws a wind speed scatter plot with V H and V D2 as the horizontal and vertical coordinates respectively in the data set N2, and linearly fits V H and V D2 in the wind speed scatter plot to obtain a straight line L1;

[0092] The cleaning module calculates the distance of each data point in the wind speed scatter plot obtained by the screening module to the straight line L1 to obtain a distance set M, and obtains a data set N3 after cleaning;

[0093] The fitting module linearly fits V H and V D2 in the data set N3 obtained by the cleaning module again as the horizontal and vertical coordinates respectively to obtain the transfer function between V H and V D2 ;

[0094] The extraction module extracts the historical data of the wind turbine in front of 90 days in the running process every 30 days for the wind turbine installed with the control laser radar and forms a data set N4;

[0095] The elimination module performs data cleaning on the data set N4 obtained by the extraction module to eliminate the data in which the unit running state is not normal power generation, and obtains a data set N5;

[0096] The conversion module screens V H in the data set N5 obtained by the elimination module;Data set N6 is composed of data greater than 0 and e2 is 100%, and the V H is converted into the wind speed V at the distance D2 in front of the wind wheel D2 The data set N5 after conversion is defined as N7.

[0097] The arrangement module arranges the wind speed V D2 and the active power in the data set N7 according to the size of the wind speed V D2 in the data set N7 obtained by the conversion module to obtain the data set N8, and the data in the data set N8 is divided into bins with each 0.5 m / s as a wind speed interval, the average value μ and the standard deviation σ of the power in each wind speed interval are calculated to obtain each sub-wind speed interval.

[0098] The output module calculates the average value of the wind speed V D2 corresponding to each data point in each sub-wind speed interval obtained by the arrangement module, the average value of the active power, saves the wind speed-power data, and obtains the wind speed-power curve of the wind turbine within 90 days based on radar wind measurement through difference fitting, and draws it together with the guaranteed power curve of the wind turbine to show in a graph.

[0099] In another embodiment of the present application, a terminal device is provided, which includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, and are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement corresponding method processes or corresponding functions; the processor in the embodiment of the present application can be used for the operation of the wind turbine power curve calculation method based on the nacelle control wind measurement radar, including:

[0100] Obtain the wind turbine rotor diameter D and the nacelle control wind measurement radar wind measurement distance H, calculate the wind measurement distance D2 for the wind turbine power curve; through the laser wind measurement radar, continuously and synchronously test the wind speed information at the wind measurement distance D2 and H distance in front of the rotor for several days; obtain the average value of the axis projection wind speed at the D2 and H distance in front of the rotor and the average value of the data efficiency measured by the laser radar in the test time period to form a data set N1, define the average value of the axis projection wind speed at the D2 distance in front of the rotor in the data set N1 as V D2 , define the average value of the axis projection wind speed at the H distance in front of the rotor in the data set N1 as V H , define the average value of the data efficiency at the D2 distance in front of the rotor in the data set N1 as e1, and define the average value of the data efficiency at the H distance in front of the rotor in the data set N1 as e2; select the wind measurement data in the data set N1 whose V D2 and V H are greater than 0 and the data efficiency is 100% to form a data set N2, draw a wind speed scatter plot with V H and V D2 as the horizontal and vertical coordinates respectively in the data set N2, and perform linear fitting on V H and V D2 in the wind speed scatter plot to obtain a straight line L1; calculate the distance of each data point in the wind speed scatter plot to the straight line L1 to obtain a distance set M, and obtain a data set N3 after cleaning; perform linear fitting again with V H and V D2 as the horizontal and vertical coordinates respectively in the data set N3 to obtain the transfer function between V H and V D2 ; for the wind turbine equipped with the control laser radar, in the running process, extract the historical data of the wind turbine in the previous 90 days every 30 days and form a data set N4; perform data cleaning on the data set N4 to eliminate the data whose unit operation state is not normal power generation to obtain a data set N5; select the data in the data set N5 whose V H is greater than 0 and e2 is 100% to form a data set N6, and convert V H in the data set N6 to the wind speed V D2 at the D2 distance in front of the rotor through the transfer function, and define the data set N5 after conversion as N7; arrange the wind speed V D2 and the active power in the data set N7 according to the size of the wind speed V D2 to obtain a data set N8, and divide the data in the data set N8 into bins with every 0.5 m / s as a wind speed interval, calculate the average value μ and the standard deviation σ of the power in each wind speed interval to obtain each sub wind speed interval; calculate the wind speed V D2The mean value and the active power mean value, save the wind speed-power data and obtain the wind speed-power curve of the wind turbine within 90 days based on the radar wind measurement through the difference fitting, and draw the wind speed-power curve and the guaranteed power curve of the wind turbine in a figure for display.

[0101] In another embodiment of the present application, the present application also provides a storage medium, specifically a computer readable storage medium (Memory), which is a memory device in a terminal device, used for storing programs and data. It can be understood that the computer readable storage medium herein can include a built-in storage medium in the terminal device, and of course can also include an extended storage medium supported by the terminal device. The computer readable storage medium provides a storage space, which stores an operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer readable storage medium herein can be a high-speed RAM memory or a non-volatile memory such as at least one disk memory.

[0102] The one or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to realize the corresponding steps of the wind turbine power curve calculation method based on the nacelle control wind measurement radar in the above-mentioned embodiments; the one or more instructions in the computer readable storage medium are loaded and executed by the processor as follows:

[0103] The wind turbine rotor diameter D and the nacelle control wind measurement radar wind measurement distance H are obtained, and the wind measurement distance D2 for the wind turbine power curve is calculated; the wind speed information at the wind measurement distance D2 and the distance H in front of the rotor is continuously and synchronously tested for several days by the laser wind measurement radar; the mean value of the axis projection wind speed at the distance D2 and the distance H in front of the rotor measured by the laser radar in the test period and the mean value of the data availability are obtained to form a data set N1, the mean value of the axis projection wind speed at the distance D2 in front of the rotor in the data set N1 is defined as V D2 , the mean value of the axis projection wind speed at the distance H in front of the rotor in the data set N1 is defined as V H , the mean value of the data availability at the distance D2 in front of the rotor in the data set N1 is defined as e1, and the mean value of the data availability at the distance H in front of the rotor in the data set N1 is defined as e2; the wind measurement data in which V D2 and V H are greater than 0 and the data availability is 100% in the data set N1 are screened to form a data set N2, and the wind speed scatter plot is drawn with V H and V D2 as the horizontal coordinate and the vertical coordinate respectively, and V H and VD2 A linear fitting is performed to obtain a straight line L1; the distance of each data point in the wind speed scatter plot to the straight line L1 is calculated to obtain a distance set M, and after cleaning, a data set N3 is obtained; V H and V D2 are taken as the abscissa and the ordinate respectively, linear fitting is performed again to obtain the transfer function between V H and V D2 ; for the wind turbine equipped with the control laser radar, during operation, historical data of the wind turbine in the previous 90 days are extracted every 30 days and composed into a data set N4; data set N4 is subjected to data cleaning, and data in which the operation state of the wind turbine is not normal power generation is removed to obtain a data set N5; data in which V H is greater than 0 and e2 is 100% in data set N5 is screened to compose a data set N6, and V H in data set N6 is converted into the wind speed V D2 at the distance D2 in front of the wind wheel through the transfer function; the data set after conversion of data set N5 is defined as N7; according to the size of the wind speed V D2 in data set N7, the wind speed V D2 and the active power in data set N7 are arranged to obtain a data set N8, and the data in data set N8 is divided into bins with every 0.5 m / s as a wind speed interval, the average value μ and the standard deviation σ of the power in each wind speed interval are calculated to obtain each sub-wind speed interval; the average value of the wind speed V D2 and the average value of the active power corresponding to each data point in each sub-wind speed interval are calculated, the wind speed-power data are saved, and the wind speed-power curve of the wind turbine in 90 days based on radar wind measurement is obtained through difference fitting, and is plotted in a figure together with the guaranteed power curve of the wind turbine for display.

[0104] To make the objects, technical solutions, and advantages of the embodiments of the present application clearer, the following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by a person of ordinary skill in the art without creative work on the basis of the embodiments in the present application belong to the scope of protection of the present application.

[0105] The following is a specific application example of the present application on a certain wind turbine:

[0106] Please refer to Figure 2 , VH and V D2 Linear fitting is performed to obtain a straight line L1.

[0107] Referring to Figure 3 , the quartile method is used to clean the data set N2, and linear fitting is performed to obtain V H and V D2 , the transfer function between V H and V D2 is fitted to obtain V D2＝ 1.036V H + 0.526.

[0108] Referring to Figure 4 , data cleaning is performed on the data set N4, and data of non-normal power generation such as shutdown, idling, fault, maintenance, start-up, and limited power of the unit is removed to obtain a data set N5. In this figure, the gray points are the non-normal power generation data points removed, and the black points are the data points in the data set N5.

[0109] Referring to Figure 5 , the unit power curve obtained after the data set N8 is cleaned of a large range of outlier data points.

[0110] In summary, the wind turbine power curve calculation method and system based on the nacelle control wind measurement radar of the application convert the wind measurement data of the laser radar for unit control into wind measurement data meeting the distance requirements of the power curve test, so as to further obtain the real power curve and power generation performance of the unit, and the wind measurement data of the control wind measurement radar is also fully utilized. The power curve obtained by the application is more in line with the real situation of the unit than the power curve obtained by the traditional anemometer data, and has higher reference value.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit. In addition, the specific names of the functional units and modules are only for easy distinction, and do not limit the protection scope of the application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0112] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in a certain embodiment can be referred to the relevant description of other embodiments.

[0113] Those skilled in the art can appreciate that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0114] In the embodiments provided by the present application, it should be understood that the disclosed apparatus / terminal and method can be implemented in other ways. For example, the apparatus / terminal embodiments described above are merely schematic, for example, the division of the modules or units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0115] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment.

[0116] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0117] The integrated module / unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the computer-readable medium can include or exclude contents according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0118] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The functions specified in one or more flows and / or blocks

[0119] These computer program instructions can also be stored in a computer-readable memory capable of instructing the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The functions specified in one or more flows and / or blocks

[0120] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable data processing devices to generate a computer implemented process, so that the instructions executed on the computer or other programmable data processing devices provide a process for implementing the functions specified in the flowchart Figure 1 one flow or multiple flows and / or the functions specified in the block Figure 1 one block or multiple blocks.

[0121] The above is only to illustrate the technical idea of the present application, and cannot limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A method for calculating power curve of a wind turbine based on nacelle control wind finding radar, characterized in that, The method comprises the following steps: S1, obtaining the wind wheel diameter D of the wind turbine and the wind measurement distance H of the nacelle control wind measurement radar, and calculating the wind measurement distance D2 for the wind turbine power curve; S2, continuously and synchronously testing the wind speed information at the wind measurement distance D2 and H in front of the wind wheel for several days through the laser wind measurement radar; if the nacelle control wind measurement radar can directly measure the wind speed information at the wind measurement distance D2 and H in front of the wind wheel through setting, the nacelle control wind measurement radar is set to continuously and synchronously test the wind speed information at the wind measurement distance D2 and H in front of the wind wheel for at least 60 days; if the nacelle control wind measurement radar cannot simultaneously measure the wind speed at the wind measurement distance D2 and H in front of the wind wheel through setting, a laser wind measurement radar suitable for the performance calculation of the wind turbine is installed on the nacelle to continuously and synchronously test the wind speed information at the wind measurement distance D2 and H in front of the wind wheel for at least 60 days; S3, obtaining the average of the axis-projected wind speed at the D2 and H distances in front of the wind wheel measured by the laser radar in the test time period and the average of the data validity rate to form a data set N1, defining the average of the axis-projected wind speed at the D2 distance in front of the wind wheel in the data set N1 as V D2 , defining the average of the axis-projected wind speed at the H distance in front of the wind wheel in the data set N1 as V H , defining the average of the data validity rate at the D2 distance in front of the wind wheel in the data set N1 as e1, and defining the average of the data validity rate at the H distance in front of the wind wheel in the data set N1 as e2, the axis-projected wind speed at the D2 and H distances in front of the wind wheel, the data validity rate, the axis-projected wind speed at the D2 distance in front of the wind wheel in N1, the axis-projected wind speed at the H distance in front of the wind wheel in N1, the data validity rate at the D2 distance in front of the wind wheel in N1, and the data validity rate at the H distance in front of the wind wheel in N1 are all 10 min average data; S4. Filter V from dataset N1 obtained in step S3. D2 and V H Data set N2 consists of wind measurement data where all values ​​are greater than 0 and the data validity rate is 100%. Data set N2 contains V... H and V D2 Plot wind speed scatter plots on the x and y axes respectively, and analyze the V values ​​in the wind speed scatter plots. H and V D2 Perform linear fitting to obtain the straight line L1; S5, calculating the distance of each data point in the wind speed scatter diagram obtained in step S4 to the straight line L1 to obtain a distance set M, and obtaining a data set N3 after cleaning; S6. V in data set N3 from step S5 H and V D2 are linearly fitted again, obtaining a transfer function between V H and V D2 ; S7, for the wind turbine equipped with the control laser radar, in the operation process, every 30 days, the historical data of the wind turbine in the previous 90 days is extracted and composed into a data set N4, the corresponding radar wind measurement data and historical operation data at the same time are the average values of the radar wind measurement data and historical operation data within the same 10 min, and the historical data includes 10 min level radar wind measurement data V H , e2, and 10 min level unit state, active power, rotor speed, blade pitch angle and other unit operation data; S8, performing data cleaning on the data set N4 obtained in step S7 to remove data in a non-normal power generation state of the wind turbine to obtain a data set N5; S9, the data set N5 obtained in the screening step S8 is filtered to obtain a data set N6 H The data set N6 is converted into a wind speed V at a distance D2 in front of the wind wheel H D2 The data set N7 is obtained by converting the data set N5​ S10, the wind speed V in the data set N7 obtained according to step S9 D2 The size of the wind speed V in the data set N7 D2 The data set N8 is arranged according to the wind speed V and the active power, and the data in the data set N8 is divided into bins with every 0.5 m / s as a wind speed interval, the average value μ and the standard deviation σ in each wind speed interval are calculated to obtain each sub wind speed interval; S11、Calculate the wind speed V corresponding to each data point in each sub-wind speed interval obtained in step S10 D2 The mean value and the active power mean value are saved, and the wind speed-power data are fitted by difference to obtain the wind speed-power curve of the unit within 90 days based on radar wind measurement, which is plotted in a graph together with the unit guaranteed power curve for display.

2. The nacelle control wind lidar based wind turbine power curve calculation method according to claim 1, characterized in that, In step S1, the wind turbine power curve uses the wind measurement distance D2 in the range of 2D-4D.

3. The nacelle control wind lidar based wind turbine power curve calculation method according to claim 1, characterized in that, In step S5, the quartile method is used to clean the data set N2 according to the size of the distance set M, and the cleaned data set is defined as N3.

4. The nacelle control wind lidar based wind turbine power curve calculation method of claim 1, wherein, In step S6, V H and V D2 the transfer function between V V D2 =aV H +b where a is the slope of the transfer function between V H and V D2 and b is the intercept of the transfer function between V H and V D2 .

5. The nacelle control wind lidar based wind turbine power curve calculation method according to claim 1, characterized in that, In step S8, the non-normal power generation data includes shutdown, idling, fault, maintenance, start-up and limited power data.

6. The nacelle control wind lidar based wind turbine power curve calculation method according to claim 1, characterized in that, In step S10, large-range outlier data points with active power less than μ-3σ and active power greater than μ+3σ in each wind speed interval are removed to obtain each sub-wind speed interval.

7. A wind turbine power curve calculation system based on nacelle control wind finding radar, characterized in that, The method comprises the following steps: The data module obtains the wind wheel diameter D of the wind turbine and the wind measurement distance H of the nacelle control wind measurement radar, and calculates the wind measurement distance D2 for the wind turbine power curve; The test module continuously and synchronously tests the wind speed information at the wind measurement distance D2 and H in front of the wind wheel for several days through the laser wind measurement radar; The synthetic module obtains the average of the axis-projected wind speed at the D2 and H distances in front of the wind wheel and the average of the data availability measured by the laser radar in the test module test period to form a data set N1, defines the average of the axis-projected wind speed at the D2 distance in front of the wind wheel in the data set N1 as V D2 , defines the average of the axis-projected wind speed at the H distance in front of the wind wheel in the data set N1 as V H , defines the average of the data availability at the D2 distance in front of the wind wheel in the data set N1 as e1, and defines the average of the data availability at the H distance in front of the wind wheel in the data set N1 as e2, the axis-projected wind speed at the D2 and H distances in front of the wind wheel, the data availability, the axis-projected wind speed at the D2 distance in front of the wind wheel in N1, the axis-projected wind speed at the H distance in front of the wind wheel in N1, the data availability at the D2 distance in front of the wind wheel in N1, and the data availability at the H distance in front of the wind wheel in N1 are all 10 min average data; The screening module screens the V D2 and V H in the data set N1 obtained by the synthesis module, and the data set N2 is composed of the wind measurement data whose V H and V D2 are greater than 0 and whose data efficiency is 100%; the wind speed scatter plot is drawn with V H and V D2 as the horizontal and vertical coordinates respectively, and linear fitting is performed on V H and V D2 in the wind speed scatter plot to obtain a straight line L1. The cleaning module calculates the distance of each data point in the wind speed scatter diagram obtained by the screening module to the straight line L1 to obtain a distance set M, and obtains a data set N3 after cleaning; Fitting module to the data set N3 to obtain V H and V D2 respectively abscissa and ordinate again linearly fitted to obtain the transfer function between V H and V D2 ​ The extraction module extracts historical data of the wind turbine in the previous 90 days every 30 days during operation to form a data set N4, and the corresponding radar wind measurement data and historical operation data at the same time are the average values of the radar wind measurement data and historical operation data within 10 minutes, and the historical data include 10-minute radar wind measurement data V H , e2, and 10-minute unit operation data such as unit state, active power, rotor speed, blade pitch angle, etc. The removal module performs data cleaning on the data set N4 obtained by the extraction module to remove data in a non-normal power generation state of the wind turbine to obtain a data set N5; and The method comprises the following steps: The conversion module converts the V in the data set N5 obtained by the screening and rejection module into the wind speed V at the distance D2 in front of the wind wheel H The data set N6 is composed of the data greater than 0 and e2 being 100%, and the V in the data set N6 is converted into the wind speed V at the distance D2 in front of the wind wheel through the transfer function obtained by the fitting module H The conversion module converts the V in the data set N5 obtained by the screening and rejection module into the wind speed V at the distance D2 in front of the wind wheel D2 The data set N7 is defined as the data set after the conversion of the data set N5 The permutation module, based on the wind speed V in dataset N7 obtained from the transformation module... D2 The size of the wind speed V in dataset N7 D2 The dataset N8 is obtained by arranging the active power and the data in the dataset. The dataset N8 is divided into compartments with each wind speed interval being 0.5 m / s. The average power μ and standard deviation σ in each wind speed interval are calculated to obtain each sub-wind speed interval. The output module calculates the wind speed V corresponding to each data point in each sub-wind speed interval obtained by the arrangement module D2 The mean value and the active power mean value are saved, and the wind speed-power curve of the unit within 90 days based on radar wind measurement is obtained by difference fitting, and it is plotted in a graph with the unit guaranteed power curve to show.

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