CN116498502A - Wind turbine generator power curve calculation method and system based on cabin control wind-finding radar - Google Patents
Wind turbine generator power curve calculation method and system based on cabin control wind-finding radar Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
- F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
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Abstract
The invention discloses a wind turbine generator power curve calculation method and system based on a cabin control wind measuring radar. The obtained power curve of the wind turbine is more real and reliable, the power curve distortion caused by inaccurate transfer functions of the wind meter of the engine room or faults of the wind meter is effectively avoided, the power generation performance of the wind turbine is truly reflected, meanwhile, radar wind measurement data can be fully utilized, and the waste of resources is avoided.
Description
Technical Field
The invention belongs to the technical field of wind power generation, and particularly relates to a wind turbine generator power curve calculation method and system based on a cabin control wind-finding radar.
Background
According to the wind power theory, the airflow of wind can be distorted before reaching the wind wheel, the wind speed can be reduced, and the kinetic energy of wind can be converted into pressure potential energy. In order to ensure the accuracy of the power curve of the wind turbine, the wind speed at a certain distance in front of the wind wheel is usually selected as a reference, and the GB/T18451.2 power characteristic test of the wind turbine sets that the distance from the wind measuring equipment to the wind turbine is 2D-4D, and 2.5D is recommended, wherein D is the diameter of the wind wheel.
The power curve of a wind turbine can generally be obtained by two methods.
The wind speed of the wind meter of the machine set is obtained by processing and fitting machine set operation data such as wind speed of a cabin anemometer, active power and the like, wherein the wind speed of the wind meter of the machine set is obtained by converting an original measured current signal of the wind meter of the machine set into a wind speed at a distance of 2D-4D in front of a wind wheel required by a standard through transfer function processing, but the accuracy of the transfer function of the wind meter of the machine set is to be verified, and in addition, the wind meter of the machine set is generally influenced by wake flow and inertia to reduce the accuracy of the measured wind speed, so that the accuracy of a machine set power curve obtained based on the data of the wind meter of the machine set is reduced.
And the other is to measure the wind speed at a certain distance between 2D and 4D in front of the wind wheel by wind measuring equipment such as a wind measuring laser radar and the like according to standard regulation, and process and fit operation data such as active power of the unit to obtain a power curve of the unit. However, the test method has high cost and is not suitable for long-time test and evaluation in the running process of the unit.
In addition, a plurality of wind turbine generators are installed with cabin control wind measuring radars, wind speed information at a fixed distance in front of a wind wheel is measured in real time, and the wind turbine generators are involved in the control of the wind turbine generators to improve the control effect of the wind turbine generators. The laser wind-finding radar for unit control is generally short in wind-finding distance, lower in cost than the laser radar for power curve test, and has a space for further development and utilization.
Disclosure of Invention
The invention aims to solve the technical problems of providing a wind turbine generator power curve calculation method and a wind turbine generator power curve calculation system based on a cabin control wind-finding radar aiming at the defects in the prior art, and the method and the system are used for solving the technical problems of power curve distortion caused by inaccurate transfer functions of an anemometer or failure of the anemometer.
The invention adopts the following technical scheme:
a wind turbine generator power curve calculation method based on cabin control wind-finding radar comprises the following steps:
s1, acquiring the diameter D of a wind wheel of a wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 ；
S2, continuously and synchronously testing the wind wheel front wind measuring distance D for a plurality of days at least through a cabin wind measuring laser radar 2 And wind speed information at the H distance;
s3, obtaining the front D of the wind wheel measured by the laser radar in the test time period of the step S2 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 ；
S4, screening the data set N obtained in the step S3 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Wind speed is plotted for the abscissa and ordinate respectively Scatter plot and for V in wind speed scatter plot H And V D2 Performing linear fitting to obtain a straight line L 1 ；
S5, calculating a straight line L from each data point in the wind speed scatter diagram obtained in the step S4 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 ；
S6, obtaining a data set N in the step S5 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
s7, for the wind turbine generator set provided with the control laser radar, in the operation process, extracting historical data of the wind turbine generator set for the first 90 days every 30 days and forming a data set N 4 ；
S8, regarding the data set N obtained in the step S7 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 ；
S9, screening the data set N obtained in the step S8 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is processed through the transfer function obtained in the step S6 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
S10, a data set N obtained according to the step S9 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Dividing the data into bins, and calculating the average power mu and standard deviation sigma in each wind speed interval to obtain each sub-wind speed interval;
s11, calculating the wind speed V corresponding to each data point in each sub wind speed interval obtained in the step S10 D2 The average value and the active power average value, the wind speed-power data are saved, a wind speed power curve based on radar wind measurement within 90 days of the unit is obtained through difference fitting, and the wind speed power curve is ensured with the unitLine drawing is shown in a single figure.
Specifically, in step S1, the wind distance D for the power curve of the wind turbine generator is measured 2 The distance of (2) is 2D-4D.
Specifically, in step S2, if the nacelle control wind-finding radar can directly measure the front D of the wind wheel by setting 2 And the wind speed information at the H distance, setting a wind measuring distance D in front of the wind wheel for at least 60 days by using a cabin control wind measuring radar in continuous synchronous test 2 And wind speed information at the H distance. If the cabin control wind-finding radar can not simultaneously measure the front D of the wind wheel through arrangement 2 And the wind speed at the distance H, installing a laser wind measuring radar suitable for unit performance calculation on the engine room, and continuously and synchronously testing the front D of the wind wheel for at least 60 days 2 And wind speed information at the H distance.
Specifically, in step S3, the wind wheel is at the front D 2 And the projection wind speed of the axis at the distance H, the data efficiency and N 1 Front D of middle wind wheel 2 Projecting wind speed from axis at distance N 1 Axis projection wind speed at H distance in front of middle wind wheel, N 1 Front D of middle wind wheel 2 Data efficiency at distance and N 1 The data effective rate of the distance H in front of the middle wind wheel is 10min average data.
Specifically, in step S5, the data set N is mapped according to the size of the distance set M by using a quartile method 2 Cleaning, namely defining a cleaned data set as N 3 。
Specifically, in step S6, V H And V D2 The transfer function between them is:
V D2 ＝aV H +b
wherein a is V H And V D2 Slope of transfer function between, b is V H And V D2 An intercept of the transfer function between.
Specifically, in step S7, the radar wind measurement data and the historical operation data corresponding to the same time line are the same average value of the radar wind measurement data and the historical operation data within 10min, and the historical data includes 10 min-level radar wind measurement data V H 、e 2 10min stage unit state, active power,And the running data of the unit such as the rotating speed of the wind wheel, the variable pitch angle of the blades and the like.
Specifically, in step S8, the abnormal power generation data includes shutdown, idling, malfunction, maintenance, startup, and power limit data.
Specifically, in step S10, large-scale outlier data points with active power smaller than μ -3σ and active power larger than μ+3σ in each wind speed interval are removed, so as to obtain each sub wind speed interval.
In a second aspect, an embodiment of the present invention provides a wind turbine generator power curve calculation system based on a nacelle control wind-finding radar, including:
the data module is used for acquiring the diameter D of a wind wheel of the wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 ；
The testing module is used for continuously and synchronously testing the wind measuring distance D in front of the wind wheel for at least a plurality of days through the laser wind measuring radar 2 And wind speed information at the H distance;
the synthesis module is used for obtaining the front D of the wind wheel measured by the laser radar in the test time period of the test module 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 ；
The screening module screens the data set N obtained by the synthesis module 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 ；
The cleaning module is used for calculating the straight line L from each data point in the wind speed scatter diagram obtained by the screening module 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 ；
Fitting module to obtain data set N by cleaning module 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
the extraction module is used for extracting historical data of the wind turbine generator set 90 days before every 30 days in the running process for the wind turbine generator set provided with the control laser radar and forming a data set N 4 ；
The rejecting module is used for rejecting the data set N obtained by the extracting module 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 ；
The conversion module screens the data set N obtained by the rejection module 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is obtained through the transfer function obtained by the fitting module 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
The arrangement module is used for obtaining a data set N according to the conversion module 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Dividing the data into bins, and calculating the average power mu and standard deviation sigma in each wind speed interval to obtain each sub-wind speed interval;
the output module is used for calculating the wind speed V corresponding to each data point in each sub wind speed interval obtained by the arrangement module D2 The average value and the active power average value, the wind speed-power data are saved, a wind speed power curve based on radar wind measurement within 90 days of the unit is obtained through difference fitting, and the wind speed power curve and the unit guarantee power curve are drawn in a graph for carrying outAnd (5) displaying.
Compared with the prior art, the invention has at least the following beneficial effects:
according to the wind turbine generator power curve calculation method based on the cabin control wind measuring radar, laser radar is adopted to synchronously test and collect the long-distance wind speed in front of a wind wheel meeting the power curve test requirement of the wind turbine and the wind speed in front of a wind wheel for the control of the wind turbine, then two-wheel cleaning and fitting are carried out on radar wind measuring data in two distances to obtain a transfer function between two wind measuring data, so that the short-distance radar wind measuring data for the control of the wind turbine is converted into incoming wind speed meeting the power curve test requirement, and the cabin anemometer data is replaced to be cleaned and fitted with the running data of the wind turbine generator, so that the real power curve of the wind turbine generator is obtained. The obtained power curve of the wind turbine is more real and reliable, the power curve distortion caused by inaccurate transfer functions of the wind meter of the engine room or faults of the wind meter can be effectively avoided, the power generation performance of the wind turbine is truly reflected, meanwhile, radar wind measurement data can be fully utilized, and the waste of resources is avoided.
Further, wind measuring distance D for power curve of wind turbine generator 2 Too close or too far from the wind turbine is not desirable because the measured wind speed too close to it is affected by the airflow distortion and the correlation between the measured wind speed and the output power will decrease too far from it. Recommended wind distance D for wind turbine generator power curve 2 2D to 4D is preferable, and 2.5D is generally preferable.
Furthermore, the data are all average values of 10min, and the data granularity can ensure the accuracy of the result while reducing the calculated amount.
Further, the data points far away from the straight line L1 are removed through a statistical analysis method of a quartile method, so that the data fitting effect is improved.
Further, the meaning V obtained H And meaning V D2 Transfer function between, can be V H Conversion to V meeting the test requirements of the power curve D2 。
Furthermore, the time stamps of the historical radar wind measurement data and the historical operation data need to be strictly matched, that is, the radar wind measurement data and the historical operation data corresponding to the same time line need to be the average value of the radar wind measurement data and the historical operation data within the same 10 min. 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 is affected.
Further, the abnormal power generation data comprise data of the wind turbine generator in abnormal power generation states of the wind turbine generator in shutdown, idling, fault, overhaul, starting, power limiting and the like.
Further, the Laiyida criterion (3 sigma criterion) is adopted to remove large-scale outlier data in the wind speed power scatter diagram, namely, data with active power smaller than mu-3 sigma and active power larger than mu+3 sigma in each wind speed interval are removed.
It will be appreciated that the advantages of the second aspect may be found in the relevant description of the first aspect, and will not be described in detail herein.
In summary, the laser radar wind measurement data for controlling the unit is converted into the wind measurement data meeting the requirement of the power curve test distance, so that the real power curve and the power generation performance of the unit are further obtained, and the wind measurement data of the wind measurement radar are controlled to be fully utilized; compared with the traditional power curve obtained based on anemometer data, the obtained power curve is more in line with the real situation of the unit, and the reference value is higher.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a data set N 2 Middle V H And V D2 Performing linear fitting to obtain a schematic diagram of a straight line L1;
FIG. 3 is a block diagram of a quartile pair dataset N 2 Fitting linear fitting after washing to obtain V H And V D2 Schematic of transfer function between;
FIG. 4 is a data set N 4 Performing a data cleaning schematic;
FIG. 5 is a dataset N 8 After cleaning off large-scale outlier data pointsAnd (5) obtaining a schematic diagram of the power curve of the unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it will be understood that the terms "comprises" and "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. 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 be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.
It should be understood that although the terms first, second, third, etc. may be used to describe the preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish one preset range from another. For example, a first preset range may also be referred to as a second preset range, and similarly, a second preset range may also be referred to as a first preset range without departing from the scope of embodiments of the present invention.
Depending on the context, the word "if" as used herein may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to detection". Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.
Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the accompanying drawings. The figures are not drawn to scale, wherein certain details are exaggerated for clarity of presentation and may have been omitted. The shapes of the various regions, layers and their relative sizes, positional relationships shown in the drawings are merely exemplary, may in practice deviate due to manufacturing tolerances or technical limitations, and one skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions as actually required.
Referring to fig. 1, the method for calculating the power curve of the wind turbine generator based on the cabin control wind-finding radar of the invention comprises the following steps:
s1, obtaining the diameter D of a wind wheel of a wind turbine generator, controlling wind measuring distance H of a wind measuring radar of a cabin, and calculating to obtain the wind measuring distance D which can be used for a power curve of the wind turbine generator 2 ；
Wherein D is 2 Should be within a range of 2D and 4D distances, typically 2.5D is chosen.
S2, continuously and synchronously testing the front wind measuring distance D of the wind wheel for 60 days at least through a cabin wind measuring radar 2 And wind speed information at the H distance;
if the cabin control wind-finding radar directly measures the front D of the wind wheel through arrangement 2 And the wind speed information at the H distance, setting a wind measuring distance D in front of the wind wheel for at least 60 days by using a cabin control wind measuring radar in continuous synchronous test 2 And wind speed information at the H distance. If the cabin controls the wind-finding radar;
the nacelle is set upControlling wind measuring radar to continuously and synchronously test wind wheel front wind measuring distance D for 60 days at least 2 And wind speed information at the H distance. If the cabin control wind-finding radar can not simultaneously measure the front D of the wind wheel through arrangement 2 And the wind speed at the distance H, installing a laser wind measuring radar suitable for unit performance calculation on the engine room, and continuously and synchronously testing the front D of the wind wheel for at least 60 days 2 And wind speed information at the H distance.
S3, obtaining the front D of the wind wheel measured by the laser radar in the test time period of the step S2 2 And forming a data set N by using the 10min average value of the axis projection wind speed at the H distance and the 10min average value of the data effective rate 1 Definition of N 1 Front D of middle wind wheel 2 The mean value of the projection wind speed of the axis at the distance is V in 10min D2 Definition of N 1 The mean value of 10min of the projected wind speed of the axis at the position of H distance in front of the middle wind wheel is V H Definition of N 1 Front D of middle wind wheel 2 The average value of the effective rate of the data at the distance is e in 10min 1 Definition of N 1 The effective rate of the data at the distance H in front of the middle wind wheel is 10min with the average value of e 2 ；
S4, screening the data set N obtained in the step S3 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 V in (1) H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and obtaining V in the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 ；
S5, calculating a straight line L from each data point in the wind speed scatter diagram obtained in the step S4 1 Obtaining a distance set M, and adopting a quartile method to pair the data set N according to the size of the distance set M 2 Further cleaning is performed, and the cleaned data set is defined as N 3 ；
S6, the cleaned data set N obtained in the step S5 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
V H and V D2 The transfer function between them is:
V D2 ＝aV H +b
wherein a is V H And V D2 Slope of transfer function between, b is V H And V D2 An intercept of the transfer function between.
S7, for the wind turbine generator set provided with the control laser radar, in the operation process, extracting historical data of the wind turbine generator set for the first 90 days every 30 days and forming a data set N 4 ；
The historical data at least comprises 10 min-level radar wind measurement data V H 、e 2 And unit operation data such as 10 min-level unit state, active power, wind wheel rotating speed, blade pitch angle and the like.
It should be noted that, the time stamps of the historical radar wind measurement data and the historical operation data extracted in the step S7 need to be strictly matched, that is, the radar wind measurement data and the historical operation data corresponding to the same time line need to be the average value of the radar wind measurement data and the historical operation data within the same 10 min. 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 is affected.
S8, regarding the data set N obtained in the step S7 4 Data cleaning is carried out, and abnormal power generation data such as shutdown, idling, fault, overhaul, starting, power limiting and the like are removed from the running state of the unit to obtain a data set N 5 ；
S9, screening out the data set N obtained in the step S8 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is processed through the transfer function obtained in the step S6 6 V in (1) H Is converted into the front D of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
S10, a data set N obtained according to the step S9 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval pair dataSet N 8 Dividing the data into bins, calculating the average power (mu) and standard deviation (sigma) in each wind speed interval, and removing large-range outlier data points with active power smaller than mu-3 sigma and active power larger than mu+3 sigma in each wind speed interval to obtain each sub-wind speed interval;
S11, calculating the wind speed V corresponding to each data point in each sub-wind speed interval in the step S10 D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within the last 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
In still another embodiment of the present invention, a wind turbine power curve calculation system based on a cabin control wind-finding radar is provided, where the system can be used to implement the wind turbine power curve calculation method based on a cabin control wind-finding radar, and specifically, the wind turbine power curve calculation system based on a cabin control wind-finding radar includes a data module, a test module, a synthesis module, a screening module, a cleaning module, a fitting module, an extraction module, a rejection module, a conversion module, an arrangement module, and an output module.
The data module is used for acquiring the diameter D of a wind wheel of the wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 ；
The testing module is used for continuously and synchronously testing the wind measuring distance D in front of the wind wheel for at least a plurality of days through the laser wind measuring radar 2 And wind speed information at the H distance;
the synthesis module is used for obtaining the front D of the wind wheel measured by the laser radar in the test time period of the test module 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 ；
The screening module screens the data set N obtained by the synthesis module 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 ；
The cleaning module is used for calculating the straight line L from each data point in the wind speed scatter diagram obtained by the screening module 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 ；
Fitting module to obtain data set N by cleaning module 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
the extraction module is used for extracting historical data of the wind turbine generator set 90 days before every 30 days in the running process for the wind turbine generator set provided with the control laser radar and forming a data set N 4 ；
The rejecting module is used for rejecting the data set N obtained by the extracting module 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 ；
The conversion module screens the data set N obtained by the rejection module 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is obtained through the transfer function obtained by the fitting module 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
The arrangement module is used for obtaining a data set N according to the conversion module 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And the active power are arranged to obtain dataSet N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Dividing the data into bins, and calculating the average power mu and standard deviation sigma in each wind speed interval to obtain each sub-wind speed interval;
the output module is used for calculating the wind speed V corresponding to each data point in each sub wind speed interval obtained by the arrangement module D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
In yet another embodiment of the present invention, a terminal device is provided, the terminal device including a processor and a memory, the memory for storing a computer program, the computer program including program instructions, the processor for executing the program instructions stored by the computer storage medium. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., which are the computational core and control core of the terminal adapted to implement one or more instructions, in particular to load and execute one or more instructions to implement the corresponding method flow or corresponding functions; the processor according to the embodiment of the invention can be used for the operation of a wind turbine generator power curve calculation method based on a cabin control wind-finding radar, and comprises the following steps:
obtaining the diameter D of a wind wheel of a wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 The method comprises the steps of carrying out a first treatment on the surface of the Wind-measuring distance D in front of wind wheel for at least continuously and synchronously testing for several days by laser wind-measuring radar 2 And wind speed information at the H distance; obtaining the front D of the wind wheel measured by the laser radar in the test time period 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data setN 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 The method comprises the steps of carrying out a first treatment on the surface of the Screening data set N 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 The method comprises the steps of carrying out a first treatment on the surface of the Calculating each data point in the wind speed scatter diagram to a straight line L 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 The method comprises the steps of carrying out a first treatment on the surface of the In data set N 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween; for the wind turbine generator set provided with the control laser radar, in the operation process, historical data of the wind turbine generator set, which is 90 days before each 30 days is extracted, are formed into a data set N 4 The method comprises the steps of carrying out a first treatment on the surface of the For data set N 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 The method comprises the steps of carrying out a first treatment on the surface of the Screening data set N 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is transferred through the transfer function 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 The method comprises the steps of carrying out a first treatment on the surface of the From dataset N 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Data are divided into bins, and the average power mu and standard deviation in each wind speed interval are calculatedSigma, obtaining each sub wind speed interval; calculating the wind speed V corresponding to each data point in each sub wind speed interval D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
In a further embodiment of the present invention, the present invention also provides a storage medium, in particular, a computer readable storage medium (Memory), which is a Memory device in a terminal device, for storing programs and data. It will be appreciated that the computer readable storage medium herein may include both a built-in storage medium in the terminal device and an extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also stored in the memory space are one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. The computer readable storage medium may be a high-speed RAM Memory or a Non-Volatile Memory (Non-Volatile Memory), such as at least one magnetic disk Memory.
One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the respective steps of the wind turbine power curve calculation method according to the above embodiments with respect to controlling a wind lidar based on a nacelle; one or more instructions in a computer-readable storage medium are loaded by a processor and perform the steps of:
Obtaining the diameter D of a wind wheel of a wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 The method comprises the steps of carrying out a first treatment on the surface of the Wind-measuring distance D in front of wind wheel for at least continuously and synchronously testing for several days by laser wind-measuring radar 2 And wind speed information at the H distance; obtaining the front D of the wind wheel measured by the laser radar in the test time period 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 The method comprises the steps of carrying out a first treatment on the surface of the Screening data set N 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 The method comprises the steps of carrying out a first treatment on the surface of the Calculating each data point in the wind speed scatter diagram to a straight line L 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 The method comprises the steps of carrying out a first treatment on the surface of the In data set N 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween; for the wind turbine generator set provided with the control laser radar, in the operation process, historical data of the wind turbine generator set, which is 90 days before each 30 days is extracted, are formed into a data set N 4 The method comprises the steps of carrying out a first treatment on the surface of the For data set N 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 The method comprises the steps of carrying out a first treatment on the surface of the Screening data set N 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is transferred through the transfer function 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 The method comprises the steps of carrying out a first treatment on the surface of the From dataset N 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Data are divided into bins, and the average power mu and standard deviation in each wind speed interval are calculatedSigma, obtaining each sub wind speed interval; calculating the wind speed V corresponding to each data point in each sub wind speed interval D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following is a specific application example of the invention on a certain wind turbine generator set:
referring to FIG. 2, data set N 2 Middle V H And V D2 And performing linear fitting to obtain a straight line L1.
Referring to FIG. 3, a quartile pair is shown for data set N 2 Fitting linear fitting after washing to obtain V H And V D2 Transfer function between the two, gray scattered points in the figure are cleaned scattered points, and a data set consisting of black scattered points is N 3 Embodiment N 3 V in (1) H And V D2 Fitting to obtain a transfer function of V D2＝ 1.036V H +0.526。
Referring to FIG. 4, for data set N 4 Data cleaning is carried out, and abnormal power generation data such as shutdown, idling, fault, overhaul, starting, power limiting and the like are removed from the running state of the unit to obtain a data set N 5 . The gray points in the figure are the abnormal hair which is removedElectrical data points, black points are the remaining data set N 5 Is included.
Referring to FIG. 5, data set N 8 And cleaning out the unit power curve obtained after a large range of outlier data points.
In summary, according to the wind turbine generator power curve calculation method and system based on the cabin control wind-finding radar, the laser radar wind-finding data used for the control of the wind turbine generator are converted into the wind-finding data meeting the requirement of the power curve test distance, so that the real power curve and the power generation performance of the wind turbine generator are further obtained, and the wind-finding data of the control wind-finding radar are fully utilized. Compared with the traditional power curve obtained based on anemometer data, the power curve obtained by the method provided by the invention is more in line with the real situation of the unit, and has higher reference value.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the apparatus/terminal embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RandomAccess Memory, RAM), an electrical carrier wave signal, a telecommunications signal, a software distribution medium, etc., it should be noted that the computer readable medium may contain content that is appropriately increased or decreased according to the requirements of jurisdictions and patent practices, such as in certain jurisdictions, according to the jurisdictions and patent practices, the computer readable medium does not contain electrical carrier wave signals and telecommunications signals.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above is only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by this, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. The wind turbine generator power curve calculation method based on the cabin control wind-finding radar is characterized by comprising the following steps of:
s1, acquiring the diameter D of a wind wheel of a wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 ；
S2, continuously and synchronously testing the wind measuring distance D in front of the wind wheel for at least a plurality of days through a laser wind measuring radar 2 And wind speed information at the H distance;
s3, obtaining the front D of the wind wheel measured by the laser radar in the test time period of the step S2 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 Data effective rate of H distance in front of middle wind wheelMean value of e 2 ；
S4, screening the data set N obtained in the step S3 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 ；
S5, calculating a straight line L from each data point in the wind speed scatter diagram obtained in the step S4 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 ；
S6, obtaining a data set N in the step S5 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
s7, for the wind turbine generator set provided with the control laser radar, in the operation process, extracting historical data of the wind turbine generator set for the first 90 days every 30 days and forming a data set N 4 ；
S8, regarding the data set N obtained in the step S7 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 ；
S9, screening the data set N obtained in the step S8 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is processed through the transfer function obtained in the step S6 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
S10, a data set N obtained according to the step S9 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Dividing the data into bins, and calculating the average power mu and standard deviation sigma in each wind speed interval to obtain each subA wind speed interval;
s11, calculating the wind speed V corresponding to each data point in each sub wind speed interval obtained in the step S10 D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
2. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S1, the power curve of the wind turbine generator is calculated using a wind-finding distance D 2 The distance of (2) is 2D-4D.
3. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S2, if the nacelle-controlled wind-finding radar can directly measure the front D of the wind wheel by setting up 2 And the wind speed information at the H distance, setting a wind measuring distance D in front of the wind wheel for at least 60 days by using a cabin control wind measuring radar in continuous synchronous test 2 And wind speed information at the H distance; if the cabin control wind-finding radar can not simultaneously measure the front D of the wind wheel through arrangement 2 And the wind speed at the distance H, installing a laser wind measuring radar suitable for unit performance calculation on the engine room, and continuously and synchronously testing the front D of the wind wheel for at least 60 days 2 And wind speed information at the H distance.
4. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S3, the wind wheel is ahead D 2 And the projection wind speed of the axis at the distance H, the data efficiency and N 1 Front D of middle wind wheel 2 Projecting wind speed from axis at distance N 1 Axis projection wind speed at H distance in front of middle wind wheel, N 1 Front D of middle wind wheel 2 Data efficiency at distance and N 1 The data effective rate of the distance H in front of the middle wind wheel is 10min average data.
5. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S5, a data set N is divided according to the size of a distance set M by using a quartile method 2 Cleaning, namely defining a cleaned data set as N 3 。
6. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S6, V H And V D2 The transfer function between them is:
V D2 ＝aV H +b
wherein a is V H And V D2 Slope of transfer function between, b is V H And V D2 An intercept of the transfer function between.
7. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S7, the radar wind-finding data and the historical operating data corresponding to the same time line are the same average of the radar wind-finding data and the historical operating data within 10min, and the historical data includes 10-min-level radar wind-finding data V H 、e 2 And unit operation data such as 10 min-level unit state, active power, wind wheel rotating speed, blade pitch angle and the like.
8. The method for calculating a power curve of a wind turbine generator based on a nacelle-controlled wind-finding radar according to claim 1, wherein in step S8, the abnormal power generation data includes shutdown, idling, failure, maintenance, startup, and power limit data.
9. The method for calculating a power curve of a wind turbine generator based on a nacelle control wind-finding radar according to claim 1, wherein in step S10, large-scale outlier data points with active power smaller than μ -3σ and active power larger than μ+3σ in each wind speed interval are removed to obtain each sub-wind speed interval.
10. Wind turbine generator system power curve calculation system based on cabin control wind-finding radar, characterized by comprising:
the data module is used for acquiring the diameter D of a wind wheel of the wind turbine generator and the wind measuring distance H of a cabin control wind measuring radar, and calculating to obtain the wind measuring distance D for a power curve of the wind turbine generator 2 ；
The testing module is used for continuously and synchronously testing the wind measuring distance D in front of the wind wheel for at least a plurality of days through the laser wind measuring radar 2 And wind speed information at the H distance;
the synthesis module is used for obtaining the front D of the wind wheel measured by the laser radar in the test time period of the test module 2 And the mean value of the axis projection wind speed at the H distance and the mean value of the data effective rate form a data set N 1 Defining a data set N 1 Distance D for measuring wind in front of middle wind wheel 2 The mean value of the axis projection wind speed at the distance is V D2 Defining a data set N 1 The mean value of the axis projection wind speed at the position of H distance in front of the middle wind wheel is V H Defining a data set N 1 Front D of middle wind wheel 2 The mean value of the data effective rate at the distance is e 1 Defining a data set N 1 The average value of the effective rate of the data at the position H distance in front of the middle wind wheel is e 2 ；
The screening module screens the data set N obtained by the synthesis module 1 Middle V D2 And V H The anemometry data which are all larger than 0 and have 100% of data effective rate form a data set N 2 In data set N 2 Middle V H And V D2 Drawing a wind speed scatter diagram for the abscissa and the ordinate respectively, and carrying out V on the wind speed scatter diagram H And V D2 Performing linear fitting to obtain a straight line L 1 ；
The cleaning module is used for calculating the straight line L from each data point in the wind speed scatter diagram obtained by the screening module 1 Obtaining a distance set M, and obtaining a data set N after cleaning 3 ；
Fitting module to obtain data set N by cleaning module 3 V in (1) H And V D2 Performing linear fitting again for the abscissa and the ordinate respectively to obtain V H And V D2 A transfer function therebetween;
the extraction module is used for extracting historical data of the wind turbine generator set 90 days before every 30 days in the running process for the wind turbine generator set provided with the control laser radar and forming a data set N 4 ；
The rejecting module is used for rejecting the data set N obtained by the extracting module 4 Data cleaning is carried out, and data of abnormal power generation of the unit operation state is removed to obtain a data set N 5 ；
The conversion module screens the data set N obtained by the rejection module 5 Middle V H Greater than 0 and e 2 Data set N is composed for 100% of data 6 And the data set N is obtained through the transfer function obtained by the fitting module 6 V in (1) H Converted into a wind measuring distance D in front of the wind wheel 2 Wind speed V at distance D2 Data set N 5 The converted dataset is defined as N 7 ；
The arrangement module is used for obtaining a data set N according to the conversion module 7 Medium wind speed V D2 Is of the size of (2) to the data set N 7 Wind velocity V in (a) D2 And active power are arranged to obtain a data set N 8 And takes every 0.5m/s as a wind speed interval to the data set N 8 Dividing the data into bins, and calculating the average power mu and standard deviation sigma in each wind speed interval to obtain each sub-wind speed interval;
the output module is used for calculating the wind speed V corresponding to each data point in each sub wind speed interval obtained by the arrangement module D2 And (3) saving the wind speed-power data, obtaining a wind speed power curve based on radar wind measurement within 90 days of the unit through difference fitting, and drawing the wind speed power curve and the unit guarantee power curve in a graph for display.
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| CN202310552478.4A CN116498502A (en) | 2023-05-16 | 2023-05-16 | Wind turbine generator power curve calculation method and system based on cabin control wind-finding radar |
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