Method, device and equipment for generating power curve of wind generating set and medium

Abstract

The invention relates to the technical field of wind power generation, and discloses a wind generating set power curve generation method, device and equipment and a medium. According to the method, the standard power generation data and the field wind frequency distribution corresponding to the non-benchmark unit can be obtained, and the standard power generation data comprises the corresponding relation between the standard power and the wind speed. And dividing a wind speed interval in the standard power generation data into a plurality of wind speed sections, and determining standard power corresponding to each wind speed section. And determining a standard power limit value corresponding to each wind speed section according to the standard power corresponding to each wind speed section. On the basis of the standard power limit value corresponding to each wind speed section, abnormal data points are recognized and removed from the wind speed power scatter data of the non-benchmark unit, data enhancement is carried out on the removed scatter data of the non-benchmark unit according to field wind frequency distribution, and enhanced scatter data of the non-benchmark unit are obtained; and generating the power curve of the non-benchmark unit according to the enhanced scatter data, thereby improving the accuracy of the power curve of the non-benchmark unit.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method, device, equipment and medium for generating a power curve of a wind power generator set. Background Art

[0002] As the trend of wind turbines becoming larger and larger continues to increase, the importance of wind turbine performance testing is increasing. Ensuring that wind turbines operate in optimal conditions can effectively improve power generation efficiency, reduce failure rates, extend service life, and ensure grid stability and power supply quality.

[0003] In actual operation, the output power of a wind turbine is affected by many factors. Related technologies generally evaluate the performance of a wind turbine based on its power curve.

[0004] However, the accuracy of the wind turbine power curve generated by the related technology is low. Summary of the invention

[0005] The present invention provides a method, device, equipment and medium for generating a power curve of a wind generator set, which are used to solve the defect of low accuracy of the power curve of the wind generator set in the related art and improve the accuracy of the power curve of the wind generator set.

[0006] In a first aspect, the present invention provides a method for generating a power curve of a wind turbine generator set, comprising: Obtaining standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed; Dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments, and determining the standard power corresponding to each wind speed segment in the standard power generation data; Determine the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment; Based on the standard power limit corresponding to each wind speed segment, identifying and eliminating abnormal data points in the wind speed and power scatter point data of the non-benchmark unit, to obtain the eliminated scatter point data of the non-benchmark unit; Performing data enhancement on the eliminated scattered point data of the non-benchmark unit according to the on-site wind frequency distribution to obtain enhanced scattered point data of the non-benchmark unit; A power curve of the non-benchmark unit is generated according to the enhanced scattered point data of the non-benchmark unit.

[0007] Optionally, dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments includes: Based on a preset wind speed step, the wind speed interval in the standard power generation data is divided into a plurality of wind speed segments, and the length of each wind speed segment is equal to the preset wind speed step.

[0008] Optionally, when the standard power generation data is a standard power curve, determining the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment includes: For any of the wind speed segments, determine the starting wind speed point and the ending wind speed point of the wind speed segment, determine the first standard power and the second standard power corresponding to the starting wind speed point and the ending wind speed point in the standard power curve, respectively, determine the high power and the low power of the first standard power and the second standard power, multiply the high power and the low power by a preset upper limit coefficient and a preset lower limit coefficient, respectively, to obtain the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment, and use the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment as a whole as the standard power limit value corresponding to the wind speed segment; Among them, the upper limit coefficient is greater than 1, and the lower limit coefficient is greater than 0 and less than 1.

[0009] Optionally, when the standard power generation data is power wind speed scatter data of a benchmark unit, determining the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment includes: Searching the power and wind speed scatter point data of the benchmark unit to see whether there is abnormal power greater than a preset power threshold; If the abnormal power is found in the power and wind speed scatter data of the benchmark unit, the abnormal power and the corresponding wind speed are deleted from the power and wind speed scatter data of the benchmark unit to obtain the scatter data of the benchmark unit after deletion, and use it as the target scatter data; If the abnormal power is not found in the power wind speed scatter point data of the benchmark unit, the power wind speed scatter point data of the benchmark unit is directly used as the target scatter point data; According to the target scattered point data, a standard power limit value corresponding to each wind speed segment is determined.

[0010] Optionally, determining the standard power limit corresponding to each wind speed segment according to the target scattered point data includes: For any of the wind speed segments, the power distribution corresponding to the wind speed segment is determined in the target scattered point data, the corresponding average power and standard deviation are calculated according to the power distribution corresponding to the wind speed segment, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are determined based on the sigma statistical principle‌, the average power and the standard deviation, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are taken as a whole as the standard power limit value corresponding to the wind speed segment.

[0011] Optionally, based on the standard power limit corresponding to each wind speed segment, identifying and eliminating abnormal data points in the wind speed and power scatter point data of the non-benchmark unit to obtain the eliminated scatter point data of the non-benchmark unit includes: For any data point in the wind speed power scatter data of the non-benchmark unit, determine the target wind speed segment corresponding to the data point, and determine the standard power limit value corresponding to the target wind speed segment; if the power in the data point does not match the standard power limit value corresponding to the target wind speed segment, determine the data point as the target data point; All the determined target data points are taken as the abnormal data points as a whole, and the abnormal data points are eliminated from the wind speed and power scatter point data of the non-benchmark unit to obtain the scatter point data after elimination of the non-benchmark unit.

[0012] Optionally, performing data enhancement on the eliminated scattered data of the non-benchmark unit according to the on-site wind frequency distribution to obtain the enhanced scattered data of the non-benchmark unit includes: Determining the occurrence frequency of each wind speed segment according to the on-site wind frequency distribution; According to the occurrence frequency of each wind speed segment, the eliminated scattered point data of the non-benchmark unit are resampled to obtain the resampled scattered point data of the non-benchmark unit, and the number of data points corresponding to any wind speed segment in the resampled scattered point data matches the occurrence frequency of the wind speed segment; The resampled scattered data of the non-benchmark unit is used as the enhanced scattered data of the non-benchmark unit.

[0013] In a second aspect, the present invention provides a wind turbine generator power curve generating device, comprising: An acquisition unit, used to acquire standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed; A division unit, used for dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments; A first determining unit, configured to determine a standard power corresponding to each wind speed segment in the standard power generation data; A second determining unit, configured to determine a standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment; an identification unit, configured to identify abnormal data points in the wind speed power scatter point data of the non-benchmark unit based on the standard power limit corresponding to each wind speed segment; A removal unit, used to remove the abnormal data points from the wind speed and power scatter data of the non-benchmark unit to obtain the removed scatter data of the non-benchmark unit; A data enhancement unit, configured to perform data enhancement on the eliminated scattered data of the non-benchmark unit according to the on-site wind frequency distribution to obtain enhanced scattered data of the non-benchmark unit; A generating unit is used to generate a power curve of the non-benchmark unit according to the enhanced scattered point data of the non-benchmark unit.

[0014] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for generating a power curve of a wind turbine generator set according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for generating a power curve of a wind turbine generator set according to the first aspect or any corresponding embodiment thereof.

[0016] The method, device, equipment and medium for generating a power curve of a wind turbine provided by the present invention can obtain the standard power generation data and on-site wind frequency distribution corresponding to a non-benchmark unit, wherein the standard power generation data includes the corresponding relationship between the standard power and the wind speed. The wind speed interval in the standard power generation data is divided into a plurality of wind speed segments, and the standard power corresponding to each wind speed segment is determined in the standard power generation data. According to the standard power corresponding to each wind speed segment, the standard power limit corresponding to each wind speed segment is determined. Based on the standard power limit corresponding to each wind speed segment, abnormal data points are identified and eliminated in the wind speed power scatter data of the non-benchmark unit to obtain the eliminated scatter data of the non-benchmark unit. The eliminated scatter data of the non-benchmark unit is data enhanced according to the on-site wind frequency distribution to obtain the enhanced scatter data of the non-benchmark unit. The power curve of the non-benchmark unit is generated according to the enhanced scatter data of the non-benchmark unit. The present invention can effectively improve the accuracy of the power curve of the non-benchmark unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flow chart of a method for generating a power curve of a wind turbine generator set provided by an embodiment of the present invention; Figure 2 A guaranteed power curve provided by an embodiment of the present invention; Figure 3 A power wind speed scatter plot of a benchmark unit provided by an embodiment of the present invention; Figure 4 A schematic diagram of on-site wind frequency distribution provided by an embodiment of the present invention; Figure 5 A wind speed power scatter diagram of a non-benchmark unit provided in an embodiment of the present invention; Figure 6 A wind speed power scatter plot after eliminating non-benchmark unit data provided by an embodiment of the present invention; Figure 7 A schematic structural diagram of a wind turbine generator power curve generating device provided by an embodiment of the present invention; Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] As the trend of wind turbines becoming larger and larger continues to increase, the performance testing of wind turbine equipment is becoming increasingly important to ensure that wind turbines operate in the best condition, improve power generation efficiency, reduce failure rates, extend service life, and ensure the stability of the power grid and the quality of power supply.

[0021] In actual operation, the power output of wind turbines is affected by many factors, such as wind speed, wind direction, and unit status. In order to accurately evaluate the performance of wind turbines, it is necessary to calculate the power curve of the unit. However, the existing power curve calculation methods have certain limitations, such as insufficient data processing and inaccurate calculation results. Therefore, it is very important to accurately eliminate data based on the unit operation data and then calculate the power curve of the wind turbine.

[0022] Combine the following Figure 1-Figure 6 The wind turbine generator set power curve generation method of the present invention is described.

[0023] like Figure 1 As shown, this embodiment proposes a first method for generating a power curve of a wind turbine generator set, which may include the following steps: S101. Obtain standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed.

[0024] It should be noted that during the process of wind turbines generating electricity based on wind power, technicians can limit the output power of the wind turbines, that is, the wind turbines can output power of A under the action of wind power, but technicians limit their output power as needed, so that the wind turbines output power of B (B is less than A). The benchmark unit is a wind turbine that the technicians have not limited in power, and its output power is the maximum power that can be output under the action of wind power.

[0025] It should be noted that, in this embodiment, a benchmark unit can be selected from a plurality of wind turbines whose output power is not restricted when operating on site. When determining whether a certain wind turbine can be used as a benchmark unit, the wind speed power scatter data of the wind turbine can be obtained first. The power wind speed scatter data of the wind turbine can include multiple data points, each of which includes the corresponding power and wind speed. After that, the technicians manually identify and remove abnormal data points (such as data points with obviously abnormal power) from the wind speed power scatter data. After removing the abnormal data points, if the total number of remaining data points is not less than 90% of the total number of original data points, and the number of remaining data points in each wind speed segment is not less than 90% of the number of original data points, then the wind turbine can be selected as the benchmark unit, and the wind speed power scatter data of the wind turbine after removing the abnormal data points is determined as the wind speed power scatter data of the benchmark unit. Otherwise, it can be prohibited to select the wind turbine as the benchmark unit, effectively ensuring the data standardization of the benchmark unit, so as to improve the accuracy of the power curve generated subsequently.

[0026] It is understandable that the non-benchmark unit may be a wind turbine generator set that is not a benchmark unit. Specifically, the non-benchmark unit may be a wind turbine generator set whose output power is artificially limited during wind power generation.

[0027] Specifically, the standard power generation data may include the maximum power that the wind turbine generator set can output at different wind speeds, that is, the standard power generation power, and specifically includes the corresponding relationship between the wind speed and the standard power generation power.

[0028] Optionally, the standard power generation data may be a standard power curve, such as Figure 2 Guaranteed power curve shown.

[0029] Optionally, the standard power generation data may also be the power and wind speed scatter data of the benchmark unit, such as Figure 3It should be noted that if there is no benchmark unit on site, this embodiment can select a wind turbine generator set on site to obtain the power wind speed scatter data of the wind turbine generator set, and manually remove the power-limited data points and abnormal data points, and the remaining data points are used as the above-mentioned standard power generation data.

[0030] Among them, the on-site wind frequency distribution is the wind frequency distribution of the non-benchmark unit operation site, such as Figure 4 The on-site wind frequency distribution is shown.

[0031] S102: Divide the wind speed interval in the standard power generation data into a plurality of wind speed segments.

[0032] Among them, the wind speed range in the standard power generation data may include the wind speed range at the operation site of the non-benchmark unit.

[0033] Specifically, in this embodiment, the wind speed interval in the standard power generation data can be divided into a plurality of continuous and non-overlapping wind speed segments.

[0034] Optionally, step S102 may include: Based on the preset wind speed step length, the wind speed interval in the standard power generation data is divided into a plurality of wind speed segments, and the length of each wind speed segment is equal to the preset wind speed step length.

[0035] Optionally, the preset wind speed step size may be 0.1 meters per second.

[0036] S103. Determine the standard power corresponding to each wind speed range in the standard power generation data.

[0037] Specifically, in this embodiment, according to each wind speed segment, the standard power corresponding to each wind speed segment can be determined in the standard power generation data.

[0038] S104. Determine the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment.

[0039] Specifically, this embodiment can calculate the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment.

[0040] Specifically, the standard power limit value may include a standard power upper limit value and / or a standard power lower limit value.

[0041] Optionally, when the standard power generation data is a standard power curve, step S104 may include: For any wind speed segment, determine the starting wind speed point and the ending wind speed point of the wind speed segment, determine the first standard power and the second standard power corresponding to the starting wind speed point and the ending wind speed point in the standard power curve, determine the high power and the low power in the first standard power and the second standard power, multiply the high power and the low power by the preset upper limit coefficient and the lower limit coefficient respectively, obtain the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment, and use the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment as a whole as the standard power limit value corresponding to the wind speed segment; Among them, the upper limit coefficient is greater than 1, and the lower limit coefficient is greater than 0 and less than 1.

[0042] It should be noted that the specific sizes of the upper limit coefficient and the lower limit coefficient can be set by technical personnel according to actual conditions, and this embodiment does not limit them.

[0043] S105. Based on the standard power limit corresponding to each wind speed segment, identify abnormal data points in the wind speed power scatter data of the non-benchmark unit.

[0044] Among them, abnormal data points may include all data points whose power exceeds the standard power limit. For example, data point A1 includes the corresponding wind speed a1 and power b1, and the standard power upper limit corresponding to wind speed a1 is b0. If b1 is greater than b0, then data point A is an abnormal data point. For another example, data point A2 includes the corresponding wind speed a2 and power b2, and the standard power lower limit corresponding to wind speed a2 is b3. If b2 is less than b3, then data point A2 is an abnormal data point.

[0045] Specifically, this embodiment may first obtain the wind speed power scatter data of the non-benchmark unit. The power wind speed scatter data of the non-benchmark unit may include multiple data points, each data point including the corresponding power and wind speed, such as Figure 5 The various data points in the wind speed power scatter plot shown in FIG. Then, abnormal data points are identified in the wind speed power scatter data.

[0046] It should be noted that, in this embodiment, unreasonable data points can be identified based on the standard power upper limit value and the standard power lower limit value corresponding to each wind speed segment.

[0047] S106. Eliminate abnormal data points from the wind speed and power scatter point data of the non-benchmark unit to obtain the scatter point data after elimination of the non-benchmark unit.

[0048] Specifically, this embodiment can remove abnormal data points from the wind speed and power scatter data of non-benchmark units, and all remaining data points are the scatter data after removal. Figure 6 The wind speed power scatter plot shown is after the non-benchmark unit data are eliminated. The red data points are abnormal data points, and the green data points are the scattered data after elimination.

[0049] S107. Perform data enhancement on the eliminated scattered data of the non-benchmark units according to the on-site wind frequency distribution to obtain enhanced scattered data of the non-benchmark units.

[0050] Specifically, this embodiment can perform data enhancement on the scattered data after elimination of non-benchmark units according to the on-site wind frequency distribution.

[0051] S108. Generate a power curve of the non-benchmark unit according to the enhanced scattered data of the non-benchmark unit.

[0052] Specifically, this embodiment can draw a power curve of the non-benchmark unit based on the enhanced scattered data of the non-benchmark unit.

[0053] It should be noted that this embodiment combines the standard power generation of the wind turbine and the on-site wind frequency distribution to perform data enhancement and optimization processing, thereby accurately calculating the power curve of the wind turbine and improving the accuracy and efficiency of the wind turbine performance evaluation.

[0054] The method for generating a power curve of a wind turbine generator set proposed in this embodiment can obtain the standard power generation data and on-site wind frequency distribution corresponding to the non-benchmark unit, and the standard power generation data includes the corresponding relationship between the standard power and the wind speed. The on-site wind speed interval in the standard power generation data is divided into multiple wind speed segments, and the standard power corresponding to each wind speed segment is determined in the standard power generation data. According to the standard power corresponding to each wind speed segment, the standard power limit corresponding to each wind speed segment is determined. Based on the standard power limit corresponding to each wind speed segment, abnormal data points are identified and eliminated in the wind speed power scatter data of the non-benchmark unit to obtain the eliminated scatter data of the non-benchmark unit. The eliminated scatter data of the non-benchmark unit is enhanced according to the on-site wind frequency distribution to obtain the enhanced scatter data of the non-benchmark unit. The power curve of the non-benchmark unit is generated according to the enhanced scatter data of the non-benchmark unit. This embodiment can effectively improve the accuracy of the power curve of the non-benchmark unit.

[0055] based on Figure 1 This embodiment proposes a second method for generating a power curve of a wind turbine generator set. When the standard power generation data is the power and wind speed scatter data of a benchmark generator set, the above step S104 may include: Check whether there is abnormal power greater than a preset power threshold in the power and wind speed scatter data of the benchmark unit; If abnormal power is found in the power and wind speed scatter data of the benchmark unit, the abnormal power and the corresponding wind speed are deleted from the power and wind speed scatter data of the benchmark unit to obtain the scatter data after deletion of the benchmark unit, and the scatter data is used as the target scatter data; If no abnormal power is found in the power and wind speed scatter data of the benchmark unit, the power and wind speed scatter data of the benchmark unit will be directly used as the target scatter data; According to the target scattered data, the standard power limit corresponding to each wind speed segment is determined.

[0056] Optionally, the above-mentioned determining the standard power limit corresponding to each wind speed segment according to the target scattered point data includes: For any wind speed segment, the power distribution corresponding to the wind speed segment is determined in the target scattered data, and the corresponding average power and standard deviation are calculated according to the power distribution corresponding to the wind speed segment. The standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are determined based on the sigma statistical principle, the average power and the standard deviation, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are taken as a whole as the standard power limit value corresponding to the wind speed segment.

[0057] The preset power threshold may be set by a technician according to the operating data of the wind turbine generator set, and this embodiment does not limit this.

[0058] Optionally, the above step S105 may include: For any data point in the wind speed power scatter data of the non-benchmark unit, determine the target wind speed segment corresponding to the data point, and determine the standard power limit corresponding to the target wind speed segment. If the power in the data point does not match the standard power limit corresponding to the target wind speed segment, determine the data point as the target data point; All the identified target data points are considered as abnormal data points as a whole.

[0059] At this time, the above step S106 is still: removing abnormal data points from the wind speed and power scatter data of the non-benchmark unit to obtain the scatter data after removal of the non-benchmark unit.

[0060] Specifically, when the standard power limit corresponding to each wind speed segment includes a standard power upper limit value and a standard power lower limit value, for any data point, the present embodiment can first determine the target wind speed segment corresponding to the data point, that is, the target wind speed segment to which the wind speed in the data point belongs, and then determine the standard power upper limit value and the standard power lower limit value corresponding to the target wind speed segment. If the power in the data point is greater than the standard power upper limit value, or less than the standard power lower limit value, it can be determined that the power in the data point does not match the standard power limit value corresponding to the target wind speed segment, and the data point is determined as the target data point.

[0061] Optionally, the above step S107 may include: Determine the occurrence frequency of each wind speed segment based on the on-site wind frequency distribution; According to the frequency of occurrence of each wind speed segment, the scattered data after elimination of the non-benchmark unit is resampled to obtain the resampled scattered data of the non-benchmark unit. The number of data points corresponding to any wind speed segment in the resampled scattered data matches the frequency of occurrence of the wind speed segment. The resampled scattered data of the non-benchmark unit are used as the enhanced scattered data of the non-benchmark unit.

[0062] Specifically, the present embodiment can utilize the on-site wind frequency distribution to perform data enhancement on the scattered data after elimination of the non-benchmark unit, such as data enhancement through resampling. For example, when resampling, the present embodiment can upsample the wind speed in each wind speed segment of the scattered data after elimination of the non-benchmark unit based on the normal distribution. Based on the on-site wind frequency distribution, if the data for the wind speed between 5.1 and 5.2 meters per second should have 100 points, but the actual data has only 10 points, then 90 data points are automatically generated between 5.1 and 5.2 meters per second according to the normal distribution for supplementation. Afterwards, the present embodiment can interpolate the power according to the wind speed obtained through data enhancement using an interpolation method (such as linear interpolation, quadratic interpolation, and cubic spline interpolation) to fill in the data gaps and obtain the resampled scattered data of the non-benchmark unit.

[0063] The method for generating a power curve of a wind turbine generator set proposed in this embodiment can select a reference power curve, a benchmark unit, and a wind frequency distribution diagram measured by a wind tower as a reference for calculating the unit power; if the calculated power curve differs too much from this, further analysis is required. This embodiment can effectively avoid data loss or bias caused by data elimination, thereby affecting the accuracy of the power curve, through optimization processing such as data screening and data enhancement. This embodiment can be applied to different types of wind turbine generator sets, has good versatility, and provides reliable technical support for wind turbine performance evaluation.

[0064] like Figure 7 As shown, this embodiment provides a device for generating a power curve of a wind turbine generator set, which may include: An acquisition unit 701 is used to acquire standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed; A division unit 702, used to divide the wind speed interval in the standard power generation data into a plurality of wind speed segments; A first determining unit 703 is used to determine the standard power corresponding to each wind speed segment in the standard power generation data; The second determining unit 704 is used to determine the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment; An identification unit 705 is used to identify abnormal data points in the wind speed power scatter data of the non-standard unit based on the standard power limit corresponding to each wind speed segment; A removal unit 706 is used to remove abnormal data points from the wind speed and power scatter data of the non-benchmark unit to obtain the scatter data after removal of the non-benchmark unit; A data enhancement unit 707 is used to enhance the scattered data of the non-benchmark units after elimination according to the on-site wind frequency distribution to obtain enhanced scattered data of the non-benchmark units; The generating unit 708 is used to generate a power curve of the non-benchmark unit according to the enhanced scattered point data of the non-benchmark unit.

[0065] It should be noted that the processing of the acquisition unit 701, the division unit 702, the first determination unit 703, the second determination unit 704, the identification unit 705, the elimination unit 706, the data enhancement unit 707 and the generation unit 708 and the beneficial effects thereof can be respectively referred to in Figure 1 Steps S101 to S108 in the above are not described in detail.

[0066] Optionally, the dividing unit 702 is further configured to: Based on the preset wind speed step length, the wind speed interval in the standard power generation data is divided into a plurality of wind speed segments, and the length of each wind speed segment is equal to the preset wind speed step length.

[0067] Optionally, when the standard power generation data is a standard power curve, the second determining unit 704 is further configured to: For any wind speed segment, determine the starting wind speed point and the ending wind speed point of the wind speed segment, determine the first standard power and the second standard power corresponding to the starting wind speed point and the ending wind speed point in the standard power curve, determine the high power and the low power in the first standard power and the second standard power, multiply the high power and the low power by the preset upper limit coefficient and the lower limit coefficient respectively, obtain the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment, and use the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment as a whole as the standard power limit value corresponding to the wind speed segment; Among them, the upper limit coefficient is greater than 1, and the lower limit coefficient is greater than 0 and less than 1.

[0068] Optionally, when the standard power generation data is power wind speed scatter data of a benchmark unit, the second determining unit 704 is further configured to: Check whether there is abnormal power greater than a preset power threshold in the power and wind speed scatter data of the benchmark unit; If abnormal power is found in the power and wind speed scatter data of the benchmark unit, the abnormal power and the corresponding wind speed are deleted from the power and wind speed scatter data of the benchmark unit to obtain the scatter data after deletion of the benchmark unit, and the scatter data is used as the target scatter data; If no abnormal power is found in the power and wind speed scatter data of the benchmark unit, the power and wind speed scatter data of the benchmark unit will be directly used as the target scatter data; According to the target scattered data, the standard power limit corresponding to each wind speed segment is determined.

[0069] Optionally, the second determining unit 704 is further configured to: For any wind speed segment, the power distribution corresponding to the wind speed segment is determined in the target scattered data, and the corresponding average power and standard deviation are calculated according to the power distribution corresponding to the wind speed segment. The standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are determined based on the sigma statistical principle, the average power and the standard deviation, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are taken as a whole as the standard power limit value corresponding to the wind speed segment.

[0070] Optionally, the identification unit 705 is further configured to: For any data point in the wind speed power scatter data of the non-benchmark unit, determine the target wind speed segment corresponding to the data point, and determine the standard power limit corresponding to the target wind speed segment. If the power in the data point does not match the standard power limit corresponding to the target wind speed segment, determine the data point as the target data point; All the identified target data points are considered as abnormal data points as a whole.

[0071] Optionally, the data enhancement unit 707 is further configured to: Determine the occurrence frequency of each wind speed segment based on the on-site wind frequency distribution; According to the frequency of occurrence of each wind speed segment, the scattered data after elimination of the non-benchmark unit is resampled to obtain the resampled scattered data of the non-benchmark unit. The number of data points corresponding to any wind speed segment in the resampled scattered data matches the frequency of occurrence of the wind speed segment. The resampled scattered data of the non-benchmark unit are used as the enhanced scattered data of the non-benchmark unit.

[0072] The wind turbine power curve generating device proposed in this embodiment can obtain the standard power generation data and on-site wind frequency distribution corresponding to the non-benchmark unit, and the standard power generation data includes the corresponding relationship between the standard power and the wind speed. The wind speed interval in the standard power generation data is divided into multiple wind speed segments, and the standard power corresponding to each wind speed segment is determined in the standard power generation data. According to the standard power corresponding to each wind speed segment, the standard power limit corresponding to each wind speed segment is determined. Based on the standard power limit corresponding to each wind speed segment, the abnormal data points are identified and eliminated in the wind speed power scatter data of the non-benchmark unit to obtain the eliminated scatter data of the non-benchmark unit. The eliminated scatter data of the non-benchmark unit is enhanced according to the on-site wind frequency distribution to obtain the enhanced scatter data of the non-benchmark unit. The power curve of the non-benchmark unit is generated according to the enhanced scatter data of the non-benchmark unit. This embodiment can effectively improve the accuracy of the power curve of the non-benchmark unit.

[0073] The wind turbine power curve generating device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0074] The embodiment of the present invention also provides a computer device having the above Figure 7 The wind turbine generator power curve generating device shown.

[0075] See also Figure 8 , a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 8 A processor 10 is taken as an example.

[0076] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0077] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0078] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function. The data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage devices. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0079] The memory 20 may include a volatile memory, such as a random access memory. The memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive. The memory 20 may also include a combination of the above-mentioned types of memory.

[0080] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0081] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating a power curve of a wind turbine generator set, characterized in that: include: Obtaining standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed; Dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments, and determining the standard power corresponding to each wind speed segment in the standard power generation data; Determine the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment; Based on the standard power limit corresponding to each wind speed segment, identifying and eliminating abnormal data points in the wind speed and power scatter point data of the non-benchmark unit, to obtain the eliminated scatter point data of the non-benchmark unit; Performing data enhancement on the eliminated scattered point data of the non-benchmark unit according to the on-site wind frequency distribution to obtain enhanced scattered point data of the non-benchmark unit; A power curve of the non-benchmark unit is generated according to the enhanced scattered point data of the non-benchmark unit.

2. The method according to claim 1, characterized in that The step of dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments includes: Based on a preset wind speed step, the wind speed interval in the standard power generation data is divided into a plurality of wind speed segments, and the length of each wind speed segment is equal to the preset wind speed step.

3. The method according to claim 1, characterized in that When the standard power generation data is a standard power curve, determining the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment includes: For any of the wind speed segments, determine the starting wind speed point and the ending wind speed point of the wind speed segment, determine the first standard power and the second standard power corresponding to the starting wind speed point and the ending wind speed point in the standard power curve, respectively, determine the high power and the low power of the first standard power and the second standard power, multiply the high power and the low power by a preset upper limit coefficient and a preset lower limit coefficient, respectively, to obtain the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment, and use the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment as a whole as the standard power limit value corresponding to the wind speed segment; Among them, the upper limit coefficient is greater than 1, and the lower limit coefficient is greater than 0 and less than 1.

4. The method according to claim 1, characterized in that When the standard power generation data is the power wind speed scatter data of the benchmark unit, determining the standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment includes: Searching the power and wind speed scatter point data of the benchmark unit to see whether there is abnormal power greater than a preset power threshold; If the abnormal power is found in the power and wind speed scatter data of the benchmark unit, the abnormal power and the corresponding wind speed are deleted from the power and wind speed scatter data of the benchmark unit to obtain the scatter data of the benchmark unit after deletion, and use it as the target scatter data; If the abnormal power is not found in the power wind speed scatter point data of the benchmark unit, the power wind speed scatter point data of the benchmark unit is directly used as the target scatter point data; According to the target scattered point data, a standard power limit value corresponding to each wind speed segment is determined.

5. The method according to claim 4, characterized in that Determining the standard power limit value corresponding to each wind speed segment according to the target scattered point data includes: For any of the wind speed segments, the power distribution corresponding to the wind speed segment is determined in the target scattered point data, the corresponding average power and standard deviation are calculated according to the power distribution corresponding to the wind speed segment, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are determined based on the sigma statistical principle‌, the average power and the standard deviation, and the standard power upper limit value and the standard power lower limit value corresponding to the wind speed segment are taken as a whole as the standard power limit value corresponding to the wind speed segment.

6. The method according to claim 1, characterized in that The method of identifying and eliminating abnormal data points in the wind speed and power scatter point data of the non-benchmark unit based on the standard power limit corresponding to each wind speed segment to obtain the eliminated scatter point data of the non-benchmark unit includes: For any data point in the wind speed power scatter data of the non-benchmark unit, determine the target wind speed segment corresponding to the data point, and determine the standard power limit value corresponding to the target wind speed segment; if the power in the data point does not match the standard power limit value corresponding to the target wind speed segment, determine the data point as the target data point; All the determined target data points are taken as the abnormal data points as a whole, and the abnormal data points are eliminated from the wind speed and power scatter point data of the non-benchmark unit to obtain the scatter point data after elimination of the non-benchmark unit.

7. The method according to claim 1, characterized in that The step of performing data enhancement on the eliminated scattered point data of the non-benchmark unit according to the on-site wind frequency distribution to obtain the enhanced scattered point data of the non-benchmark unit includes: Determining the occurrence frequency of each wind speed segment according to the on-site wind frequency distribution; According to the occurrence frequency of each wind speed segment, the eliminated scattered point data of the non-benchmark unit are resampled to obtain the resampled scattered point data of the non-benchmark unit, and the number of data points corresponding to any wind speed segment in the resampled scattered point data matches the occurrence frequency of the wind speed segment; The resampled scattered data of the non-benchmark unit is used as the enhanced scattered data of the non-benchmark unit.

8. A wind turbine generator power curve generating device, characterized in that: include: An acquisition unit, used to acquire standard power generation data and on-site wind frequency distribution corresponding to the non-standard unit, wherein the standard power generation data includes a corresponding relationship between standard power and wind speed; A division unit, used for dividing the wind speed interval in the standard power generation data into a plurality of wind speed segments; A first determining unit, configured to determine a standard power corresponding to each wind speed segment in the standard power generation data; A second determining unit, configured to determine a standard power limit corresponding to each wind speed segment according to the standard power corresponding to each wind speed segment; an identification unit, configured to identify abnormal data points in the wind speed power scatter point data of the non-benchmark unit based on the standard power limit corresponding to each wind speed segment; A removal unit, used to remove the abnormal data points from the wind speed and power scatter data of the non-benchmark unit to obtain the removed scatter data of the non-benchmark unit; A data enhancement unit, configured to perform data enhancement on the eliminated scattered data of the non-benchmark unit according to the on-site wind frequency distribution to obtain enhanced scattered data of the non-benchmark unit; A generating unit is used to generate a power curve of the non-benchmark unit according to the enhanced scattered point data of the non-benchmark unit.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for generating a power curve of a wind turbine generator set according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for generating a power curve of a wind turbine generator set according to any one of claims 1 to 7.

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