Offshore wind turbine generator power curve test method and related device
By collecting and correcting the operating data of offshore wind turbines, and utilizing the nacelle wind speed transfer function and CFD methods, the problem of difficult hub wind speed measurement of offshore wind turbines was solved, enabling accurate power curve testing and performance evaluation, and improving the operational efficiency and decision-making accuracy of wind farms.
Patent Information
- Application Number
- CN202411153400.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-21
- Publication Date
- 2026-03-03
AI Technical Summary
Existing technologies make it difficult to accurately measure the free-flow wind speed at the hub height of offshore wind turbines, resulting in inaccurate power curve testing.
The operation data of offshore wind turbines are collected, corrected by the nacelle wind speed transfer function (NTF), and the overall flow field is calculated using CFD methods to plot error-free power curves.
This improves the accuracy and reliability of data, ensures the precision of power curves, enables timely detection of performance degradation or potential faults, and enhances the operational efficiency and scientific decision-making of wind farms.
Smart Images
Figure CN121593952A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of wind turbine power testing technology, and specifically relates to a method and related apparatus for testing the power curve of offshore wind turbines. Background Technology
[0002] The power curve of a wind turbine refers to the relationship between the output active power of the wind turbine and wind speed. It describes how the power output of the wind turbine changes with wind speed, directly reflecting the power characteristics of the wind turbine. It is the most important direct indicator for measuring the power generation performance of the wind turbine and estimating the power loss of the wind turbine. Therefore, the quality of the power curve directly determines the quality of the wind turbine's power generation performance. Wind turbine manufacturers provide a guaranteed power curve (referred to as the guaranteed power curve) under standard air density conditions as stipulated in the technical contract. The actual power curve is affected by many external factors and conditions, and often differs from the ideal power curve. It must be obtained from the actual operation of the wind turbine. Power curves based on actual operating data can be exported through the wind turbine's SCADA system. However, because the wind speed calculation rules are set, adjusted, or controlled by the wind turbine manufacturer, the power curve exported from the system is usually not accurate. The industry typically uses power curve testing to obtain the wind turbine's power curve. For onshore wind turbines, the actual measurement of the power curve is relatively simple and can be easily achieved by following IEC or national standard guidelines. However, for offshore wind power, due to environmental constraints, it is difficult to measure the free-flow wind speed at the hub height of the wind turbine using traditional methods, thus posing a new challenge. Summary of the Invention
[0003] The purpose of this invention is to provide a method and related apparatus for testing the power curve of offshore wind turbines, so as to solve the problem that it is difficult to measure the free-flow wind speed at the hub height of wind turbines using traditional methods.
[0004] To achieve the above objectives, the present invention adopts the following technical solution:
[0005] In a first aspect, the present invention provides a method for testing the power curve of an offshore wind turbine, comprising:
[0006] Collect operational data of offshore wind turbines and preprocess the data to obtain data that only includes the wind turbines under non-fault conditions;
[0007] Based on data from wind turbines under non-fault conditions, a nacelle wind speed transfer function (NTF) is created.
[0008] The nacelle wind speed is corrected based on the nacelle wind speed transfer function NTF to obtain error-free wind speed data;
[0009] Using error-free wind speed data, combined with the power output data of wind turbine units, power curves and power coefficients are plotted.
[0010] The overall flow field of the offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of the overall flow field calculated by CFD are corrected, power data of other units are obtained, and power curves of other units are calculated.
[0011] Optionally, collect operational data from offshore wind turbines, including:
[0012] Voltage, current, temperature, humidity, atmospheric pressure, wind turbine operating status code, rotor speed, wind turbine pitch, wind offset angle, wind turbine current, voltage, active power, reactive power data, nacelle wind speed, and nacelle wind direction.
[0013] Optionally, voltage and current data of wind turbine power generation can be obtained through a power measurement device; temperature, humidity, and atmospheric pressure data can be obtained through temperature, humidity, and barometers, and the hub height can be corrected through the data from the wind measurement tower; the nacelle-type laser wind radar can be used to measure the nacelle wind speed, and the laser radar can be calibrated and compared using a cup anemometer and a wind measurement tower before measurement.
[0014] Optional, correction process:
[0015] 1) If there is a wind measurement tower in the sea area within the same wind farm range for testing wind turbines, install temperature, humidity and atmospheric pressure sensors at the hub height of the wind turbines on the wind measurement tower, and use the data on the wind measurement tower to characterize the location of the wind turbines.
[0016] 2) Install temperature, humidity and atmospheric pressure sensors on the bottom platform of the test wind turbine and make corrections based on the height difference from the hub.
[0017] Optionally, the operating data can be preprocessed to obtain data containing only the wind turbine's non-faulty state, including:
[0018] Data on wind turbine shutdowns caused by wind turbine malfunctions; data on manual shutdowns during testing; data on measuring instrument malfunctions; and sector data that needs to be removed due to obstacles and the wake of the wind turbine.
[0019] Optionally, based on data from the wind turbine under non-fault conditions, a nacelle wind speed transfer function (NTF) is created, including:
[0020] Using the wind speed measured by lidar as a reference, and comparing it with the wind speed sensor data inside the cabin, a transfer function NTF between the cabin wind speed and the reference wind speed is established through regression analysis and curve fitting.
[0021] Collect wind speed data V measured by lidar refThe wind speed data V measured by the wind speed sensor inside the cabin nacelle Using polynomial regression to fit V ref and V nacelle The relationship between them:
[0022] V nacelle =a0+a1·V ref +a2·V ref2 +…+a n ·V refn
[0023] Where n is the order of the polynomial, and a0, a1, ..., an are the coefficients of the polynomial;
[0024] Based on the collected data, statistical software was used to perform curve fitting to determine the optimal regression model parameters; the transfer function NTF is regarded as another expression of the above regression model, describing the conversion relationship from lidar wind speed to nacelle wind speed.
[0025] Once the regression model is determined, the NTF is expressed as:
[0026] NTF(V ref ) = the fitted function (V) ref )
[0027] That is, V ref V obtained by substituting into the regression model nacelle The predicted value is the output of NTF.
[0028] Optionally, the nacelle wind speed is corrected based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data, including:
[0029] The real-time measured lidar wind speed V ref_real Substituting into NTF, the corrected nacelle wind speed V is calculated. nacelle_corrected :
[0030] V nacelle_corrected =f(V ref_real )
[0031] In the monitoring and control system of wind turbine generators, the modified nacelle wind speed V is used. nacelle_corrected Replace the original nacelle wind speed sensor data.
[0032] Optionally, the entire flow field of the offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of the CFD-calculated flow field are then corrected. Power data for other turbine units are obtained, and power curves for other turbine units are calculated, including:
[0033] The overall flow field of the offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of one turbine is measured using lidar. The overall wind speed and direction distribution calculated by CFD is corrected. The power data of the SCADA (Supervisory Control and Data Acquisition) system of other turbines is obtained, and the power curves of other turbines are calculated.
[0034] Secondly, the present invention provides a power curve testing system for offshore wind turbines, comprising:
[0035] The data acquisition module is used to collect the operating data of offshore wind turbines and preprocess the operating data to obtain data that only includes the wind turbines under non-fault conditions.
[0036] The transfer function creation module is used to create the nacelle wind speed transfer function NTF based on data from the wind turbine under non-fault conditions.
[0037] The correction module is used to correct the nacelle wind speed based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data.
[0038] The output comparison module is used to draw power curves and power coefficients using error-free wind speed data and the power output data of wind turbines, and compares them with the guaranteed power curve to complete the test.
[0039] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a method for testing the power curve of an offshore wind turbine.
[0040] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a method for testing the power curve of an offshore wind turbine.
[0041] Compared with the prior art, the present invention has the following technical effects:
[0042] This invention collects and preprocesses various operational data to eliminate abnormal data caused by faults, manual shutdowns, instrument malfunctions, and environmental factors (such as obstacles and wake effects), ensuring that the data used in subsequent analysis are all data from wind turbines under non-fault conditions, thereby improving the accuracy and reliability of the data.
[0043] This invention utilizes a nacelle-type laser wind-measuring radar, combined with a cup anemometer and a wind-measuring tower for calibration and comparison, to create a nacelle wind speed transfer function (NTF). This step effectively eliminates errors and deviations in the wind speed measurement process, making the nacelle wind speed data closer to the true value, and providing a more accurate wind speed basis for subsequent power curve plotting.
[0044] This invention, based on error-free wind speed data and wind turbine power output data, produces more accurate power curves and power coefficients. By comparing these curves with the guaranteed power curve, a comprehensive assessment of whether the wind turbine performance meets design requirements can be achieved, providing crucial reference for wind farm operation and maintenance.
[0045] This invention, through precise power curve testing, can promptly detect performance degradation or potential malfunctions in wind turbines, enabling appropriate maintenance and optimization measures to be taken. This helps improve the overall operational efficiency of wind farms and reduce power generation losses due to equipment failures.
[0046] The accurate power curves and performance evaluation results of this invention help wind farm managers and investors make more scientific and rational decisions, such as equipment selection, layout optimization, and operation strategy adjustment, thereby further promoting the sustainable development of the wind power industry.
[0047] In summary, the proposed offshore wind turbine power curve testing method demonstrates significant technical effectiveness in improving data accuracy, optimizing wind speed measurement, enhancing power curve testing precision, improving wind farm operational efficiency, supporting decision-making, and promoting technological innovation. Attached Figure Description
[0048] Figure 1 This is a flowchart of the present invention.
[0049] Figure 2 This is a system structure diagram of the present invention.
[0050] Figure 3 This is a logic block diagram for calculating the power curves of other generating units in this invention. Detailed Implementation
[0051] The present invention will be further described below with reference to the accompanying drawings:
[0052] Example 1, please refer to Figure 1 A method for testing the power curve of an offshore wind turbine, comprising:
[0053] Collect operational data of offshore wind turbines and preprocess the data to obtain data that only includes the wind turbines under non-fault conditions;
[0054] Based on data from wind turbines under non-fault conditions, a nacelle wind speed transfer function (NTF) is created.
[0055] The nacelle wind speed is corrected based on the nacelle wind speed transfer function NTF to obtain error-free wind speed data;
[0056] Using error-free wind speed data, combined with the power output data of the wind turbine, a power curve and power coefficient are plotted and compared with the guaranteed power curve to complete the test.
[0057] This invention collects and preprocesses various operational data to eliminate abnormal data caused by faults, manual shutdowns, instrument malfunctions, and environmental factors (such as obstacles and wake effects), ensuring that the data used in subsequent analysis are all data from wind turbines under non-fault conditions, thereby improving the accuracy and reliability of the data.
[0058] Example 2: This invention provides a method for testing the power curve of an offshore wind turbine, specifically including:
[0059] First, the meteorological equipment of the wind measurement tower is fully calibrated and verified to ensure that the equipment accuracy meets the test requirements and that the measurement data can accurately reflect the on-site environment.
[0060] This includes, but is not limited to, the calibration of equipment such as anemometers, wind vanes, and barometers, as well as synchronous calibration with the database, to ensure data continuity and consistency.
[0061] Comparison of wind measurement methods using wind measurement towers and lidar:
[0062] Independent wind measurements are performed using lidar, and the data is compared with that from a wind measurement tower to verify the accuracy of the tower's data. Lidar, as a high-precision wind measurement device, can provide more accurate wind speed and direction data, which can be used to calibrate or verify wind measurement tower data.
[0063] Installation of power characteristic testing equipment:
[0064] Install the necessary equipment for power characteristic testing on the wind turbine, such as power meters and tachometers. Ensure that all equipment is installed correctly and can accurately measure the various operating parameters of the wind turbine.
[0065] Test data collection:
[0066] The testing program was started to collect operational and meteorological data from the wind turbines.
[0067] Data collection should cover different wind speeds, wind directions, and power output ranges to ensure the comprehensiveness and accuracy of test results.
[0068] Invalid data removal:
[0069] The collected data undergoes initial screening to remove invalid or abnormal data points. Invalid data may be caused by equipment malfunctions, data transmission errors, or environmental factors, and requires careful identification and removal.
[0070] If equipment malfunctions or data anomalies occur during testing, they should be addressed promptly and testing should continue.
[0071] Ensure the continuity of the testing process and the integrity of the data.
[0072] Does it meet the database requirements?
[0073] Check whether the collected data meets the requirements of the test database.
[0074] Requirements include data format, data accuracy, and data integrity.
[0075] Create nacelle wind speed:
[0076] By using data from wind measurement towers or lidar, combined with measurement data from wind turbine units, nacelle wind speed data can be created.
[0077] Nacelle wind speed is one of the important indicators for evaluating the performance of wind turbines.
[0078] Create the nacelle wind speed transfer function (NTF):
[0079] In this step, the wind speed measured by lidar (or the wind speed measured by a verified wind tower) is used as a reference and compared with the wind speed sensor data inside the cabin.
[0080] A transfer function (NTF) between cabin wind speed and reference wind speed is established using regression analysis, curve fitting, or other mathematical methods. This function describes how cabin wind speed changes with the reference wind speed.
[0081] Based on data from wind turbines under non-fault conditions, a nacelle wind speed transfer function (NTF) is created, including:
[0082] Using the wind speed measured by lidar as a reference, and comparing it with the wind speed sensor data inside the cabin, a transfer function NTF between the cabin wind speed and the reference wind speed is established through regression analysis and curve fitting.
[0083] Collect wind speed data V measured by lidar ref The wind speed data V measured by the wind speed sensor inside the cabin nacelle Using polynomial regression to fit V ref and V nacelle The relationship between them:
[0084] V nacelle =a0+a1·V ref +a2·V ref2 +…+a n ·V refn
[0085] Where n is the order of the polynomial, and a0, a1, ..., an are the coefficients of the polynomial;
[0086] Based on the collected data, statistical software was used to perform curve fitting to determine the optimal regression model parameters; the transfer function NTF is regarded as another expression of the above regression model, describing the conversion relationship from lidar wind speed to nacelle wind speed.
[0087] Once the regression model is determined, the NTF is expressed as:
[0088] NTF(V ref ) = the fitted function (V) ref )
[0089] That is, V ref V obtained by substituting into the regression model nacelle The predicted value is the output of NTF.
[0090] Note that when creating an NTF, various factors may need to be considered, such as wind direction, unit type, and environmental conditions, to ensure the accuracy and applicability of the transfer function.
[0091] Correcting nacelle wind speed using NTF:
[0092] The created NTF is used to correct the nacelle wind speed to eliminate errors and biases in the wind speed measurement process.
[0093] The nacelle wind speed is corrected based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data, including:
[0094] The real-time measured lidar wind speed V ref_real Substituting into NTF, the corrected nacelle wind speed V is calculated. nacelle_corrected :
[0095] V nacelle_corrected =f(V ref_real )
[0096] In the monitoring and control system of wind turbine generators, the modified nacelle wind speed V is used. nacelle_corrected Replace the original nacelle wind speed sensor data.
[0097] Using the corrected nacelle wind speed data, combined with the wind turbine's power output data, power curves and key performance parameters such as Cp (power factor) are plotted.
[0098] Based on the collected data and nacelle wind speed data, the power curve and performance parameters such as Cp (power factor) of the wind turbine are plotted.
[0099] A power curve is a graphical representation of the power output capability of a wind turbine at different wind speeds.
[0100] Comparison with the guarantee power curve:
[0101] The plotted power curve is compared with the guaranteed power curve of the wind turbine.
[0102] Assess the difference and compliance between the actual performance and the guaranteed performance of the wind turbine.
[0103] SCADA data acquisition
[0104] 1) During the power curve test, in order to understand the operating status of the wind turbine at the corresponding moment, it is necessary to collect the SCADA data of the wind turbine at the same time, including: wind turbine operating status code (second level) (power limit, grid connection status), rotor speed, wind turbine pitch, wind offset angle (yaw angle), wind turbine current, voltage, active power, reactive power data, nacelle wind speed and nacelle wind direction.
[0105] 2) The wind turbine manufacturer should output the above signals from the relevant modules in the control cabinet as voltage signals and connect them to the data acquisition system for wind turbine power curve testing. If the above connection operation cannot be performed, the corresponding data must be exported from SCADA after the wind measurement is completed, and the time must be aligned. The first method should be used first.
[0106] Temperature, humidity and atmospheric pressure measurements
[0107] Atmospheric temperature and pressure data are typically presented as voltage or current signals, which can be connected to a data acquisition system for transmission. If the temperature and pressure sensors are not located at the hub height, the height needs to be corrected according to the algorithm provided by the wind turbine power curve testing standard. Considering the stringent sealing requirements of offshore turbines, it is not recommended to drill holes in the top of the test turbine nacelle to install temperature, humidity, and barometers. Alternative solutions include: 1) If there is a wind measurement tower in the vicinity of the test wind turbine (within the same wind farm or within 3km), it is recommended to install temperature, humidity, and atmospheric pressure sensors at the hub height of the wind turbine on the nearby wind measurement tower, using the data from the wind measurement tower to characterize the location of the wind turbine; 2) Install temperature, humidity, and atmospheric pressure sensors on the bottom platform of the test wind turbine, and correct for the height difference from the hub using a formula.
[0108] Data filtering methods and standards:
[0109] To ensure that only data collected when the wind turbines are in a non-faulty state is used for analysis, and that the data has not been corrupted, data sets in the following situations should be removed from the database:
[0110] 1) External conditions other than wind speed exceed the operating range of the wind turbine;
[0111] 2) Wind turbine failure caused the wind turbine to shut down;
[0112] 3) Manual shutdowns during testing due to various reasons;
[0113] 4) Measuring instrument fault data;
[0114] 5) Sector data that needs to be removed due to obstacles and the wake of wind turbines.
[0115] In another embodiment of the present invention, a power curve testing system for offshore wind turbines is provided, which can be used to implement the above-described method for testing the power curve of offshore wind turbines. Specifically, the system includes:
[0116] The data acquisition module is used to collect the operating data of offshore wind turbines and preprocess the operating data to obtain data that only includes the wind turbines under non-fault conditions.
[0117] The transfer function creation module is used to create the nacelle wind speed transfer function NTF based on data from the wind turbine under non-fault conditions.
[0118] The correction module is used to correct the nacelle wind speed based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data.
[0119] The output comparison module is used to draw power curves and power coefficients using error-free wind speed data and the power output data of wind turbines, and compares them with the guaranteed power curve to complete the test.
[0120] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.
[0121] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a power curve testing method for offshore wind turbines.
[0122] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the terminal. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the offshore wind turbine power curve testing method in the above embodiments.
[0123] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0124] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, 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, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A method for testing the power curve of an offshore wind turbine, characterized in that, include: Collect operational data of offshore wind turbines and preprocess the data to obtain data that only includes the wind turbines under non-fault conditions; Based on data from wind turbines under non-fault conditions, a nacelle wind speed transfer function (NTF) is created. The nacelle wind speed is corrected based on the nacelle wind speed transfer function NTF to obtain error-free wind speed data; Using error-free wind speed data, combined with the power output data of wind turbine units, power curves and power coefficients are plotted. The overall flow field of the offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of the overall flow field calculated by CFD are corrected, power data of other units are obtained, and power curves of other units are calculated.
2. The method for testing the power curve of an offshore wind turbine according to claim 1, characterized in that, Collect operational data from offshore wind turbines, including: Voltage, current, temperature, humidity, atmospheric pressure, wind turbine operating status code, rotor speed, wind turbine pitch, wind offset angle, wind turbine current, voltage, active power, reactive power data, nacelle wind speed, and nacelle wind direction; The operating data is preprocessed to obtain data containing only the wind turbine's non-faulty state, including: Data on wind turbine shutdowns caused by wind turbine malfunctions; data on manual shutdowns during testing; data on measuring instrument malfunctions; and sector data that needs to be removed due to obstacles and the wake of the wind turbine.
3. The method for testing the power curve of an offshore wind turbine according to claim 2, characterized in that, The voltage and current data of the wind turbine's power generation are obtained through a power measurement device; temperature, humidity, and atmospheric pressure data are obtained through temperature, humidity, and barometers, and the hub height is corrected using data from the wind measurement tower; the nacelle-type laser wind radar is used to measure the nacelle wind speed, and the laser radar is calibrated and compared using a cup anemometer and a wind measurement tower before measurement.
4. The method for testing the power curve of an offshore wind turbine according to claim 3, characterized in that, Correction process: 1) If there is a wind measurement tower in the sea area within the same wind farm range for testing wind turbines, install temperature, humidity and atmospheric pressure sensors at the hub height of the wind turbines on the wind measurement tower, and use the data on the wind measurement tower to characterize the location of the wind turbines. 2) Install temperature, humidity and atmospheric pressure sensors on the bottom platform of the test wind turbine and make corrections based on the height difference from the hub.
5. The method for testing the power curve of an offshore wind turbine according to claim 1, characterized in that, Based on data from wind turbines under non-fault conditions, a nacelle wind speed transfer function (NTF) is created, including: Using the wind speed measured by lidar as a reference, and comparing it with the wind speed sensor data inside the cabin, a transfer function NTF between the cabin wind speed and the reference wind speed is established through regression analysis and curve fitting. Collect wind speed data V measured by lidar ref The wind speed data V measured by the wind speed sensor inside the cabin nacelle Using polynomial regression to fit V ref and V nacelle The relationship between them: V nacelle =a0+a1·V ref +a2·V ref2 +…+a n ·V refn Where n is the order of the polynomial, a0, a1, ..., a n These are the coefficients of the polynomial; Based on the collected data, statistical software was used to perform curve fitting to determine the optimal regression model parameters; the transfer function NTF is regarded as another expression of the above regression model, describing the conversion relationship from lidar wind speed to nacelle wind speed. Once the regression model is determined, the NTF is expressed as: NTF(V ref ) = the fitted function (V) ref ) That is, V ref V obtained by substituting into the regression model nacelle The predicted value is the output of NTF.
6. The method for testing the power curve of an offshore wind turbine according to claim 5, characterized in that, The nacelle wind speed is corrected based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data, including: The real-time measured lidar wind speed V ref_real Substituting into NTF, the corrected nacelle wind speed V is calculated. nacelle_corrected : V nacelle_corrected =f(V ref_real ) In the monitoring and control system of wind turbine generators, the modified nacelle wind speed V is used. nacelle_corrected Replace the original nacelle wind speed sensor data.
7. The method for testing the power curve of an offshore wind turbine according to claim 1, characterized in that, The overall flow field of an offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of the CFD-calculated overall flow field are then corrected. Power data for other turbine units are obtained, and their power curves are calculated, including: The overall flow field of the offshore wind farm is calculated using computational fluid dynamics (CFD) methods. The wind speed and direction distribution of one turbine is measured using lidar. The overall wind speed and direction distribution calculated by CFD is corrected. The power data of the SCADA (Supervisory Control and Data Acquisition) system of other turbines is obtained, and the power curves of other turbines are calculated.
8. A power curve testing system for offshore wind turbines, characterized in that, include: The data acquisition module is used to collect the operating data of offshore wind turbines and preprocess the operating data to obtain data that only includes the wind turbines under non-fault conditions. The transfer function creation module is used to create the nacelle wind speed transfer function NTF based on data from the wind turbine under non-fault conditions. The correction module is used to correct the nacelle wind speed based on the nacelle wind speed transfer function (NTF) to obtain error-free wind speed data. The output comparison module is used to draw power curves and power coefficients using error-free wind speed data and the power output data of wind turbines, and compares them with the guaranteed power curve to complete the test.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the offshore wind turbine power curve testing method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the offshore wind turbine power curve testing method as described in any one of claims 1 to 7.