Fan data counterfeiting discrimination method and related device

Abstract

The invention discloses a draught fan data counterfeiting distinguishing method and a related device. The draught fan data counterfeiting distinguishing method comprises the steps that a draught fan with suspected data counterfeiting is recognized; the active power, the total generating capacity, the daily generating capacity, the real-time wind speed and the cabin temperature of the draught fan with the suspected data counterfeiting are obtained; comparing the active power, the total generating capacity, the daily generating capacity, the real-time wind speed and the cabin temperature of the fan with the suspected data counterfeiting with an active power curve, a total generating capacity curve, a daily generating capacity curve, a real-time wind speed curve and a cabin temperature curve in a real-time database to determine whether the data in the real-time database is counterfeited or not; the method and the related device can judge whether the fan data is counterfeited or not.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and relates to a method for determining whether wind turbine data is falsified and a related device. Background Art

[0002] With the booming wind power industry, the efficient and stable operation of wind turbines is crucial for ensuring power supply, improving energy efficiency, and achieving sustainable development goals. During operation, wind turbines generate massive amounts of operational data, covering key parameters such as turbine speed, power output, temperature, and vibration. This data is stored in a real-time database.

[0003] The phenomenon of wind turbine data falsification has quietly grown, seriously disrupting normal operational management. Data falsifiers conceal the true status of wind turbines through tampering and fabrication, resulting in a significant disconnect between the information provided to management and the actual situation. This distorted information not only hinders management's accurate understanding of wind turbine status, preventing the timely detection of potential safety hazards and performance issues, which in turn may lead to equipment failures or even safety accidents, posing a threat to the safe and stable operation of wind farms. It also negatively impacts the statistics of key performance indicators such as actual power generation and availability. Power generation is a key indicator of wind farm economic performance. Data falsification can lead to inaccurate power generation statistics, affecting the wind farm's revenue calculations and market competitiveness. Availability is a key parameter reflecting wind turbine operational reliability. Data falsification can distort availability, misleading management in formulating wind turbine maintenance and replacement strategies, and increasing operating costs.

[0004] Therefore, identifying whether wind turbine data in real-time databases is falsified and using this information to gain in-depth understanding and control of wind turbines has become a critical issue that needs to be addressed in the wind power industry. Unfortunately, a comprehensive, effective, and universally applicable identification method has not yet been established in the existing technology system. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a method for determining whether wind turbine data is falsified and a related device. The method and the related device can determine whether the wind turbine data is falsified.

[0006] To achieve the above-mentioned object, the present invention discloses a method for identifying falsified wind turbine data, comprising:

[0007] Identify wind turbines suspected of data falsification;

[0008] Obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines suspected of data falsification;

[0009] The active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification are compared with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database to determine whether the data in the real-time database is falsified.

[0010] The further improvement of the method for identifying falsified wind turbine data according to the present invention is as follows:

[0011] Furthermore, the process of identifying wind turbines suspected of data falsification is as follows:

[0012] Obtain the real-time active power of all wind turbines at different times;

[0013] When the difference between the real-time active power of two wind turbines is less than x more than a preset number of times at the same time in one day, the two wind turbines are considered to be suspected of data falsification.

[0014] Furthermore, the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification are compared with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database respectively to determine whether the data in the real-time database is falsified. The process is as follows:

[0015] When the deviation between the fitting value on the active power curve and the active power of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the total power generation curve and the total power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the daily power generation curve and the daily power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the real-time wind speed curve and the real-time wind speed of the wind turbine suspected of data falsification exceeds 1%, and the deviation between the fitting value on the cabin temperature curve and the cabin temperature of the wind turbine suspected of data falsification exceeds 1%, it is considered that the wind turbine data in the real-time database is falsified.

[0016] Furthermore, it also includes: when it is believed that the wind turbine data in the real-time database is falsified, an early warning signal is issued.

[0017] The present invention discloses a system for identifying falsified wind turbine data, comprising:

[0018] Identification module, used to identify wind turbines suspected of data falsification;

[0019] An acquisition module is used to obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines suspected of data falsification;

[0020] The determination module is used to compare the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database, so as to determine whether the data in the real-time database is falsified.

[0021] The further improvement of the system for identifying falsified wind turbine data according to the present invention is as follows:

[0022] Furthermore, the process of identifying wind turbines suspected of data falsification is as follows:

[0023] Obtain the real-time active power of all wind turbines at different times;

[0024] When the difference between the real-time active power of two wind turbines is less than x more than a preset number of times at the same time in one day, the two wind turbines are considered to be suspected of data falsification.

[0025] Furthermore, the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification are compared with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database respectively to determine whether the data in the real-time database is falsified. The process is as follows:

[0026] When the deviation between the fitting value on the active power curve and the active power of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the total power generation curve and the total power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the daily power generation curve and the daily power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the real-time wind speed curve and the real-time wind speed of the wind turbine suspected of data falsification exceeds 1%, and the deviation between the fitting value on the cabin temperature curve and the cabin temperature of the wind turbine suspected of data falsification exceeds 1%, it is considered that the wind turbine data in the real-time database is falsified.

[0027] Furthermore, it also includes: when it is believed that the wind turbine data in the real-time database is falsified, an early warning signal is issued.

[0028] The present invention discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for determining whether wind turbine data is falsified are implemented.

[0029] The present invention discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the method for determining whether wind turbine data is falsified are implemented.

[0030] The present invention has the following beneficial effects:

[0031] During specific operation, the method for determining whether wind turbine data is falsified and the related device described in the present invention compare the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database, respectively, to determine whether the data in the real-time database is falsified. The comprehensive judgment of whether the data is falsified is made from the perspectives of active power, total power generation, daily power generation, real-time wind speed and cabin temperature, with high accuracy, providing an effective data basis for the regulation of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0033] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0035] In the description of the present invention, it is to be understood that the terms “include” and “comprise” indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terms used in the present specification are only for the purpose of describing particular embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] It should be further understood that the term "and / or" as used in the present specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0038] It should be understood that although the terms "first," "second," and "third" may be used to describe preset ranges in embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are merely used to distinguish one preset range from another. For example, without departing from the scope of embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0039] The word "if," as used herein, may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to the determination" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0040] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] The accompanying drawings illustrate various schematic diagrams of structures according to embodiments disclosed herein. These figures are not drawn to scale; for clarity, some details are exaggerated and some details may be omitted. The shapes of the various regions and layers shown in the figures, as well as their relative sizes and positional relationships, are merely exemplary and may deviate in practice due to manufacturing tolerances or technical limitations. Those skilled in the art may design regions / layers with different shapes, sizes, and relative positions as needed.

[0042] Example 1

[0043] refer to Figure 1 The method for determining whether wind turbine data is falsified according to the present invention comprises the following steps:

[0044] 1) Obtain real-time data of wind turbine active power;

[0045] 2) Compare the active power of all wind turbines in pairs;

[0046] 3) If the difference in active power between two wind turbines is less than x for more than 50 times at the same time in a day, it is recorded as suspected fraud, where x is 500W;

[0047] 4) Obtain the ID and specific date t of the wind turbines suspected of fraud within a month, taking the fraudulent data of wind turbines A and B on day t as an example;

[0048] 5) Obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines A and B, which are suspected of data falsification;

[0049] 6) Obtain the active power curves s1 and s2 corresponding to the counterfeit wind turbines a and b on day t from the real-time database

[0050] 7) Determine the deviation between the fitted values ​​of the active power curves s1 and s2 and the active power at several moments on day t. If the deviation is less than 1%, go to step 8);

[0051] 8) Obtain the total power generation curves s3 and s4 corresponding to the fraudulent wind turbines a and b on day t from the real-time database, where the total power generation is the power generation value since the wind turbines were connected to the grid;

[0052] 9) Determine the deviation between the fitting values ​​of the total power generation curves s3 and s4 and the total power generation at several moments on day t. When the deviation between the two is less than or equal to 1%, proceed to step 10);

[0053] 10) Query the daily power generation curves s5 and s6 corresponding to the fraudulent wind turbines a and b on day t from the real-time database;

[0054] 11) Determine the deviation between the fitted values ​​of the daily power generation curves s5 and s6 and the daily power generation at several moments on day t. When the deviation between the two is less than or equal to 1%, proceed to step 12);

[0055] 12. Query the real-time wind speed curves s7 and s8 corresponding to the fraudulent fans a and b on day t from the real-time database;

[0056] 13) Determine the deviation between the fitted values ​​of the real-time wind speed curves s7 and s8 and the real-time wind speed at several moments on day t. When the deviation between the two is less than or equal to 1%, proceed to step 14);

[0057] 14) Query the corresponding cabin temperature curves s9 and s10 of the fraudulent fans a and b on day t from the real-time database;

[0058] 15) Determine the deviation between the fitted values ​​of the cabin temperature curves s9 and s10 and the cabin temperatures at several times on day t. If the deviation is less than or equal to 1%, proceed to step 16);

[0059] 16) If the wind turbine data is falsified, the relevant site managers will be notified and ordered to make corrections, and the wind turbines that are not operating normally will be repaired or inspected.

[0060] Example 2

[0061] The system for identifying falsified wind turbine data according to the present invention comprises:

[0062] Identification module, used to identify wind turbines suspected of data falsification;

[0063] An acquisition module is used to obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines suspected of data falsification;

[0064] The determination module is used to compare the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database, so as to determine whether the data in the real-time database is falsified.

[0065] In this embodiment, the process of identifying wind turbines suspected of data falsification is as follows:

[0066] Obtain the real-time active power of all wind turbines at different times;

[0067] When the difference between the real-time active power of two wind turbines is less than x more than a preset number of times at the same time in one day, the two wind turbines are considered to be suspected of data falsification.

[0068] In this embodiment, the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of the wind turbine suspected of data falsification are compared with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve, and cabin temperature curve in the real-time database, respectively, to determine whether the data in the real-time database is falsified. The process is as follows:

[0069] When the deviation between the fitting value on the active power curve and the active power of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the total power generation curve and the total power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the daily power generation curve and the daily power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the real-time wind speed curve and the real-time wind speed of the wind turbine suspected of data falsification exceeds 1%, and the deviation between the fitting value on the cabin temperature curve and the cabin temperature of the wind turbine suspected of data falsification exceeds 1%, it is considered that the wind turbine data in the real-time database is falsified.

[0070] In this embodiment, the method further includes: issuing an early warning signal when it is believed that the wind turbine data in the real-time database is falsified.

[0071] The division of modules in the embodiments of the present application is illustrative and is merely a logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the present application may be integrated into a single processor, or may exist physically separately, or two or more modules may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or software functional modules.

[0072] Example 3

[0073] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for determining whether wind turbine data falsification are implemented include: identifying a wind turbine suspected of data falsification; obtaining the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of the wind turbine suspected of data falsification; and comparing the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve, and cabin temperature curve in a real-time database to determine whether the data in the real-time database is falsified. The memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus. The internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard architecture bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the programs may include program codes, and the program codes include computer operation instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0074] Example 4

[0075] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for determining whether wind turbine data is falsified, for example, including: identifying wind turbines suspected of data falsification; obtaining the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of the wind turbines suspected of data falsification; and comparing the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of the wind turbines suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve, and cabin temperature curve in a real-time database, respectively, to determine whether the data in the real-time database is falsified. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0076] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0077] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0078] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1The function specified in one or more boxes.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0080] Those skilled in the art will readily identify other embodiments of the present invention after considering the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0081] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0082] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for identifying falsified wind turbine data, characterized in that: include: Identify wind turbines suspected of data falsification; Obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines suspected of data falsification; The active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification are compared with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database to determine whether the data in the real-time database is falsified.

2. The method for identifying falsified wind turbine data according to claim 1, characterized in that: The process of identifying wind turbines suspected of data falsification is as follows: Obtain the real-time active power of all wind turbines at different times; When the difference between the real-time active power of two wind turbines is less than x more than a preset number of times at the same time in one day, the two wind turbines are considered to be suspected of data falsification.

3. The method for identifying falsified wind turbine data according to claim 1, characterized in that: The process of comparing the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database to determine whether the data in the real-time database is falsified is as follows: When the deviation between the fitting value on the active power curve and the active power of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the total power generation curve and the total power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the daily power generation curve and the daily power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the real-time wind speed curve and the real-time wind speed of the wind turbine suspected of data falsification exceeds 1%, and the deviation between the fitting value on the cabin temperature curve and the cabin temperature of the wind turbine suspected of data falsification exceeds 1%, it is considered that the wind turbine data in the real-time database is falsified.

4. The method for identifying falsified wind turbine data according to claim 1, characterized in that: Also includes: When it is believed that the wind turbine data in the real-time database is falsified, an early warning signal is issued.

5. A system for identifying falsified wind turbine data, characterized in that: include: Identification module, used to identify wind turbines suspected of data falsification; An acquisition module is used to obtain the active power, total power generation, daily power generation, real-time wind speed, and cabin temperature of wind turbines suspected of data falsification; The determination module is used to compare the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database, so as to determine whether the data in the real-time database is falsified.

6. The system for identifying falsified wind turbine data according to claim 5, characterized in that: The process of identifying wind turbines suspected of data falsification is as follows: Obtain the real-time active power of all wind turbines at different times; When the difference between the real-time active power of two wind turbines is less than x more than a preset number of times at the same time in one day, the two wind turbines are considered to be suspected of data falsification.

7. The system for identifying falsified wind turbine data according to claim 5, characterized in that: The process of comparing the active power, total power generation, daily power generation, real-time wind speed and cabin temperature of the wind turbine suspected of data falsification with the active power curve, total power generation curve, daily power generation curve, real-time wind speed curve and cabin temperature curve in the real-time database to determine whether the data in the real-time database is falsified is as follows: When the deviation between the fitting value on the active power curve and the active power of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the total power generation curve and the total power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the daily power generation curve and the daily power generation of the wind turbine suspected of data falsification exceeds 1%, the deviation between the fitting value on the real-time wind speed curve and the real-time wind speed of the wind turbine suspected of data falsification exceeds 1%, and the deviation between the fitting value on the cabin temperature curve and the cabin temperature of the wind turbine suspected of data falsification exceeds 1%, it is considered that the wind turbine data in the real-time database is falsified.

8. The system for identifying wind turbine data falsification according to claim 5, characterized in that: Also includes: When it is believed that the wind turbine data in the real-time database is falsified, an early warning signal is issued.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for determining whether wind turbine data is falsified are implemented as described in any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for determining whether wind turbine data is falsified are implemented as described in any one of claims 1 to 4.

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