A data inversion method, device, equipment and medium

Abstract

The present application belongs to the technical field of data processing, and particularly relates to a data inversion method, device, equipment and medium, and solves the problem that it is difficult to obtain relatively accurate hourly wind resource data according to existing data in the prior art. The data inversion method provided by the present application adjusts the mesoscale data by taking the characteristic data as an index, so that the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meets a preset standard, and the gradually hourly inversion data is obtained after collection and arrangement. The method provided by the present application realizes that the characteristics of the mesoscale data are close to the actual measurement data through modification of the mesoscale data, and can inversely obtain a set of hourly wind speed data according to the existing wind resource evaluation result.

Description

Technical Field

[0001] This invention belongs to the field of wind power generation, specifically relating to a data inversion method, apparatus, equipment, and medium. Background Technology

[0002] Since 2000, China's wind power development has been rapid. Centralized and distributed wind power projects have been developed in most parts of the country. Today, some of the early wind power projects have reached the end of their operational lifespan. These projects generally have the following options:

[0003] 1) Project life extension. Monitor the main equipment of the wind farm to obtain the project's health status, and repair or replace aging components. The ultimate goal is to extend the project's service life.

[0004] 2) Project decommissioning. After the project reaches its service life, it will be dismantled and the land restored to its original state.

[0005] 3) Upgrading and renovation projects using a large-scale replacement method. This involves dismantling existing wind turbines and installing new ones, as well as upgrading the substation equipment to meet the requirements of the new turbines. This achieves equipment renewal and iteration for the project. This type of work typically reuses some existing substation equipment, while the wind turbine equipment is usually upgraded, potentially resulting in a significant improvement in power generation capacity.

[0006] Generally, project owners prefer to use the third method to preserve and increase the value of their assets, namely, upgrading existing projects by replacing smaller ones with larger ones. In this case, a reassessment of the project's wind energy resources is necessary.

[0007] However, the operational status of wind turbines means that wind measurement results cannot accurately reflect the existing wind energy resources of wind farms. Most of the wind measurement data from the initial construction of wind farms has been lost. Although wind farm archives collect feasibility studies or preliminary design reports from the initial construction phase, which include assessments of wind energy resources, the lack of hourly data makes power generation capacity assessment difficult. How to obtain relatively accurate hourly wind resource data based on existing information, and then assess power generation, is a major problem facing wind resource engineers. Summary of the Invention

[0008] The purpose of this invention is to provide a data inversion method, apparatus, device and medium to solve the problem that it is difficult to obtain relatively accurate hourly wind resource data based on existing data in the prior art.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] In a first aspect, the present invention provides a data inversion method, comprising the following steps:

[0011] Obtain first-level mesoscale data of the wind power generation area;

[0012] Determine the wind measurement period for the actual wind measurement data;

[0013] Based on the wind measurement period of the actual wind measurement data, the first mesoscale data is truncated to obtain the second mesoscale data;

[0014] Determine the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and use the characteristic data as an indicator;

[0015] Adjust the second mesoscale data, determine the characteristic data of the adjusted second mesoscale data, and make the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meet the preset standard to obtain the third mesoscale data.

[0016] The third mesoscale data is collected and organized to obtain gradually smaller inversion data.

[0017] As a further improvement of the present invention, obtaining the first mesoscale data of the wind power generation area includes: determining the location of the wind measuring tower as the target area, and obtaining the original mesoscale data of the wind measuring tower location as the first mesoscale data.

[0018] As a further improvement of the present invention, in the step of determining the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and using the characteristic data as an indicator, the characteristic data includes daily variation, annual variation, frequency distribution and Weibull distribution.

[0019] As a further improvement of the present invention, the step of determining the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and using the characteristic data as an indicator, includes:

[0020] Obtain the feasibility study or preliminary design report for the wind power generation area, and determine the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data based on the feasibility study or preliminary design report.

[0021] As a further improvement of the present invention, based on the wind measurement period of the actual wind measurement data, the first mesoscale data is extracted, including: extracting the first mesoscale data for the same period as the wind measurement period of the actual wind measurement data.

[0022] As a further improvement of the present invention, the second mesoscale data is adjusted, and the characteristic data of the adjusted second mesoscale data is determined so that the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meets a preset standard, thereby obtaining the third mesoscale data, including:

[0023] Adjust the wind speed of the second mesoscale data so that the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data continuously approach the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data;

[0024] After each adjustment, compare the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data with the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data. If the daily variation, annual variation, frequency distribution, and Weibull distribution differ from the measured data by no more than a preset proportion, stop the adjustment operation and use the second mesoscale data at this time as the third mesoscale data.

[0025] As a further improvement of the present invention, the preset ratio is 3%.

[0026] In a second aspect, the present invention provides a data inversion apparatus, comprising:

[0027] The data acquisition module is used to acquire first-level mesoscale data of the wind power generation area;

[0028] The first determining module is used to determine the wind measurement period for the actual wind measurement data;

[0029] The data extraction module is used to extract data from the first mesoscale data based on the wind measurement period of the actual wind measurement data to obtain the second mesoscale data.

[0030] The second determining module is used to determine the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and to use the characteristic data as an indicator.

[0031] The data adjustment module is used to adjust the second mesoscale data, determine the characteristic data of the adjusted second mesoscale data, and make the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meet the preset standard to obtain the third mesoscale data.

[0032] The data processing module is used to collect and process the third mesoscale data to obtain gradually smaller inversion data.

[0033] In a third aspect, the present invention provides an electronic device including a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the data inversion method as described above.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium storing at least one instruction that, when executed by a processor, implements the data inversion method described above.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] The data inversion method provided by this invention uses characteristic data as an indicator to adjust mesoscale data, ensuring that the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meets a preset standard. After collection and processing, hourly inversion data is obtained. The method provided by this invention, through the modification of mesoscale data, achieves characteristics that closely resemble measured data, and can invert a set of hourly wind speed data based on existing wind resource assessment results. Attached Figure Description

[0037] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0038] Figure 1 This is a flowchart illustrating a data inversion method according to an embodiment of the present invention;

[0039] Figure 2 This is a structural block diagram of a data inversion device according to an embodiment of the present invention;

[0040] Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0041] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0042] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0043] Example 1

[0044] This invention provides a data inversion method that modifies mesoscale data to make its characteristics closely resemble measured data, and inverts a set of hourly wind speed data based on existing wind resource assessment results.

[0045] like Figure 1 As shown, a data inversion method includes the following steps:

[0046] S1. Obtain the first mesoscale data of the wind power generation area.

[0047] In one optional embodiment, obtaining the first mesoscale data of the wind power generation area includes: determining the location of the wind measurement tower as the target area, and obtaining the original mesoscale data of the wind measurement tower location as the first mesoscale data.

[0048] It is understood that the data obtained in this solution are all from the location of the wind measurement tower. The wind measurement tower referred to in this solution includes the tower body, which is equipped with anemometers, wind vanes, and monitoring equipment such as temperature and air pressure at different heights. It can continuously monitor the wind conditions at the wind farm site around the clock, and the measurement data is recorded and stored on a data logger installed on the tower body. The wind measurement tower is erected within the wind farm site and can be either a folding frame structure or a cylindrical structure.

[0049] S2. Determine the wind measurement period for the actual wind measurement data.

[0050] S3. Based on the wind measurement period of the actual wind measurement data, the first mesoscale data is truncated to obtain the second mesoscale data.

[0051] In one optional embodiment, first mesoscale data is extracted from the same time period as the actual wind measurement data. In this scheme, the extracted first mesoscale data corresponds to the wind measurement time period of the actual wind measurement data. Correspondingly, after modifying the mesoscale data of the wind measurement time period, the target data can be obtained.

[0052] S4. Determine the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and use the characteristic data as an indicator.

[0053] In one alternative embodiment, the characteristic data includes daily variation, annual variation, frequency distribution, and Weibull distribution.

[0054] In one specific embodiment, step S4 includes: obtaining a feasibility study or preliminary design report for the wind power generation area, and determining the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data based on the feasibility study or preliminary design report.

[0055] S5. Adjust the second mesoscale data, determine the characteristic data of the adjusted second mesoscale data, and make the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meet the preset standard to obtain the third mesoscale data.

[0056] In one optional embodiment, step S5 includes: adjusting the wind speed of the second mesoscale data so that the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data continuously approach the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data; after each adjustment, comparing the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data with the daily variation, annual variation, frequency distribution, and Weibull distribution of the actual wind measurement data; if the daily variation, annual variation, frequency distribution, and Weibull distribution differ from the measured data by no more than a preset proportion, stopping the adjustment operation, and using the second mesoscale data at this time as the third mesoscale data.

[0057] In one specific embodiment, the preset ratio is 3%.

[0058] This scheme selects representative characteristic data such as daily variation, annual variation, frequency distribution, and Weibull distribution as standards. The characteristic data indicate the degree of characteristic of the mesoscale data. When the characteristic data are close, the adjustment is considered to be complete.

[0059] S6. The third mesoscale data is collected and organized to obtain gradually smaller inversion data.

[0060] The data inversion method described above demonstrates that by revising mesoscale data, a set of hourly wind resource inversion data with wind resource characteristics close to the measured data can be obtained, thereby solving the problem of lack of hourly data in power generation assessment.

[0061] Example 2

[0062] like Figure 2 As shown, based on the same inventive concept as the above embodiments, the present invention also provides a data inversion apparatus, comprising:

[0063] The data acquisition module is used to acquire first-level mesoscale data of the wind power generation area;

[0064] The first determining module is used to determine the wind measurement period for the actual wind measurement data;

[0065] The data extraction module is used to extract data from the first mesoscale data based on the wind measurement period of the actual wind measurement data to obtain the second mesoscale data.

[0066] The second determining module is used to determine the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and to use the characteristic data as an indicator.

[0067] The data adjustment module is used to adjust the second mesoscale data, determine the characteristic data of the adjusted second mesoscale data, and make the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meet the preset standard to obtain the third mesoscale data.

[0068] The data processing module is used to collect and process the third mesoscale data to obtain gradually smaller inversion data.

[0069] Example 3

[0070] like Figure 3 As shown, the present invention also provides an electronic device 100 for implementing a data inversion method of Embodiment 1;

[0071] The electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on at least one processor 102, and at least one communication bus 104.

[0072] The memory 101 can be used to store computer program 103. The processor 102 implements the steps of a data inversion method of Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101.

[0073] The memory 101 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0074] At least one processor 102 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. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0075] The memory 101 in the electronic device 100 stores multiple instructions to implement a data inversion method, and the processor 102 can execute multiple instructions to achieve the following:

[0076] Obtain first-level mesoscale data of the wind power generation area;

[0077] Determine the wind measurement period for the actual wind measurement data;

[0078] Based on the wind measurement period of the actual wind measurement data, the first mesoscale data is truncated to obtain the second mesoscale data;

[0079] Determine the characteristic data of the actual wind measurement data and the characteristic data of the second mesoscale data, and use the characteristic data as an indicator;

[0080] Adjust the second mesoscale data, determine the characteristic data of the adjusted second mesoscale data, and make the difference between the characteristic data of the adjusted second mesoscale data and the characteristic data of the actual wind measurement data meet the preset standard to obtain the third mesoscale data.

[0081] The third mesoscale data is collected and organized to obtain gradually smaller inversion data.

[0082] Example 4

[0083] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0089] 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 data inversion method, characterized in that, If the hourly wind measurement data from the initial construction of the wind power generation area has been lost, but the feasibility study or preliminary design report is retained in the wind farm archives, the following steps are included: The location of the wind measurement tower is determined as the target area, and the original mesoscale data of the wind measurement tower location is obtained as the first mesoscale data; Determine the wind measurement period of the actual wind measurement data, and extract the first mesoscale data that is in the same period as the wind measurement period of the actual wind measurement data to obtain the second mesoscale data; Obtain the feasibility study or preliminary design report of the wind power generation area, determine the daily variation, annual variation, frequency distribution and Weibull distribution of the actual wind measurement data based on the feasibility study or preliminary design report, and determine the daily variation, annual variation, frequency distribution and Weibull distribution of the second mesoscale data, and use the daily variation, annual variation, frequency distribution and Weibull distribution as adjustment indicators; The wind speed of the second mesoscale data is adjusted so that the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data are continuously closer to those of the actual wind measurement data. After each adjustment, a comparison is made. When the difference between the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data and the actual wind measurement data does not exceed 3%, the adjustment is stopped, and the second mesoscale data at this time is used as the third mesoscale data. The third mesoscale data is collected and organized to obtain hourly inversion data.

2. A data inversion device, characterized in that, This is used for data inversion in situations where hourly actual wind measurement data from the initial construction of a wind power generation area has been lost, but the feasibility study or preliminary design report is retained in the wind farm archives. This includes: The data acquisition module is used to determine the location of the wind measurement tower as the target area and acquire the original mesoscale data of the wind measurement tower location as the first mesoscale data. The first determining module is used to determine the wind measurement period of the actual wind measurement data; The data extraction module is used to extract first mesoscale data that is in the same time period as the actual wind measurement data to obtain second mesoscale data. The second determining module is used to obtain the feasibility study or preliminary design report of the wind power generation area, determine the daily variation, annual variation, frequency distribution and Weibull distribution of the actual wind measurement data according to the feasibility study or preliminary design report, and determine the daily variation, annual variation, frequency distribution and Weibull distribution of the second mesoscale data, and use the daily variation, annual variation, frequency distribution and Weibull distribution as adjustment indicators; The data adjustment module is used to adjust the wind speed of the second mesoscale data so that the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data are continuously closer to those of the actual wind measurement data. After each adjustment, a comparison is made. When the difference between the daily variation, annual variation, frequency distribution, and Weibull distribution of the second mesoscale data and the actual wind measurement data does not exceed 3%, the adjustment is stopped, and the second mesoscale data at this time is used as the third mesoscale data. The data processing module is used to collect and process the third mesoscale data to obtain hourly inversion data.

3. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the data inversion method of claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the data inversion method of claim 1.

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