Wind power plant wake flow evaluation method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of wind power generation, in particular to a wind power plant wake flow evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: providing initial conditions and boundary conditions based on global reanalysis data; preprocessing the numerical weather forecasting mode based on the initial condition and the boundary condition, presetting a fan parameter scheme, running the preprocessed numerical weather forecasting mode based on the fan parameter scheme, and obtaining a WRF output file considering the fan influence and a WRF output file not considering the fan influence; and obtaining the influence of the fan on the atmosphere by using the WRF output file considering the fan influence and the WRF output file not considering the fan influence, and calculating to obtain wind power plant wake flow data. Through a numerical weather forecast mode based on a fan parameterization model, wake flow characteristic length and wake flow area wind speed reduction proportion characteristic parameters of a wind power plant are identified, a three-dimensional space-time evolution rule of a wind power plant wake flow area is researched, fan arrangement of an electric field is optimized, and micro-siting is guided.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and in particular to a method, device, electronic device and storage medium for evaluating a wind farm wake. Background Art

[0002] As the clean energy technology with the greatest decarbonization potential, wind energy is an important driving force for addressing climate change, helping the world reduce 1.1 billion tons of carbon dioxide emissions each year. Global wind power installed capacity is growing rapidly, wind power development is gradually moving towards the deep sea, and the units are gradually becoming larger. In order to improve the wind energy capture and power generation capacity of wind turbines, the size of wind turbines has gradually increased, and the length of blades has gradually increased. The diameter of wind turbines has reached 236 meters (Musial et al., 2022). As wind turbines become larger, the loss of wake is more obvious. The wake loss of wind farms may cause considerable capacity loss, especially when the wind speed is lower than the rated wind speed. It is crucial to improve the economic benefits of wind power generation. In the design and planning of wind farms, dozens of wind turbines are often arranged according to a certain rule. When the spacing and arrangement of wind turbines are unreasonable, the wake effect greatly affects the power generation benefits. At present, the research on wind turbine wake at home and abroad is mainly based on the wake model of numerical calculation and analysis. The structure is simple and the error is large. It is impossible to obtain the wind farm wake characteristics that consider the real atmospheric motion state under actual engineering conditions. Summary of the invention

[0003] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0004] To this end, the first purpose of this application is to propose a wind farm wake assessment method to solve the problems that the existing technical means for studying wind turbine wakes are mainly based on the wake model of numerical calculation and analysis, which has a simple structure and large errors, and cannot obtain the wind farm wake characteristics that consider the real atmospheric motion state under actual engineering conditions.

[0005] The second object of the present application is to provide a device.

[0006] The third objective of the present application is to provide an electronic device.

[0007] A fourth objective of the present application is to provide a computer-readable storage medium.

[0008] The fifth objective of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first embodiment of the present application proposes a method for evaluating a wind farm wake, comprising:

[0010] Providing initial and boundary conditions based on global reanalysis data;

[0011] Preprocessing the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model;

[0012] Preset a wind turbine parameter scheme, run the preprocessing numerical weather forecast model based on the wind turbine parameter scheme, and obtain a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine;

[0013] The WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine are used to obtain the influence of the wind turbine on the atmosphere, and the wind farm wake data is calculated.

[0014] Preferably, the preprocessing of the numerical weather forecast model based on the initial condition and the boundary condition to obtain the preprocessed numerical weather forecast model comprises:

[0015] Preprocess the numerical weather forecast model, set the model grid, nested mode running time, extract terrain data, decompress the data, perform horizontal interpolation, and set the sub-grid parameterization scheme of the WRF model's microphysics, cumulus, radiation, and boundary layer.

[0016] Preferably, the preset fan parameter scheme includes:

[0017] Set up the wind turbine parameterization scheme, determine the basic parameters, thrust coefficient curve and power output curve of the wind turbine, set the position of each wind turbine in the wind farm in the model, the rated power of the wind turbine, rated wind speed, cut-in wind speed, cut-out wind speed, rotor diameter and hub height wind speed parameters, and perform vertical interpolation.

[0018] Preferably, the running of the preprocessing numerical weather forecast model based on the wind turbine parameter scheme to obtain a WRF output file considering the influence of the wind turbine and a WRF output file not considering the influence of the wind turbine comprises:

[0019] Conduct simulation tests considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model based on wind turbine parameterization, and obtain the WRF output file considering the influence of wind turbines;

[0020] Carry out simulation tests without considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model without considering the influence of wind turbines, and obtain the WRF output file without considering the influence of wind turbines.

[0021] Preferably, the step of obtaining the influence of wind turbines on the atmosphere by using the WRF output file considering the influence of wind turbines and the WRF output file not considering the influence of wind turbines to calculate the wind farm wake data comprises:

[0022] Subtracting the WRF output file with the wind turbine effect from the WRF output file without considering the wind turbine effect to obtain the wind turbine effect on the atmosphere;

[0023] Based on the impact of the wind turbine on the atmosphere, the wind speed distribution is analyzed, the wake area downstream of the wind farm is identified, the wind speed reduction ratio and the characteristic length of the wake area are calculated, and the three-dimensional spatiotemporal evolution law of the wake is analyzed to guide the micro-site selection of the wind farm.

[0024] Preferably, the calculation formula for the impact of the fan on the atmosphere is:

[0025] wrfout3=wrfout1-wrfout2

[0026] Among them, wrfout3 is the impact of wind turbines on the atmosphere, wrfout1 is the WRF output file considering the impact of wind turbines, and wrfout2 is the WRF output file without considering the impact of wind turbines.

[0027] To achieve the above-mentioned purpose, the second embodiment of the present application proposes a wind farm wake assessment device, comprising:

[0028] Initial conditions module, which provides initial and boundary conditions based on global reanalysis data;

[0029] A preprocessing module, which preprocesses the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model;

[0030] A calculation module, presetting a wind turbine parameter scheme, running the preprocessing numerical weather forecasting model based on the wind turbine parameter scheme, and obtaining a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine;

[0031] The analysis module uses the WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine to obtain the influence of the wind turbine on the atmosphere and calculate the wind farm wake data.

[0032] To achieve the above-mentioned purpose, the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0033] The memory stores computer-executable instructions;

[0034] The processor executes the computer-executable instructions stored in the memory to implement any of the above methods.

[0035] To achieve the above-mentioned purpose, the fourth aspect embodiment of the present application proposes a computer-readable storage medium, including computer-executable instructions stored in the computer-readable storage medium, and the computer-executable instructions are used to implement any of the methods described above when executed by a processor.

[0036] To achieve the above-mentioned purpose, the fifth aspect of the present application proposes a computer program product, including a computer program / instructions, which implement the method described in the first aspect when executed by a processor.

[0037] The present application provides a method for evaluating the wake of a wind farm. The method obtains the atmospheric motion state under the interaction between the atmospheric boundary layer and the actual wind turbine generator set through the coupling effect of a weather forecast model and a wind turbine parameterized model. The method grasps the influence of the atmospheric boundary layer corresponding to the actual existence of the wind turbine through the wind turbine parameterized model, obtains the three-dimensionally distributed wind farm information, identifies and obtains the precise three-dimensional spatial distribution characteristics of the wake area of ​​the wind farm, obtains the spatiotemporal distribution characteristics such as the characteristic length of the wind turbine wake and the wind speed reduction ratio in the wind turbine wake area, identifies the wind speed distribution in the wind farm wake area, studies the three-dimensional spatial characteristics and change laws of the wind turbine wake, and provides guidance for the micro-site selection of wind farms and the optimal arrangement of wind turbines.

[0038] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0040] Figure 1 A flowchart of a first specific embodiment of a method for evaluating a wind farm wake provided by the present invention;

[0041] Figure 2 This is a flow chart of a method for evaluating the wind farm wake based on numerical weather forecast model;

[0042] Figure 3 A structural block diagram of a wind farm wake assessment device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The core of the present invention is to provide a wind farm wake assessment method, device, electronic device and storage medium. Through a numerical weather forecast model based on a wind turbine parameterized model, characteristic parameters such as the characteristic length of the wind farm wake and the wind speed reduction ratio in the wake area are identified, and the three-dimensional spatiotemporal evolution law of the wind farm wake area is studied. This is used to optimize the layout of wind turbines in wind farms and guide micro-site selection.

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. 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.

[0045] Please refer to Figure 1 , Figure 1 This is a flow chart of a first specific embodiment of a method for evaluating a wind farm wake provided by the present invention; the specific operation steps are as follows:

[0046] Step S101: providing initial conditions and boundary conditions based on global reanalysis data;

[0047] Step S102: preprocessing the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model;

[0048] Preprocess the numerical weather forecast model, set the model grid, nested mode running time, extract terrain data, decompress the data, perform horizontal interpolation, and set the sub-grid parameterization scheme of the WRF model's microphysics, cumulus, radiation, and boundary layer.

[0049] Step S103: Preset a wind turbine parameter scheme, run the preprocessing numerical weather forecast model based on the wind turbine parameter scheme, and obtain a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine;

[0050] Set up the wind turbine parameterization scheme, determine the basic parameters, thrust coefficient curve and power output curve of the wind turbine, set the position of each wind turbine in the wind farm in the model, the rated power of the wind turbine, rated wind speed, cut-in wind speed, cut-out wind speed, rotor diameter and hub height wind speed parameters, and perform vertical interpolation.

[0051] Conduct simulation tests considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model based on wind turbine parameterization, and obtain the WRF output file considering the influence of wind turbines;

[0052] Carry out simulation tests without considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model without considering the influence of wind turbines, and obtain the WRF output file without considering the influence of wind turbines.

[0053] Step S104: using the WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine to obtain the influence of the wind turbine on the atmosphere, and calculating the wind farm wake data.

[0054] Subtracting the WRF output file with the wind turbine effect from the WRF output file without considering the wind turbine effect to obtain the wind turbine effect on the atmosphere;

[0055] Based on the impact of the wind turbine on the atmosphere, the wind speed distribution is analyzed, the wake area downstream of the wind farm is identified, the wind speed reduction ratio and the characteristic length of the wake area are calculated, and the three-dimensional spatiotemporal evolution law of the wake is analyzed to guide the micro-site selection of the wind farm.

[0056] The calculation formula for the impact of the fan on the atmosphere is:

[0057] wrfout3=wrfout1-wrfout2

[0058] Among them, wrfout3 is the impact of wind turbines on the atmosphere, wrfout1 is the WRF output file considering the impact of wind turbines, and wrfout2 is the WRF output file without considering the impact of wind turbines.

[0059] This embodiment provides a method for evaluating the wake of a wind farm. The method uses the numerical weather forecast model WRF to couple with a wind turbine model to perform integral operations, obtains the state of the atmospheric boundary layer when the wind turbine is present, obtains the three-dimensional wind speed distribution and identifies the wind turbine wake area, conducts research on the wind speed distribution characteristics inside the wind farm and in the wake area, systematically studies the three-dimensional spatial characteristics and variation laws of the wind turbine wake, identifies the width and propagation of the wake from the wake point to the near wake area and the far wake area, calculates the wind speed reduction ratio of the wake area, the wake length and other spatiotemporal distribution characteristics, and analyzes the three-dimensional spatiotemporal evolution law of the wake, thereby providing guiding suggestions for micro-site selection and optimal arrangement of wind turbines in wind farms.

[0060] Based on the above embodiment, this embodiment describes a method for evaluating the wake of a wind farm. Figure 2 As shown, the details are as follows:

[0061] Wake effect: refers to the phenomenon that wind speed decreases downstream while wind turbines obtain energy from the wind. The reduction of wind speed in the wake area will cause the loss of power generation of wind turbines in the wake area. In addition, the reduction of wind speed in the wake area will increase the turbulence intensity and affect the fatigue load and aerodynamic performance of wind turbines. The energy loss caused by the wake effect has an important impact on the operating income of wind farms.

[0062] The WRF model is a mainstream numerical model used in atmospheric science research. It is often used in regional weather forecasts and numerical simulations with spatial scales ranging from tens of meters to thousands of meters and time scales within a week. It has the advantages of flexibility, efficiency and advancement. Its ARW dynamic kernel is fully compressible and non-static. The WRF-ARW model has a complete pre-processing system, flexible and changeable spatial regions, grid nesting design and rich physical process parameterization schemes. It is widely used in atmospheric science operational forecasts and scientific research. In order to study the interaction between wind farms and the atmosphere under the WRF model, Fitch et al. proposed a wind farm parameterization (WFP) model that applies a momentum source to the mean flow field. The model assumes that part of the energy obtained by the wind turbine from the environment is converted into electrical energy, and the rest is converted into turbulent kinetic energy.

[0063] Global reanalysis data for the time period of wind resource assessment are selected to provide initial and boundary conditions.

[0064] The numerical weather forecast model performs WPS preprocessing, sets the model grid, nested mode running time, etc., extracts terrain data, decompresses the data, and performs horizontal interpolation. Set the subgrid parameterization schemes for microphysics, cumulus, radiation, boundary layer, etc. of the WRF model.

[0065] Carry out simulation tests on the interaction between the considered wind turbine and the real atmosphere, set up the wind turbine parameterization scheme, determine the basic parameters, thrust coefficient curve and power output curve of the wind turbine, set the position of each wind turbine in the wind farm in the model, the rated power of the wind turbine, rated wind speed, cut-in wind speed, cut-out wind speed, rotor diameter, hub height and other wind speed parameters, perform vertical interpolation, run the WRF model based on wind turbine parameterization, and obtain the WRF output file wrfout1 that takes the influence of wind turbine into account in the real atmosphere.

[0066] Carry out simulation tests without considering the wind turbines, perform vertical interpolation, run the WRF model without considering the influence of wind turbines, and obtain the WRF output file wrfout2 of the real atmosphere without considering the influence of wind turbines.

[0067] By subtracting the simulation results of the interaction between the fan and the real atmosphere from the simulation results of the fan not being considered, the impact of the fan on the atmospheric environment is obtained, namely wrfout3.

[0068] Analyze wind farm characteristics based on wrfout3 files, identify the wake area downstream of the wind farm, calculate the wind speed reduction ratio and wake length of the wind turbine, and analyze the three-dimensional spatiotemporal evolution of the wake. Carry out numerical weather forecast calculations based on wind turbine parameterization under various wind turbine arrangements, evaluate the wake generated by wind farms under different wind turbine arrangement conditions, and recommend wind turbine arrangement plans based on wake effects for micro-site selection of wind farms.

[0069] A wind farm wake assessment method provided by an embodiment of the present invention utilizes a numerical weather forecast model based on a wind turbine parameterized model to analyze the wind farm wake characteristics obtained under the interaction between the real atmospheric boundary layer and the wind turbine, obtain the precise three-dimensional spatial distribution characteristics of the wind farm wake area, accurately obtain the wind turbine wake characteristic length, wind speed reduction ratio and other spatiotemporal distribution characteristics of the wind turbine wake area, correct the wind farm unit design wake parameters, and can be used for wind farm micro-site selection and optimization of wind turbine layout.

[0070] Please refer to Figure 3 , Figure 3 A structural block diagram of a wind farm wake assessment device provided by an embodiment of the present invention; the specific device may include:

[0071] An initial condition module 100 provides initial conditions and boundary conditions based on global reanalysis data;

[0072] A preprocessing module 200 preprocesses the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model;

[0073] The calculation module 300 presets a wind turbine parameter scheme, runs the preprocessing numerical weather forecast model based on the wind turbine parameter scheme, and obtains a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine;

[0074] The analysis module 400 uses the WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine to obtain the influence of the wind turbine on the atmosphere, and calculates the wind farm wake data.

[0075] A wind farm wake assessment device of the present embodiment is used to implement the aforementioned wind farm wake assessment method. Therefore, the specific implementation method of a wind farm wake assessment device can be seen in the embodiment part of a wind farm wake assessment method in the previous text. For example, the initial condition module 100, the preprocessing module 200, the calculation module 300, and the analysis module 400 are respectively used to implement steps S101, S102, S103, and S104 in the aforementioned wind farm wake assessment method. Therefore, its specific implementation method can refer to the description of the corresponding various parts of the embodiment, which will not be repeated here.

[0076] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0077] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0078] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0079] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0080] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0081] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0082] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0083] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0084] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0085] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0086] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0087] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0088] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0089] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for evaluating a wind farm wake, characterized in that: include: Providing initial and boundary conditions based on global reanalysis data; Preprocessing the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model; Preset a wind turbine parameter scheme, run the preprocessing numerical weather forecast model based on the wind turbine parameter scheme, and obtain a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine; The WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine are used to obtain the influence of the wind turbine on the atmosphere, and the wind farm wake data is calculated.

2. The method for evaluating the wind farm wake according to claim 1, characterized in that: The preprocessing of the numerical weather forecast model based on the initial condition and the boundary condition to obtain the preprocessed numerical weather forecast model includes: Preprocess the numerical weather forecast model, set the model grid, nested mode running time, extract terrain data, decompress the data, perform horizontal interpolation, and set the sub-grid parameterization scheme of the WRF model's microphysics, cumulus, radiation, and boundary layer.

3. The method for evaluating the wind farm wake according to claim 1, characterized in that: The preset fan parameter scheme includes: Set up the wind turbine parameterization scheme, determine the basic parameters, thrust coefficient curve and power output curve of the wind turbine, set the position of each wind turbine in the wind farm in the model, the rated power of the wind turbine, rated wind speed, cut-in wind speed, cut-out wind speed, rotor diameter and hub height wind speed parameters, and perform vertical interpolation.

4. The method for evaluating the wind farm wake according to claim 1, characterized in that: The step of running the preprocessing numerical weather forecast model based on the wind turbine parameter scheme to obtain a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine comprises: Conduct simulation tests considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model based on wind turbine parameterization, and obtain the WRF output file considering the influence of wind turbines; Carry out simulation tests without considering the interaction between wind turbines and the real atmosphere, perform vertical interpolation, run the WRF model without considering the influence of wind turbines, and obtain the WRF output file without considering the influence of wind turbines.

5. The method for evaluating the wind farm wake according to claim 1, characterized in that: The method of using the WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine to obtain the influence of the wind turbine on the atmosphere and calculating the wind farm wake data includes: Subtracting the WRF output file with the wind turbine effect from the WRF output file without considering the wind turbine effect to obtain the wind turbine effect on the atmosphere; Based on the impact of the wind turbine on the atmosphere, the wind speed distribution is analyzed, the wake area downstream of the wind farm is identified, the wind speed reduction ratio and the characteristic length of the wake area are calculated, and the three-dimensional spatiotemporal evolution law of the wake is analyzed to guide the micro-site selection of the wind farm.

6. The method for evaluating the wind farm wake according to claim 5, characterized in that: The calculation formula for the impact of the fan on the atmosphere is: wrfout3=wrfout1-wrfout2 Among them, wrfout3 is the impact of wind turbines on the atmosphere, wrfout1 is the WRF output file considering the impact of wind turbines, and wrfout2 is the WRF output file without considering the impact of wind turbines.

7. A wind farm wake assessment device, characterized in that: include: Initial conditions module, which provides initial and boundary conditions based on global reanalysis data; A preprocessing module, which preprocesses the numerical weather forecast model based on the initial condition and the boundary condition to obtain a preprocessed numerical weather forecast model; A calculation module, presetting a wind turbine parameter scheme, running the preprocessing numerical weather forecasting model based on the wind turbine parameter scheme, and obtaining a WRF output file that considers the influence of the wind turbine and a WRF output file that does not consider the influence of the wind turbine; The analysis module uses the WRF output file considering the influence of the wind turbine and the WRF output file not considering the influence of the wind turbine to obtain the influence of the wind turbine on the atmosphere and calculate the wind farm wake data.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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