Modeling system and modeling method for wind power generation equipment

Abstract

The invention provides a wind power generation equipment modeling system and modeling method, and relates to the field of wind power generation. Comprising the steps that wind power generation equipment in different areas monitors output power data, external environment parameters and hardware parameters in a plurality of preset time periods, and an anemometer tower monitors external wind environment parameters in different areas in a plurality of preset time periods. A plurality of groups of output power maximum values, hardware effective influence parameters and external environment effective influence parameters are obtained and determined by analyzing modeling equipment, modeling is carried out through a polynomial expansion method, the ratio of the maximum power generation efficiency of each wind power generation equipment to hardware is obtained, modeling is completed, modeling application is carried out by matching different areas, and the modeling efficiency of the wind power generation equipment is improved. Or modeling of wind power generation equipment at different heights in multiple areas is carried out in combination with different external wind environment parameters. Through the modeling system and the modeling method, modeling of the maximum power generation efficiency / hardware cost ratio of the wind power generation equipment in different areas is achieved, and reasonable modeling processing before batch installation of the wind power generation equipment is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a wind power generation equipment modeling system and a modeling method. Background Art

[0002] When wind power generation equipment is installed in different environmental areas, it needs better hardware parameters suitable for the regional wind environment to achieve the maximum power generation efficiency / hardware cost ratio. Hardware such as wind rotors, generators, blades, and towers are all important hardware parts that affect power generation efficiency. Appropriate hardware parameters and hardware costs, as well as adaptation to different wind environments in multiple regions, are important factors in achieving the maximum power generation efficiency / hardware cost ratio.

[0003] In various areas with different wind environments, how to properly monitor and analyze different wind environments, hardware parameters, and costs, and based on the actual operating conditions such as the power generation efficiency of wind power generation equipment and combined with effective operating conditions, obtain the maximum power generation efficiency of wind power generation equipment in multiple different areas, as well as the maximum power generation efficiency / hardware cost ratio through modeling is an urgent problem to be solved. Even how to analyze and process the existing small number of wind power generation equipment, and combine the actual wind environment analysis and processing in multiple regions to obtain a higher power generation efficiency / hardware cost ratio of wind power generation equipment in different regions, so as to adapt to better wind power generation equipment hardware parameters in different regions and different wind environments and installation settings suitable for different wind environments in different regions, there is an urgent need for a modeling system and method for wind power generation equipment to achieve this goal. Summary of the invention

[0004] To solve the problems in the above background technology or at least a part of them, the present invention provides a wind power generation equipment modeling system and a modeling method.

[0005] In a first aspect, the present invention provides a wind power generation equipment modeling system, comprising a plurality of first monitoring and storage modules, which are respectively arranged in the first control systems of a plurality of wind power generation equipment in a plurality of regions, and are used to monitor the output power data of a plurality of wind power generation equipment in a plurality of preset time periods in different regions, and the external environment parameters monitored by the designated wind power generation equipment corresponding to the output power data, and store them in the first data storage unit and the second data storage unit of the plurality of first monitoring and storage modules respectively, and store the real-time hardware parameters of the corresponding wind power generation equipment in a plurality of preset time periods in the third data storage unit of the plurality of first monitoring and storage modules;

[0006] It also includes a plurality of second monitoring and storage modules, which are respectively arranged in the second control systems of the wind towers in the plurality of regions, and monitor the external wind environment parameters at a plurality of different heights in different regions in the plurality of preset time periods and store the parameters in the fourth data storage unit arranged therein;

[0007] It also includes an analysis and modeling device, which, when establishing connections with the plurality of first monitoring storage modules respectively, receives and stores the output power data, external environment parameters, and real-time hardware parameters in the first data storage unit, the second data storage unit, and the third data storage unit sent by the plurality of first monitoring storage modules in a plurality of preset time periods correspondingly by the plurality of first storage units, the second data storage unit, and the third data storage unit;

[0008] When the analysis and modeling device establishes connections with the plurality of second monitoring storage modules respectively, the plurality of fourth storage units provided with the second storage modules receive and store the external wind environment parameters in the plurality of preset time periods sent by the fourth data storage units of the plurality of second monitoring storage modules;

[0009] The analysis and modeling device receives and stores multiple sets of output power data of multiple wind power generation equipment within multiple preset time periods, external environmental parameters corresponding to the output power data, and corresponding real-time hardware parameters, and further processes the multiple sets of output power data, external environmental parameters, and hardware parameters through a built-in central processing module, and obtains the effective maximum values ​​of the multiple sets of output power of multiple regions in multiple preset time periods and the corresponding characteristic values ​​that effectively affect the external environmental parameters and the hardware parameters according to the processing;

[0010] The analytical modeling device is based on the effective maximum output power of multiple wind power generation equipment, combined with the corresponding effective hardware parameter characteristic values ​​and effective external environment parameter characteristic values, and constructs a model through the polynomial expansion method to deduce the maximum power generation efficiency of each wind power generation equipment, and obtains the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation equipment, and according to the modeling results of the wind power generation equipment, compares and adapts the characteristic values ​​of its effective external environment parameters with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, so as to achieve the matching application of the modeling results of the wind power generation equipment in different regions; or, the analytical modeling device is based on the effective maximum output power of multiple wind power generation equipment, combined with the corresponding effective hardware parameter characteristic values, effective external environment parameter characteristic values, and external wind environment parameter characteristic values ​​at different heights in different regions, obtains the output power data of multiple wind power generation equipment through Monte Carlo simulation, and constructs a model using the polynomial expansion method to deduce the maximum power generation efficiency of each wind power generation equipment at different heights in multiple regions, and obtains the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation equipment applied to multiple regions and at different heights.

[0011] Preferably, in the matching application of the modeling results and in obtaining the output power through Monte Carlo simulation and modeling with the polynomial expansion method, the characteristic values ​​of the external wind environment parameters at different heights in different regions are compared and matched in the same proportion with the wind speed and wind direction parameter indicators of the wind speed and wind direction parameter indicators in the characteristic values ​​of the parameters that effectively affect the external environment, so as to verify their effectiveness and establish the characteristic values ​​of the parameters that effectively affect the external wind environment, so as to further realize the matching application of the modeling results of wind power generation equipment in different regions, or further obtain the output power data of multiple wind power generation equipment through Monte Carlo simulation, and construct the model using the polynomial expansion method.

[0012] Preferably, when there are multiple wind power generation equipments installed in the several areas, they include at least two or more wind power generation equipments with different hardware parameters; and the differences in hardware parameters and the monitored external environmental parameters are realized by installing multiple wind power generation equipments in multiple environmental areas with different external wind environment parameters respectively; so that the analysis and modeling equipment can integrate multiple differences, as well as combine the differences or references of the external wind environment parameters of the wind measurement tower, to achieve the modeling of multiple wind power generation equipments in multiple areas under different external wind environment parameters or the application of further modeling results.

[0013] Preferably, the output power data monitored by the wind power generation equipment is measured by connecting a power meter to the output end of the wind power generation equipment, and the monitored output power data is sent by connecting to the first monitoring storage module and stored in the first data storage unit of the first monitoring storage module;

[0014] The external environmental parameters of the wind power generation equipment include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, which are connected to the first monitoring storage module through the equipment anemometer / wind speed sensor to send the monitored external environmental parameters and store them in the second data storage unit in the first monitoring storage module;

[0015] The hardware parameter indicators of the wind power generation equipment include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, which are stored in the third data storage unit in the first monitoring storage module, and according to the update of the hardware parameters and the use of the iteration cycle, multiple preset time periods are set, and within the specified multiple preset time periods, the hardware parameters are all referred to and stored as real-time hardware parameters;

[0016] The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured by multiple wind measuring towers through wind measuring equipment, and the wind measuring equipment is connected to the second monitoring storage module to send the measured external wind environment parameters and store them in the fourth data storage unit.

[0017] Preferably, the first control system of the wind power generation equipment also includes a first clock module configured with an RTC chip, which assists in the establishment of multiple preset time periods; when sending and storing output power data, external environmental parameters, and real-time hardware parameters to the first data storage unit, the second data storage unit, and the third data storage unit of the first control system, the first clock module generates timestamps corresponding to the various types of data and stores them in the first data storage unit, the second data storage unit, and the third data storage unit, so that the analysis and modeling device receives the various types of data of each wind power generation equipment while receiving its timestamp data, and the analysis and modeling device retrieves the output power data, external environmental parameters, and real-time hardware parameters within the specified preset time period according to multiple timestamps to implement modeling of the wind power generation equipment.

[0018] Preferably, the second control system of the wind tower also includes a second clock module configured with an RTC chip, which assists in the establishment of multiple preset time periods; when sending and storing wind speed and wind direction measurement data at multiple different heights to the fourth data storage unit of the second control system, the second clock module generates a timestamp for the corresponding measurement data and stores it in the fourth data storage unit, so that the analysis and modeling device receives the measurement data of the wind tower at the same time as its timestamp data, and the analysis and modeling device retrieves the measurement data within the specified preset time period according to multiple timestamps to implement the modeling of the wind power generation equipment or provide the application of the results after the wind power generation equipment is modeled.

[0019] In a second aspect, the present invention provides a method for modeling a wind power generation device, comprising the following steps:

[0020] S1: for a plurality of wind power generation equipment in a plurality of different regions, respectively collect their output power data and external environment parameters corresponding to the output power data in a plurality of preset time periods, and store them in a first data storage unit and a second data storage unit of the wind power generation equipment, respectively; and collect the hardware parameters of the corresponding wind power generation equipment in a plurality of preset time periods, and store them in a third data storage unit of the wind power generation equipment;

[0021] S2: by connecting the first monitoring storage module of the plurality of wind power generation equipment to the analysis modeling device, obtaining and storing a plurality of groups of monitored output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation equipment, wherein the plurality of groups of monitored hardware parameters and / or external environmental parameters are different, and the plurality of groups of output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation equipment are respectively stored in a plurality of groups of first storage units, a second storage unit and a third storage unit of the first storage module of the analysis modeling device;

[0022] S3: analyzing the probability distribution of output power maximization in each group of output power data;

[0023] S4: determining, according to the curve distribution of the output power values ​​in the plurality of groups of output power data, the effective maximum value that can represent each group of output power, and determining the characteristic values ​​of the hardware parameters and the external environment parameters corresponding to the effective maximum value of each group of output power;

[0024] S5: according to the influence degree of different hardware parameters and external environment parameters on the output power of multiple wind power generation equipment, effectively influencing hardware parameters and effectively influencing external environment parameters are determined from multiple sets of hardware parameters and external environment parameters;

[0025] S6: In the plurality of preset time periods, a plurality of wind towers are used to monitor a plurality of sets of external wind environment parameters at different heights in a plurality of different areas and the sets of external wind environment parameters are stored in a plurality of fourth data storage units provided in the plurality of wind towers, respectively; and an analysis and modeling device is connected to the second monitoring storage modules of the plurality of wind towers to receive and store the sets of external wind environment parameters in the plurality of fourth storage units provided in the second storage modules;

[0026] S7: The analysis modeling device is based on the effective maximum output power of multiple wind power generation equipment, combined with the corresponding effective influencing hardware parameters and effective influencing external environmental parameter characteristic values, and uses the polynomial expansion method to construct a model to deduce the maximum power generation efficiency of each wind power generation equipment, and combines its hardware cost to obtain the ratio of the maximum power generation efficiency to the hardware cost, thereby completing the modeling of multiple wind power generation equipment; and according to the modeling results of the wind power generation equipment, by comparing and adapting the characteristic values ​​of its effective influencing external environmental parameters with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, the matching application of the modeling results of the wind power generation equipment in different regions is achieved;

[0027] Alternatively, the analysis and modeling device is based on the effective maximum output power of multiple wind power generation equipment, and obtains the output power data of multiple wind power generation equipment through Monte Carlo simulation by combining the corresponding effective influencing hardware parameters, the effective influencing external environmental parameter characteristic values, and the external wind environment parameters at different heights in different regions, and constructs a model using the polynomial expansion method to calculate the maximum power generation efficiency of each wind power generation equipment at different heights in multiple regions, and obtains the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation equipment applied to multiple regions and at different heights.

[0028] Preferably, in the S7 step, when the output power data of multiple wind power generation equipment are obtained by Monte Carlo simulation and the model is constructed by using the polynomial expansion method, and when the modeling results of the wind power generation equipment are matched and applied in different areas according to the modeling results of the wind power generation equipment, the external wind environment parameters at different heights in different areas that are compared and adapted / combined are the characteristic values ​​that effectively affect the external wind environment parameters, that is, the wind speed and wind direction parameter indicators of the external wind environment parameters are compared and matched with the wind speed and wind direction parameter indicators in the characteristic values ​​that effectively affect the external environment parameters by the same proportion, and the effectiveness is verified before establishing the characteristic values ​​that effectively affect the external wind environment parameters.

[0029] Preferably, the output power data monitored by the wind power generation equipment is measured by connecting a power meter to the output end of the wind power generation equipment, and the monitored output power data is sent by connecting to the first monitoring storage module and stored in the first data storage unit of the first monitoring storage module;

[0030] The external environmental parameters of the wind power generation equipment include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, which are connected to the first monitoring storage module through the equipment anemometer / wind speed sensor to send the monitored external environmental parameters and store them in the second data storage unit in the first monitoring storage module;

[0031] The hardware parameter indicators of the wind power generation equipment include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, and are stored in the third data storage unit in the first monitoring storage module, and according to the update and use iteration cycle of the hardware parameters, multiple preset time periods are set, and within the specified multiple preset time periods, the hardware parameters are all referred to and stored as real-time hardware parameters. When there are multiple wind power generation equipment in the multiple regions, the hardware parameters of multiple wind power generation equipment in any region have differences in several hardware parameter categories;

[0032] The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured by multiple wind measuring towers through wind measuring equipment, and the wind measuring equipment is connected to the second monitoring storage module to send the measured external wind environment parameters and store them in the fourth data storage unit.

[0033] Preferably, the setting of the preset time periods in the data collected by the multiple wind power generation equipment is respectively realized by setting a first clock module configured with an RTC chip in the first control system thereof; when sending and storing the output power data, external environmental parameters, and real-time hardware parameters to the first data storage unit, the second data storage unit, and the third data storage unit of the first control system, the first clock module generates timestamps corresponding to the various types of data and stores them in the first data storage unit, the second data storage unit, and the third data storage unit, so that the analysis and modeling device receives the various types of data of each wind power generation equipment while receiving its timestamp data, and the analysis and modeling device retrieves the output power data, external environmental parameters, and real-time hardware parameters within the specified preset time period according to multiple timestamps to implement modeling of the wind power generation equipment.

[0034] Preferably, the setting of the preset time periods in the data collected by the multiple wind towers is respectively achieved by setting a second clock module configured with an RTC chip in the second control system thereof; when sending and storing multiple wind speed and wind direction measurement data at different heights to the fourth data storage unit of the second control system, the timestamp of the corresponding measurement data is generated by the second clock module and stored in the fourth data storage unit, so that the analysis and modeling device receives the timestamp data of the measurement data of the wind tower at the same time, and the analysis and modeling device retrieves the measurement data within the specified preset time period according to the multiple timestamps to implement the modeling of the wind power generation equipment or provide the application of the results after the wind power generation equipment is modeled.

[0035] The present invention provides a wind power generation equipment modeling system and modeling method, which have the following beneficial effects:

[0036] 1. The present invention monitors and stores the output power data, external environment parameters, and hardware parameters of several wind power generation equipment in multiple regions, and monitors and stores the external wind environment parameters of different regions through wind towers in different regions, so that the analysis modeling device establishes connections with the wind power generation equipment and the wind towers to obtain and store them respectively, and processes the various data monitored and stored in multiple set time periods through a central processing module to obtain multiple groups of effective maximum values ​​of output power sets and corresponding groups of characteristic values ​​that effectively affect the external environment parameters and effectively affect the hardware parameters; and further, based on the effective maximum values ​​of the output powers of multiple wind power generation equipment, combined with the corresponding characteristic values ​​that effectively affect the hardware parameters and effectively affect the external environment parameters Eigenvalue, build a model through the polynomial expansion method, calculate the maximum power generation efficiency of each wind power generation equipment, and combine its hardware cost to obtain the ratio of maximum power generation efficiency to hardware cost, complete the modeling of multiple wind power generation equipment, and according to the modeling results of wind power generation equipment, compare the effective influence characteristic values ​​of external environmental parameters with the effective influence characteristic values ​​of external wind environment parameters at different heights in multiple regions, realize the matching application of wind power generation equipment modeling results in different regions, realize the modeling results of the maximum power generation efficiency / hardware cost ratio of multiple wind power generation equipment placed in different regions, and apply them to specified areas and specified heights, which greatly improves the power generation efficiency of wind power generation equipment in wind environments in different regions and lowers the cost.

[0037] 2. After obtaining multiple groups of effective maximum output power and the corresponding characteristic values ​​of each group of parameters that effectively affect the external environment and effectively affect the hardware parameters by analyzing the central processing module in the modeling equipment, based on the effective maximum output power of multiple wind power generation equipment, combined with the corresponding effective hardware parameters, characteristic values ​​of parameters that effectively affect the external environment, and parameters that effectively affect the external wind environment at different heights in different regions, the output power data of multiple wind power generation equipment are obtained through Monte Carlo simulation, and the model is constructed using the polynomial expansion method. The maximum power generation efficiency of each wind power generation equipment at different heights in multiple regions is calculated, and the ratio of the maximum power generation efficiency to the hardware cost is obtained in combination with its hardware cost, thereby completing the modeling and direct application of multiple wind power generation equipment applied to multiple regions and at different heights.

[0038] 3. The present invention uses two modeling methods to achieve modeling through multiple monitoring indicators of different wind power generation equipment, and adapts the modeling results to the external wind environments in different regions and at different heights for matching and application. In addition, the modeling is completed according to multiple data indicators of wind power generation equipment and the external wind environments in different regions and at different heights to be applied to different wind environments, which greatly guarantees the power generation efficiency, and obtains the maximum power generation efficiency / hardware cost ratio according to the modeling results, so as to achieve the optimal installation configuration according to the modeling results before installing wind power generation equipment on a large scale and in large quantities in different regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the overall structure of a wind power generation equipment modeling system of the present invention;

[0040] Figure 2 A schematic diagram of a method flow of a wind power generation equipment modeling method of the present invention;

[0041] Figure 3 Another method flow chart of a method for modeling a wind power generation equipment according to the present invention is shown.

[0042] Among them, 1. wind power generation equipment; 11. first monitoring storage module; 111. first data storage unit; 112. second data storage unit; 113. third data storage unit; 12. first clock module; 13. power meter; 2. analysis and modeling equipment; 21. first storage module; 211. first storage unit; 212. second storage unit; 213. third storage unit; 22. second storage module; 224. fourth storage unit; 23. central processing module; 3. wind measurement tower; 31. second monitoring storage module; 314. fourth data storage unit; 32. second clock module; 33. wind measurement equipment. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] In the description of the embodiments of the present invention, "multiple" means at least 2, and "several" means 1 or more; in addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0045] The invention provides a wind power generation equipment modeling system and a modeling method.

[0046] Example 1

[0047] refer to Figure 1 , Figure 1 The figure is a schematic diagram of the overall structure of a wind power generation equipment modeling system of the present invention.

[0048] The present invention provides a wind power generation equipment modeling system, comprising a plurality of first monitoring and storage modules 11, which are respectively arranged in the first control systems of a plurality of wind power generation equipment 1 in a plurality of regions, and are used to monitor the output power data of a plurality of wind power generation equipment 1 in a plurality of preset time periods in different regions, and the external environment parameters monitored by the designated wind power generation equipment 1 corresponding to the output power data, and store them in the first data storage units 111 and the second data storage units 112 of the plurality of first monitoring and storage modules 11, respectively, and store the real-time hardware parameters of the corresponding wind power generation equipment 1 in a plurality of preset time periods in the third data storage units 113 of the plurality of first monitoring and storage modules 11;

[0049] It also includes a plurality of second monitoring and storage modules 31, which are respectively arranged in the second control systems of the wind towers 3 in the plurality of regions, and monitor the external wind environment parameters at a plurality of different heights in different regions in the plurality of preset time periods and store the parameters in the fourth data storage unit 314 arranged therein;

[0050] It also includes an analysis and modeling device 2, which, when establishing connections with multiple first monitoring storage modules 11 respectively, receives and stores the output power data, external environment parameters, and real-time hardware parameters in multiple preset time periods in the first data storage unit 111, the second data storage unit 112, and the third data storage unit 113 sent by the multiple first monitoring storage modules 11 correspondingly by the multiple groups of first storage units 211, second storage units 212, and third storage units 213 of the first storage modules 21 respectively; the connection method can be a wireless network connection, such as a WI FI network connection supported by the analysis and modeling device 2, the first monitoring storage module 11, and the first control system, and a wired network connection, such as an optical fiber connection;

[0051] When the analysis and modeling device 2 establishes connections with the multiple second monitoring and storage modules 31 respectively, the multiple fourth storage units 224 of the second storage module 22 therein correspond to receive and store the external wind environment parameters within the multiple preset time periods sent by the fourth data storage unit 314 of the multiple second monitoring and storage modules 31; the connection method can be a wireless network connection, such as a WI FI network connection supported by the analysis and modeling device 2, the second monitoring and storage module 31 and the second control system respectively, and a wired network connection, such as an optical fiber connection;

[0052] The analysis and modeling device 2 receives and stores multiple sets of output power data of multiple wind power generation equipment 1 in multiple preset time periods, external environmental parameters corresponding to the output power data, and corresponding real-time hardware parameters, and further processes the multiple sets of output power data, external environmental parameters, and hardware parameters through the built-in central processing module 23, and obtains the effective maximum values ​​of the multiple sets of output power in multiple preset time periods in multiple regions and the corresponding characteristic values ​​that effectively affect the external environmental parameters and the hardware parameters according to the processing;

[0053] The analysis modeling device 2 is based on the effective maximum output power of multiple wind power generation equipment 1, combined with the corresponding effective hardware parameter characteristic values ​​and effective external environment parameter characteristic values, and constructs a model through the polynomial expansion method to infer the maximum power generation efficiency of each wind power generation equipment 1, and combines its hardware cost to obtain the ratio of the maximum power generation efficiency to the hardware cost, completes the modeling of multiple wind power generation equipment 1, and according to the modeling results of the wind power generation equipment 1, compares and adapts the characteristic values ​​of the effective external environment parameter with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, so as to achieve the modeling results of the wind power generation equipment 1 in different regions. Matching application; or, the analysis and modeling device 2 is based on the effective maximum output power of multiple wind power generation equipment 1, combined with the corresponding effective hardware parameter characteristic values, effective external environment parameter characteristic values, and external wind environment parameter characteristic values ​​at different heights in different regions, and obtains the output power data of multiple wind power generation equipment 1 through Monte Carlo simulation, and uses the polynomial expansion method to construct a model, calculates the maximum power generation efficiency of each wind power generation equipment 1 at different heights in multiple regions, and combines its hardware cost to obtain the ratio of maximum power generation efficiency to hardware cost, thereby completing the modeling of multiple wind power generation equipment 1 applied to multiple regions and at different heights.

[0054] As a preferred embodiment, in the matching application of the modeling results and in obtaining the output power through Monte Carlo simulation and modeling with the polynomial expansion method, the characteristic values ​​of the external wind environment parameters at different heights in different regions are compared and matched in the same proportion with the wind speed and wind direction parameter indicators of the wind speed and wind direction parameter indicators in the characteristic values ​​of the parameters that effectively affect the external environment, so as to verify their effectiveness and establish the characteristic values ​​of the parameters that effectively affect the external wind environment, so as to further realize the matching application of the modeling results of the wind power generation equipment 1 in different regions, or further obtain the output power data of multiple wind power generation equipment 1 through Monte Carlo simulation, and construct the model using the polynomial expansion method.

[0055] Among them, when there are multiple wind power generation equipment 1 installed in the several areas, they include at least two or more wind power generation equipment 1 with different hardware parameters; and by installing multiple wind power generation equipment 1 in multiple environmental areas with different external wind environment parameters, the differences in hardware parameters and the differences in monitored external environmental parameters are realized; so that the analysis and modeling equipment 2 can comprehensively consider the differences in the above-mentioned multiple situations, as well as the differences or references of the external wind environment parameters of the wind measurement tower 3, to achieve the modeling of multiple wind power generation equipment 1 in multiple areas under different external wind environment parameters or the application of further modeling results.

[0056] As a preferred embodiment, the output power data monitored by the wind power generation equipment 1 is measured by connecting a power meter 13 to the output end of the wind power generation equipment 1, and is connected to the first monitoring storage module 11 to send the monitored output power data, and is stored in the first data storage unit 111 of the first monitoring storage module 11;

[0057] The external environmental parameters of the wind power generation equipment 1 include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, which are connected to the first monitoring storage module 11 through the equipment anemometer / wind speed sensor to send the monitored external environmental parameters and store them in the second data storage unit 112 in the first monitoring storage module 11;

[0058] The hardware parameter indicators of the wind power generation equipment 1 include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, which are stored in the third data storage unit 113 in the wind power generation equipment 1, and according to the update of the hardware parameters and the use of the iteration cycle, the setting of multiple preset time periods is realized, and it is realized that within the specified multiple preset time periods, the hardware parameters are all referred to and stored as real-time hardware parameters; the various hardware parameters are directly entered into the third data storage unit 113 by technical personnel in this field when installing the equipment and iterating the hardware. Further various hardware parameters such as the selection of wind turbines with suitable parameters / power, the setting and installation of suitable tower height, the use of gearboxes with suitable parameters, and other hardware and parameters that effectively affect the maximum power generation efficiency that are well known to technical personnel in this field are not elaborated here.

[0059] The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured and obtained by multiple wind measuring towers 3 through wind measuring equipment 33, and the wind measuring equipment 33 is connected to the second monitoring storage module 31 to send the measured external wind environment parameters and store them in the fourth data storage unit 314; the wind measuring equipment 33 is obtained through the existing technology, and the external wind environment parameters are monitored, obtained, and stored at least through the wind speed sensor and wind direction sensor of the wind measuring equipment 33.

[0060] As an optional embodiment, the first control system of the wind power generation equipment 1 also includes a first clock module 12 configured with an RTC chip, which assists in the establishment of multiple preset time periods; when sending and storing output power data, external environmental parameters, and real-time hardware parameters to the first data storage unit 111, the second data storage unit 112, and the third data storage unit 113 of the first control system, the first clock module 12 generates timestamps corresponding to the various types of data and stores them in the first data storage unit 111, the second data storage unit 112, and the third data storage unit 113, so that the analysis and modeling device 2 receives the various types of data of each wind power generation equipment 1 while receiving its timestamp data, and the analysis and modeling device 2 retrieves the output power data, external environmental parameters, and real-time hardware parameters within the specified preset time period according to multiple timestamps to implement modeling of the wind power generation equipment 1.

[0061] Furthermore, the second control system of the wind tower 3 also includes a second clock module 32 configured with an RTC chip, which assists in the establishment of multiple preset time periods; when sending and storing wind speed and wind direction measurement data at multiple different heights to the fourth data storage unit 314 of the second control system, the second clock module 32 generates a timestamp for the corresponding measurement data and stores it in the fourth data storage unit 314, so that the analysis and modeling device 2 receives the measurement data of the wind tower 3 at the same time as its timestamp data, and the analysis and modeling device 2 retrieves the measurement data within the specified preset time period according to multiple timestamps to implement the modeling of the wind power generation equipment 1 or provide the result application after the wind power generation equipment 1 is modeled.

[0062] For the establishment of the above two types of multiple preset time periods, the same multiple preset time periods are called according to multiple timestamps at the same moment to realize modeling of the wind power generation equipment 1 and achieve reliability of the modeling result.

[0063] Example 2

[0064] refer to Figure 1-Figure 3 , Figure 1 A schematic diagram of the overall structure of a wind power generation equipment modeling system of the present invention; Figure 2 A schematic diagram of a method flow of a wind power generation equipment modeling method of the present invention; Figure 3 Another method flow chart of a method for modeling a wind power generation equipment according to the present invention is shown.

[0065] In a second aspect, the present invention provides a method for modeling a wind power generation device, comprising the following steps:

[0066] S1: for a plurality of wind power generation devices 1 in a plurality of different regions, respectively collect their output power data and external environment parameters corresponding to the output power data in a plurality of preset time periods, and store them in the first data storage unit 111 and the second data storage unit 112 of the wind power generation device 1, respectively; and collect the corresponding hardware parameters of the wind power generation device 1 in a plurality of preset time periods, and store them in the third data storage unit 113 of the wind power generation device 1;

[0067] S2: by connecting the first monitoring storage module 11 of the plurality of wind power generation equipment 1 to the analysis modeling device 2, obtaining and storing a plurality of groups of monitored output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation equipment 1, wherein the plurality of groups of monitored hardware parameters and / or external environmental parameters are different, and the plurality of groups of output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation equipment 1 are respectively stored in the plurality of groups of first storage units 211, second storage units 212 and third storage units 213 of the first storage module 21 of the analysis modeling device 2;

[0068] S3: analyzing the probability distribution of output power maximization in each group of output power data;

[0069] S4: determining, according to the curve distribution of the output power values ​​in the plurality of groups of output power data, the effective maximum value that can represent each group of output power, and determining the characteristic values ​​of the hardware parameters and the external environment parameters corresponding to the effective maximum value of each group of output power;

[0070] S5: according to the influence degree of different hardware parameters and external environment parameters on the output power of the plurality of wind power generation devices 1, effectively influencing hardware parameters and effectively influencing external environment parameters are determined from the plurality of sets of hardware parameters and external environment parameters;

[0071] S6: In the plurality of preset time periods, a plurality of wind towers 3 are used to monitor a plurality of sets of external wind environment parameters at different heights in a plurality of different areas and the sets of the parameters are stored in a plurality of fourth data storage units 314 provided in the plurality of wind towers 3, respectively; and an analysis and modeling device 2 is connected to the second monitoring storage modules 31 of the plurality of wind towers 3, respectively, to receive and store the sets of external wind environment parameters in the plurality of fourth storage units 224 provided in the second storage modules 22 thereof;

[0072] S7: The analysis modeling device 2 constructs a model based on the effective maximum output power of multiple wind power generation equipment 1, in combination with the corresponding effective hardware parameters and effective external environment parameter characteristic values, uses the polynomial expansion method to calculate the maximum power generation efficiency of each wind power generation equipment 1, and calculates the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation equipment 1; and according to the modeling results of the wind power generation equipment 1, compares and adapts the characteristic values ​​of its effective external environment parameters with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, thereby achieving matching application of the modeling results of the wind power generation equipment 1 in different regions;

[0073] Alternatively, the analysis and modeling device 2 is based on the effective maximum output power of multiple wind power generation equipment 1, and obtains the output power data of multiple wind power generation equipment 1 through Monte Carlo simulation by combining the corresponding effective influencing hardware parameters, the effective influencing external environmental parameter characteristic values, and the external wind environment parameters at different heights in different regions, and constructs a model using the polynomial expansion method to calculate the maximum power generation efficiency of each wind power generation equipment 1 at different heights in multiple regions, and obtains the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation equipment 1 applied to multiple regions and at different heights.

[0074] Preferably, in the S7 step, when the output power data of multiple wind power generation equipment 1 are obtained by Monte Carlo simulation and the model is constructed by using the polynomial expansion method, and when the modeling results of the wind power generation equipment 1 are matched and applied in different areas according to the modeling results of the wind power generation equipment 1, the compared and adapted / combined external wind environment parameters at different heights in different areas are effectively affecting the characteristic values ​​of the external wind environment parameters, that is, the wind speed and wind direction parameter indicators of the external wind environment parameters are compared and matched with the wind speed and wind direction parameter indicators in the said effective characteristic values ​​of the external environment parameters by the same proportion, and the effectiveness is verified before establishing the characteristic values ​​of the external wind environment parameters.

[0075] Preferably, the output power data monitored by the wind power generation equipment 1 is measured by connecting a power meter 13 to the output end of the wind power generation equipment 1, and is connected to the first monitoring storage module 11 to send the monitored output power data, and is stored in the first data storage unit 111 of the first monitoring storage module 11;

[0076] The external environmental parameters of the wind power generation equipment 1 include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, which are connected to the first monitoring storage module 11 through the equipment anemometer / wind speed sensor to send the monitored external environmental parameters and store them in the second data storage unit 112 in the first monitoring storage module 11;

[0077] The hardware parameter indicators of the wind power generation equipment 1 include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, and are stored in the third data storage unit 113 in the first monitoring storage module 11, and according to the update of the hardware parameters and the use of the iteration cycle, multiple preset time periods are set, and within the specified multiple preset time periods, the hardware parameters are all referred to and stored as real-time hardware parameters. When there are multiple wind power generation equipment in the multiple regions, the hardware parameters of multiple wind power generation equipment 1 in any region have differences in several hardware parameter categories;

[0078] The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured by multiple wind measuring towers 3 through wind measuring equipment 33, and are connected to the second monitoring storage module 31 through the wind measuring equipment 33 to send the measured external wind environment parameters and store them in the fourth data storage unit 314.

[0079] As an optional embodiment, the setting of the preset time periods in the data collected by the multiple wind power generation devices 1 is respectively achieved by setting a first clock module 12 configured with an RTC chip in its first control system; when sending and storing the output power data, external environmental parameters, and real-time hardware parameters to the first data storage unit 111, the second data storage unit 112, and the third data storage unit 113 of the first control system, the first clock module 12 generates timestamps corresponding to the various types of data and stores them in the first data storage unit 111, the second data storage unit 112, and the third data storage unit 113, so that the analysis and modeling device 2 receives the various types of data of each wind power generation device 1 while receiving its timestamp data, and the analysis and modeling device 2 retrieves the output power data, external environmental parameters, and real-time hardware parameters within the specified preset time period according to multiple timestamps to implement modeling of the wind power generation device 1.

[0080] Furthermore, the setting of the preset time periods in the data collected by the multiple wind towers 3 is respectively achieved by setting a second clock module 32 configured with an RTC chip in the second control system thereof; when sending and storing multiple wind speed and wind direction measurement data at different heights to the fourth data storage unit 314 of the second control system, the timestamp of the corresponding measurement data is generated by the second clock module 32 and stored in the fourth data storage unit 314, so that the analysis and modeling device 2 receives the measurement data of the wind tower 3 and its timestamp data at the same time, and the analysis and modeling device 2 retrieves the measurement data within the specified preset time period according to the multiple timestamps to implement the modeling of the wind power generation equipment 1 or provide the result application after the wind power generation equipment 1 is modeled.

[0081] Among them, for the establishment of the above-mentioned two types of multiple preset time periods, the same multiple preset time periods are called according to multiple timestamps at the same moment to realize the modeling of the wind power generation equipment 1 to achieve the reliability of the modeling results, and cooperate with the update of hardware parameters and the use of iteration cycles to realize the further setting of multiple preset time periods, and further within the specified preset time period, the hardware parameters are referred to and stored as real-time hardware parameters.

[0082] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wind power generation equipment modeling system, characterized in that: The invention comprises a plurality of first monitoring and storage modules (11), which are respectively arranged in the first control systems of a plurality of wind power generation equipment (1) in a plurality of regions, and are used to monitor the output power data of a plurality of wind power generation equipment (1) in a plurality of preset time periods in different regions, and the external environment parameters monitored by the designated wind power generation equipment (1) corresponding to the output power data, and store them in the first data storage unit (111) and the second data storage unit (112) of the plurality of first monitoring and storage modules (11), respectively, and store the real-time hardware parameters of the corresponding wind power generation equipment (1) in a plurality of preset time periods in the third data storage unit (113) of the plurality of first monitoring and storage modules (11); It also includes a plurality of second monitoring and storage modules (31), which are respectively arranged in the second control systems of the wind towers (3) in the plurality of regions, and monitor the external wind environment parameters at a plurality of different heights in different regions in the plurality of preset time periods and store the parameters in a fourth data storage unit (314) arranged therein; It also includes an analysis and modeling device (2), which, when establishing connections with the plurality of first monitoring storage modules (11) respectively, receives and stores the output power data, external environment parameters, and real-time hardware parameters in the first data storage unit (111), the second data storage unit (112), and the third data storage unit (113) sent by the plurality of first monitoring storage modules (11) in a plurality of preset time periods correspondingly by the plurality of first monitoring storage modules (11) and the plurality of first storage units (211), the second data storage unit (112), and the third data storage unit (113); When the analysis and modeling device (2) establishes connections with the plurality of second monitoring storage modules (31) respectively, the plurality of fourth storage units (224) of the second storage modules (22) therein correspond to receiving and storing the external wind environment parameters of the fourth data storage unit (314) within the plurality of preset time periods sent by the plurality of second monitoring storage modules (31); The analysis and modeling device (2) receives and stores multiple sets of output power data of multiple wind power generation devices (1) within multiple preset time periods, external environmental parameters corresponding to the output power data, and corresponding real-time hardware parameters, and further processes the multiple sets of output power data, external environmental parameters, and hardware parameters through a built-in central processing module (23), and obtains effective maximum values ​​of multiple sets of output power in multiple preset time periods in multiple regions and corresponding characteristic values ​​that effectively affect the external environmental parameters and effectively affect the hardware parameters based on the processing; The analysis modeling device (2) is based on the effective maximum output power of multiple wind power generation devices (1), combined with the corresponding effective hardware parameter characteristic values ​​and effective external environment parameter characteristic values, and constructs a model through a polynomial expansion method to infer the maximum power generation efficiency of each wind power generation device (1), and obtains the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation devices (1), and based on the modeling results of the wind power generation devices (1), comparing and adapting the characteristic values ​​of the effective external environment parameter with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, so as to achieve the modeling results of the wind power generation devices (1) in different regions. or, the analysis and modeling device (2) is based on the effective maximum output power of multiple wind power generation devices (1), combined with the corresponding effective hardware parameter characteristic values, effective external environment parameter characteristic values, and external wind environment parameter characteristic values ​​at different heights in different regions, to obtain the output power data of multiple wind power generation devices (1) through Monte Carlo simulation, and use the polynomial expansion method to build a model, calculate the maximum power generation efficiency of each wind power generation device (1) at different heights in multiple regions, and combine its hardware cost to obtain the ratio of the maximum power generation efficiency to the hardware cost, thereby completing the modeling of multiple wind power generation devices (1) applied to multiple regions and at different heights.

2. A wind power generation equipment modeling system according to claim 1, characterized in that: In the matching application of the modeling results and in obtaining the output power through Monte Carlo simulation and modeling with the polynomial expansion method, the characteristic values ​​of the external wind environment parameters at different heights in different regions are matched by comparing their wind speed and wind direction parameter indicators with the wind speed and wind direction parameter indicators in the characteristic values ​​of the parameters that effectively affect the external environment in the same proportion, so as to verify their effectiveness and establish the characteristic values ​​of the parameters that effectively affect the external wind environment, so as to further realize the matching application of the modeling results of the wind power generation equipment (1) in different regions, or further obtain the output power data of multiple wind power generation equipment (1) through Monte Carlo simulation, and use the polynomial expansion method to build the model.

3. A wind power generation equipment modeling system according to claim 2, characterized in that: When there are multiple wind power generation equipment (1) installed in the plurality of areas, at least two or more wind power generation equipment (1) with different hardware parameters are included; and the differences in hardware parameters and monitored external environmental parameters are achieved by installing the multiple wind power generation equipment (1) in multiple environmental areas with different external wind environmental parameters respectively; so that the analysis and modeling equipment (2) can integrate the multiple differences, and combine the differences or references of the external wind environmental parameters of the wind measurement tower (3), so as to achieve the modeling of multiple wind power generation equipment (1) in multiple areas under different external wind environmental parameters or the application of further modeling results.

4. A wind power generation equipment modeling system according to claim 3, characterized in that: The output power data monitored by the wind power generation equipment (1) is measured and obtained by connecting a power meter (13) to the output end of the wind power generation equipment (1), and the monitored output power data is sent by connecting to the first monitoring storage module (11) and stored in the first data storage unit (111) of the first monitoring storage module (11); The external environmental parameters of the wind power generation equipment (1) include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, and the equipment anemometer / wind speed sensor is connected to the first monitoring storage module (11) to send the monitored external environmental parameters and store them in the second data storage unit (112) in the first monitoring storage module (11); The hardware parameter indicators of the wind power generation equipment (1) include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, and are stored in a third data storage unit (113) in the first monitoring storage module (11), and multiple preset time periods are set according to the update and use iteration cycle of the hardware parameters, and the hardware parameters are all referred to and stored as real-time hardware parameters within the specified multiple preset time periods; The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured by a plurality of wind measuring towers (3) using wind measuring equipment (33), and the wind measuring equipment (33) is connected to the second monitoring storage module (31) to send the measured external wind environment parameters and store them in a fourth data storage unit (314).

5. A wind power generation equipment modeling system according to any one of claims 1 to 4, characterized in that: The first control system of the wind power generation equipment (1) further comprises a first clock module (12) configured with an RTC chip, which assists in establishing a plurality of preset time periods; when sending and storing output power data, external environmental parameters, and real-time hardware parameters to the first data storage unit (111), the second data storage unit (112), and the third data storage unit (113) of the first control system, the first clock module (12) generates a timestamp corresponding to each type of data and stores the timestamp in the first data storage unit (111), the second data storage unit (112), and the third data storage unit (113), so that the analysis and modeling device (2) receives the timestamp data of each type of data of each wind power generation equipment (1) at the same time, and the analysis and modeling device (2) retrieves the output power data, external environmental parameters, and real-time hardware parameters in the specified preset time period according to the multiple timestamps to implement modeling of the wind power generation equipment (1).

6. A wind power generation equipment modeling system according to claim 5, characterized in that: The second control system of the wind tower (3) further comprises a second clock module (32) configured with an RTC chip, which assists in establishing a plurality of preset time periods; when sending and storing a plurality of wind speed and wind direction measurement data at different heights to the fourth data storage unit (314) of the second control system, a timestamp of the corresponding measurement data is generated by the second clock module (32) and stored in the fourth data storage unit (314), so that the analysis and modeling device (2) receives the measurement data of the wind tower (3) and simultaneously receives its timestamp data, and the analysis and modeling device (2) retrieves the measurement data within the specified preset time period according to the plurality of timestamps to implement the modeling of the wind power generation device (1) or provide the application of the modeled results of the wind power generation device (1).

7. A method for modeling a wind power generation equipment based on the wind power generation equipment modeling system according to any one of claims 1 to 6, characterized in that: The following steps are involved: S1: For a plurality of wind power generation devices (1) in a plurality of different regions, the output power data and the external environment parameters corresponding to the output power data are collected in a plurality of preset time periods, and the data are stored in a first data storage unit (111) and a second data storage unit (112) of the wind power generation devices (1), respectively; and the hardware parameters of the corresponding wind power generation devices (1) in a plurality of preset time periods are collected and stored in a third data storage unit (113) of the wind power generation devices (1); S2: by connecting the first monitoring storage module (11) of the plurality of wind power generation devices (1) to the analysis modeling device (2), a plurality of groups of monitored output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation devices (1) are acquired and stored, wherein the plurality of groups of monitored hardware parameters and / or external environmental parameters are different, and the plurality of groups of output power data, corresponding external environmental parameters and hardware parameters corresponding to the plurality of wind power generation devices (1) are respectively stored in the plurality of groups of first storage units (211), second storage units (212) and third storage units (213) of the first storage module (21) of the analysis modeling device (2); S3: analyzing the probability distribution of output power maximization in each group of output power data; S4: determining, according to the curve distribution of the output power values ​​in the plurality of groups of output power data, the effective maximum value that can represent each group of output power, and determining the characteristic values ​​of the hardware parameters and the external environment parameters corresponding to the effective maximum value of each group of output power; S5: according to the influence degree of different hardware parameters and external environment parameters on the output power of the plurality of wind power generation devices (1), effectively influencing hardware parameters and effectively influencing external environment parameters are determined from the plurality of sets of hardware parameters and external environment parameters; S6: In the plurality of preset time periods, a plurality of wind measuring towers (3) are used to monitor a plurality of sets of external wind environment parameters at different heights in a plurality of different areas and the sets of external wind environment parameters are stored in a plurality of fourth data storage units (314) provided in the plurality of wind measuring towers (3), and an analysis and modeling device (2) is connected to the second monitoring storage modules (31) of the plurality of wind measuring towers (3) to receive and store the sets of external wind environment parameters in the plurality of fourth storage units (224) of the second storage modules (22) provided therein; S7: The analysis modeling device (2) is based on the effective maximum output power of the multiple wind power generation devices (1), combined with the corresponding effective influencing hardware parameters and effective influencing external environment parameter characteristic values, and uses the polynomial expansion method to construct a model, calculates the maximum power generation efficiency of each wind power generation device (1), and calculates the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of the multiple wind power generation devices (1); and based on the modeling results of the wind power generation devices (1), the characteristic values ​​of the effective influencing external environment parameters are compared and adapted with the characteristic values ​​of the external wind environment parameters at different heights in multiple regions, so as to achieve matching application of the modeling results of the wind power generation devices (1) in different regions; Alternatively, the analysis and modeling device (2) is based on the effective maximum output power of multiple wind power generation devices (1), and obtains the output power data of multiple wind power generation devices (1) by combining the corresponding effective influencing hardware parameters, the effective influencing external environment parameter characteristic values, and the external wind environment parameters at different heights in different regions through Monte Carlo simulation, and uses the polynomial expansion method to construct a model, calculates the maximum power generation efficiency of each wind power generation device (1) at different heights in multiple regions, and calculates the ratio of the maximum power generation efficiency to the hardware cost in combination with its hardware cost, thereby completing the modeling of multiple wind power generation devices (1) applied to multiple regions and at different heights.

8. A wind power generation equipment modeling method according to claim 7, characterized in that: In the step S7, when the output power data of multiple wind power generation equipment (1) are obtained by Monte Carlo simulation and the model is constructed by using the polynomial expansion method, and when the modeling results of the wind power generation equipment (1) are matched and applied in different areas according to the modeling results of the wind power generation equipment (1), the external wind environment parameters at different heights in different areas that are compared and adapted / combined are effective influencing the characteristic values ​​of the external wind environment parameters, that is, the wind speed and wind direction parameter indicators of the external wind environment parameters are compared and matched with the wind speed and wind direction parameter indicators in the effective influencing external environment parameter characteristic values ​​in the same proportion, and the effective influencing external wind environment parameter characteristic values ​​are established after verifying their effectiveness.

9. A wind power generation equipment modeling method according to claim 7, characterized in that: The output power data monitored by the wind power generation equipment (1) is measured and obtained by connecting a power meter (13) to the output end of the wind power generation equipment (1), and the monitored output power data is sent by connecting to the first monitoring storage module (11) and stored in the first data storage unit (111) of the first monitoring storage module (11); The external environmental parameters of the wind power generation equipment (1) include wind speed meteorological parameters measured by the equipment anemometer / wind speed sensor and wind direction meteorological parameters measured by the equipment wind vane, and the equipment anemometer / wind speed sensor is connected to the first monitoring storage module (11) to send the monitored external environmental parameters and store them in the second data storage unit (112) in the first monitoring storage module (11); The hardware parameter indicators of the wind power generation equipment (1) include equipment generator parameters, equipment blade parameters, gearbox parameters, and tower parameters, and are stored in a third data storage unit (113) in the first monitoring storage module (11), and multiple preset time periods are set according to the update and use iteration cycle of the hardware parameters, and the hardware parameters are all referred to and stored as real-time hardware parameters within the specified multiple preset time periods. When there are multiple wind power generation equipment (1) in the multiple regions, the hardware parameters of the multiple wind power generation equipment (1) in any region have differences in several hardware parameter categories; The wind speed and wind direction parameters of the external wind environment parameters in different areas and at different heights are measured by a plurality of wind measuring towers (3) using wind measuring equipment (33), and are connected to the second monitoring storage module (31) via the wind measuring equipment (33) to send the measured external wind environment parameters and store them in the fourth data storage unit (314).

10. A wind power generation equipment modeling method according to claim 7, characterized in that: The setting of the preset time periods in the data collected by the plurality of wind power generation devices (1) is achieved by respectively setting a first clock module (12) configured with an RTC chip in the first control system thereof; when sending and storing the output power data, external environment parameters, and real-time hardware parameters to the first data storage unit (111), the second data storage unit (112), and the third data storage unit (113) of the first control system, the first clock module (12) generates a timestamp corresponding to each type of data and stores the timestamp in the first data storage unit (111), the second data storage unit (112), and the third data storage unit (113), so that the analysis and modeling device (2) receives the timestamp data of each type of data from each wind power generation device (1) at the same time, and the analysis and modeling device (2) retrieves the output power data, external environment parameters, and real-time hardware parameters in the specified preset time period according to the multiple timestamps to implement modeling of the wind power generation device (1).

11. A wind power generation equipment modeling method according to claim 10, characterized in that: The setting of the preset time periods in the data collected by the multiple wind towers (3) is achieved by respectively setting a second clock module (32) configured with an RTC chip in the second control system; when sending and storing multiple wind speed and wind direction measurement data at different heights to the fourth data storage unit (314) of the second control system, the timestamp of the corresponding measurement data is generated by the second clock module (32) and stored in the fourth data storage unit (314), so that the analysis and modeling device (2) receives the measurement data of the wind towers (3) and receives the timestamp data thereof at the same time, and the analysis and modeling device (2) retrieves the measurement data within the specified preset time period according to the multiple timestamps to implement the modeling of the wind power generation device (1) or provide the application of the results after the modeling of the wind power generation device (1).

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