Method for quickly calculating and analyzing wind resources
Through computer programming tools, the original wind measurement data of wind power is automatically processed and analyzed, which solves the problems of large amount of data and low efficiency in wind resource evaluation by wind power designers, and achieves fast and accurate wind resource calculation and analysis.
Patent Information
- Application Number
- CN202411208472.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-30
- Publication Date
- 2024-12-27
AI Technical Summary
Wind power designers face difficulties in sorting and calculating a large amount of original wind measurement data when conducting wind resource evaluation, resulting in large workload, low efficiency, and need to write a large number of charts.
Computer programming tools are used to automatically obtain and process original wind measurement data, and calculate comprehensive assessment of wind energy resources through a series of steps, including data absence statistics, wind shear index fitting, air density calculation, turbulence intensity analysis, wind energy parameter calculation, frequency distribution Statistics and maximum wind speed assessment, using chart tools to display results.
This greatly improves the work efficiency and quality of wind resource assessment, reduces manual calculation steps, and realizes rapid wind resource calculation and analysis.
Smart Images
Figure CN119204404A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of wind resource assessment technology, and in particular to a method for rapidly performing wind resource calculation and analysis. Background Art
[0002] Wind power parity and competitive bidding have become the general trend of wind power in my country. The accuracy of wind resource assessment affects the benefits of wind farms. In the process of writing wind power project research reports, designers need to collate and analyze wind measurement data, evaluate wind energy elements measured by wind towers, evaluate wind energy resources in representative years of wind farms, and conduct comprehensive evaluation of wind energy resources based on the original wind measurement data of wind towers. Since the original wind measurement data of wind towers contain characteristic data such as wind speed, wind direction, temperature, and air pressure recorded every ten minutes every day of the year, the amount of data is very large and difficult to organize, and there are many functional points and calculations that need to be calculated and evaluated, and a large number of charts are required.
[0003] Therefore, how to reduce the workload of designers in wind resource assessment and improve work efficiency has become a pain point that needs to be solved urgently. Summary of the invention
[0004] The technical problem to be solved by the present invention is to provide a method for quickly calculating and analyzing wind resources. With the help of computer programming tools, the original wind measurement data can be automatically obtained, the statistics can be quickly calculated and analyzed, and a comprehensive evaluation of wind energy resources can be performed, thereby greatly improving work quality and work efficiency.
[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for rapidly calculating and analyzing wind resources comprises the following steps: Step 1, read the original wind measurement data to obtain all characteristic data at each time point; Step 2: Based on the data from step 1, count the number of missing data and the completeness rate at each height; Step 3, according to the data in step 1, the wind shear index of each altitude layer is calculated, and the comprehensive wind shear index is calculated by fitting the power law function equation; Step 4, based on the data in step 1, calculate the average air density per month and the air density at different hub heights; Step 5, calculating the turbulence intensity based on the data in step 1; Step 6, based on the data of step 1 and step 4, calculate the wind energy parameters of each altitude layer, the average wind speed and wind power density at different altitudes in each month, and the daily average wind speed and wind power density; Step 7, based on the data from step 1 and step 4, statistics are collected on the wind speed and wind energy frequency distribution, the wind speed and wind energy frequency distribution, the main wind direction and main wind energy direction at each altitude, and the daily changes of the main wind direction and main wind energy at each altitude; Step 8, calculating the maximum wind speed once in 50 years based on the data in Step 1 and Step 4; Step 9. Finally, based on the data from steps 2 to 8, conduct a comprehensive assessment of wind energy resources.
[0006] A further improvement of the technical solution of the present invention is that step 1 specifically includes: The original wind measurement data includes: the average value, variance value, maximum value and minimum value of wind speed, wind direction, temperature and air pressure at each height at each time point; The StreamReader method is used to read the string of the original wind measurement data file, and all the information at each time point is stored in the specified array, so as to obtain all the characteristic data at each time point.
[0007] A further improvement of the technical solution of the present invention is that step 2 specifically includes: Traverse all the strings in the array in step 1. When a string is found to be empty, record its type characteristics and height, and accumulate the number of times. After the traversal is completed, classify it according to wind speed, wind direction, temperature, and air pressure, so as to count the number of missing data and the completeness rate of each altitude layer; The statistical results include: the number of times wind speed, wind direction, temperature and air pressure should be measured at each altitude, the number of times missed measurements and the completeness rate.
[0008] A further improvement of the technical solution of the present invention is that step 3 specifically includes: Get all the height values and wind speed values from the array in step 1, calculate the wind shear value between every two heights, and then get the wind shear index and power law fitting curve of each layer through the power law function fitting equation, and automatically display the power law fitting curve graph in the specified interface through the plotting tool; The calculation results include: wind shear index between different altitude layers, comprehensive wind shear index and power law fitting curve.
[0009] A further improvement of the technical solution of the present invention is that step 4 specifically includes: Get the temperature and air pressure values of each month from the array in step 1, calculate the average temperature, average air pressure and air density of each month, and then calculate the estimated air density value according to the temperature and pressure altitude, wheel hub height and the measured air density value, and display the month and air density graph in the specified interface through the plot tool; The calculation results include: monthly average temperature, average air pressure, air density, air density values calculated for different wheel hub heights, and monthly air density curves.
[0010] A further improvement of the technical solution of the present invention is that step 5 specifically includes: First, obtain the average wind speed and variance wind speed at each height from the array in step 1, calculate the average turbulence and the average turbulence of the 15m / s wind speed segment, and then extract the wind speed values at different heights according to the wind speed segment, calculate the representative turbulence values of the different wind speed segments at each height, then extract the wind direction values at different heights according to different wind directions, calculate the representative turbulence values of the different wind direction segments at each height, and finally display the graphics of wind speed turbulence and wind direction turbulence at the highest three heights in the specified interface through the plotting tool; The calculation results of turbulence intensity include: turbulence calculation results at each height, representative turbulence calculation results of different wind speed segments at each height, representative turbulence calculation results of different wind direction segments at each height, and turbulence diagrams of wind speed and wind direction.
[0011] A further improvement of the technical solution of the present invention is that step 6 specifically includes: Step 6.1, calculate the wind energy parameters at each altitude layer: Extract the average wind speed at all heights and the cube sum of samples according to the whole year and wind speed in the 3-25m / s segment from the array in step 1, and use the air density value calculated in step 4 to calculate the average power density and wind speed number; The calculation results include: average wind speed, average wind power density and wind speed number for each altitude layer in the whole year and standard wind speed range; Step 6.2, calculate the average wind speed and wind power density at different heights for each month: First, extract the average wind speed, the cube sum of samples and the number of samples according to the month from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the average wind speed and wind power density line graphs at different heights in the specified interface; The calculation results include: average wind speed and wind power density data at each altitude layer each month, and the corresponding line graph; Step 6.3, calculate the daily average wind speed and wind power density: First, extract the average wind speed, the cube sum of samples and the number of samples by hour from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graphs at different heights in the specified interface; The calculation results include: wind speed and wind power density data at each altitude layer at every hour, and the corresponding line graph.
[0012] A further improvement of the technical solution of the present invention is that step 7 specifically includes: Step 7.1, calculate the daily changes of wind speed and power density per month: First, extract the average wind speed, the cube sum of samples and the number of samples from the array in step 1 according to each month and each hour, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graph at different heights for each month in the specified interface; The statistical results include: data on wind speed and wind power density at each altitude layer at each hour of each month, and the corresponding line graph; Step 7.2, statistical wind speed and wind energy frequency distribution: First, extract the average wind speed at different wind speed segments at different heights from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind speed frequency and wind energy frequency, and use the plot tool to display the wind speed frequency and wind energy frequency bar graphs at different heights to the specified interface; The statistical results include: the distribution of wind speed and wind energy frequency at different wind speed ranges at each altitude layer, and the corresponding bar graphs; Step 7.3, count the daily changes of the main wind direction and main wind energy at each altitude: First, extract the average wind direction in different wind direction segments at different heights from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind direction frequency and wind energy direction frequency, and use the plot tool to display the wind direction frequency and wind energy direction frequency radar charts at different heights to the specified interface; The statistical results include: the distribution of wind direction and wind energy direction frequency at each altitude layer in different wind direction segments, and the corresponding radar chart; Step 7.4, count the daily changes of the main wind direction and main wind energy at each altitude: First, extract the average wind direction in different wind direction segments in different months from the array in step 1, calculate the wind direction frequency data, and then use the air density value calculated in step 4 to calculate the wind energy frequency data, and use the plot tool to display the daily change radar chart of the wind direction at different heights in each month and the daily change radar chart of the main wind energy to the specified interface; The statistical results include: the monthly changes of the main wind direction and main wind energy at each altitude in different wind direction segments, and the corresponding radar charts.
[0013] A further improvement of the technical solution of the present invention is that step 8 specifically includes: extracting the average wind speed from the array in step 1 according to different heights, first calculating the sample value of the 5-day thunderstorm method at the height and the maximum wind speed of the standard air once in 50 years, and then using the 5-fold wind speed method to calculate the maximum wind speed at different heights and the corresponding maximum wind speed of the standard air once in 50 years.
[0014] A further improvement of the technical solution of the present invention is that step 9 specifically includes: comprehensive analysis data of wind speed and wind power density values at different heights of the wind tower, air density values, in which wind speed range and frequency of occurrence of wind speed and wind energy at each height of the wind tower, wind direction of the wind tower and the direction in which wind energy is mainly concentrated; the evaluation results include: statistics of wind energy parameters at each height layer, air density, wind speed and wind energy frequency distribution, and main wind direction and main wind energy direction.
[0015] Due to the adoption of the above technical solution, the technical progress achieved by the present invention is: The present invention first reads the original wind measurement data from the wind tower, uses a self-made program and drawing tool to display the calculation results and charts required for the wind power project report to a specified location, and finally uses the conclusions drawn above to conduct a comprehensive assessment of wind energy resources, thereby achieving the purpose of quickly performing wind resource calculation and analysis without the need for manual step-by-step calculations, greatly improving the work efficiency and work quality of writing wind power project reports. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. Figure 1 is a flow chart of a method for quickly calculating and analyzing wind resources provided in an embodiment of the present invention; Figure 2 is a schematic diagram of a result table of counting missing data in an embodiment of the present invention; Figure 3 is a schematic diagram of a result table of calculating a wind shear index in an embodiment of the present invention; Figure 4 is a graphical schematic diagram of the result of calculating the wind shear index in an embodiment of the present invention; Figure 5 is a schematic diagram of a result table of calculating air density in an embodiment of the present invention; Figure 6 is a graphical diagram of the result of calculating air density in an embodiment of the present invention; Figure 7 is a schematic diagram of a table of results of calculating turbulence intensity in an embodiment of the present invention; Figure 8 is a graphical schematic diagram of the result of calculating turbulence intensity in an embodiment of the present invention; Fig. 9 1 is a schematic diagram of a statistical table of wind energy parameters at each altitude layer in an embodiment of the present invention; Fig.101 is a schematic diagram of the result table of average wind speed and wind power density in each month in an embodiment of the present invention; Fig.11 is a graphical diagram of the results of the average wind speed and wind power density in each month in an embodiment of the present invention; Fig.12 is a schematic diagram of a result table of wind speed and wind energy frequency distribution in an embodiment of the present invention; Fig.13 is a graphical diagram of the results of wind speed and wind energy frequency distribution in an embodiment of the present invention; Fig.14 1 is a schematic diagram of the result table of daily changes of monthly wind speed and power density in an embodiment of the present invention; Fig.15 is a graphical diagram of the results of daily changes in monthly wind speed and power density in an embodiment of the present invention; Fig.16 is a schematic diagram of a result table of wind speed and wind energy frequency distribution in an embodiment of the present invention; Fig.17 is a graphical diagram of the results of wind speed and wind energy frequency distribution in an embodiment of the present invention; Fig.18 is a schematic diagram of a result table of frequency distribution of wind direction and wind energy direction in an embodiment of the present invention; Fig.19 is a graphical schematic diagram of the result of the frequency distribution of wind direction and wind energy direction in an embodiment of the present invention; Fig. 20 is a result table schematic diagram of the main wind direction in an embodiment of the present invention; Fig.21 is a result graphical schematic diagram of the main wind direction in an embodiment of the present invention; Fig. 22 is a schematic diagram of a table showing the result of daily changes in main wind energy in an embodiment of the present invention; Fig.23 is a graphical diagram of the result of daily changes in main wind energy in an embodiment of the present invention; Fig.24 The table shows the results of the maximum wind speed once in 50 years in the embodiment of the present invention. Figure 1 ; Fig.25 The table shows the results of the maximum wind speed once in 50 years in the embodiment of the present invention. Figure 2 ; Fig.26 It is a schematic diagram of the display results of the comprehensive evaluation of wind energy resources in an embodiment of the present invention. DETAILED DESCRIPTION
[0017] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatus.
[0018] The present invention is further described in detail below with reference to the accompanying drawings and embodiments: like Figure 1 As shown, a method for quickly calculating and analyzing wind resources includes the following steps: Step 1, read the original wind measurement data to obtain all characteristic data at each time point; Specifically, firstly, the StreamReader method is used to read the string of the original wind measurement data file, and all the information at each time point is stored in the specified array, so as to obtain all the characteristic data at each time point.
[0019] Step 2: Based on the data from step 1, count the number of missing data and the completeness rate at each height; Specifically, all the strings in the array in step 1 are traversed. When a string is found to be empty, its type characteristics and height are recorded, and the number of times is accumulated. After the traversal is completed, it is classified according to wind speed, wind direction, temperature, and air pressure, so as to count the number of missing data and the completeness rate of each altitude layer; Figure 2 shown.
[0020] Step 3, according to the data in step 1, the wind shear index of each altitude layer is calculated, and the comprehensive wind shear index is calculated by fitting the power law function equation; Specifically, all height values and wind speed values are obtained from the array in step 1, the wind shear value between every two heights is calculated, and then the wind shear index and power law fitting curve of each layer are obtained through the power law function fitting equation, and the power law fitting curve is automatically displayed in the specified interface through the plotting tool; Figure 3 , 4 shown.
[0021] Step 4, based on the data in step 1, calculate the average air density per month and the air density at different hub heights; Specifically, the temperature and air pressure values of each month are obtained from the array in step 1, and the average temperature, average air pressure and air density of each month are calculated. Then, the estimated air density value is calculated according to the temperature and pressure altitude, wheel hub height and the measured air density value, and the month and air density graph is displayed in the specified interface through the plotting tool; Figure 5 , 6 shown.
[0022] Step 5, calculating the turbulence intensity based on the data in step 1; Specifically: first obtain the average wind speed and variance wind speed at each height from the array in step 1, calculate the average turbulence and the average turbulence of the 15m / s wind speed segment, then extract the wind speed values at different heights according to the wind speed segment, calculate the representative turbulence values of different wind speed segments at each height, then extract the wind direction values at different heights according to different wind directions, calculate the representative turbulence values of different wind direction segments at each height, and finally display the wind speed turbulence and wind direction turbulence graphics of the highest three heights in the specified interface through the plotting tool; Figure 7 , 8 shown.
[0023] Step 6, based on the data of step 1 and step 4, calculate the wind energy parameters of each altitude layer, the average wind speed and wind power density at different altitudes in each month, and the daily average wind speed and wind power density; Specifically include: Step 6.1, calculate the wind energy parameters at each altitude: extract the average wind speed and the cube sum of samples at all altitudes according to the whole year and wind speed in the 3-25m / s segment from the array in step 1, and use the air density value calculated in step 4 to calculate the average power density and wind speed number; Fig. 9 , 10 , as shown in 11.
[0024] Step 6.2, calculate the average wind speed and wind power density at different heights for each month: extract the average wind speed, the cube sum of samples and the number of samples according to the month from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the average wind speed and wind power density line graph at different heights to the specified interface; Fig.12 , 13 shown.
[0025] Step 6.3, calculate the daily average wind speed and wind power density: extract the average wind speed, the cube sum of samples and the number of samples by hour from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graphs at different heights in the specified interface; Fig.14 , 15 shown.
[0026] Step 7, based on the data from step 1 and step 4, statistics are collected on the wind speed and wind energy frequency distribution, the wind speed and wind energy frequency distribution, the main wind direction and main wind energy direction at each altitude, and the daily changes of the main wind direction and main wind energy at each altitude; Specifically include: Step 7.1, count the daily changes of wind speed and power density each month: extract the average wind speed, the cube sum of samples and the number of samples from the array in step 1 according to each hour of each month, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graphs at different heights for each month in the specified interface; Fig.16 , 17 shown.
[0027] Step 7.2, statistical wind speed and wind energy frequency distribution: extract the average wind speed in different wind speed segments at different heights from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind speed frequency and wind energy frequency, and use the plot tool to display the wind speed frequency and wind energy frequency bar graphs at different heights to the specified interface; Fig.18 , 19 shown.
[0028] Step 7.3, count the daily changes of the main wind direction and main wind energy at each altitude: extract the average wind direction in different wind direction segments at different altitudes from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind direction frequency and wind energy direction frequency, and display the wind direction frequency and wind energy direction frequency radar chart at different altitudes to the specified interface through the plot tool; Fig. 20 , 21 shown.
[0029] Step 7.4, count the daily changes of the main wind direction and main wind energy at each altitude: extract the average wind direction in different wind direction segments according to different months from the array in step 1, calculate the wind direction frequency data, and then use the air density value calculated in step 4 to calculate the wind energy frequency data, and use the plot tool to display the daily change radar chart of the wind direction and the daily change radar chart of the main wind energy at different altitudes of each month to the specified interface, such as Fig. 22 , 23 as shown. Step 8, calculating the maximum wind speed once in 50 years based on the data in Step 1 and Step 4; Specifically, the average wind speed is extracted from the array in step 1 according to different heights. First, the sample value of the 5-day thunderstorm method and the maximum wind speed of the standard air space once in 50 years at the height are calculated. Then, the maximum wind speed at different heights and the corresponding maximum wind speed of the standard air space once in 50 years are calculated using the 5-fold wind speed method, such as Fig.24 , 25 shown.
[0030] Step 9, finally, conduct a comprehensive assessment of wind energy resources based on the data from steps 2 to 8; Specifically: wind speed and wind power density values at different heights of the wind tower, air density values, wind speed ranges and frequency of wind speed and wind power at each height of the wind tower, wind direction of the wind tower and comprehensive analysis data on the direction in which wind power is mainly concentrated, such as Fig.26 shown.
[0031] The present invention reads the original wind measurement data, analyzes and calculates the data according to different functional points, automatically displays the calculation result tables and graphs, and finally summarizes the data to conduct a comprehensive assessment of wind energy resources. This solves the pain points that designers need to process huge amounts of data and write a large number of charts when conducting wind resource assessments, greatly improves work efficiency and work quality, and achieves the purpose of quickly performing wind resource calculation and analysis.
[0032] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for rapidly calculating and analyzing wind resources, characterized in that: The following steps are involved: Step 1, read the original wind measurement data to obtain all characteristic data at each time point; Step 2: Based on the data from step 1, count the number of missing data and the completeness rate at each height; Step 3, according to the data in step 1, the wind shear index of each altitude layer is calculated, and the comprehensive wind shear index is calculated by fitting the power law function equation; Step 4, based on the data in step 1, calculate the average air density per month and the air density at different hub heights; Step 5, calculating the turbulence intensity based on the data in step 1; Step 6, based on the data of step 1 and step 4, calculate the wind energy parameters of each altitude layer, the average wind speed and wind power density at different altitudes in each month, and the daily average wind speed and wind power density; Step 7, based on the data from step 1 and step 4, statistics are collected on the wind speed and wind energy frequency distribution, the wind speed and wind energy frequency distribution, the main wind direction and main wind energy direction at each altitude, and the daily changes of the main wind direction and main wind energy at each altitude; Step 8, calculating the maximum wind speed once in 50 years based on the data in Step 1 and Step 4; Step 9. Finally, based on the data from steps 2 to 8, conduct a comprehensive assessment of wind energy resources.
2. A method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 1 specifically includes: The original wind measurement data includes: the average value, variance value, maximum value and minimum value of wind speed, wind direction, temperature and air pressure at each height at each time point; The StreamReader method is used to read the string of the original wind measurement data file, and all the information at each time point is stored in the specified array, so as to obtain all the characteristic data at each time point.
3. A method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 2 specifically includes: Traverse all the strings in the array in step 1. When a string is found to be empty, record its type characteristics and height, and accumulate the number of times. After the traversal is completed, classify it according to wind speed, wind direction, temperature, and air pressure, so as to count the number of missing data and the completeness rate of each altitude layer; The statistical results include: the number of times wind speed, wind direction, temperature and air pressure should be measured at each altitude, the number of times missed measurements and the completeness rate.
4. A method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 3 specifically includes: Get all the height values and wind speed values from the array in step 1, calculate the wind shear value between every two heights, and then get the wind shear index and power law fitting curve of each layer through the power law function fitting equation, and automatically display the power law fitting curve graph in the specified interface through the plotting tool; The calculation results include: wind shear index between different altitude layers, comprehensive wind shear index and power law fitting curve.
5. The method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 4 specifically includes: Get the temperature and air pressure values of each month from the array in step 1, calculate the average temperature, average air pressure and air density of each month, and then calculate the estimated air density value according to the temperature and pressure altitude, wheel hub height and the measured air density value, and display the month and air density graph in the specified interface through the plot tool; The calculation results include: monthly average temperature, average air pressure, air density, air density values calculated for different wheel hub heights, and monthly air density curves.
6. A method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 5 specifically includes: First, obtain the average wind speed and variance wind speed at each height from the array in step 1, calculate the average turbulence and the average turbulence of the 15m / s wind speed segment, and then extract the wind speed values at different heights according to the wind speed segment, calculate the representative turbulence values of the different wind speed segments at each height, then extract the wind direction values at different heights according to different wind directions, calculate the representative turbulence values of the different wind direction segments at each height, and finally display the graphics of wind speed turbulence and wind direction turbulence at the highest three heights in the specified interface through the plotting tool; The calculation results of turbulence intensity include: turbulence calculation results at each height, representative turbulence calculation results of different wind speed segments at each height, representative turbulence calculation results of different wind direction segments at each height, and turbulence diagrams of wind speed and wind direction.
7. A method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 6 specifically includes: Step 6.1, calculate the wind energy parameters at each altitude layer: Extract the average wind speed at all heights and the cube sum of samples according to the whole year and wind speed in the 3-25m / s segment from the array in step 1, and use the air density value calculated in step 4 to calculate the average power density and wind speed number; The calculation results include: average wind speed, average wind power density and wind speed number for each altitude layer in the whole year and standard wind speed range; Step 6.2, calculate the average wind speed and wind power density at different heights for each month: First, extract the average wind speed, the cube sum of samples and the number of samples according to the month from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the average wind speed and wind power density line graphs at different heights in the specified interface; The calculation results include: average wind speed and wind power density data at each altitude layer each month, and the corresponding line graph; Step 6.3, calculate the daily average wind speed and wind power density: First, extract the average wind speed, the cube sum of samples and the number of samples by hour from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graphs at different heights in the specified interface; The calculation results include: wind speed and wind power density data at each altitude layer at every hour, and the corresponding line graph.
8. The method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 7 specifically includes: Step 7.1, calculate the daily changes of wind speed and power density per month: First, extract the average wind speed, the cube sum of samples and the number of samples from the array in step 1 according to each month and each hour, and then use the air density value calculated in step 4 to calculate the wind power density, display it in the specified table, and use the plot tool to display the wind speed and wind power density line graph at different heights for each month in the specified interface; The statistical results include: data on wind speed and wind power density at each altitude layer at each hour of each month, and the corresponding line graph; Step 7.2, statistical wind speed and wind energy frequency distribution: First, extract the average wind speed at different wind speed segments at different heights from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind speed frequency and wind energy frequency, and use the plot tool to display the wind speed frequency and wind energy frequency bar graphs at different heights to the specified interface; The statistical results include: the distribution of wind speed and wind energy frequency at different wind speed ranges at each altitude layer, and the corresponding bar graphs; Step 7.3, count the daily changes of the main wind direction and main wind energy at each altitude: First, extract the average wind direction in different wind direction segments at different heights from the array in step 1, and then use the air density value calculated in step 4 to calculate the wind direction frequency and wind energy direction frequency, and use the plot tool to display the wind direction frequency and wind energy direction frequency radar charts at different heights to the specified interface; The statistical results include: the distribution of wind direction and wind energy direction frequency at each altitude in different wind direction segments, and the corresponding radar chart; Step 7.4, count the daily changes of the main wind direction and main wind energy at each altitude: First, extract the average wind direction in different wind direction segments in different months from the array in step 1, calculate the wind direction frequency data, and then use the air density value calculated in step 4 to calculate the wind energy frequency data, and use the plot tool to display the daily change radar chart of the wind direction at different heights in each month and the daily change radar chart of the main wind energy to the specified interface; The statistical results include: the monthly changes of the main wind direction and main wind energy at each altitude layer in different wind direction segments, and the corresponding radar charts.
9. The method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 8 specifically includes: extracting the average wind speed from the array in step 1 according to different heights, first calculating the sample value of the 5-day thunderstorm method at the height and the maximum wind speed of the standard air once in 50 years, and then using the 5-fold wind speed method to calculate the maximum wind speed at different heights and the corresponding maximum wind speed of the standard air once in 50 years.
10. The method for rapidly calculating and analyzing wind resources according to claim 1, characterized in that: Step 9 specifically includes: comprehensive analysis data of wind speed and wind power density values at different heights of the wind tower, air density values, wind speed range and frequency of wind speed and wind energy at each height of the wind tower, wind direction of the wind tower and the direction in which wind energy is mainly concentrated; the evaluation results include: wind energy parameter statistics at each height layer, air density, wind speed and wind energy frequency distribution, and main wind direction and main wind energy direction.