Method and device for determining normal working wind speed of heliostat based on DNI and wind speed

Abstract

The application discloses a method and device for determining normal working wind speed of a heliostat based on DNI and wind speed, comprising the following steps: S1, obtaining DNI data and wind speed data of at least one preset period of a place where a solar-thermal power station is located, and extracting wind speed frequency distribution in the period according to the wind speed data; S2, screening available data under the condition that illumination time is met and DNI is greater than a preset value in the DNI data and the wind speed frequency distribution data; S3, calculating DNI data corresponding to each level of wind speed in the available data and calculating the proportion of the DNI data in the total DNI data, and generating a DNI cumulative distribution function; S4, generating a wind force grade cumulative distribution function through the available data; and S5, jointly analyzing the optimal working wind speed value of the heliostat through the DNI cumulative distribution function and the wind force grade cumulative distribution function. The application can effectively help mechanical design of the heliostat, and the normal working wind speed of the heliostat determined by jointly considering the DNI distribution frequency and the wind speed frequency can reach optimal heat collection at the lowest cost.

Description

Technical Field

[0001] This application relates to the field of solar thermal power generation technology, and more specifically, to a method and apparatus for determining the normal operating wind speed of a heliostat based on DNI and wind speed. Background Technology

[0002] The world is currently facing extremely serious energy and environmental problems, and solar thermal power generation is one of the key technologies for solving these problems. Tower molten salt solar thermal power generation is one of the technical routes for solar thermal power generation, which can generally be divided into three systems: a concentrating solar collector system, a heat storage and exchange system, and a conventional power generation system. The concentrating solar collector system consists of a concentrating system and a heat collection system. The cost of the concentrator (heliostat) accounts for 45% to 70% of the initial investment, and the annual average efficiency of the concentrating field is generally 58% to 72%. Therefore, research on the concentrating process has a significant impact on system efficiency and cost. In the mechanical design of the heliostat body, it is necessary to consider the different wind speeds under normal operation (ensuring tracking accuracy), without damage under any operating state (without considering tracking accuracy), and without damage under protective state.

[0003] There are generally two methods to determine the normal operating wind speed of a heliostat. Method one follows the experience of previous research and practice, and the normal operating wind speed value is determined to be 13 m / s. Method two is based on the wind speed corresponding to 90% of the cumulative distribution function of wind speed frequency.

[0004] However, both methods have certain drawbacks. The disadvantage of method one is that different project locations have extremely different climates, air densities, and wind speed frequency distributions. Using the same standard will result in some project locations having a wind speed setting of 13 m / s that is higher than the actual needs, causing a great waste of heliostat materials; while in other project locations, the wind speed setting of 13 m / s will be lower than the actual needs, causing the heliostat to malfunction.

[0005] Method 2, compared to Method 1, considers the wind speed frequency distribution at different project locations, making it more targeted towards wind speed. However, it does not consider the DNI frequency, which may result in the calculated wind speeds at which the heliostats can operate normally in some locations having an excessively high or low DNI frequency. An excessively high DNI frequency leads to wasted costs; an excessively low DNI frequency results in insufficient heat collection. Summary of the Invention

[0006] This invention provides a method for determining the normal operating wind speed of a heliostat based on DNI and wind speed. The method includes:

[0007] S1. Obtain DNI data and wind speed data for at least one preset period at the location of the solar thermal power plant, and extract the wind speed frequency distribution within the period based on the wind speed data.

[0008] S2. Filter available data from DNI data and wind speed frequency distribution data that meet the conditions of illumination time and DNI greater than the preset value;

[0009] S3. Calculate the sum of DNI data corresponding to each wind speed level in the available data and calculate its proportion of the total sum of DNI data to generate the DNI cumulative distribution function.

[0010] S4. Generate a cumulative distribution function of wind force level using available data;

[0011] S5. Analyze the optimal working wind speed of the heliostat by combining the DNI cumulative distribution function and the wind force level cumulative distribution function.

[0012] Furthermore, in step S1, the DNI data is obtained through a database, meteorological calculation software, or solar energy resource assessment tools, or by calculating meteorological data and satellite remote sensing observation data of the location of the solar thermal power plant, or by obtaining actual measurement data from the photometric station at the location of the solar thermal power plant; the DNI data is the hourly DNI value of the location of the solar thermal power plant within a period;

[0013] The wind speed data is the hourly wind speed at the heliostat installation height at the location of the solar thermal power plant, corresponding to the DNI data time.

[0014] Furthermore, in step S1, the step of extracting the wind speed frequency distribution within the period based on the wind speed data includes: rounding the acquired wind speed data and converting it into wind speed frequency distribution data, wherein the wind speed frequency distribution data is obtained by dividing the wind speed data into multiple wind speed intervals based on multiple identical preset wind speed values.

[0015] Furthermore, step S2 includes the following steps:

[0016] First, the DNI data and wind speed frequency distribution data are filtered according to the sunrise and sunset times of each day in the preset cycle, and only the DNI data and wind speed frequency distribution data during the sunshine period are retained.

[0017] Secondly, the DNI data and wind speed frequency distribution data during the sunshine period were further filtered, and the DNI data and wind speed frequency distribution data corresponding to the time when the DNI was greater than the preset value were retained.

[0018] Finally, the filtered DNI data and wind speed frequency distribution data are correlated according to the corresponding time to generate usable data.

[0019] Furthermore, in step S3, the calculation of the proportion of all DNI data includes: calculating the sum of DNI data for each wind level corresponding to the time in the available data, and calculating the proportion of the sum of DNI data for each wind level corresponding to the time in the sum of DNI data for all wind levels.

[0020] Furthermore, in step S3, generating the DNI cumulative distribution function includes: calculating the proportion of DNI data for each wind force level and the time corresponding to wind force levels below that level, as well as the proportion of DNI data for all wind force levels at all corresponding times, and generating the DNI cumulative distribution function using all proportion data.

[0021] Furthermore, step S4 includes: calculating the proportion of time corresponding to each wind speed level to the total time in the available data based on the wind speed frequency distribution data of each wind speed level in the available data, and generating a cumulative distribution function of wind force level through this proportion.

[0022] Furthermore, in step S5, when the maximum wind force level of the cumulative distribution function of wind force level is less than or equal to the preset wind speed, the working wind speed of the heliostat is set to the value corresponding to the maximum wind force level in the cumulative distribution function of wind force level.

[0023] When the maximum wind speed of the cumulative distribution function of wind force level is greater than the preset wind speed, an initial threshold is set, and the wind speed level corresponding to the threshold DNI data and the proportion is judged. If the wind speed level corresponding to the threshold is less than or equal to the preset wind speed, the threshold is selected as the working wind speed of the heliostat. If the wind speed level corresponding to the threshold is greater than the preset wind speed, the initial threshold is reduced, and the corresponding wind speed is reselected as the working wind speed of the heliostat.

[0024] A device for determining the normal operating wind speed of a heliostat based on DNI and wind speed is also provided. The device for determining the normal operating wind speed of a heliostat includes a computing device and a data acquisition device.

[0025] The acquisition device is used to acquire DNI data and wind speed data;

[0026] The computing device filters available data from the DNI and wind speed frequency distribution data that meet the conditions of illumination time and DNI greater than a preset value; generates cumulative distribution functions for DNI and wind force level respectively; and determines the normal operating wind speed of the heliostat through the cumulative distribution function.

[0027] Furthermore, the device for determining the normal operating wind speed of the heliostat includes a storage device for storing the collected DNI data and wind speed data, as well as intermediate data during the process of obtaining the normal operating wind speed of the heliostat.

[0028] The beneficial effects of this application are:

[0029] This invention proposes a method for determining the normal operating wind speed of a heliostat. This method takes into account both the DNI distribution frequency and wind speed frequency at the location of the heliostat. By comprehensively considering the power generation efficiency and construction cost through the DNI distribution frequency and wind speed frequency, the normal operating wind speed of the heliostat determined by this method can effectively help the mechanical design of the heliostat to achieve optimal heat collection at the lowest cost. Attached Figure Description

[0030] The advantages of the above and additional aspects of this application will become apparent and readily understood in the description of the embodiments in conjunction with the following drawings, wherein:

[0031] Figure 1 This is a flowchart of a method for determining the normal operating wind speed of a heliostat based on DNI and wind speed. Detailed Implementation

[0032] To better understand the above-mentioned objectives, features, and advantages of this application, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of this application can be combined with each other.

[0033] In the following description, many specific details are set forth in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of this application is not limited to the specific embodiments disclosed below.

[0034] like Figure 1 As shown, this embodiment provides a method for determining the normal operating wind speed of a heliostat based on DNI and wind speed. The method includes:

[0035] S1. Obtain DNI data and wind speed data for at least one preset period at the location of the solar thermal power plant, and extract the wind speed frequency distribution within the period based on the wind speed data.

[0036] Specifically, DNI data is obtained through databases, meteorological calculation software, or solar energy resource assessment tools. It can also be obtained by calculating meteorological data and satellite remote sensing observation data of the location of the solar thermal power plant, or by obtaining actual measurement data from the photometric station at the location of the solar thermal power plant. The DNI data is the hourly DNI value of the location of the solar thermal power plant within a period. The wind speed data is the hourly wind speed at the heliostat installation height at the location of the solar thermal power plant corresponding to the time of the DNI data.

[0037] In this embodiment, the preset period is a complete year; in other embodiments, it can be multiple complete years. Furthermore, if data from certain months of a year is not valuable, the preset period may exclude these months. For example, the collection period set for regions with polar nights may exclude months without sunlight, such as January to March 21 and September 23 to December, and analyze data using a period of less than 12 months or accurate to the day.

[0038] The acquired wind speed data is rounded and converted into wind speed frequency distribution data. The wind speed frequency distribution data is divided into multiple wind speed intervals based on multiple identical preset wind speed values.

[0039] In one embodiment, the wind speed frequency distribution uses 1 m / s intervals as wind speed ranges, with each interval's number representing the median value; for example, a 5 m / s interval would be 4.6 m / s - 5.5 m / s. In other embodiments, the wind speed frequency distribution can also use other wind speed values ​​to set the wind speed intervals, such as 2 m / s intervals or 0.5 m / s intervals.

[0040] S2. Filter available data from DNI data and wind speed frequency distribution data that meet the conditions of illumination time and DNI greater than the preset value;

[0041] First, the DNI data and wind speed frequency distribution data were filtered based on the sunrise and sunset times of each day throughout the year, retaining only the DNI data and wind speed frequency distribution data during the sunshine period;

[0042] Secondly, the DNI data and wind speed frequency distribution data during the sunshine period are further filtered, retaining the DNI data and wind speed frequency distribution data corresponding to the time when the DNI is greater than the preset value. In this embodiment, the preset value is 100. In other embodiments, the preset value can also be adjusted according to the actual situation, such as 95 or 105. However, the preset value cannot be set too low, as a low DNI indicates insufficient solar irradiance, and the solar thermal power plant cannot generate electricity effectively.

[0043] Finally, the filtered DNI data and wind speed frequency distribution data are correlated according to the corresponding time to generate usable data.

[0044] S3. Calculate the sum of DNI data corresponding to each wind speed level in the available data and calculate its proportion of the total DNI data, generating the DNI cumulative distribution function;

[0045] Calculate the sum of DNI data for each wind level and time period in the available data, and calculate the proportion of the sum of DNI data for each wind level and time period to the sum of DNI data for all wind levels.

[0046] Furthermore, the proportion of DNI data for each wind force level and the corresponding time at wind force levels below that level, as well as the sum of DNI data for all wind force levels at all corresponding times, is calculated separately. A cumulative distribution function of DNI is then generated using all the proportional data.

[0047] S4. Generate a cumulative distribution function of wind force level using available data;

[0048] Calculate the proportion of time corresponding to each wind speed level in the total available data based on the wind speed frequency distribution data of each wind speed level in the available data, and generate the cumulative distribution function of wind speed level using this proportion.

[0049] S5. Analyze the optimal working wind speed of the heliostat by combining the DNI cumulative distribution function and the wind force level cumulative distribution function.

[0050] When wind speeds reach 13 m / s, the mechanical design of heliostats requires significantly more investment to cope with increasing wind speeds. Therefore, considering the optimal wind speed for heliostat operation necessitates taking into account the costs incurred under high wind speeds, the corresponding effective operating time at high wind speeds, and the DNI (Dynamic Niche Intake) data and proportion at high wind speeds. If the DNI data and proportion are low at high wind speeds, even if the investment is made to accommodate high wind speeds, it will not generate equivalent economic value. Conversely, if the DNI data and proportion remain high at high wind speeds, then investing additional resources for high wind speed operations is economically worthwhile.

[0051] Therefore, the joint analysis also needs to consider two cases separately. When the maximum wind force level of the cumulative distribution function of wind force level is less than or equal to 13 m / s, the design idea of ​​obtaining the maximum DNI as the normal operating wind speed of the heliostat is adopted. Therefore, the operating wind speed of the heliostat is set to the value corresponding to the maximum wind force level in the cumulative distribution function of wind force level.

[0052] When the maximum wind speed in the cumulative distribution function of wind force is greater than 13 m / s, a balance between design cost and DNI (Depth Intensity Number) needs to be considered. Set 95% as the initial threshold, and determine the wind speed corresponding to the threshold's DNI data and percentage. If the wind speed corresponding to the threshold is less than or equal to 13 m / s, then that threshold is selected as the heliostat's operating wind speed. If the wind speed corresponding to the threshold is greater than 13 m / s, then the wind speed corresponding to 90% of the cumulative distribution function of wind force is selected as the heliostat's operating wind speed.

[0053] This invention proposes a method for determining the normal operating wind speed of a heliostat. This method takes into account both the DNI distribution frequency and wind speed frequency at the location of the heliostat. By comprehensively considering the power generation efficiency and construction cost through the DNI distribution frequency and wind speed frequency, the normal operating wind speed of the heliostat determined by this method can effectively help the mechanical design of the heliostat to achieve optimal heat collection at the lowest cost.

[0054] This invention further illustrates, through an embodiment, a method for determining the normal operating wind speed of a heliostat based on DNI and wind speed.

[0055] Direct normal radiation (DNI) data can be obtained through NASA databases, meteorological calculation software Meteonorm, solar resource assessment tool Solargis, meteorological data of the location of the solar thermal power plant, satellite remote sensing observation data, and through certain calculation methods, or through actual measurement data from photometric stations at the location of the solar thermal power plant.

[0056] Of these, actual measurement data is the most accurate; however, its long acquisition cycle and high cost mean it is not commonly used in practical applications. Most data obtained through meteorological data, satellite remote sensing, and meteorological software are not actual measurements but rather assessments based on certain calculation methods. Furthermore, even if the recorded data is accurate, it cannot accurately reflect future weather conditions, especially given the significant changes in weather patterns in recent years and the increasing prevalence of alternating years of high and low rainfall. Therefore, meteorological data can only serve as a reference for weather conditions over the next 25 years. Regarding the accuracy of meteorological software, Solargis is generally considered superior to Meteonorm, which in turn is superior to NASA. NASA data tends to be overestimated, while Meteonorm data tends to be underestimated.

[0057] This embodiment uses Solargis, a solar energy resource assessment tool, to obtain satellite remote sensing data and geographic information system technology of the location of the solar thermal power plant, and performs calculations using scientific algorithms.

[0058] SolarGIS is a solar energy resource assessment tool developed by SolarGIS SRO in Europe. It utilizes satellite remote sensing data, GIS (Geographic Information System) technology, and advanced scientific algorithms to obtain a high-resolution database of solar energy resources and climate elements, covering Europe, Africa, and Asia. It is now widely used in the early development, resource assessment, and power generation calculation of photovoltaic, concentrated photovoltaic, and solar thermal projects.

[0059] Wind speed data is obtained through the Xihe Energy Big Data Platform, which provides hourly wind speed data for the location of the solar thermal power plant corresponding to the DNI data time.

[0060] Wind speed frequency distribution refers to calculating the frequency of wind speed occurrences within each wind speed interval, with 1 m / s as a unit. In this embodiment, the hourly wind speeds at the location of the solar thermal power plant are rounded down and converted into wind speed frequency distribution data.

[0061] We statistically analyzed the sunrise and sunset times and the times when DNI ≥ 100 for each day of the year. We then removed the data corresponding to times with no sunshine and DNI < 100 from the DNI data and wind speed frequency distribution data, retaining only the usable data.

[0062] Calculate the proportion of DNI data for each wind force level and the corresponding time below that wind force level, as well as the proportion of DNI data for all wind force levels and the corresponding time.

[0063] Generate the DNI cumulative distribution function, with wind speed level as the x-axis and the cumulative proportion of DNI data as the y-axis. Perform curve fitting based on each point. The starting point of the cumulative distribution function is 0, and each point represents the cumulative proportion of DNI data corresponding to wind speeds less than or equal to the x-axis level.

[0064] Simultaneously, a cumulative distribution function of wind force level is generated. The cumulative distribution function of wind force level uses wind force level as the abscissa and the ordinate as the cumulative proportion of duration. Curve fitting is performed based on each point. The starting point of the cumulative distribution function is 0, and each point represents the cumulative proportion of the duration of wind speed less than or equal to the abscissa level in the total time of the available data.

[0065] When the maximum wind speed in the cumulative wind speed distribution function is less than or equal to 13 m / s, the working wind speed of the heliostat is set to the value corresponding to the maximum wind speed in the cumulative wind speed distribution function. When the maximum wind speed in the cumulative wind speed distribution function is greater than 13 m / s, 95% is set as the initial threshold, and the wind speed level corresponding to the threshold and the percentage is judged. If the wind speed level corresponding to the threshold is less than or equal to 13 m / s, then the threshold is selected as the working wind speed of the heliostat. If the wind speed level corresponding to the threshold is greater than 13 m / s, then the wind speed corresponding to 90% in the cumulative wind speed distribution function is selected as the working wind speed of the heliostat. If the wind speed corresponding to 90% is still high, the threshold can be further reduced.

[0066] The present invention also provides a device for determining the normal operating wind speed of a heliostat based on DNI and wind speed, the device comprising a storage device, a computing device, and a data acquisition device.

[0067] The data acquisition device can be a combination of a solar radiation sensor and a wind speed sensor, which can measure the actual data at a photometer station at the location of the solar thermal power plant; or it can be a data interface that can directly import the required DNI data and wind speed data through meteorological software and databases.

[0068] The computing device is a computer or cloud computing platform capable of running analysis software. First, the computing device rounds the wind speed data acquired by the acquisition device, converting it into wind speed frequency distribution data. Second, the computing device selects usable data from the DNI data and wind speed frequency distribution data that meet the conditions of sufficient illumination time and a DNI greater than a preset value. Third, the computing device calculates the sum of the DNI data corresponding to each wind speed level in the usable data and calculates its proportion of the total DNI data, generating a cumulative DNI distribution function. Fourth, the computing device generates a cumulative wind force distribution function from the usable data. Finally, the computing device jointly analyzes the optimal operating wind speed value for the heliostat using the cumulative DNI distribution function and the cumulative wind force distribution function.

[0069] The storage device is a hard drive or network cloud disk used for local storage, to save the DNI data and wind speed data acquired by the acquisition device, as well as the process data generated by the computing device during the calculation process.

[0070] The present invention proposes a wind speed device for normal operation of a heliostat, which can take into account the DNI distribution frequency and wind speed frequency at the location of the heliostat. By comprehensively considering the power generation efficiency and construction cost through the DNI distribution frequency and wind speed frequency, it can effectively help the mechanical design of the heliostat, balance construction costs and power generation, and maximize benefits.

[0071] Although this application has been disclosed in detail with reference to the accompanying drawings, it should be understood that these descriptions are merely exemplary and not intended to limit the application of this application. The scope of protection of this application is defined by the appended claims and may include various variations, modifications, and equivalents of the invention without departing from the scope and spirit of this application.

Claims

1. A method for determining the normal operating wind speed of a heliostat based on DNI and wind speed, characterized in that, The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed includes: S1. Obtain DNI data and wind speed data for at least one preset period at the location of the solar thermal power plant, and extract the wind speed frequency distribution within the period based on the wind speed data. S2. Filter available data from DNI data and wind speed frequency distribution data that meet the conditions of illumination time and DNI greater than the preset value; S3. Calculate the sum of DNI data corresponding to each wind speed level in the available data and calculate its proportion of the total sum of DNI data to generate the DNI cumulative distribution function. S4. Generate a cumulative distribution function of wind force level using available data; S5. Analyze the optimal working wind speed of the heliostat by combining the DNI cumulative distribution function and the wind force level cumulative distribution function. In step S3, generating the DNI cumulative distribution function includes: calculating the proportion of DNI data for each wind force level and the time corresponding to wind force levels below their respective wind force levels, and the proportion of the sum of DNI data for all wind force levels at all corresponding times, and generating the DNI cumulative distribution function using all proportion data; In step S5, when the maximum wind force level of the cumulative distribution function of wind force level is less than or equal to the preset wind speed, the working wind speed of the heliostat is set to the value corresponding to the maximum wind force level in the cumulative distribution function of wind force level. When the maximum wind speed of the cumulative distribution function of wind force is greater than the preset wind speed, an initial threshold is set, and the wind force corresponding to the DNI data and the proportion of the initial threshold is determined. If the wind force corresponding to the initial threshold is less than or equal to the preset wind speed, the wind force corresponding to the initial threshold is selected as the working wind speed of the heliostat. If the wind force corresponding to the initial threshold is greater than the preset wind speed, the initial threshold is reduced, and the corresponding wind speed is reselected as the working wind speed of the heliostat.

2. The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed according to claim 1, characterized in that, In step S1, the DNI data is obtained through a database, meteorological calculation software, or solar energy resource assessment tools, or by calculating meteorological data and satellite remote sensing observation data of the location of the solar thermal power plant, or by obtaining actual measurement data from the photometric station at the location of the solar thermal power plant; the DNI data is the hourly DNI value of the location of the solar thermal power plant within a period; The wind speed data is the hourly wind speed at the heliostat installation height at the location of the solar thermal power plant, corresponding to the DNI data time.

3. The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed according to claim 1, characterized in that, In step S1, the step of extracting the wind speed frequency distribution within the period based on the wind speed data includes: rounding the acquired wind speed data and converting it into wind speed frequency distribution data, wherein the wind speed frequency distribution data is obtained by dividing the wind speed data into multiple wind speed intervals based on multiple identical preset wind speed values.

4. The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed according to claim 1, characterized in that, Step S2 includes the following steps: First, the DNI data and wind speed frequency distribution data are filtered according to the sunrise and sunset times of each day in the preset cycle, and only the DNI data and wind speed frequency distribution data during the sunshine period are retained. Secondly, the DNI data and wind speed frequency distribution data during the sunshine period were further filtered, and the DNI data and wind speed frequency distribution data corresponding to the time when the DNI was greater than the preset value were retained. Finally, the filtered DNI data and wind speed frequency distribution data are correlated according to the corresponding time to generate usable data.

5. The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed according to claim 1, characterized in that, In step S3, the calculation of the proportion of the total DNI data includes: calculating the DNI data for each wind level and time in the available data, and calculating the proportion of the DNI data for each wind level and time in the total DNI data for all wind levels.

6. The method for determining the normal operating wind speed of a heliostat based on DNI and wind speed according to claim 1, characterized in that, Step S4 includes: calculating the proportion of time corresponding to each wind speed level to the total time in the available data based on the wind speed frequency distribution data of each wind speed level in the available data, and generating a cumulative distribution function of wind force level through this proportion.

7. A device for determining the normal operating wind speed of a heliostat, based on the method for determining the normal operating wind speed of a heliostat according to any one of claims 1-6, characterized in that, The device for determining the normal operating wind speed of the heliostat includes a computing device and a data acquisition device; The acquisition device is used to acquire DNI data and wind speed data; The computing device filters available data from the DNI and wind speed frequency distribution data that meet the conditions of illumination time and DNI greater than a preset value; generates cumulative distribution functions for DNI and wind force level respectively; and determines the normal operating wind speed of the heliostat through the cumulative distribution function.

8. The device for determining the normal operating wind speed of a heliostat according to claim 7, characterized in that, The device for determining the normal operating wind speed of the heliostat includes a storage device, which is used to store the collected DNI data and wind speed data, as well as intermediate data during the process of obtaining the normal operating wind speed of the heliostat.

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