Method and apparatus for calculating and evaluating loss of light collection efficiency of heliostat

Abstract

The present invention relates to a method and apparatus for calculating and evaluating the loss of light collection efficiency of a heliostat. 【Solution means】The present invention simulates the pulsating wind load distribution of a heliostat at different elevation-azimuth angles by CFD calculation, extracts the aerodynamic admittance function and shape parameters, constructs a pulsating wind load spectrum prediction model, calculates the pulsating wind load spectrum by combining the attitude parameters of the heliostat, applies the pulsating wind load spectrum to the structural model of the heliostat mirror by finite element analysis, obtains the instantaneous dynamic response, displacement and strain distribution characteristics of the heliostat, simulates the influence of mirror deformation on the light reflection path, quantifies the instantaneous influence on the light collection efficiency of the deformed mirror, and generates a dynamic curve of the change of light collection efficiency over time.

Description

Technical Field

[0001] The present invention relates to the technical field of solar thermal power generation, and more specifically, to a method and apparatus for calculating and evaluating the loss of the light collection efficiency of a heliostat.

Background Art

[0002] Solar thermal power generation is a clean and efficient method of utilizing renewable energy. A heliostat functions as a core member of a light collection system, and its performance directly affects the efficiency of the entire solar thermal power generation system. A heliostat reflects sunlight and focuses the light rays on a heat absorption tower to convert light energy into heat energy. However, under the action of a complex wind environment, a heliostat is significantly affected by wind loads, causing structural deformation and vibration, and further significantly reducing the light collection efficiency. According to research, wind loads may reduce the average light collection rate of a heliostat from 95.5% to 72.2%, resulting in serious solar energy loss, reduced utilization rate of equipment, and significantly increased power generation costs.

[0003] The influence of wind loads on a heliostat is expressed in various forms, including static wind loads and pulsating wind loads. Pulsating wind loads are caused by the spatio-temporal variation of wind speed and have high randomness and complexity. Currently, research on the wind loads of a heliostat and their effects mainly focuses on the following aspects.

[0004] 1. Wind tunnel tests and numerical simulations: The distribution characteristics of wind loads are studied through wind tunnel tests or numerical fluid dynamics (CFD) simulations. However, these methods are usually only applicable to specific operating conditions, and it is difficult to quickly predict the wind load effects in complex operating conditions.

[0005] 2. Structural deformation analysis: The finite element method is widely applied to the wind load response analysis of a heliostat to predict the structural deformation and vibration caused by wind loads. However, such research usually ignores the influence of deformation on the light ray focusing performance.

[0006] 3. Light collection efficiency evaluation: The conventional method for evaluating light collection efficiency is mainly based on ray tracing analysis under ideal operating conditions, and the influence under non-ideal operating conditions due to wind load is not fully considered, making it difficult to accurately quantify the loss of light collection efficiency caused by wind load.

[0007] In summary, in the prior art, there are still many drawbacks in quickly predicting the wind load effect of heliostats and its influence on light collection efficiency in complex wind environments. On the one hand, there is a lack of a unified model that can effectively predict the pulsating wind load of heliostats in different wind environments. On the other hand, there is a lack of systematic research on the calculation of the deformation and light collection efficiency loss of heliostats. Therefore, in complex operating conditions, by being able to efficiently and accurately predict the wind load of heliostats and its influence on light collection performance, a calculation method and device for the light collection efficiency loss of heliostats based on the prediction of wind load by the response surface method can be provided, which can provide important reference for the design and optimization of solar thermal power generation systems.

Summary of the Invention

Problems to be Solved by the Invention

[0008] To solve the technical problems existing in the above background art, the present invention solves the deficiencies in predicting the wind load of heliostats and evaluating its influence on light collection efficiency in complex wind environments in the prior art, and can efficiently and accurately analyze the pulsating wind load effect and its dynamic influence on light collection efficiency under different operating conditions of heliostats, and provides a calculation and evaluation method and device for the light collection efficiency loss of heliostats.

Means for Solving the Problems

[0009] To achieve the above technical means, in a first aspect, an efficient cross-document information extraction system based on a large-scale language model according to the present invention is Step 1: Using the autoregressive model method to generate the pulsating wind speed at the inlet of the flow field, establishing the flow field calculation region, and obtaining the pulsating wind load data of the heliostat at different elevation angles - azimuth angles; Step 2: Based on the extracted pulsating wind load data, analyzing its frequency domain characteristics, and calculating the aerodynamic admittance function of the wind load on the heliostat mirror for different combinations of elevation angles - azimuth angles; Step 3: Performing non - linear fitting on the aerodynamic admittance function using the least - squares method to obtain the shape parameters of the aerodynamic admittance function of the wind load for different combinations of elevation angles - azimuth angles; Step 4: Statistically analyzing the shape parameters of the aerodynamic admittance function for different combinations of elevation angles - azimuth angles, establishing a polynomial fitting model using the response surface method, and constructing a unified pulsating wind load spectrum prediction model adaptable to the operating conditions of all postures of the heliostat; Step 5: Substituting the elevation angle and azimuth angle of the heliostat corresponding to the actual heliostat structure posture into the unified pulsating wind load spectrum prediction model, and calculating to obtain the pulsating wind load spectrum of the heliostat mirror under actual operating conditions; Step 6: Establishing a finite - element model of the heliostat structure, applying the pulsating wind load spectrum to the finite - element model, and obtaining the instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load; Step 7: Simulating the sunlight transmission path using the ray - tracing method and determining the instantaneous light - collecting efficiency of the deformed mirror.

[0010] Furthermore, the said Step 1 includes: Step: Simulating the random fluctuation characteristics of the wind speed in the actual wind environment using the autoregressive model, and generating a pulsating wind speed time series conforming to the random characteristics in time - space; Step: Based on the generated pulsating wind speed time series, establishing a flow field numerical calculation region using the numerical fluid dynamics method; Step: Performing numerical simulation on the flow field by the CFD method to extract the pulsating wind load data of the heliostat mirror.

[0011] Furthermore, step 1 further includes a step of performing a rationality verification on the established flow field calculation region.

[0012] Furthermore, step 2 is a step of calculating the wind pressure power spectrum based on the formula of the quasi-steady wind pressure spectrum, and the formula of the quasi-steady wind pressure spectrum is as follows,

Number

Number

Number

Number

Number

[0013] Furthermore, step 3 is a step of performing non-linear fitting on the aerodynamic admittance function using the least squares method to obtain the shape parameters a, b, c, and the mathematical model of the aerodynamic admittance function is as follows,

Number

[0014] Furthermore, step 4 is Performing fitting with the cosine values of the elevation angle α and the azimuth angle β as the input variables of the polynomial fitting model, and the shape parameters a, b, and c as the output variables of the polynomial fitting model to generate fitting results. The formula of the model is specifically as follows:

Number

Number

Number

Number

Equation

[0015] In a second aspect, an apparatus for calculating and evaluating the light collection efficiency loss of a heliostat based on the prediction of wind loads by the response surface method according to the present invention generates a pulsating wind speed number, generates a pulsating wind speed at the inlet of the flow field by the autoregressive model method, and combines numerical simulation and test data to establish a flow field calculation region capable of reflecting the actual characteristics of the wind field, a data generation module calculates the pulsating wind load spectrum of the heliostat mirror under different operating conditions based on the input data provided by the data generation module, and calculates the aerodynamic admittance function of the wind load of the heliostat mirror for different combinations of elevation angles and azimuth angles, a wind load calculation module performs non-linear fitting on the aerodynamic admittance function using the least squares method to obtain a shape parameter, a shape parameter calculation module Statistically analyze the shape parameters of the aerodynamic admittance function for different combinations of elevation angles and azimuth angles, establish a polynomial fitting model using the response surface method, and construct a unified pulsating wind load spectrum prediction model that adapts to the operating conditions of all postures of the heliostat. A model construction module, Substitute the elevation angle and azimuth angle of the heliostat corresponding to the actual heliostat structure posture into the unified pulsating wind load spectrum prediction model, and calculate the pulsating wind load spectrum of the heliostat mirror under the actual operating conditions. A calculation module, Establish a finite element model of the heliostat structure, apply the pulsating wind load spectrum to the finite element model, and obtain the instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load. A structural response analysis module, Simulate the solar ray transmission path using the ray tracing method, and determine the instantaneous light collection efficiency of the deformed mirror. An optical performance evaluation module, including.

[0016] In a third aspect, a computer-readable storage medium including a stored program, when the program is executed, controls a device in which the computer-readable storage medium is located to execute a method for calculating and evaluating the light collection efficiency loss of a heliostat based on the prediction of wind load by the above-mentioned response surface method.

Advantages of the Invention

[0017] The beneficial effects of the present invention are as follows.

[0018] 1. Efficiency: The unified pulsating wind load spectrum prediction model enables rapid calculation of pulsating wind loads in complex wind environments.

[0019] 2. Accuracy: By combining finite element analysis and the ray tracing method, the dynamic influence of mirror deformation on light collection efficiency can be accurately quantified.

[0020] 3. Applicability: It is applicable to the analysis of the wind load effect and optical performance of heliostats under various elevation and azimuth operating conditions, and provides a reliable basis for the design optimization of solar thermal power generation systems.

Brief Description of the Drawings

[0021] The drawings constituting a part of the present invention provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are for interpreting the present invention, but do not unduly limit the present invention.

[0022]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Modes for Carrying Out the Invention

[0023] Hereinafter, the present invention will be further described with reference to the drawings and embodiments.

[0024] Note that all of the following detailed descriptions are illustrative and are intended to provide further explanation of the present invention. Unless otherwise specified, each technical term and scientific term used in this embodiment has the same meaning as commonly understood by those skilled in the technical field to which the present invention pertains.

[0025] Note that the terms used herein are for the purpose of describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. For example, unless otherwise indicated by the context, in this specification, the singular forms also include the plural forms, and when the terms "include" and / or "comprise" are used in this specification, it should be understood that features, steps, operations, components, assemblies, and / or combinations thereof are present.

[0026] In the present invention, the orientation or positional relationship indicated by terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", etc. is based on the orientation or positional relationship shown in the drawings, and is merely a relative term determined for explaining the structural relationship of each member or element of the present invention, and does not specifically refer to any member or element in the present invention and should not be understood as limiting the present invention.

[0027] In the present invention, terms such as "fixed connection", "connection", "coupling", etc. should be understood in a broad sense, which means that they may be fixedly connected, integrally connected, removably connected, directly connected, or indirectly connected through an intermediate medium. Relevant scientific researchers or technicians in this field can determine the specific meaning of the above terms in the present invention according to specific circumstances and should not be understood as limiting the present invention.

[0028] (Example 1) This embodiment provides a method for calculating the light collection efficiency loss of a heliostat based on the prediction of wind loads by the response surface method. The method is applicable to the wind load analysis and optical performance evaluation of heliostats in complex wind environments. The method realizes the prediction of the pulsating wind load of the heliostat mirror, the deformation analysis of the mirror structure, and the evaluation of the influence of the deformation on the light collection efficiency by dividing steps. Specifically, as shown in FIG. 1, the method includes the following steps S101 to S107.

[0029] In S101, the autoregressive model method is used to generate the pulsating wind speed at the inlet of the flow field, establish the flow field calculation domain, and obtain the pulsating wind load data of the heliostat at different elevation-azimuth angles.

[0030] Specifically, S101 includes the following steps S101-1 to S101-3.

[0031] In S101-1, the autoregressive model is used to simulate the random fluctuation characteristics of the wind speed in the actual wind environment, and generate a pulsating wind speed time series that conforms to the random characteristics in space and time.

[0032] Specifically, the random fluctuation characteristics of the wind speed in the wind environment (for example, the mean wind speed, turbulence intensity, and turbulence integral scale) are input into the autoregressive model (AR model) to generate a power spectrum in which the pulsating wind speed time series can show random characteristics and periodic fluctuation characteristics in the time domain, and distribution characteristics that conform to a typical turbulence model (for example, the Von Karman theoretical spectrum) in the frequency domain. The generated power spectrum is compared with the Von Karman theoretical spectrum. If the two are highly consistent, it indicates that the data of the generated pulsating wind speed time series is accurate.

[0033] In S101-2, based on the generated pulsating wind speed time series, the numerical calculation domain of the flow field is established using the computational fluid dynamics (CFD) method (shown in FIG. 2).

[0034] The range of the flow field numerical calculation region is 6H (length in the flow direction) × 4H (height) × 6H (width), where H is the characteristic height of the heliostat, ensuring that the calculation region can cover the action range of the pulsating wind speed. The boundary conditions of the flow field numerical calculation region are set as follows. The inlet is a velocity inlet, and the pulsating wind speed time series is input. The outlet is a pressure outlet, ensuring that the air flow is freely discharged. The upper, lower, and side surfaces are set as symmetric boundaries to avoid boundary interference, and the ground is set as a non-slip wall surface to simulate the ground roughness effect. The turbulent flow characteristics of the flow field numerical calculation region are simulated using the RNG k-ε model to balance calculation efficiency and accuracy.

[0035] To ensure the accuracy of the flow field simulation, a rationality verification is performed on the simulation results. The first is to verify the distribution associated with the height of the turbulent intensity (shown in Figure 3), and the result is consistent with the experimental data. The second is to verify whether the distribution of the mean wind speed cross-section conforms to the typical logarithmic wind speed cross-section model (shown in Figure 3), and the result shows that the flow field can accurately reflect the vertical distribution characteristics of the wind speed. The third is to verify whether the power spectrum of the pulsating wind speed is consistent with the Von Karman turbulence theory (shown in Figure 4), and the verification result shows that the flow field simulation conforms to the actual wind environment.

[0036] In S101-3, a numerical simulation is performed on the flow field by the CFD method to extract the pulsating wind load data of the heliostat mirror and provide basic data support for subsequent analysis.

[0037] In S102, based on the extracted pulsating wind load data, its frequency domain characteristics are analyzed, and the aerodynamic admittance function of the wind load of the heliostat mirror for different combinations of elevation angles and azimuth angles is calculated.

[0038] Specifically, S102 includes the following steps S102-1 to S102-2.

[0039] In S102-1, the wind pressure power spectrum is calculated based on the formula of the quasi-steady wind pressure spectrum, and the formula of the quasi-steady wind pressure spectrum is as follows.

Number

Number

Number

Number

[0040] In S102-2, the aerodynamic admittance function is defined as the ratio of the formula in the frequency domain of the fluctuating wind load data to the quasi-steady wind pressure spectrum, and the formula of the aerodynamic admittance function is as follows.

Number

[0041] In S103, the least squares method is used to perform non-linear fitting on the aerodynamic admittance function to obtain the shape parameters of the aerodynamic admittance function of the wind load for different combinations of elevation angles and azimuth angles.

[0042] Specifically, as shown in Figure 5, S103 includes the following step S103-1.

[0043] In S103-1, non-linear fitting is performed on the aerodynamic admittance function using the least squares method to obtain the shape parameters a, b, and c, and the mathematical model of the aerodynamic admittance function is as follows.

Number

[0044] In this embodiment, based on the pulsating wind load time-domain data obtained from the CFD simulation, its frequency-domain characteristics are analyzed, and the power spectral density of the aerodynamic admittance function is calculated. Also, by optimizing the shape parameters of the aerodynamic admittance function model using the non-linear fitting method, the dynamic response characteristics of the wind load on the heliostat mirror under different operating conditions can be accurately reflected.

[0045] In S104, the shape parameters of the aerodynamic admittance function for different combinations of elevation angles - azimuth angles are statistically analyzed, a polynomial fitting model is established using the response surface method, and a unified pulsating wind load spectrum prediction model adapted to the operating conditions of all postures of the heliostat is constructed.

[0046] Specifically, S104 includes the following steps S104-1 to S104-2.

[0047] In S104-1, the cosine values of the elevation angle α and the azimuth angle β are used as the input variables of the polynomial fitting model, and the shape parameters a, b, and c are used as the output variables of the polynomial fitting model for fitting to generate the fitting result, and the formula of the model is specifically as follows.

Number

[0048] As shown in Figure 6, the fitting model can accurately describe the rule that the shape parameters change with the elevation angle and the azimuth angle.

[0049] In S104-2, in order to quickly predict the wind load spectra at different elevation angles and azimuth angles, based on the fitting results, a unified pulsating wind load spectrum prediction model is constructed, and the formula of the model is as follows.

Number

Number

Number

[0050] In S105, the elevation angle and the azimuth angle of the heliostat corresponding to the actual heliostat structure posture are substituted into the unified pulsating wind load spectrum prediction model to calculate and obtain the pulsating wind load spectrum of the heliostat mirror in the actual operating condition.

[0051] Specifically, based on the unified pulsating wind load spectrum prediction model, the actual heliostat attitude parameters (e.g., elevation angle and azimuth angle) are combined to calculate the wind load spectrum under specific environmental conditions, which serves as the external loading condition for mirror deformation analysis.

[0052] In this embodiment, according to the formula of the pulsating wind load spectrum, the pulsating wind load distribution at the actual attitude (elevation angle and azimuth angle) of the mirror can be directly calculated, the dynamic characteristics of the wind load action can be extracted, and basic data (shown in Figure 7) can be provided for subsequent structural analysis.

[0053] In S106, a finite element model of the heliostat structure is established, the pulsating wind load spectrum is applied to the finite element model, and the instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load is obtained.

[0054] Specifically, the pulsating wind load spectrum is loaded into the heliostat by the finite element method, the dynamic response of the mirror is analyzed, a finite element model of the heliostat structure is constructed using the geometric characteristics and material parameters of the heliostat, the calculated pulsating wind load spectrum is applied, the displacement distribution and stress distribution of the mirror at different times are recorded, and basic data is provided for optical performance evaluation.

[0055] Specifically, a finite element model of the heliostat structure is constructed using the geometric characteristics and material parameters of the heliostat, and the calculated pulsating wind load spectrum is applied. Through dynamic response analysis, the displacement distribution and stress distribution of the mirror at different times are recorded, and basic data is provided for optical performance evaluation.

[0056] In S107, the ray tracing method is used to simulate the solar ray transmission path and determine the instantaneous light collection efficiency of the deformed mirror.

[0057] Specifically, S107 includes the following steps S107-1 to S107-4.

[0058] In S107-1, the instantaneous deformation data of the mirror obtained by finite element analysis is introduced into the ray tracing calculation program.

[0059] The instantaneous deformation data of the mirror includes the three-dimensional coordinates and normal vector information of the mirror nodes at each moment. These information are used to reconstruct the actual shape of the mirror so that the ray tracing process can reflect the dynamic deformation caused by the wind load of the mirror.

[0060] In S107-2, according to the geometric optical principle, it is simulated to irradiate the deformed mirror with sunlight in the form of parallel light. As shown in FIG. 8, the light ray is reflected by the mirror, and the reflection direction is determined by the normal vector of the mirror and the incident light ray direction. Since the normal vector of the deformed mirror is different for each node, the direction distribution of the reflected light ray changes.

[0061] In S107-3, it is determined whether the reflected light ray converges on the target receiver. If the reflected light ray cannot reach the target receiver, it means that there is a deviation in the light collection performance due to the mirror deformation. Further, the number of effective light rays m 1 converging on the target receiver within a certain time and the total number of incident light rays m total are statistically counted, and the instantaneous light collection efficiency is obtained by calculation according to the following formula.

Equation

[0062] In S107-4, the instantaneous light collection efficiency at multiple time points is statistically counted, the average light collection efficiency of the mirror is calculated, the light spot distribution on the target receiver is analyzed, and the optical influence of the dynamic deformation of the mirror is quantified.

[0063] This embodiment constructs an aerodynamic characteristic model, a dynamic response model and an optical performance evaluation model of the heliostat, and comprehensively analyzes the dynamic deformation characteristics of the heliostat under the action of wind load and its dynamic influence on the light collection efficiency by combining the pulsating wind load spectrum and the ray tracing method.

[0064] Specifically, the present invention first simulates the pulsating wind load distribution in the operating conditions of different elevation-azimuth angles of the heliostat by CFD calculation using a method that combines numerical simulation and theoretical analysis, extracts the aerodynamic admittance function and its important shape parameters, and constructs a pulsating wind load spectrum prediction model applicable to the operating conditions of all postures of the heliostat. Based on this model, by combining the actual posture parameters of the heliostat, the pulsating wind load spectrum in a specific wind environment of the mirror is calculated.

[0065] By finite element analysis, the predicted pulsating wind load spectrum is applied to the structural model of the heliostat mirror to simulate the instantaneous dynamic response of the heliostat under the action of wind load and obtain the displacement and strain distribution characteristics of the mirror. Furthermore, in combination with the ray tracing method, the influence of the dynamic deformation of the mirror on the ray reflection path is simulated, the instantaneous influence on the light collection efficiency of the deformed mirror is quantified, and a dynamic curve of the change of the light collection efficiency over time is generated.

[0066] In addition, the present invention quantitatively analyzes the dynamic influence of factors such as wind load, wind speed, and mirror posture on the light collection efficiency by statistically analyzing the simulation results of a plurality of typical operating conditions. Based on data analysis, the change rules of important parameters are extracted, the influence mechanism of wind load on the optical performance of the heliostat is clarified, and a scientific basis can be provided for optimizing the design and wind resistance of the support structure of the heliostat.

[0067] Using the above method, the present invention systematically simulates and analyzes the entire process of the dynamic response of the heliostat under the action of wind load, clarifies the relationship between the dynamic deformation of the mirror and the light beam focusing performance, and can realize an efficient prediction of the light collection efficiency loss in a complex wind environment. According to the present invention, the heat absorption efficiency of a tower-type solar thermal power plant can be effectively improved, and important engineering application value and technical support are provided for the design optimization and operation stability of the solar thermal power generation system.

[0068] (Example 2) This embodiment provides a calculation and evaluation device for the light collection efficiency loss of a heliostat based on the prediction of wind loads by the response surface method. As shown in FIG. 9, the device includes the following functional modules 901 to 907.

[0069] The data generation module 901 generates pulsating wind speed data, generates pulsating wind speed at the inlet of the flow field by the autoregressive model method, combines numerical simulation and test data to establish a flow field calculation area that can reflect the actual characteristics of the wind field, and provides input conditions for wind load analysis. The data generation module simultaneously acquires the pulsating wind load data of the heliostat at different actual attitude parameters (for example, different elevation angles and azimuth angles), and provides parametric input for the calculation of subsequent modules.

[0070] The wind load calculation module 902 calculates the pulsating wind load spectrum under different operating conditions of the heliostat mirror based on the input data provided by the data generation module, and calculates the aerodynamic admittance function of the wind load of the heliostat mirror for different combinations of elevation angle - azimuth angle.

[0071] The shape parameter calculation module 903 performs non - linear fitting on the aerodynamic admittance function using the least - squares method to obtain shape parameters.

[0072] The result output from this module includes the dynamic wind load distribution of the mirror nodes, and provides load conditions for subsequent structural analysis.

[0073] The model construction module 904 statistically analyzes the shape parameters of the aerodynamic admittance function for different combinations of elevation angle - azimuth angle, establishes a polynomial fitting model using the response surface method, and constructs a unified pulsating wind load spectrum prediction model applicable to the operating conditions of all attitudes of the heliostat.

[0074] The calculation module 905 substitutes the elevation angle and azimuth angle of the heliostat corresponding to the actual heliostat structure posture into the unified pulsating wind load spectrum prediction model, and calculates the pulsating wind load spectrum of the heliostat mirror under the actual operating conditions.

[0075] The structural response analysis module 906 establishes a finite element model of the heliostat structure, applies the pulsating wind load spectrum to the finite element model, and obtains the instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load. Under the combined action of the pulsating wind load and the gravity load, this module performs time history analysis using a dynamic explicit solver, outputs the displacement, strain and stress distribution of the mirror nodes, and obtains the dynamic deformation data of the mirror.

[0076] The optical performance evaluation module 907 simulates the solar ray transmission path using the ray tracing method and determines the instantaneous light collection efficiency of the deformed mirror.

[0077] Specifically, based on the dynamic deformation data provided by the structural response analysis module, the ray tracing method is used to simulate the transmission path of the solar rays, and the light collection efficiency deviation of the mirror is calculated. This module inputs the instantaneous shape of the mirror nodes into the ray tracing program, simulates the ray reflection process according to the geometric optical principle, and evaluates whether the reflected rays converge on the target receiver. By counting the number of effective rays and the total number of rays, the instantaneous light collection efficiency is calculated, and the change situation of the optical performance of the mirror is output.

[0078] Due to the synergistic effect of the above seven modules, the device can complete the entire process from the generation of wind field data to the dynamic response analysis and light collection efficiency evaluation of the heliostat. The device provides important technical support for the optimization of the wind resistance design of the heliostat and the improvement of the performance of the solar thermal power generation system.

[0079] (Example 3) A computer-readable storage medium including a stored program, when the program is executed, controls a device in which the computer-readable storage medium is located to execute a method for calculating and evaluating the light collection efficiency loss of a heliostat based on the prediction of wind load by the response surface method described in Example 1.

[0080] (Example 4) This embodiment further provides a computer device including a processor, a memory bus, a network interface, and a non-volatile memory at the hardware level. When a program stored in the hardware device is executed, a method for calculating and evaluating the light collection efficiency loss of a heliostat based on the prediction of wind load by the response surface method described in Example 2 can be realized. The storage device includes, but is not limited to, magnetic disk memory, optical memory, and CD-ROM, and various storage media for storing related program data to support the realization of the method can be used.

[0081] Embodiments of the present invention may be implemented in a complete hardware manner, may also be implemented in a hybrid form combining software and hardware, and may further be executed in a distributed computing manner in a computer cluster. These flexible implementation means ensure that the present invention can efficiently adapt to different scales and complexities of computing requirements, and provide important technical support for the wind load performance analysis and optimization of heliostats.

[0082] To better implement the above method, the device (system) and computer program product are designed as a modular architecture. By exchanging information through a clearly defined data interface between modules, important steps such as wind load spectrum generation, finite element analysis, and optical tracking calculation are realized. Each module supports independent arrangement or joint calculation and adapts to the technical requirements in specific operating situations.

[0083] In addition, the computer program according to the present invention can not only be applied to general-purpose computing devices, but also be integrated with an embedded processing unit or a cloud computing platform to make full use of the latest computing resources for efficient modeling and optimization analysis. With these modular designs and flexible computing architectures, the present invention can widely adapt to the prediction of the wind load effect of heliostats and the evaluation requirements of the light collection efficiency in different environments, and provide scientific support for improving the overall performance of solar thermal power generation.

[0084] Note that the above content and specific embodiments of the present invention are for those skilled in the art to better understand the technical solution of the present invention, and are not limited to the above specific implementation content. Without departing from the essence of the present invention, those skilled in the art can make various equivalent substitutions and improvements to the present invention, and these equivalent means should also be regarded as within the protection scope of the present invention.

[0085] For the same parts and similar parts between the embodiments in this specification, reference may be made to each other. In particular, for the embodiments of the terminal, since they are basically similar to the embodiments of the method, the description is relatively simple, and the relevant parts may refer to the description in the embodiments of the method.

[0086] In some embodiments according to the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the embodiments of the system described above are merely illustrative. For example, the division of the above units is only a logical function division, and there may be other division methods when actually implemented. For example, a plurality of units or assemblies may be combined or integrated into another system, and some features may be ignored or not executed. In another aspect, the couplings or direct couplings or communication connections shown or considered with each other may be indirect couplings or communication connections through some interfaces, systems or units, and may be in electrical, mechanical or other forms.

[0087] The unit described as a separate component may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or dispersed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution means of this embodiment.

[0088] Note that the flowchart in the drawings shows the method of the embodiments of the present disclosure. In the corresponding descriptions in the flowchart or block diagram in the drawings, the operations or steps corresponding to different blocks may occur in an order different from the order disclosed in the description, and there may be no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, or may be executed in the reverse order in some cases, which may be determined according to the related functions. Each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that executes a predetermined function or operation, or may be implemented by a combination of dedicated hardware and computer instructions.

[0089] The above description is only a preferred embodiment of the present invention and does not limit the present invention. For those skilled in the art, the present invention can have various modifications and deformations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should all be included within the protection scope of the present invention.

Claims

1. Step 1: using an autoregressive model method to generate pulsating wind speed at the inlet of the flow field, establish a flow field calculation domain, and obtain pulsating wind load data of the heliostat at different elevation-azimuth angles; Step 2: based on the extracted pulsating wind load data, analyzing its frequency domain characteristics and calculating the aerodynamic admittance function of the wind load of the heliostat mirror at different elevation-azimuth angle combinations; Step 3: performing nonlinear fitting to the aerodynamic admittance function using the least squares method to obtain shape parameters of the aerodynamic admittance function of the wind load at different elevation-azimuth angle combinations; Step 4: establishing a polynomial fitting model using response surface methodology, and inputting the shape parameters of the aerodynamic admittance function at different elevation-azimuth angle combinations into the established polynomial fitting model to construct a unified pulsating wind load spectrum prediction model that is adaptive to the operating conditions of all attitudes of the heliostat; Step 5: substituting the elevation angle and azimuth angle of the heliostat corresponding to the actual heliostat structural attitude into the unified pulsating wind load spectrum prediction model to calculate and obtain the pulsating wind load spectrum of the heliostat mirror under the actual operating condition; Step 6: establishing a finite element model of the heliostat structure, applying the pulsating wind load spectrum to the finite element model, and obtaining instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load; and step 7. simulating the solar ray transmission path using ray tracing to determine the instantaneous light collection efficiency of the deformed mirror. A method for calculating and evaluating a loss of light collection efficiency of a heliostat based on a prediction of wind load by a response surface methodology, comprising:

2. The step 1 includes: simulating the random fluctuation characteristics of wind speed in a real wind environment using an autoregressive model to generate a pulsating wind speed time series that matches the spatiotemporal random characteristics; Establishing a flow field numerical calculation domain using a computational fluid dynamics method based on the generated pulsating wind speed time series; and performing a numerical simulation on the flow field by a CFD method to extract pulsating wind load data on the heliostat mirror.

2. The method for calculating and evaluating a loss of light collection efficiency of a heliostat based on prediction of wind load by response surface methodology according to claim 1.

3. The step 1 further includes a step of performing a rationality verification on the established flow field calculation domain.

3. The method for calculating and evaluating a loss of light collection efficiency of a heliostat based on prediction of wind load by response surface methodology according to claim 2.

4. Step 2 includes: Calculating a wind pressure power spectrum based on a quasi-steady wind pressure spectrum equation, the quasi-steady wind pressure spectrum equation being: [0010] During the ceremony, [0025] represents the quasi-steady wind pressure spectral density, [0030] is the normalized mean pressure coefficient, and S ｕＨ (f) is the power spectral density of the horizontal wind speed, [0045] is the average wind speed at the reference height H, and f is the frequency in Hertz; Defining an aerodynamic admittance function as the ratio of a frequency domain expression of the pulsating wind load data to a quasi-steady wind pressure spectrum, the expression of the aerodynamic admittance function being: [0050] In the formula, S ｐ (f) is a frequency domain equation for the pulsating wind load data; 2. The method for calculating and evaluating a loss of light collection efficiency of a heliostat based on prediction of wind load by response surface methodology according to claim 1.

5. Step 3 includes: A step of performing nonlinear fitting to the aerodynamic admittance function using a least squares method to obtain shape parameters a, b, and c, where the mathematical model of the aerodynamic admittance function is as follows: [006] In the formula, a represents the amplitude change of the aerodynamic admittance function, b represents the frequency characteristic of the aerodynamic admittance function, c represents the nonlinear characteristic of the aerodynamic admittance function, and B includes a step that is a characteristic scale of the heliostat.

2. The method for calculating and evaluating a loss of light collection efficiency of a heliostat based on prediction of wind load by response surface methodology according to claim 1.

6. Step 4 includes: A step of performing fitting using the cosine value of the elevation angle α and the azimuth angle β as input variables of a polynomial fitting model and the shape parameters a, b, and c as output variables of the polynomial fitting model to generate a fitting result, the model formula being specifically as follows: [0070] where x=cos(α), y=cos(β), z is the value of the shape parameter a, b, or c, and p ｉｊ are polynomial fitting coefficients, α is the elevation angle of the heliostat, and β is the azimuth angle of the heliostat; Building a unified pulsating wind load spectrum prediction model based on the fitting result for quickly predicting wind load spectrum at different elevation and azimuth angles, the formula of the model is as follows: [0080] In the formula, S ｃｐ (f) is the power spectral density of the wind pressure coefficient, [0097] represents the average wind pressure coefficient, [0089] is the average wind speed at a given height H, ρ is the air density, and X ２ (f) is the aerodynamic admittance function, and S ｕＨ (f) is the power spectral density of the wind speed at a given height H, and L ｕＨ is the turbulence integral scale; The method for calculating and evaluating a loss of light collection efficiency of a heliostat based on a prediction of a wind load by the response surface methodology according to claim 5.

7. A data generation module generates pulsating wind speed numbers, generates pulsating wind speeds at the inlet of the flow field by an autoregressive model method, and establishes a flow field calculation domain that can reflect the actual characteristics of the wind field by combining numerical simulation and test data; a wind load calculation module that calculates pulsating wind load spectra under different operating conditions of the heliostat mirror based on input data provided by the data generation module, and calculates an aerodynamic admittance function of the wind load on the heliostat mirror under different elevation angle-azimuth angle combinations; a shape parameter calculation module that performs nonlinear fitting on the aerodynamic admittance function using a least squares method to obtain shape parameters; a model construction module for establishing a polynomial fitting model using response surface methodology, and inputting shape parameters of aerodynamic admittance functions at different elevation-azimuth angle combinations into the established polynomial fitting model to construct a unified pulsating wind load spectrum prediction model that is adaptive to the operating conditions of all attitudes of the heliostat; a calculation module for substituting the elevation angle and azimuth angle of the heliostat corresponding to the actual heliostat structural attitude into a unified pulsating wind load spectrum prediction model to calculate and obtain the pulsating wind load spectrum of the heliostat mirror under actual operating conditions; a structural response analysis module for establishing a finite element model of the heliostat structure, applying the pulsating wind load spectrum to the finite element model, and obtaining instantaneous deformation data of the heliostat mirror under the action of the pulsating wind load; and an optical performance evaluation module that uses a ray tracing method to simulate a solar ray transmission path and determine an instantaneous light collection efficiency of the deformable mirror. A calculation and evaluation device for a loss of light collection efficiency of a heliostat based on a prediction of a wind load by a response surface methodology, comprising:

8. A computer readable storage medium including a program stored therein, the program being executed to control an apparatus on which the computer readable storage medium is located to perform a method for calculating and assessing a light collection efficiency loss of a heliostat based on a prediction of a wind load by a response surface methodology according to any one of claims 1 to 6. A computer-readable storage medium.

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